[go: up one dir, main page]

Next Issue
Volume 11, December
Previous Issue
Volume 11, October
 
 

Metals, Volume 11, Issue 11 (November 2021) – 218 articles

Cover Story (view full-size image): The fatigue lives of IN718, produced by additive manufacturing (AM) as well as conventional wrought material, were successfully determined at 873 K up to 109 cycles. Therefore, ultrasonic fatigue tests were performed under fully revered loading. The AM material was investigated in its as-built condition, whereas conventional material received the typical heat treatment for IN718. Both microstructures showed fundamental differences concerning grain sizes, defect distribution, and texture. The as-built microstructure led to a significant decrease in fatigue strength compared to the heat-treated conventional IN718. The EBM material showed crystallographic crack initiation along the activated slip systems initiated by internal defects. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
12 pages, 3700 KiB  
Article
Deformation Behavior of Wrought and EBAM Ti-6Al-4V under Scratch Testing
by Artur Shugurov, Alexey Panin, Marina Kazachenok, Lyudmila Kazantseva, Sergey Martynov, Alexander Bakulin and Svetlana Kulkova
Metals 2021, 11(11), 1882; https://doi.org/10.3390/met11111882 - 22 Nov 2021
Cited by 9 | Viewed by 1951
Abstract
The microstructure, mechanical properties, and deformation behavior of wrought and electron beam additive manufactured (EBAM) Ti-6Al-4V samples under scratching were studied. As-received wrought Ti-6Al-4V was subjected to thermal treatment to obtain the samples with microstructure and mechanical characteristics similar to those of the [...] Read more.
The microstructure, mechanical properties, and deformation behavior of wrought and electron beam additive manufactured (EBAM) Ti-6Al-4V samples under scratching were studied. As-received wrought Ti-6Al-4V was subjected to thermal treatment to obtain the samples with microstructure and mechanical characteristics similar to those of the EBAM samples. As a result, both alloys consisted of colonies of α phase laths within prior β phase grains and were characterized by close values of hardness. At the same time, the Young’s modulus of the EBAM samples determined by nanoindentation was lower compared with the wrought samples. It was found that despite the same hardness, the scratch depth of the EBAM samples under loading was substantially smaller than that of the wrought alloy. A mechanism was proposed, which associated the smaller scratch depth of EBAM Ti-6Al-4V with α′→α″ phase transformations that occurred in the contact area during scratching. Ab initio calculations of the atomic structure of V-doped Ti crystallites containing α or α″ phases of titanium were carried out to support the proposed mechanism. Full article
(This article belongs to the Special Issue Microstructure and Mechanical Properties of Titanium Alloys II)
Show Figures

Figure 1

Figure 1
<p>Schematic of cutting a sample from an as-built EBAM Ti-6Al-4V bar and its scratch testing.</p>
Full article ">Figure 2
<p>Typical microstructures of the wrought (<b>a</b>,<b>c</b>) and EBAM Ti-6Al-4V samples (<b>b</b>,<b>d</b>).</p>
Full article ">Figure 3
<p>TEM bright (<b>a</b>) and dark-field micrographs (<b>b</b>,<b>c</b>) and the associated selected area electron diffraction (SAED) pattern with an indexing scheme (<b>d</b>) of the wrought Ti-6Al-4V sample. The dark-field TEM micrographs were obtained with the <math display="inline"><semantics> <mrow> <mover accent="true"> <mn>2</mn> <mo>¯</mo> </mover> <mn>1</mn> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> <mfenced> <mrow> <mn>251</mn> </mrow> </mfenced> </mrow> </semantics></math> α-Ti (<b>b</b>) and <math display="inline"><semantics> <mrow> <mn>3</mn> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> <mn>0</mn> <mfenced> <mrow> <mn>130</mn> </mrow> </mfenced> </mrow> </semantics></math> β-Ti reflections (<b>c</b>).</p>
Full article ">Figure 4
<p>TEM bright (<b>a</b>) and dark-field micrographs (<b>b</b>) and the associated SAED pattern with indexing schemes (<b>c</b>) of EBAM Ti-6Al-4V sample. The dark-field TEM micrograph was obtained with the closely spaced <math display="inline"><semantics> <mrow> <mn>0</mn> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> <mfenced> <mrow> <mn>41</mn> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> </mrow> </mfenced> </mrow> </semantics></math> α-Ti and <math display="inline"><semantics> <mrow> <mn>1</mn> <mover accent="true"> <mn>1</mn> <mo>¯</mo> </mover> <mn>0</mn> <mfenced> <mrow> <mn>221</mn> </mrow> </mfenced> </mrow> </semantics></math> β-Ti reflections (<b>b</b>).</p>
Full article ">Figure 5
<p>Longitudinal surface profiles of scratch grooves in the wrought (<b>a</b>) and EBAM (<b>b</b>) Ti-6Al-4V samples: 1—initial surface profile, 2—residual scratch profile, 3—scratch profile under loading.</p>
Full article ">Figure 6
<p>AFM images (<b>a</b>,<b>c</b>) and corresponding cross-sectional surface profiles (<b>b</b>,<b>d</b>) of scratch grooves formed in the wrought (<b>a</b>,<b>b</b>) and EBAM (<b>c</b>,<b>d</b>) Ti-6Al-4V samples.</p>
Full article ">Figure 7
<p>Energy per atom in α- and α″-Ti with 6.6 wt% of vanadium as a function of atomic volume.</p>
Full article ">
15 pages, 4002 KiB  
Review
The Grain Boundary Wetting Phenomena in the Ti-Containing High-Entropy Alloys: A Review
by Boris B. Straumal, Anna Korneva, Alexei Kuzmin, Gabriel A. Lopez, Eugen Rabkin, Alexander B. Straumal, Gregory Gerstein and Alena S. Gornakova
Metals 2021, 11(11), 1881; https://doi.org/10.3390/met11111881 - 22 Nov 2021
Cited by 61 | Viewed by 4351
Abstract
In this review, the phenomenon of grain boundary (GB) wetting by melt is analyzed for multicomponent alloys without principal components (also called high-entropy alloys or HEAs) containing titanium. GB wetting can be complete or partial. In the former case, the liquid phase forms [...] Read more.
In this review, the phenomenon of grain boundary (GB) wetting by melt is analyzed for multicomponent alloys without principal components (also called high-entropy alloys or HEAs) containing titanium. GB wetting can be complete or partial. In the former case, the liquid phase forms the continuous layers between solid grains and completely separates them. In the latter case of partial GB wetting, the melt forms the chain of droplets in GBs, with certain non-zero contact angles. The GB wetting phenomenon can be observed in HEAs produced by all solidification-based technologies. GB leads to the appearance of novel GB tie lines Twmin and Twmax in the multicomponent HEA phase diagrams. The so-called grain-boundary engineering of HEAs permits the use of GB wetting to improve the HEAs’ properties or, alternatively, its exclusion if the GB layers of a second phase are detrimental. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic binary phase diagram for the explanation of GB wetting phenomena. Bold solid lines show the bulk-phase transformation. Thin solid lines show the tie lines of the GB wetting by the melt at <span class="html-italic">T</span><sub>wmin</sub> and <span class="html-italic">T</span><sub>wmax</sub>. Vertical red dotted lines 1 to 5 show different solidification routes. Schemes between Routes 1 and 2 show the cases of complete (top) and partial (bottom) GB wetting. Micrographs on the right-hand side of the diagram are for the Al-Mg samples annealed above <span class="html-italic">T</span><sub>wmax</sub> (top micrograph, all GBs are completely wetted), between <span class="html-italic">T</span><sub>wmin</sub> and <span class="html-italic">T</span><sub>wmax</sub> (middle micrograph, some GBs are completely wetted and other GBs are partially wetted) and below <span class="html-italic">T</span><sub>wmin</sub> (bottom micrograph, no completely wetted GBs).</p>
Full article ">Figure 2
<p>SEM micrographs of equiatomic HfNbTaTiZr polycrystal after arc melting, followed by homogenization treatment at 1773 K for 5 h; (<b>a</b>) as cast, (<b>b</b>) homogenized. Reprinted with permission from Ref. [<a href="#B5-metals-11-01881" class="html-bibr">5</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 3
<p>SEM micrographs of as-cast HEAs AlCoCuFeNiC (<b>a</b>) and AlCoCuFeNiCrTi (<b>b</b>). Reprinted with permission from Ref. [<a href="#B37-metals-11-01881" class="html-bibr">37</a>]. Copyright 2017 Elsevier.</p>
Full article ">Figure 4
<p>SEM BSE micrograph of the as-cast Ti<sub>3</sub>V<sub>2</sub>NbNi<sub>0.5</sub> alloy. The matrix grains are surrounded by the eutectic bcc+ C15 mixture. Reprinted with permission from Ref. [<a href="#B13-metals-11-01881" class="html-bibr">13</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 5
<p>Pseudo-binary phase diagram of CoCrFeNi-Ta. Reprinted with permission from Ref. [<a href="#B29-metals-11-01881" class="html-bibr">29</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 6
<p>SEM micrographs of CoCrFeNi-Ta<sub>x</sub> HEA. (<b>a</b>) <span class="html-italic">x</span> = 0.1, (<b>b</b>) <span class="html-italic">x</span> = 0.25, (<b>c</b>) <span class="html-italic">x</span> = 0.75, (<b>d</b>) <span class="html-italic">x</span> = 1. Reprinted with permission from Ref. [<a href="#B29-metals-11-01881" class="html-bibr">29</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 7
<p>SEM-EDX-mapping analysis of sintered and laser-remelted HEAs: (<b>a</b>) CoCrFeNi, (<b>b</b>) CoCrFeNiAl<sub>0.5</sub>, (<b>c</b>) CoCrFeNiTi<sub>0.5</sub>Al<sub>0.5</sub>. Reprinted with permission from Ref. [<a href="#B20-metals-11-01881" class="html-bibr">20</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 8
<p>SEM micrographs of MgMoNbFeTi<sub>2</sub>Y<sub>x</sub> HEA coatings (<b>a</b>) <span class="html-italic">x</span> = 0, (<b>b</b>) <span class="html-italic">x</span> = 0.4%, (<b>c</b>) <span class="html-italic">x</span> = 0.8%, (<b>d</b>) <span class="html-italic">x</span> = 1.2% deposited by laser cladding. Reprinted with permission from Ref. [<a href="#B45-metals-11-01881" class="html-bibr">45</a>]. Copyright 2021 Elsevier.</p>
Full article ">Figure 9
<p>SEM micrographs of Al<sub>x</sub>Mo<sub>0.5</sub>NbFeTiMn HEAs deposited by laser cladding. (<b>a</b>) <span class="html-italic">x</span> = 1, (<b>b</b>) <span class="html-italic">x</span> = 1.5, (<b>c</b>) <span class="html-italic">x</span> = 2. The corresponding EDS maps for Nb and Mo are given in the bottom part. Reprinted with permission from Ref. [<a href="#B46-metals-11-01881" class="html-bibr">46</a>]. Copyright 2020 Elsevier.</p>
Full article ">Figure 10
<p>(<b>a</b>) Secondary electron image and the corresponding elemental maps of (<b>b</b>) Al, (<b>c</b>) Ti, (<b>d</b>) Ni, (<b>e</b>) Fe, (<b>f</b>) Cr and (<b>g</b>) Co of the AlCoCrFeNiTi<sub>0.5</sub> HEA. Reprinted with permission from Ref. [<a href="#B58-metals-11-01881" class="html-bibr">58</a>]. Copyright 2020 MDPI.</p>
Full article ">
18 pages, 6431 KiB  
Article
Simultaneous Improvement in Mechanical Properties and Fatigue Crack Propagation Resistance of Low Carbon Offshore Structural Steel EH36 by Cu–Cr Microalloying
by Xingdong Peng, Peng Zhang, Ke Hu, Ling Yan and Guanglong Li
Metals 2021, 11(11), 1880; https://doi.org/10.3390/met11111880 - 22 Nov 2021
Cited by 3 | Viewed by 2006
Abstract
Improving the mechanical performance of low-carbon offshore steel is of great significance in shipbuilding applications. In this paper, a new Cu-Cr microalloyed offshore structural steel (FH36) was developed based on EH36. The microstructure, mechanical properties, and fatigue crack propagation properties of rolled plates [...] Read more.
Improving the mechanical performance of low-carbon offshore steel is of great significance in shipbuilding applications. In this paper, a new Cu-Cr microalloyed offshore structural steel (FH36) was developed based on EH36. The microstructure, mechanical properties, and fatigue crack propagation properties of rolled plates of FH36, EH36, and normalizing rolled EH36 plates (EH36N) manufactured by a thermo-mechanical control process (TMCP) were analyzed and compared (to simplify, the two rolled specimens are signified by FH36T and EH36T, respectively). FH36T showed an obvious advantage in elongation with the value of 29%, 52.2% higher than the EH36T plates. The normalizing process led to a relatively lower yield stress (338 MPa), but substantially increased the elongation (33%) and lessened the yield ratio from 0.77 to 0.67. Electron back-scattered diffraction (EBSD) analysis showed that SFs of the deformation texture of FH36T and EH36N along the transverse direction (TD) and normal direction (ND) were much higher than those of the EH36T plate, which enhanced the lateral movement ability in the width and thickness direction, enhancing the ductility. Moreover, FH36 plates showed a better fatigue crack propagation resistance than rolled EH36 plates. The formation of the jagged shape grain boundaries is believed to induce a decrease of effective stress intensity factor during the fatigue crack propagation process. Full article
Show Figures

Figure 1

Figure 1
<p>Manufacture process of offshore steels.</p>
Full article ">Figure 2
<p>Specification of tensile sample: (<b>a</b>) rolling plate, (<b>b</b>) tensile specimen.</p>
Full article ">Figure 3
<p>Specification of fatigue crack propagation test.</p>
Full article ">Figure 4
<p>Microstructures of offshore structural steels: (<b>a</b>,<b>d</b>) EH36, (<b>b</b>,<b>e</b>) FH36T, and (<b>c</b>,<b>f</b>) FH36N.</p>
Full article ">Figure 5
<p>Orientation maps and distribution of grain boundaries: (<b>a</b>,<b>d</b>) EH36, (<b>b</b>,<b>e</b>) FH36T, (<b>c</b>,<b>f</b>) FH36N, and (<b>g</b>–<b>i</b>) histogram rams of frequency of grain boundaries of the offshore steels.</p>
Full article ">Figure 6
<p>Deformation textures of the studied samples represented by pole figures and ODF section: (<b>a</b>) EH36T, (<b>b</b>) FH36T, and (<b>c</b>) EH36N.</p>
Full article ">Figure 7
<p>ODF sections of <span class="html-italic">φ</span><sub>2</sub> = 45° (<span class="html-italic">φ</span><sub>1</sub>, <math display="inline"><semantics> <mi>Φ</mi> </semantics></math>= 0–90°).</p>
Full article ">Figure 8
<p>Mechanical properties and corresponding fractographs of rolled plate samples: (<b>a</b>) stress–strain curves; (<b>b</b>) mechanical properties; and (<b>c</b>–<b>e</b>) SEM fractographs of the plates of EH36T, FH36T, and EH36N.</p>
Full article ">Figure 9
<p>Contribution to the yield stress of the different strengthening mechanisms.</p>
Full article ">Figure 10
<p>Work hardening rates of the offshore structural steel.</p>
Full article ">Figure 11
<p>Fatigue crack growth behavior of offshore structural steel plates.</p>
Full article ">Figure 12
<p>Scanning electron micrographs of the fatigue fracture surfaces: (<b>a</b>) EH36T, (<b>b</b>) FH36T, (<b>c</b>) EH36N and (<b>d</b>) image of fatigue fractures.</p>
Full article ">
15 pages, 2754 KiB  
Article
Influence of Quenching and Partitioning Parameters on Phase Transformations and Mechanical Properties of Medium Manganese Steel for Press-Hardening Application
by Charline Blankart, Sebastian Wesselmecking and Ulrich Krupp
Metals 2021, 11(11), 1879; https://doi.org/10.3390/met11111879 - 22 Nov 2021
Cited by 13 | Viewed by 3015
Abstract
It has been proven that through targeted quenching and partitioning (Q & P), medium manganese steels can exhibit excellent mechanical properties combining very high strength and ductility. In order to apply the potential of these steels in industrial press hardening and to avoid [...] Read more.
It has been proven that through targeted quenching and partitioning (Q & P), medium manganese steels can exhibit excellent mechanical properties combining very high strength and ductility. In order to apply the potential of these steels in industrial press hardening and to avoid high scrap rates, it is of utmost importance to determine a robust process window for Q & P. Hence, an intensive study of dilatometry experiments was carried out to identify the influence of quenching temperature (TQ) and partitioning time (tp) on phase transformations, phase stabilities, and the mechanical properties of a lean medium manganese steel. For this purpose, additional scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and energy dispersive X-ray spectroscopy (EDX) examinations as well as tensile testing were performed. Based on the dilatometry data, an adjustment of the Koistinen–Marburger (K-M) equation for medium manganese steel was developed. The results show that a retained austenite content of 12–21% in combination with a low-phase fraction of untempered secondary martensite (max. 20%) leads to excellent mechanical properties with a tensile strength higher than 1500 MPa and a total elongation of 18%, whereas an exceeding secondary martensite phase fraction results in brittle failure. The optimum retained austenite content was adjusted for TQ between 130 °C and 150 °C by means of an adapted partitioning. Full article
(This article belongs to the Special Issue Alloy and Process Design of Metallic Materials)
Show Figures

Figure 1

Figure 1
<p>Schematic description of the Q &amp; P process and the microstructural evolution during the heat treatment.</p>
Full article ">Figure 2
<p>Schematic temperature–time diagram of the quenching and partitioning experiments for first (varying <span class="html-italic">T<sub>Q</sub></span> and t<sub>P</sub> = 60 s) and second experimental series (<span class="html-italic">T<sub>Q</sub></span> = 150/170 °C and varying t<sub>P</sub>).</p>
Full article ">Figure 3
<p>Thermocalc simulation of most stable phases for Fe-0.3%C-5%Mn-1.5%Si.</p>
Full article ">Figure 4
<p>Experimentally determined CCT-diagram for an austenitization time of 300 s at 840 °C (hardness HV30).</p>
Full article ">Figure 5
<p>Experimental and empirical determination of primary martensite’s phase fraction in dependence of <span class="html-italic">T<sub>Q</sub></span>.</p>
Full article ">Figure 6
<p>(<b>a</b>) IPF map of the cold-rolled state; (<b>b</b>) SEM image of the cold-rolled state containing small carbides; (<b>c</b>) tensile test results in combination with phase map (blue = bcc) and fracture surface of the cold-rolled state; (<b>d</b>) IPF map of the as-quenched state; (<b>e</b>) SEM image of the martensitic as-quenched state; (<b>f</b>) tensile test results in combination with phase map (blue = bcc) and fracture surface of the as-quenched state.</p>
Full article ">Figure 7
<p>(<b>a</b>) Dilatation curves for QP170_60 and QP130_60; (<b>b</b>) light optical micrograph of QP130_60; (<b>c</b>) combination of EBSD phase map (fcc = red) and IQ map of QP130_60; (<b>d</b>) light optical micrograph of QP170_60 showing primary (dark) and secondary martensite (bright); (<b>e</b>) combination of EBSD phase map (fcc = red) and IQ map of QP170_60.</p>
Full article ">Figure 8
<p><span class="html-italic">M<sub>s</sub></span> of secondary martensite in dependence of <span class="html-italic">T<sub>Q</sub></span>.</p>
Full article ">Figure 9
<p>(<b>a</b>) Resulting final phase fractions in dependence of T<sub>Q</sub>; (<b>b</b>) resulting stress–strain curves and representative fracture surface for investigated QP130_60 and QP150_60; and (<b>c</b>) resulting stress–strain curves and representative fracture surface for investigated QP170_60 and QP190_60.</p>
Full article ">Figure 10
<p>Final phase fractions in dependence of tp for (<b>a</b>) <span class="html-italic">T<sub>Q</sub></span> = 150 °C and (<b>b</b>) <span class="html-italic">T<sub>Q</sub></span> = 170 °C.</p>
Full article ">Figure 11
<p>(<b>a</b>) Mainly brittle intergranular fracture surface of QP170_300 tensile test sample containing small ductile areas and cracks; (<b>b</b>) crack running between microstructural areas with relatively low and high C content measured by EDX.</p>
Full article ">
12 pages, 3606 KiB  
Article
The Effect of Current Supply Duration during Stepwise Electrical Sintering of Silver Nanoparticles
by Iksang Lee, Arif Hussain, Hee-Lak Lee, Yoon-Jae Moon, Jun-Young Hwang and Seung-Jae Moon
Metals 2021, 11(11), 1878; https://doi.org/10.3390/met11111878 - 22 Nov 2021
Cited by 8 | Viewed by 1967
Abstract
We studied the effect of current supply duration at final-step currents during the stepwise electrical sintering of silver (Ag) nanoparticles (NPs). Ag NPs ink was inkjet-printed onto Eagle-XG glass substrates. Constant final-step currents of 0.4 and 0.5 A with various time intervals were [...] Read more.
We studied the effect of current supply duration at final-step currents during the stepwise electrical sintering of silver (Ag) nanoparticles (NPs). Ag NPs ink was inkjet-printed onto Eagle-XG glass substrates. Constant final-step currents of 0.4 and 0.5 A with various time intervals were applied to the printed samples. The final-step current of 0.5 A damaged the line at a comparatively shorter time duration. On the other hand, the lower final-step current of 0.4 A prevented the line damage at longer time durations while producing comparatively lower Ag NPs specific resistance. The minimum specific resistances of the printed samples sintered at 0.4 and 0.5 A were 3.59 μΩ∙cm and 3.79 μΩ∙cm, respectively. Furthermore, numerical temperature estimation and scanning electron microscope (SEM) analysis were conducted to elaborate on the results. The numerical temperature estimation results implied that the lower estimated peak temperature at the final-step current of 0.4 A helped prevent Ag NP line damage. The SEM micrographs suggested that a high surface porosity—caused by higher sintering peak temperatures—in the case of the 0.5 A final-step current resulted in a comparatively higher Ag NP line-specific resistance. This contribution is a step forward in the development of Ag NP sintering for printed electronics applications. Full article
Show Figures

Figure 1

Figure 1
<p>Field emission scanning electron microscope (FE-SEM) image of silver nanoparticles before sintering.</p>
Full article ">Figure 2
<p>Schematics of the stepwise current sintering setup.</p>
Full article ">Figure 3
<p>Two-dimensional numerical model of the patterned conductive ink line on the glass substrate.</p>
Full article ">Figure 4
<p>Stepwise current supply versus time plot with (<b>a</b>) the 0.4 A final-step current and (<b>b</b>) the 0.5 A final-step current.</p>
Full article ">Figure 5
<p>Specific resistance vs. time plot for 0.5 A and 0.4 A final-step currents.</p>
Full article ">Figure 6
<p>FE-SEM images of inkjet-printed silver nanoparticles sintered at a final-step current of 0.4 A at time durations of (<b>a</b>) 50 ms, (<b>b</b>) 100 ms, (<b>c</b>) 500 ms, (<b>d</b>) 1000 ms, (<b>e</b>) 2000 ms, and (<b>f</b>) 5000 ms, respectively.</p>
Full article ">Figure 7
<p>FE-SEM images of inkjet-printed silver nanoparticles sintered at the final-step current of 0.5 A at time durations of (<b>a</b>) 50 ms, (<b>b</b>) 100 ms, (<b>c</b>) 500 ms, (<b>d</b>) 1000 ms, (<b>e</b>) 2000 ms, and (<b>f</b>) 2850 ms, respectively. The images at the middle reveal 10,000× SEM images measured after sintering at final-step currents for 1150, 2150, and 2850 ms, respectively (<b>g</b>–<b>i</b>).</p>
Full article ">Figure 8
<p>Estimation of temperature during the electrical sintering of silver nanoparticle ink according to 0.5 A and 0.4 A, final-step currents.</p>
Full article ">Figure 9
<p>Relation between specific resistance of the silver nanoparticle ink and temperature with 0.5 A and 0.4 A, final-step currents.</p>
Full article ">
16 pages, 6355 KiB  
Article
Real-Time Defects Analyses Using High-Speed Imaging during Aluminum Magnesium Alloy Laser Welding
by Sabin Mihai, Diana Chioibasu, Muhammad Arif Mahmood, Liviu Duta, Marc Leparoux and Andrei C. Popescu
Metals 2021, 11(11), 1877; https://doi.org/10.3390/met11111877 - 22 Nov 2021
Cited by 6 | Viewed by 3062
Abstract
In this study a continuous wave Ytterbium-doped Yttrium Aluminum Garnet (Yb: YAG) disk laser has been used for welding of AlMg3 casted alloy. A high-speed imaging camera has been employed to record hot vapor plume features during the process. The purpose was to [...] Read more.
In this study a continuous wave Ytterbium-doped Yttrium Aluminum Garnet (Yb: YAG) disk laser has been used for welding of AlMg3 casted alloy. A high-speed imaging camera has been employed to record hot vapor plume features during the process. The purpose was to identify a mechanism of pores detection in real-time based on correlations between metallographic analyses and area/intensity of the hot vapor in various locations of the samples. The pores formation and especially the position of these pores had to be kept under control in order to weld thick samples. Based on the characterization of the hot vapor, it has been found that the increase of the vapor area that exceeded a threshold value (18.5 ± 1 mm2) was a sign of pores formation within the weld seam. For identification of the pores’ locations during welding, the monitored element was the hot vapor intensity. The hot vapor core spots having a grayscale level reaching 255 was associated with the formation of a local pore. These findings have been devised based on correlation between pores placement in welds cross-section microscopy images and the hot vapor plume features in those respective positions. Full article
(This article belongs to the Special Issue Laser-Assisted Processing of Metals and Alloys)
Show Figures

Figure 1

Figure 1
<p>Schematic of experimental set-up for laser welding monitored by a high-speed imaging camera.</p>
Full article ">Figure 2
<p>Optical microscopy images of mirror-liked polished samples AlMg3: (<b>a</b>) 200 µm and (<b>b</b>) 20 µm.</p>
Full article ">Figure 3
<p>Optical images of laser welded AlMg3 alloy cross-sections: (<b>a</b>) weld seam conducted with laser beam tilt at 40° and 12 passes, (<b>b</b>) weld seam obtained by single irradiation with a beam perpendicular to the sample surface and (<b>c</b>) weld seam with the laser beam tilt at 40° and 2 passes.</p>
Full article ">Figure 4
<p>High-speed imaging camera images of hot vapor plume expansion during the laser welding of AlMg3.</p>
Full article ">Figure 5
<p>(<b>a</b>) High-speed camera images and (<b>b</b>) plot of hot vapor plume height variation in time for each presented frame in case of AlMg3 alloy.</p>
Full article ">Figure 6
<p>Hot vapor plume height variation during laser welding of AlMg3 alloy: (<b>a</b>) images highlighted in false colors and (<b>b</b>) plot of the plumes values.</p>
Full article ">Figure 7
<p>(<b>a</b>) Plot of intensity variation mean-grey values of hot vapor plume with pore dimension, and (<b>b</b>) the value of high intensity area from the plume for each identified pore dimension.</p>
Full article ">Figure 8
<p>(<b>a</b>) Hot vapor plume variation during laser welding of AlMg3 and its correlation with pores appearance, (<b>b</b>) plot of hot vapor area variation in a selected range of frames for chosen pore and (<b>c</b>) a magnified view for highlighted regime in (<b>b</b>).</p>
Full article ">Figure 9
<p>Temperature function of the duration of laser welding process for 2 passes on the AlMg3. The inset represents a typical thermogram, whose central area served for temperature measurement.</p>
Full article ">Figure 10
<p>Schematic representation of laser welding process in conduction mode.</p>
Full article ">Figure 11
<p>Schematic representation of hot vapor plume increased intensity: (<b>a</b>) liquid movement, (<b>b</b>) pore gases being burned, (<b>c</b>) formation of a smaller spherical pore and (<b>d</b>) entrapped pore by fast solidification.</p>
Full article ">
17 pages, 10090 KiB  
Article
Corrosion Resistance of CoCrFeNiMn High Entropy Alloy Coating Prepared through Plasma Transfer Arc Claddings
by Pei-Hu Gao, Rui-Tao Fu, Bai-Yang Chen, Sheng-Cong Zeng, Bo Zhang, Zhong Yang, Yong-Chun Guo, Min-Xian Liang, Jian-Ping Li, Yong-Qing Lu, Lu Jia and Dan Zhao
Metals 2021, 11(11), 1876; https://doi.org/10.3390/met11111876 - 22 Nov 2021
Cited by 22 | Viewed by 2323
Abstract
High entropy alloy attracts great attention for its high thermal stability and corrosion resistance. A CoCrFeNiMn high-entropy alloy coating was deposited on grey cast iron through plasma transfer arc cladding. It formed fine acicular martensite near the grey cast iron, with columnar grains [...] Read more.
High entropy alloy attracts great attention for its high thermal stability and corrosion resistance. A CoCrFeNiMn high-entropy alloy coating was deposited on grey cast iron through plasma transfer arc cladding. It formed fine acicular martensite near the grey cast iron, with columnar grains perpendicular to the interface between the grey cast iron substrate and the cladding layer as well as dendrite in the middle part of the coatings. Simple FCC solid solutions present in the coatings which were similar to the powder’s structure. The coating had a microhardness of 300 ± 21.5 HV0.2 when the cladding current was 80 A for the solid solution strengthening. The HEA coating had the highest corrosion potential of −0.253 V when the plasma current was 60 A, which was much higher than the grey cast iron’s corrosion potential of −0.708 V. Meanwhile, the coating had a much lower corrosion current density of 9.075 × 10−7 mA/cm2 than the grey cast iron’s 2.4825 × 10−6 mA/cm2, which reflected that the CoCrFeNiMn HEA coating had much better corrosion resistance and lower corrosion rate than the grey cast iron for single FCC solid solution phase and a relatively higher concentration of Cr in the grain boundaries than in the grains and this could lead to corrosion protection effects. Full article
Show Figures

Figure 1

Figure 1
<p>Microstructure of CoCrFeNiMn powder: (<b>a</b>) global morphology, (<b>b</b>) cross-sectional microstructure.</p>
Full article ">Figure 2
<p>XRD pattern of CoCrFeNiMn powder.</p>
Full article ">Figure 3
<p>Microstructure of the grey cast iron.</p>
Full article ">Figure 4
<p>Cross-sectional microstructure of CoCrFeNiMn HEA coating at 70A plasma current: (<b>a</b>) global morphology with coating zone (CZ), bonding zone (BZ), heat affected zone (HAZ) and substrate zone (SZ), (<b>b</b>) bonding zone with martensite (M) and ledeburite (L), (<b>c</b>) coating zone, (<b>d</b>) coating zone after deep etching.</p>
Full article ">Figure 5
<p>Point analysis of elements in CoCrFeNiMn coating prepared at 70 A plasma current: (<b>a</b>) coating, (<b>b</b>) composition of point 1, (<b>c</b>) composition of point 2.</p>
Full article ">Figure 5 Cont.
<p>Point analysis of elements in CoCrFeNiMn coating prepared at 70 A plasma current: (<b>a</b>) coating, (<b>b</b>) composition of point 1, (<b>c</b>) composition of point 2.</p>
Full article ">Figure 6
<p>EDX maps of elements in the middle part of the CoCrFeNiMn coating prepared at 70 A plasma arc current: (<b>a</b>) microstructure; (<b>b</b>) Cr distribution; (<b>c</b>) Mn distribution; (<b>d</b>) Fe distribution; (<b>e</b>) Ni distribution; (<b>f</b>) Co distribution.</p>
Full article ">Figure 6 Cont.
<p>EDX maps of elements in the middle part of the CoCrFeNiMn coating prepared at 70 A plasma arc current: (<b>a</b>) microstructure; (<b>b</b>) Cr distribution; (<b>c</b>) Mn distribution; (<b>d</b>) Fe distribution; (<b>e</b>) Ni distribution; (<b>f</b>) Co distribution.</p>
Full article ">Figure 7
<p>XRD patterns of the HEA coatings.</p>
Full article ">Figure 8
<p>Microhardness of CoCrFeNiMn HEA coatings: (<b>a</b>) microhardness distribution along the top surface to the substrate across the cross-section of the HEA coatings, (<b>b</b>) microhardness distribution along the top surface to the substrate.</p>
Full article ">Figure 9
<p>Polarization curves of substrate and HEA coatings in different zones: (<b>a</b>) bonding zone, (<b>b</b>) Heat affected zone and (<b>c</b>) coating zone.</p>
Full article ">Figure 10
<p>Microstructure of the polished upper surface part in the CoCrFeNiMn HEA coatings after corrosion test: (<b>a</b>) 50 A, (<b>b</b>) 60 A, (<b>c</b>) 70 A and (<b>d</b>) 80 A.</p>
Full article ">Figure 11
<p>Schematic of the corrosion process of CoCrFeNiMn HEA coating in 3.5 wt.% NaCl solution.</p>
Full article ">Figure 12
<p>Electrochemical impedance spectroscopy in the middle of the CoCrFeNiMn HEA coatings (<b>a</b>). and the equivalent fitting circuit (<b>b</b>).</p>
Full article ">
15 pages, 4399 KiB  
Review
Understanding the Radiation Resistance Mechanisms of Nanocrystalline Metals from Atomistic Simulation
by Liang Zhang
Metals 2021, 11(11), 1875; https://doi.org/10.3390/met11111875 - 22 Nov 2021
Cited by 4 | Viewed by 2784
Abstract
Metallic materials produce various structural defects in the radiation environment, resulting in serious degradation of material properties. An important way to improve the radiation-resistant ability of materials is to give the microstructure of materials a self-healing ability, to eliminate the structural defects. The [...] Read more.
Metallic materials produce various structural defects in the radiation environment, resulting in serious degradation of material properties. An important way to improve the radiation-resistant ability of materials is to give the microstructure of materials a self-healing ability, to eliminate the structural defects. The research and development of new radiation-resistant materials with excellent self-healing ability, based on defects control, is one of the hot topics in materials science. Compared with conventional coarse-grained materials, nanocrystalline metals with a high density of grain boundary (GB) show a higher ability to resist radiation damage. However, the mechanism of GB’s absorption of structural defects under radiation is still unclear, and how to take advantage of the GB properties to improve the radiation resistance of metallic materials remains to be further investigated. In recent decades, atomistic simulation has been widely used to study the radiation responses of different metals and their underlying mechanisms. This paper briefly reviews the progress in studying radiation resistance mechanisms of nanocrystalline metals by employing computational simulation at the atomic scale. Full article
(This article belongs to the Special Issue Constitutive Modeling of Metallic Materials)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic of the evolution of self-interstitial atoms (SIAs) and vacancies caused by radiation in (<b>a</b>) conventional material and (<b>b</b>) nanomaterial.</p>
Full article ">Figure 2
<p>(<b>a</b>) Snapshots of an MD simulation of a collision cascade near a Σ11{131} symmetric tilt GB at 300 K. The atoms are colored by their potential energy. The atoms are colored by their potential energy. Atoms with energies less than 3.43 eV are removed to highlight the structural defects. (<b>b</b>) The number of interstitials and vacancies surviving in the bulk region near four types of GBs after 4 keV collision cascades at 300 K. The numbers are relative to the number of Frenkel pairs produced in equivalent cascades in single crystals. The symbol colors represent the following: blue—vacancy numbers for PKAs initiated in the lower grain; red—interstitial numbers for PKAs initiated in the lower grain; purple—vacancy numbers for PKAs initiated in the upper grain; green—interstitial numbers for PKAs initiated in the upper grain. Reproduced with permission from Refs. [<a href="#B4-metals-11-01875" class="html-bibr">4</a>,<a href="#B36-metals-11-01875" class="html-bibr">36</a>]. Copyright 2021 American Physical Socity.</p>
Full article ">Figure 3
<p>Schematic of the absorption–emission–recombination process during the interaction between GB and the point defects, caused by collision cascades. Reproduced with permission from Ref. [<a href="#B25-metals-11-01875" class="html-bibr">25</a>]. Copyright 2021 Clearance Center.</p>
Full article ">Figure 4
<p>(<b>a</b>) Radiation-induced defect clusters and GB evolution in Σ5(210) Cu at different doses. (<b>b</b>) SFT annihilation process via interaction with a GB. Atoms are color coded according to their structures (red—hexagonal close-packed (HCP); blue—body-centered cubic (BCC); grey—other structure, face-centered cubic (FCC); atoms not shown). Reproduced with permission from Ref. [<a href="#B66-metals-11-01875" class="html-bibr">66</a>]. Copyright 2021 Clearance Center.</p>
Full article ">Figure 5
<p>Snapshots of the atomic images before and after the interaction between SFT and different GBs at 10 K. (<b>a1</b>,<b>a2</b>) Σ5(310) GB; (<b>b1</b>,<b>b2</b>) Σ5(210) GB; (<b>c1</b>,<b>c2</b>) Σ37(750) GB; and (<b>d1</b>,<b>d2</b>) Σ61(650) GB. The atoms are colored according to centrosymmetry value, FCC atoms not shown. Reproduced with permission from Ref. [<a href="#B73-metals-11-01875" class="html-bibr">73</a>]. Copyright 2021 Clearance Center.</p>
Full article ">Figure 6
<p>(<b>a</b>–<b>f</b>) Atomic view of interaction between the migrating Σ5(310) GB and a void at different simulation time. The atoms on the void surface are colored in yellow and the structural units are outlined by the yellow solid lines. Atoms are color coded according to their structures (blue—FCC; red—other structure). Reproduced with permission from Ref. [<a href="#B74-metals-11-01875" class="html-bibr">74</a>]. Copyright 2021 Clearance Center.</p>
Full article ">Figure 7
<p>(<b>a</b>–<b>d</b>) Atomistic images showing the point defect cluster crossing a CTB at different simulation time during equilibration after radiation cascade. Atoms are color coded according to their structures (blue—BCC; red—HCP; cyan—other structure; FCC atoms not shown). Reproduced with permission from Ref. [<a href="#B82-metals-11-01875" class="html-bibr">82</a>]. Copyright 2021 Clearance Center.</p>
Full article ">Figure 8
<p>Schematics of the distortion and self-healing of a coherent twin boundary (CTB). (<b>a1</b>–<b>a3</b>) twin boundary captures interstitial atoms and becomes distortion. (<b>b1</b>–<b>b3</b>) twin boundary captures vacancies and becomes self-healing. Reproduced with permission from Ref. [<a href="#B81-metals-11-01875" class="html-bibr">81</a>]. Copyright 2015 American Chemical Society.</p>
Full article ">Figure 9
<p>(<b>a</b>) Schematic of self-healing mechanism, based on incoherent twin boundary (ITB). (<b>b</b>) Interaction between migrating ITB and SFTs. (<b>c</b>) Schematic of self-healing mechanism, based on interstitial atoms segregation. (<b>d</b>) Interaction between SFTs and defective CTBs with interstitial atom clusters. Atoms are color coded according to their structures (cyan—HCP; red—other structure; FCC atoms not shown). Reproduced with permission from Ref. [<a href="#B91-metals-11-01875" class="html-bibr">91</a>]. Copyright 2021 Clearance Center.</p>
Full article ">
11 pages, 2883 KiB  
Article
Investigation of the Extrapolation Capability of an Artificial Neural Network Algorithm in Combination with Process Signals in Resistance Spot Welding of Advanced High-Strength Steels
by Bassel El-Sari, Max Biegler and Michael Rethmeier
Metals 2021, 11(11), 1874; https://doi.org/10.3390/met11111874 - 22 Nov 2021
Cited by 11 | Viewed by 2652
Abstract
Resistance spot welding is an established joining process for the production of safety-relevant components in the automotive industry. Therefore, consecutive process monitoring is essential to meet the high quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals, [...] Read more.
Resistance spot welding is an established joining process for the production of safety-relevant components in the automotive industry. Therefore, consecutive process monitoring is essential to meet the high quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals, to ensure individual spot weld quality. The predictive accuracy of such algorithms depends on the provided training data set, and the prediction of untrained data is challenging. The aim of this paper was to investigate the extrapolation capability of a multi-layer perceptron model. That means, the predictive performance of the model was tested with data that clearly differed from the training data in terms of material and coating composition. Therefore, three multi-layer perceptron regression models were implemented to predict the nugget diameter from process data. The three models were able to predict the training datasets very well. The models, which were provided with features from the dynamic resistance curve predicted the new dataset better than the model with only process parameters. This study shows the beneficial influence of process signals on the predictive accuracy and robustness of artificial neural network algorithms. Especially, when predicting a data set from outside of the training space. Full article
(This article belongs to the Special Issue Quality Assessment and Process Management of Welded Joints)
Show Figures

Figure 1

Figure 1
<p>Experimental setup. (<b>a</b>) Schematic of the welding setup; (<b>b</b>) footage of the welding gun with a Rogowski coil and voltage sensors.</p>
Full article ">Figure 2
<p>Exemplary specimen after torsion testing: (<b>a</b>) weld nugget after torsion testing; (<b>b</b>) adhesive zone is represented by the blue ring, and the yellow circle marks the weld nugget.</p>
Full article ">Figure 3
<p>Typical DR curve for steel. The following features are marked: starting point (SP), peak no. 1 (P1), peak no. 2 (P2), end point (EP), and area (A) under the curve.</p>
Full article ">Figure 4
<p>Data overview. Green spots mark the measured diameters from supplier 1, and black spots from supplier 2.</p>
Full article ">Figure 5
<p>Predictive performance of the first model. Only process parameters were used as input for training: (<b>a</b>) scatter plot of the measured and predicted nugget diameters from dataset 1; (<b>b</b>) scatter plot of the measured and predicted nugget diameters from dataset 2. The bar charts show the predictive accuracy based on the prescribed deviation.</p>
Full article ">Figure 6
<p>Predictive performance of the second model. The training included manually extracted dynamic resistance features: (<b>a</b>) scatter plot of the measured and predicted nugget diameters from dataset 1; (<b>b</b>) scatter plot of the measured and predicted nugget diameters from dataset 2. The bar charts show the predictive accuracy based on the prescribed deviation.</p>
Full article ">Figure 7
<p>Predictive performance of the third model. The training included the dynamic resistance features extracted by ‘TSFRESH’: (<b>a</b>) scatter plot of the measured and predicted nugget diameters from dataset 1; (<b>b</b>) scatter plot of the measured and predicted nugget diameters from dataset 2. The bar charts show the predictive accuracy based on the prescribed deviation.</p>
Full article ">
16 pages, 5185 KiB  
Article
Improvement in the Resistance to Wear of Work-Rolls Used in Finishing Stands of the Hot Strip Mills
by Alberto Cofiño-Villar, Florentino Alvarez-Antolin and Carlos Hugo Alvarez-Perez
Metals 2021, 11(11), 1873; https://doi.org/10.3390/met11111873 - 21 Nov 2021
Cited by 1 | Viewed by 1629
Abstract
Work-rolls manufactured through the Indefinite Chill Double Poured (ICDP) method present an exterior work layer manufactured in a martensitic white cast iron alloyed with 4.5 %Ni, 1.7 %Cr, and 0.7 %Nb (wt.%). In its microstructure, there are abundant carbides of the type M [...] Read more.
Work-rolls manufactured through the Indefinite Chill Double Poured (ICDP) method present an exterior work layer manufactured in a martensitic white cast iron alloyed with 4.5 %Ni, 1.7 %Cr, and 0.7 %Nb (wt.%). In its microstructure, there are abundant carbides of the type M3C and MC, which give high resistance to wear, and graphite particles which improve the service behaviour of the rolls against thermal cycling. The core of the rolls is manufactured in grey cast iron of pearlitic matrix and spheroidal graphite. These work-rolls are used in the finishing stands in Hot Strip Mills for rolling slabs proceeding from continuous casting at 1200 °C. Through the application of a Design of Experiments (DoE), an attempt has been made to identify those manufacturing factors which have a significant effect on resistance to wear of these rolls and to find an optimal combination of levels of these factors which allow for improvement in resistance to wear. To increase resistance to wear, it is recommended to situate, simultaneously, the liquidus temperature and the percentage of Si in the respective ranges of 1250–1255 °C and 1.1–1.15 (wt.%). Higher liquidus temperatures favour the presence of the pro-eutectic constituent rather than the eutectic constituent. The outer zone of the work layer, in contact with the metal sheet, which is being rolled, does not show the graphitising effect of Si (0.8–1.15 wt.%). On the contrary, it confirms the hardening effect of the Si in solid solution of the ferrite. The addition of 0.02% of Mg (wt.%) and the inoculation of 6 kg/T of FeB tend to eliminate the graphitising effect of the Si, thus favouring that the undissolved carbon in the austenite is found to form carbides in contrast to the majority formation of graphite. Full article
Show Figures

Figure 1

Figure 1
<p>Manufacture by centrifugal casting: (<b>a</b>) casting of outer working layer; (<b>b</b>) casting of the core intended to achieve an optimal bond with the outer working layer; (<b>c</b>) casting of the remainder of the core and roll necks by gravity and static solidification.</p>
Full article ">Figure 2
<p>Analysis zones in the work layer.</p>
Full article ">Figure 3
<p>General microstructure of the work layer. (<b>a</b>) Experiment 1 in zone III; (<b>b</b>) experiment 3 in zone I; (<b>c</b>) experiment 4 in zone III; (<b>d</b>) experiment 7 in zone I.</p>
Full article ">Figure 3 Cont.
<p>General microstructure of the work layer. (<b>a</b>) Experiment 1 in zone III; (<b>b</b>) experiment 3 in zone I; (<b>c</b>) experiment 4 in zone III; (<b>d</b>) experiment 7 in zone I.</p>
Full article ">Figure 4
<p>Main phases and constituents. (<b>a</b>) Experiment 2 in zone I, ledeburite; (<b>b</b>) experiment 3 in zone III, graphite; (<b>c</b>) experiment 3 in zone I, carbides; (<b>d</b>) experiment 6 in zone I, carbides.</p>
Full article ">Figure 5
<p>Representation of the effects in a normal probability paper on Vol.% carbides. (<b>a</b>) Zone I; (<b>b</b>) zone III.</p>
Full article ">Figure 5 Cont.
<p>Representation of the effects in a normal probability paper on Vol.% carbides. (<b>a</b>) Zone I; (<b>b</b>) zone III.</p>
Full article ">Figure 6
<p>Graphic representation of wear in zone I (<b>a</b>) 250 °C. Representation of the effects on a normal probability paper; (<b>b</b>) 250 °C. Representation of the effects in a Pareto diagram; (<b>c</b>) 350 °C. Representation of the effects on a normal probability paper; (<b>d</b>) 350 °C. Representation of the effects in a Pareto diagram.</p>
Full article ">Figure 6 Cont.
<p>Graphic representation of wear in zone I (<b>a</b>) 250 °C. Representation of the effects on a normal probability paper; (<b>b</b>) 250 °C. Representation of the effects in a Pareto diagram; (<b>c</b>) 350 °C. Representation of the effects on a normal probability paper; (<b>d</b>) 350 °C. Representation of the effects in a Pareto diagram.</p>
Full article ">Figure 7
<p>Graphic representation of wear in zone III. (<b>a</b>) 250 °C, representation of effects on a normal probability paper. (<b>b</b>) 250 °C, representation of effects in a Pareto diagram; (<b>c</b>) 350 °C, representation of effects on a normal probability paper; (<b>d</b>) 350 °C, representation of effects in a Pareto diagram.</p>
Full article ">
16 pages, 1155 KiB  
Article
Error Uncertainty Analysis in Planar Closed-Loop Structure with Joint Clearances
by Yushu Yu, Jinglin Li, Xin Li and Yi Yang
Metals 2021, 11(11), 1872; https://doi.org/10.3390/met11111872 - 21 Nov 2021
Viewed by 1644
Abstract
For planar closed-loop structures with clearances, the angular and positional error uncertainties are studied. By using the vector translation method and geometric method, the boundaries of the errors are analyzed. The joint clearance is considered as being distributed uniformly in a circle area. [...] Read more.
For planar closed-loop structures with clearances, the angular and positional error uncertainties are studied. By using the vector translation method and geometric method, the boundaries of the errors are analyzed. The joint clearance is considered as being distributed uniformly in a circle area. A virtual link projection method is proposed to deal with the clearance affected length error probability density function (PDF) for open-loop links. The error relationship between open loop and closed loop is established. The open-loop length PDF and the closed-loop angular error PDF both approach being Gaussian distribution if there are many clearances. The angular propagation error of multi-loop structures is also investigated by using convolution. The positional errors of single and multiple loops are both discussed as joint distribution functions. Monte Carlo simulations are conducted to verify the proposed methods. Full article
(This article belongs to the Section Computation and Simulation on Metals)
Show Figures

Figure 1

Figure 1
<p>The geometrical representation of clearance joints.</p>
Full article ">Figure 2
<p>Two expression types of hinged joint with clearance. (<b>a</b>) Type 1. (<b>b</b>) Type 2.</p>
Full article ">Figure 3
<p>The closed-loop model with joint clearances.</p>
Full article ">Figure 4
<p>The multi-loop model with joint clearances.</p>
Full article ">Figure 5
<p>Equivalent <math display="inline"><semantics> <mi>β</mi> </semantics></math> after vector translations.</p>
Full article ">Figure 6
<p>The extremal configurations. (<b>a</b>) Maximum. (<b>b</b>) Minimum.</p>
Full article ">Figure 7
<p>Workspace of point <math display="inline"><semantics> <msub> <mi>C</mi> <mn>1</mn> </msub> </semantics></math>.</p>
Full article ">Figure 8
<p>The positional analysis for multi-loop structures.</p>
Full article ">Figure 9
<p>Area sections of <math display="inline"><semantics> <msub> <mi>F</mi> <mn>1</mn> </msub> </semantics></math> with 16 key points.</p>
Full article ">Figure 10
<p>Equivalent opposite link.</p>
Full article ">Figure 11
<p>Representation of equivalent linkage length.</p>
Full article ">Figure 12
<p>The PDF along axis <span class="html-italic">x</span>.</p>
Full article ">Figure 13
<p>The position of <math display="inline"><semantics> <msub> <mi>C</mi> <mn>1</mn> </msub> </semantics></math>.</p>
Full article ">Figure 14
<p>The calculation process.</p>
Full article ">Figure 15
<p>The probability density simulation of a clearance joint.</p>
Full article ">Figure 16
<p>The PDF <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <mi>X</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> along axis <span class="html-italic">x</span>.</p>
Full article ">Figure 17
<p>The PDFs along axis <span class="html-italic">x</span>. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mrow> <mn>1</mn> <mo>,</mo> <mn>2</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>X</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> curve and bar chart. (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>ρ</mi> <mrow> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>X</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> curve and bar chart.</p>
Full article ">Figure 18
<p>The angular error PDF of single closed-loop.</p>
Full article ">Figure 19
<p>The propagation angular error PDF of two closed-loops.</p>
Full article ">Figure 20
<p>The PDF of Point <math display="inline"><semantics> <msub> <mi>C</mi> <mn>1</mn> </msub> </semantics></math>. (<b>a</b>) Simulation result. (<b>b</b>) Theoretical result.</p>
Full article ">Figure 21
<p>The theoretical boundary of <math display="inline"><semantics> <msub> <mi>C</mi> <mn>1</mn> </msub> </semantics></math>.</p>
Full article ">Figure 22
<p>The simplified boundary and the simulation for point <math display="inline"><semantics> <msub> <mi>F</mi> <mn>1</mn> </msub> </semantics></math>.</p>
Full article ">Figure 23
<p>The fitting PDF pattern.</p>
Full article ">
17 pages, 11634 KiB  
Article
Early Crack Propagation in Single Tooth Bending Fatigue: Combination of Finite Element Analysis and Critical-Planes Fatigue Criteria
by Franco Concli, Lorenzo Maccioni, Lorenzo Fraccaroli and Luca Bonaiti
Metals 2021, 11(11), 1871; https://doi.org/10.3390/met11111871 - 21 Nov 2021
Cited by 15 | Viewed by 2826
Abstract
Mechanical components, such as gears, are usually subjected to variable loads that induce multiaxial non-proportional stress states, which in turn can lead to failure due to fatigue. However, the material properties are usually available in the forms of bending or shear fatigue limits. [...] Read more.
Mechanical components, such as gears, are usually subjected to variable loads that induce multiaxial non-proportional stress states, which in turn can lead to failure due to fatigue. However, the material properties are usually available in the forms of bending or shear fatigue limits. Multiaxial fatigue criteria can be used to bridge the gap between the available data and the actual loading conditions. However, different criteria could lead to different results. The main goal of this paper is to evaluate the accuracy of different criteria applied to real mechanical components. With respect to this, five different criteria based on the critical plane concept (i.e., Findley, Matake, McDiarmid, Papadopoulos, and Susmel) have been investigated. These criteria were selected because they not only assess the level of damage, but also predict the direction of crack propagation just after nucleation. Therefore, measurements (crack position and direction) on different fractured gear samples tested via Single Tooth Bending Fatigue (STBF) tests on two gear geometries were used as reference. The STBF configuration was numerically simulated via Finite Elements (FE) analyses. The results of FE were elaborated based on the above-mentioned criteria. The numerical results were compared with the experimental ones. The result of the comparison showed that all the fatigue criteria agree in identifying the most critical point. The Findley and Papadopulus criteria proved to be the most accurate in estimating the level of damage. The Susmel criterion turns out to be the most conservative one. With respect to the identification of the direction of early propagation of the crack, the Findley criterion revealed the most appropriate. Full article
(This article belongs to the Special Issue Computational Methods for Fatigue and Fracture)
Show Figures

Figure 1

Figure 1
<p>Components of <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="bold-italic">P</mi> <mi mathvariant="bold-italic">n</mi> </msub> <mrow> <mo>(</mo> <mrow> <msub> <mi>φ</mi> <mi>n</mi> </msub> <mo>,</mo> <msub> <mi>ϑ</mi> <mi>n</mi> </msub> <mo>,</mo> <mi>t</mi> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> on the plane <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">n</mi> <mrow> <mo>(</mo> <mrow> <msub> <mi>φ</mi> <mi>n</mi> </msub> <mo>,</mo> <msub> <mi>ϑ</mi> <mi>n</mi> </msub> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 2
<p><math display="inline"><semantics> <mi mathvariant="bold-italic">u</mi> </semantics></math> and <math display="inline"><semantics> <mi mathvariant="bold-italic">v</mi> </semantics></math> on the plane <math display="inline"><semantics> <mrow> <mi mathvariant="bold-italic">n</mi> <mrow> <mo>(</mo> <mrow> <msub> <mi>φ</mi> <mi>n</mi> </msub> <mo>,</mo> <msub> <mi>ϑ</mi> <mi>n</mi> </msub> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> and definition of the curve <math display="inline"><semantics> <mrow> <msub> <mi>Γ</mi> <mi>n</mi> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 3
<p>Minimum Circumscribed Circle (MCC) method.</p>
Full article ">Figure 4
<p>Cracks characteristics (χ, β) in experimental tests.</p>
Full article ">Figure 5
<p>Individuation of cracks characteristics (χ, β) in experimental tests performed on Gear A.</p>
Full article ">Figure 6
<p>Individuation of cracks characteristics (χ, β) in experimental tests performed on Gear B.</p>
Full article ">Figure 7
<p>Finite Element Model of the STBF of Gear A.</p>
Full article ">Figure 8
<p>Finite Element Model of the STBF of Gear B.</p>
Full article ">Figure 9
<p>Framework to elaborate the time-dependent stress tensor on each node implementing different fatigue criteria.</p>
Full article ">Figure 10
<p>Direction of the critical planes according to the different criteria studied at different nodes for Gear A. Numerical results in blue (segment length proportional to the damage parameter) and experimental results in red (segment length proportional to the damage parameter that lead to a unitary <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mi>F</mi> </msub> </mrow> </semantics></math>).</p>
Full article ">Figure 11
<p>Direction of the critical planes according to the different criteria studied at different nodes for Gear B. Numerical results in blue (segment length proportional to the damage parameter) and experimental results in red (segment length proportional to the damage parameter that lead to a unitary <math display="inline"><semantics> <mrow> <msub> <mi>S</mi> <mi>F</mi> </msub> </mrow> </semantics></math>).</p>
Full article ">
10 pages, 6928 KiB  
Article
Micromechanisms of Deformation and Fracture in Porous L-PBF 316L Stainless Steel at Different Strain Rates
by Nataliya Kazantseva, Pavel Krakhmalev, Mikael Åsberg, Yulia Koemets, Maxim Karabanalov, Denis Davydov, Igor Ezhov and Olga Koemets
Metals 2021, 11(11), 1870; https://doi.org/10.3390/met11111870 - 21 Nov 2021
Cited by 4 | Viewed by 2000
Abstract
The process of an unstable plastic flow associated with the strain rate sensitivity of mechanical properties was studied in porous 316L austenitic steel samples manufactured by laser powder bed fusion (L-PBF). Different micromechanisms of deformation and fracture of porous samples dependent on strain [...] Read more.
The process of an unstable plastic flow associated with the strain rate sensitivity of mechanical properties was studied in porous 316L austenitic steel samples manufactured by laser powder bed fusion (L-PBF). Different micromechanisms of deformation and fracture of porous samples dependent on strain rate were found. It was found that despite the porosity, the specimens showed high strength, which increased with the loading rate. Porosity led to lower ductility of the studied specimens, in comparison with literature data for low porous 316L L-PBF samples and resulted in de-localization of plastic deformation. With an increase in strain rate, nucleation of new pores was less pronounced, so that at the highest strain rate of 8 × 10−3 s−1, only pore coalescence was observed as the dominating microscopic mechanism of ductile fracture. Full article
Show Figures

Figure 1

Figure 1
<p>As-built state of 316L sample: (<b>a</b>) the X-ray diffractogram; (<b>b</b>) the microstructure and porosity; (<b>c</b>,<b>d</b>) SEM image.</p>
Full article ">Figure 2
<p>Microstructure of the as-build 316L sample, TEM: (<b>a</b>) dislocations, the bright-field image; (<b>b</b>) SAED pattern to (<b>a</b>), zone axis [110]γ; (<b>c</b>) twins; the dark-field image taken with twin reflex, twin plane (1−1); (<b>d</b>) SAED pattern to (<b>c</b>), zone axis [110]<sub>m</sub>||[−1−10]<sub>t</sub>.</p>
Full article ">Figure 3
<p>Tensile engineering stress–strain curves of the studied L-PBF samples, the deformation speed: 1—<math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; 2—1 <math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mtext> </mtext> <msup> <mi mathvariant="normal">s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>;</mo> </mrow> </semantics></math> 3—8<math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mtext> </mtext> <msup> <mi mathvariant="normal">s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 4
<p>The fracture surfaces and sub-fracture microstructures of the L-PBF 316L steel samples deformed with the different strain rates, (<b>a</b>,<b>c</b>,<b>e</b>) SEM images; (<b>b</b>,<b>d</b>,<b>f</b>) Electron backscattered SEM images: (<b>a</b>,<b>b</b>) <math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>c</b>,<b>d</b>) 1<math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>e</b>,<b>f</b>) 8<math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 4 Cont.
<p>The fracture surfaces and sub-fracture microstructures of the L-PBF 316L steel samples deformed with the different strain rates, (<b>a</b>,<b>c</b>,<b>e</b>) SEM images; (<b>b</b>,<b>d</b>,<b>f</b>) Electron backscattered SEM images: (<b>a</b>,<b>b</b>) <math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>c</b>,<b>d</b>) 1<math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>e</b>,<b>f</b>) 8<math display="inline"><semantics> <mrow> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 5
<p>The outer surface of the studied L-PBF samples near the fracture zone after deformation with the different strain rates, SEM images: (<b>a</b>) <math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>b</b>) 1 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>c</b>) 8 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 5 Cont.
<p>The outer surface of the studied L-PBF samples near the fracture zone after deformation with the different strain rates, SEM images: (<b>a</b>) <math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>b</b>) 1 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; (<b>c</b>) 8 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">Figure 6
<p>The pole figures with {111} and {100} zones obtained in the studied samples after deformation with the different strain rates, EBSD analysis: 1—<math display="inline"><semantics> <mrow> <mn>3</mn> <mo>×</mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>4</mn> </mrow> </msup> <msup> <mrow> <mrow> <mtext> </mtext> <mi mathvariant="normal">s</mi> </mrow> </mrow> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>; 2—1 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mtext> </mtext> <msup> <mi mathvariant="normal">s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> <mo>;</mo> </mrow> </semantics></math> 3—8 <math display="inline"><semantics> <mrow> <mo>×</mo> <mo> </mo> <msup> <mrow> <mn>10</mn> </mrow> <mrow> <mo>−</mo> <mn>3</mn> </mrow> </msup> <mtext> </mtext> <msup> <mi mathvariant="normal">s</mi> <mrow> <mo>−</mo> <mn>1</mn> </mrow> </msup> </mrow> </semantics></math>.</p>
Full article ">
15 pages, 608 KiB  
Article
Investigation on Vanadium Chemistry in Basic-Oxygen-Furnace (BOF) Slags—A First Approach
by Sophie Wunderlich, Thomas Schirmer and Ursula E. A. Fittschen
Metals 2021, 11(11), 1869; https://doi.org/10.3390/met11111869 - 20 Nov 2021
Cited by 6 | Viewed by 2035
Abstract
Basic oxygen furnace (BOF) slag accounts for the majority of all residual materials produced during steelmaking and may typically contain certain transition metals. Vanadium, in particular, came into focus in recent years because of its potential environmental toxicity as well as its economic [...] Read more.
Basic oxygen furnace (BOF) slag accounts for the majority of all residual materials produced during steelmaking and may typically contain certain transition metals. Vanadium, in particular, came into focus in recent years because of its potential environmental toxicity as well as its economic value. This study addresses the vanadium chemistry in BOF slags to better understand its recovery and save handling of the waste stream. The experimental results from the electron probe microanalysis (EPMA) study show that vanadium is preferably incorporated in calcium orthosilicate-like compounds (COS), with two variations occurring, a low vanadium COS (COS-Si) (approx. 1 wt.%), and a high vanadium COS (COS-V) (up to 18 wt.%). Additionally, vanadium is incorporated in dicalcium ferrite-like compounds (DFS) with an average amount of 3 wt.%. Using powder x-ray diffraction analysis (PXRD), EPMA, and virtual component models, stoichiometric formulas of the main vanadium-bearing phases were postulated. The stoichiometries give an estimate of the oxidation states of vanadium in the respective hosts. According to these results, trivalent vanadium is incorporated on the Fe-position in dicalcium ferrite solid solution (DFS), and V4+ and V5+ are incorporated on the Si-position of the COS. Full article
(This article belongs to the Special Issue Advances in Slag Metallurgy)
Show Figures

Figure 1

Figure 1
<p>BSE (Z) micrograph of analyzed BOF slag.</p>
Full article ">
34 pages, 8955 KiB  
Article
On the Microstructure and Properties of the Nb-23Ti-5Si-5Al-5Hf-5V-2Cr-2Sn (at.%) Silicide-Based Alloy—RM(Nb)IC
by Nikos Vellios, Paul Keating and Panos Tsakiropoulos
Metals 2021, 11(11), 1868; https://doi.org/10.3390/met11111868 - 20 Nov 2021
Cited by 13 | Viewed by 2385
Abstract
The microstructure, isothermal oxidation, and hardness of the Nb-23Ti-5Si-5Al-5Hf-5V-2Cr-2Sn alloy and the hardness and Young’s moduli of elasticity of its Nbss and Nb5Si3 were studied. The alloy was selected using the niobium intermetallic composite elaboration (NICE) alloy design methodology. [...] Read more.
The microstructure, isothermal oxidation, and hardness of the Nb-23Ti-5Si-5Al-5Hf-5V-2Cr-2Sn alloy and the hardness and Young’s moduli of elasticity of its Nbss and Nb5Si3 were studied. The alloy was selected using the niobium intermetallic composite elaboration (NICE) alloy design methodology. There was macrosegregation of Ti and Si in the cast alloy. The Nbss, αNb5Si3, γNb5Si3, and HfO2 phases were present in the as-cast or heat-treated alloy plus TiN in the near-the-surface areas of the latter. The vol.% of Nbss was about 80%. There were Ti- and Ti-and-Hf-rich areas in the solid solution and the 5-3 silicide, respectively, and there was a lamellar microstructure of these two phases. The V partitioned to the Nbss, where the solubilities of Al, Cr, Hf, and V increased with increasing Ti concentration. At 700, 800, and 900 °C, the alloy did not suffer from catastrophic pest oxidation; it followed parabolic oxidation kinetics in the former two temperatures and linear oxidation kinetics in the latter, where its mass change was the lowest compared with other Sn-containing alloys. An Sn-rich layer formed in the interface between the scale and the substrate, which consisted of the Nb3Sn and Nb6Sn5 compounds at 900 °C. The latter compound was not contaminated with oxygen. Both the Nbss and Nb5Si3 were contaminated with oxygen, with the former contaminated more severely than the latter. The bulk of the alloy was also contaminated with oxygen. The alloying of the Nbss with Sn increased its elastic modulus compared with Sn-free solid solutions. The hardness of the alloy, its Nbss, and its specific room temperature strength compared favourably with many refractory metal-complex-concentrated alloys (RCCAs). The agreement of the predictions of NICE with the experimental results was satisfactory. Full article
(This article belongs to the Special Issue Advanced Refractory Alloys)
Show Figures

Figure 1

Figure 1
<p>X-ray diffractograms of the alloy NV1 (<b>a</b>) as cast and (<b>b</b>) heat treated.</p>
Full article ">Figure 2
<p>BSE images of the microstructure of NV1. (<b>a</b>) and (<b>b</b>) as cast; (<b>c</b>) and (<b>d</b>) heat treated. (<b>a</b>) top and (<b>b</b>) bulk of NV1-AC, (<b>c</b>) near surface area of NV1-HT, and (<b>d</b>) bulk of NV1-HT. Analysis in (<b>b</b>) as follows. 1: 5-3 silicide 35.9Nb-18.8Ti-32.1Si-4.1Al-1Cr-6Hf-0.9Sn-1.2V, Nb/(Ti + Hf) = 1.45, &lt;Si&gt; = 37.1 at.%, 2: 5-3 silicide 33.7Nb-19.4Ti-33.1Si-3.9Al-0.6Cr-6.5Hf-0.8Sn-2V, Nb/(Ti + Hf) = 1.30, &lt;Si&gt; = 37.8 at.%, 3: 5-3 silicide 33.8Nb-20.8Ti-31.9Si-3.8Al-0Cr-7Hf-0.9Sn-1.8V, Nb/(Ti + Hf) = 1.22, &lt;Si&gt; = 36.6 at.%.</p>
Full article ">Figure 2 Cont.
<p>BSE images of the microstructure of NV1. (<b>a</b>) and (<b>b</b>) as cast; (<b>c</b>) and (<b>d</b>) heat treated. (<b>a</b>) top and (<b>b</b>) bulk of NV1-AC, (<b>c</b>) near surface area of NV1-HT, and (<b>d</b>) bulk of NV1-HT. Analysis in (<b>b</b>) as follows. 1: 5-3 silicide 35.9Nb-18.8Ti-32.1Si-4.1Al-1Cr-6Hf-0.9Sn-1.2V, Nb/(Ti + Hf) = 1.45, &lt;Si&gt; = 37.1 at.%, 2: 5-3 silicide 33.7Nb-19.4Ti-33.1Si-3.9Al-0.6Cr-6.5Hf-0.8Sn-2V, Nb/(Ti + Hf) = 1.30, &lt;Si&gt; = 37.8 at.%, 3: 5-3 silicide 33.8Nb-20.8Ti-31.9Si-3.8Al-0Cr-7Hf-0.9Sn-1.8V, Nb/(Ti + Hf) = 1.22, &lt;Si&gt; = 36.6 at.%.</p>
Full article ">Figure 3
<p>Details of lamellar microstructure and composition (at.%) of phases in the bulk of NV1-AC. (<b>a</b>) Analyses 1 to 6 as follows: 1: solid solution 42.8Nb-30.6Ti-1.7Si-5.9Al-4.1Cr-5.1Hf-2.9Sn-6.9V, 2: solid solution 38.1Nb-31.7Ti-2.2Si-5.7Al-6.1Cr-5.7Hf-2.7Sn-7.8V, 3: lamellar microstructure 39.2Nb-22.7Ti-19.7Si-4.4Al-1.1Cr-8.2Hf-1.3Sn-3.4V,&lt;Si&gt; = 25.4 at.%, 4: solid solution 58.5Nb-21.6Ti-2Si-5.2Al-1.9Cr-4.4Hf-2.3Sn-4.1V, 5: 5-3 silicide 23.1Nb-22.2Ti-35.3Si-3.2Al-0.7Cr-13.1Hf-0.5Sn-1.9V, Nb/(Ti + Hf) = 0.65, &lt;Si&gt; = 39 at.%, 6: 5-3 silicide 23Nb-21.9Ti-35.5Si-3.5Al-0.5Cr-13.3Hf-0.4Sn-1.9V, Nb/(Ti + Hf) = 0.65, &lt;Si&gt;= 39.4 at.%. (<b>b</b>) Analyses 1 to 8 as follows: 1: lamellar microstructure 40.2Nb-23.9Ti-17.5Si-4.6Al-1.3Cr-7.3Hf-1.6Sn-3.6V, &lt;Si&gt; = 23.7 at.%, 2: lamellar microstructure 39.2Nb-23.1Ti-18.6Si-4.8Al-1.2Cr-7.7Hf-1.6Sn-3.8V, &lt;Si&gt; = 25 at.%, 3: solid solution 40.2Nb-31.3Ti-1.5Si-6.1Al-5Cr-4.9Hf-3.1Sn-7.9V, 4: solid solution 48.5Nb-26.7Ti-2.5Si-5.4Al-3.9Cr-4.9Hf-2.6Sn-6.4V, 5: solid solution 60.3Nb-20.9Ti-1.8Si-5Al-1.3Cr-4.3Hf-2.3Sn-4.1V, 6: solid solution 41.7Nb-29.6Ti-2.6Si-5.8Al-4.3Cr-5.6Hf-2.8Sn-7.6V, 7: 5-3 silicide 22Nb-23Ti-35Si-3.6Al-0.7Cr-13Hf-0.4Sn-2.3V, Nb/(Ti + Hf) = 0.61, &lt;Si &gt; =39 at.%, 8: 5-3 silicide 24.5Nb-21.6Ti-35.5Si-3.6Al-0.4Cr-12.4Hf-0Sn-2V, Nb/(Ti + Hf) = 0.72, &lt;Si&gt; = 39.1 at.%, 9: 5-3 silicide 24.1Nb-22.1Ti-35.3Si-3.5Al-0.4Cr-12.4Hf-0.4Sn-1.8V, Nb/(Ti + Hf) = 0.7, &lt;Si&gt; = 39.2 at.%. (<b>c</b>) Analyses 1 to 8 as follows: 1: lamellar microstructure 40.1Nb-22.7Ti-18.3Si-4.7Al-1.3Cr-7.7Hf-1.6Sn-3.6V, &lt;Si&gt; = 24.6 at.%, 2: lamellar microstructure 38.7Nb-23Ti-20.1Si-4.4Al-1.1Cr-8Hf-1.4Sn-3.3V, &lt;Si&gt; = 25.9 at.%, 3: solid solution 38Nb-33.2Ti-1.5Si-5.5Al-6.6Cr-4.1Hf-3Sn-8.1V, 4: solid solution 38.3Nb-32Ti-2Si-5.8Al-5.8Cr-5Hf-3Sn-8.1V, 5: hafnia 34Hf-66O, 6: 5-3 silicide 25.6Nb-21.5Ti-35.3Si-3.4Al-0Cr-11.8Hf-0.4Sn-2V, Nb/(Ti + Hf) = 0.77, &lt;Si&gt; = 39.1 at.%, 7: 5-3 silicide 23.5Nb-22.4Ti-35.3Si-3.4Al-0Cr-12.6Hf-0.5Sn-2.3V, Nb/(Ti + Hf) = 0.67, &lt;Si&gt; = 39.2 at.%, 8: solid solution 59.7Nb-21.2Ti-2.3Si-4.8Al-1.4Cr-4Hf-2.3Sn-4.3V.</p>
Full article ">Figure 3 Cont.
<p>Details of lamellar microstructure and composition (at.%) of phases in the bulk of NV1-AC. (<b>a</b>) Analyses 1 to 6 as follows: 1: solid solution 42.8Nb-30.6Ti-1.7Si-5.9Al-4.1Cr-5.1Hf-2.9Sn-6.9V, 2: solid solution 38.1Nb-31.7Ti-2.2Si-5.7Al-6.1Cr-5.7Hf-2.7Sn-7.8V, 3: lamellar microstructure 39.2Nb-22.7Ti-19.7Si-4.4Al-1.1Cr-8.2Hf-1.3Sn-3.4V,&lt;Si&gt; = 25.4 at.%, 4: solid solution 58.5Nb-21.6Ti-2Si-5.2Al-1.9Cr-4.4Hf-2.3Sn-4.1V, 5: 5-3 silicide 23.1Nb-22.2Ti-35.3Si-3.2Al-0.7Cr-13.1Hf-0.5Sn-1.9V, Nb/(Ti + Hf) = 0.65, &lt;Si&gt; = 39 at.%, 6: 5-3 silicide 23Nb-21.9Ti-35.5Si-3.5Al-0.5Cr-13.3Hf-0.4Sn-1.9V, Nb/(Ti + Hf) = 0.65, &lt;Si&gt;= 39.4 at.%. (<b>b</b>) Analyses 1 to 8 as follows: 1: lamellar microstructure 40.2Nb-23.9Ti-17.5Si-4.6Al-1.3Cr-7.3Hf-1.6Sn-3.6V, &lt;Si&gt; = 23.7 at.%, 2: lamellar microstructure 39.2Nb-23.1Ti-18.6Si-4.8Al-1.2Cr-7.7Hf-1.6Sn-3.8V, &lt;Si&gt; = 25 at.%, 3: solid solution 40.2Nb-31.3Ti-1.5Si-6.1Al-5Cr-4.9Hf-3.1Sn-7.9V, 4: solid solution 48.5Nb-26.7Ti-2.5Si-5.4Al-3.9Cr-4.9Hf-2.6Sn-6.4V, 5: solid solution 60.3Nb-20.9Ti-1.8Si-5Al-1.3Cr-4.3Hf-2.3Sn-4.1V, 6: solid solution 41.7Nb-29.6Ti-2.6Si-5.8Al-4.3Cr-5.6Hf-2.8Sn-7.6V, 7: 5-3 silicide 22Nb-23Ti-35Si-3.6Al-0.7Cr-13Hf-0.4Sn-2.3V, Nb/(Ti + Hf) = 0.61, &lt;Si &gt; =39 at.%, 8: 5-3 silicide 24.5Nb-21.6Ti-35.5Si-3.6Al-0.4Cr-12.4Hf-0Sn-2V, Nb/(Ti + Hf) = 0.72, &lt;Si&gt; = 39.1 at.%, 9: 5-3 silicide 24.1Nb-22.1Ti-35.3Si-3.5Al-0.4Cr-12.4Hf-0.4Sn-1.8V, Nb/(Ti + Hf) = 0.7, &lt;Si&gt; = 39.2 at.%. (<b>c</b>) Analyses 1 to 8 as follows: 1: lamellar microstructure 40.1Nb-22.7Ti-18.3Si-4.7Al-1.3Cr-7.7Hf-1.6Sn-3.6V, &lt;Si&gt; = 24.6 at.%, 2: lamellar microstructure 38.7Nb-23Ti-20.1Si-4.4Al-1.1Cr-8Hf-1.4Sn-3.3V, &lt;Si&gt; = 25.9 at.%, 3: solid solution 38Nb-33.2Ti-1.5Si-5.5Al-6.6Cr-4.1Hf-3Sn-8.1V, 4: solid solution 38.3Nb-32Ti-2Si-5.8Al-5.8Cr-5Hf-3Sn-8.1V, 5: hafnia 34Hf-66O, 6: 5-3 silicide 25.6Nb-21.5Ti-35.3Si-3.4Al-0Cr-11.8Hf-0.4Sn-2V, Nb/(Ti + Hf) = 0.77, &lt;Si&gt; = 39.1 at.%, 7: 5-3 silicide 23.5Nb-22.4Ti-35.3Si-3.4Al-0Cr-12.6Hf-0.5Sn-2.3V, Nb/(Ti + Hf) = 0.67, &lt;Si&gt; = 39.2 at.%, 8: solid solution 59.7Nb-21.2Ti-2.3Si-4.8Al-1.4Cr-4Hf-2.3Sn-4.3V.</p>
Full article ">Figure 4
<p>Mass change versus time of the alloys NV1, NV3, NV4, NV5, NV6, and NV8 at (<b>a</b>) 700 °C, (<b>b</b>) 800 °C, and (<b>c</b>) 900 °C. Ranking of alloys from best to worst oxidation in (<b>a</b>) NV4, NV5, NV8, NV6, NV3, NV1, and MASC; (<b>b</b>) NV5, NV8, NV4, NV1, NV6, MASC, and NV3; and (<b>c</b>) NV1, NV3, NV4, NV5, NV6, MASC, and NV8.</p>
Full article ">Figure 4 Cont.
<p>Mass change versus time of the alloys NV1, NV3, NV4, NV5, NV6, and NV8 at (<b>a</b>) 700 °C, (<b>b</b>) 800 °C, and (<b>c</b>) 900 °C. Ranking of alloys from best to worst oxidation in (<b>a</b>) NV4, NV5, NV8, NV6, NV3, NV1, and MASC; (<b>b</b>) NV5, NV8, NV4, NV1, NV6, MASC, and NV3; and (<b>c</b>) NV1, NV3, NV4, NV5, NV6, MASC, and NV8.</p>
Full article ">Figure 5
<p>The oxidised specimens of the alloys NV1 (top row) and MASC (bottom row) at 700, 800, and 900 °C.</p>
Full article ">Figure 6
<p>X-ray diffractogram of the oxides formed on NV1 after isothermal oxidation in static air at 900 °C for 100 h.</p>
Full article ">Figure 7
<p>BSE images of the microstructure of NV1 after isothermal oxidation at 800 °C. (<b>a</b>) Oxide scale, interface between scale and substrate and bulk of oxidised specimen, 1 scale, 2–8 Nb<sub>ss</sub>, Nb<sub>5</sub>Si<sub>3</sub> is the bright contrast phase. (<b>b</b>) Oxide scale and interface between scale and substrate, 1–3 and 11 Nb<sub>5</sub>Si<sub>3</sub>, 4 to 9 Nb<sub>ss</sub>, 10 and 13 Si-rich oxide, 12 Nb- and Ti-rich oxide; the thin white contrast phase at the interface of Nb-and-Ti-rich oxide with Nb<sub>ss</sub> on the left-hand side of analysis 11 is the Sn-rich phase; see text. (<b>c</b>) Bulk microstructure: 1 Nb<sub>ss</sub>; 2 oxidised Nb<sub>ss</sub>; 3, 4 oxidised lamellar microstructure; 5 Nb<sub>5</sub>Si<sub>3</sub>. (<b>d</b>) Bulk microstructure: 1, 3 Nb<sub>ss</sub>; 2, 7 Nb<sub>5</sub>Si<sub>3</sub>; 5, 6 oxidised lamellar microstructure.</p>
Full article ">Figure 7 Cont.
<p>BSE images of the microstructure of NV1 after isothermal oxidation at 800 °C. (<b>a</b>) Oxide scale, interface between scale and substrate and bulk of oxidised specimen, 1 scale, 2–8 Nb<sub>ss</sub>, Nb<sub>5</sub>Si<sub>3</sub> is the bright contrast phase. (<b>b</b>) Oxide scale and interface between scale and substrate, 1–3 and 11 Nb<sub>5</sub>Si<sub>3</sub>, 4 to 9 Nb<sub>ss</sub>, 10 and 13 Si-rich oxide, 12 Nb- and Ti-rich oxide; the thin white contrast phase at the interface of Nb-and-Ti-rich oxide with Nb<sub>ss</sub> on the left-hand side of analysis 11 is the Sn-rich phase; see text. (<b>c</b>) Bulk microstructure: 1 Nb<sub>ss</sub>; 2 oxidised Nb<sub>ss</sub>; 3, 4 oxidised lamellar microstructure; 5 Nb<sub>5</sub>Si<sub>3</sub>. (<b>d</b>) Bulk microstructure: 1, 3 Nb<sub>ss</sub>; 2, 7 Nb<sub>5</sub>Si<sub>3</sub>; 5, 6 oxidised lamellar microstructure.</p>
Full article ">Figure 8
<p>(<b>a</b>) Bright contrast layer at the interface between oxide scale and substrate. (<b>b</b>) Sn X-ray map. (<b>c</b>) Oxygen X-ray map. (<b>d</b>) Line scan showing thin layer to be rich in Sn.</p>
Full article ">Figure 9
<p>Sn-rich layer formed at the interface between oxide scale and NV1 substrate at 900 °C. Analysis point 1 is on the right-hand side of the bright contrast layer and corresponds to Nb<sub>6</sub>Sn<sub>5</sub>, whereas the analysis point 6 is on the left-hand side of the point 1 and corresponds to Nb<sub>3</sub>Sn. Notice the heavily oxidised areas of Ti-rich Nb<sub>ss</sub> in the subscale microstructure.</p>
Full article ">Figure 10
<p>Data for (<b>b</b>) modulus and (<b>c</b>) hardness of Nb<sub>ss</sub> and Nb<sub>5</sub>Si<sub>3</sub> in NV1-AC for (<b>a</b>) a nano-indentation line scan crossing a Nb<sub>5</sub>Si<sub>3</sub> grain located between two Nb<sub>ss</sub> grains. The three smaller nano-indentations on the left-hand side of (<b>a</b>) above the row of lager nano-indentations were produced with a load of 4000 μN.</p>
Full article ">Figure 11
<p>Data for (<b>b</b>) modulus and (<b>c</b>) hardness of Nb<sub>ss</sub> and Nb<sub>5</sub>Si<sub>3</sub> in NV1-HT for (<b>a</b>) a nanoindentation line scan crossing a Nb<sub>5</sub>Si<sub>3</sub> grain located between two Nb<sub>ss</sub> grains.</p>
Full article ">
8 pages, 2909 KiB  
Article
One-Step Electrodeposition of Superhydrophobic Coating on 316L Stainless Steel
by Andrea Zaffora, Francesco Di Franco, Bartolomeo Megna and Monica Santamaria
Metals 2021, 11(11), 1867; https://doi.org/10.3390/met11111867 - 20 Nov 2021
Cited by 11 | Viewed by 2413
Abstract
Superhydrophobic coatings were fabricated through a one-step electrochemical process onto the surface of 316L stainless steel samples. The presence of hierarchical structures at micro/nanoscale and manganese stearate into the coatings gave superhydrophobicity to the coating, with contact angle of ~160°, and self-cleaning ability. [...] Read more.
Superhydrophobic coatings were fabricated through a one-step electrochemical process onto the surface of 316L stainless steel samples. The presence of hierarchical structures at micro/nanoscale and manganese stearate into the coatings gave superhydrophobicity to the coating, with contact angle of ~160°, and self-cleaning ability. Corrosion resistance of 316L samples was also assessed also after the electrodeposition process through Electrochemical Impedance Spectra recorded in an aqueous solution mimicking seawater condition. Full article
(This article belongs to the Special Issue Corrosion and Protection of Stainless Steels)
Show Figures

Figure 1

Figure 1
<p>Contact angle values, as function of electrodeposition time, for SS samples after the electrodeposition process using two different solvents with (<b>a</b>) mirror-like and (<b>b</b>) 2B G320 surface finishing.</p>
Full article ">Figure 2
<p>SEM micrographs of SS samples coated by using (<b>a</b>) DMSO and (<b>b</b>) Ethanol as solvent in the electrodeposition process. Inset: higher magnification SEM micrograph.</p>
Full article ">Figure 3
<p>FT-IR spectra of coated SS samples and stearic acid powder.</p>
Full article ">Figure 4
<p>Self-cleaning test of the SS samples with (<b>a</b>) mirror-like and (<b>b</b>) 2B G320 surface finishing before electrodeposition process.</p>
Full article ">Figure 5
<p>Self-cleaning test for SS samples treated in (<b>a</b>) DMSO-containing solution and in (<b>b</b>) ethanol-containing solution. (<b>c</b>) Self-cleaning test of the SS sample treated in ethanol-containing solution with an electrodeposition time of 20 s.</p>
Full article ">Figure 6
<p>EIS spectra, recorded at corrosion potential, in Nyquist representation related to SS 316L samples after electrodeposition process with different treatment times. Solvent used: (<b>a</b>) DMSO; (<b>b</b>) Ethanol. Continuous lines: fitting lines.</p>
Full article ">Figure 7
<p>Electrical equivalent circuit used to fit impedance spectra shown in <a href="#metals-11-01867-f006" class="html-fig">Figure 6</a>a,b.</p>
Full article ">
15 pages, 4925 KiB  
Article
Effect of La and Sc Co-Addition on the Mechanical Properties and Thermal Conductivity of As-Cast Al-4.8% Cu Alloys
by Zhao-Xi Song, Yuan-Dong Li, Wen-Jing Liu, Hao-Kun Yang, Yang-Jing Cao and Guang-Li Bi
Metals 2021, 11(11), 1866; https://doi.org/10.3390/met11111866 - 20 Nov 2021
Cited by 9 | Viewed by 2268
Abstract
The effects of La and La+Sc addition on mechanical properties and thermal conductivity of Al-4.8Cu alloy were comprehensively studied. The as-cast samples were characterized by optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD) and first-principles methods. The results reveal that the [...] Read more.
The effects of La and La+Sc addition on mechanical properties and thermal conductivity of Al-4.8Cu alloy were comprehensively studied. The as-cast samples were characterized by optical microscopy (OM), scanning electron microscopy (SEM), X-ray diffraction (XRD) and first-principles methods. The results reveal that the grain morphology of Al-4.8Cu alloy changes from dendrite to fine equiaxed grain with La, La+Sc addition. The average grain size of Al-Cu-La (Al-4.8Cu-0.4La) and Al-Cu-La-Sc (Al-4.8Cu-0.4La-0.4Sc) decreased by 37.2% (70.36 μm) and 63.3% (119.64 μm) respectively compared with Al-Cu (Al-4.8Cu). Al-Cu-La has the highest elongation among the three which is 34.4% (2.65%) higher than Al-Cu. Al-Cu-La-Sc has the highest ultimate tensile strength and yield strength which are 55.1% (80.9 MPa) and 65.2% (62.1 MPa) higher than Al-Cu, respectively. The thermal conductivity of Al-Cu-La and Al-Cu-La-Sc is 10.0% (18.797 W·m−1·k−1) and 6.5% (12.178 W·m−1·k−1) higher than Al-Cu alloy respectively. Compared with Al-Cu, Al-Cu-La has less shrinkage and porosity, the presence of Al4La and AlCu3 contribute a lot to the decrease of specific heat capacity and the increase of plasticity and toughness. The porosity of Al-Cu-La-Sc does not significantly decrease compared with Al-Cu-La, the presence of Al3Sc and AlCuSc bring about the increase of specific heat capacity and brittleness. Full article
(This article belongs to the Special Issue Processing, Microstructure and Mechanical Properties of Alloys)
Show Figures

Figure 1

Figure 1
<p>Representative OM images of the as-cast (<b>a</b>) Al-Cu, (<b>b</b>) Al-Cu-La, (<b>c</b>) Al-Cu-La-Sc alloys.</p>
Full article ">Figure 2
<p>Map and point analysis of Al-Cu-La alloy (<b>a</b>) Backscattered electron image, (<b>b</b>) Image of Al, (<b>c</b>) Image of Cu, (<b>d</b>) Image of La, (<b>e</b>) Point analysis.</p>
Full article ">Figure 3
<p>Map and point analysis of Al-Cu-La-Sc alloy (<b>a</b>) Backscattered electron image, (<b>b</b>) Image of Al, (<b>c</b>) Image of Cu, (<b>d</b>) Image of La, (<b>e</b>) Image of Sc, (<b>f</b>) Point analysis.</p>
Full article ">Figure 3 Cont.
<p>Map and point analysis of Al-Cu-La-Sc alloy (<b>a</b>) Backscattered electron image, (<b>b</b>) Image of Al, (<b>c</b>) Image of Cu, (<b>d</b>) Image of La, (<b>e</b>) Image of Sc, (<b>f</b>) Point analysis.</p>
Full article ">Figure 4
<p>The mechanical properties (<b>a</b>) and engineering stress-strain curves (<b>b</b>) of Al-Cu, Al-Cu-La, Al-Cu-La-Sc alloys.</p>
Full article ">Figure 5
<p>Properties of thermal conductivity of Al-Cu, Al-Cu-La, Al-Cu-La-Sc alloys: (<b>a</b>) Thermal conductivity, (<b>b</b>) Specific heat capacity and Thermal diffusivity.</p>
Full article ">Figure 6
<p>Fracture morphology of (<b>a</b>), (<b>d</b>) Al-Cu; (<b>b</b>), (<b>e</b>) Al-Cu-La; (<b>c</b>), (<b>f</b>) Al-Cu-La-Sc alloys. (<b>g</b>) Effect of pores on fracture morphology.</p>
Full article ">Figure 6 Cont.
<p>Fracture morphology of (<b>a</b>), (<b>d</b>) Al-Cu; (<b>b</b>), (<b>e</b>) Al-Cu-La; (<b>c</b>), (<b>f</b>) Al-Cu-La-Sc alloys. (<b>g</b>) Effect of pores on fracture morphology.</p>
Full article ">Figure 7
<p>XRD patterns and α-Al lattice constants of Al-Cu, Al-Cu-La, Al-Cu-La-Sc alloys.</p>
Full article ">Figure 8
<p>Variation trend of specific heat capacity of (<b>a</b>) Al-Cu, (<b>b</b>) Al-Cu-La, (<b>c</b>) Al-Cu-La-Sc alloys with temperature in equilibrium solidification state.</p>
Full article ">Figure 9
<p>The ratio of measured density to ideal density of Al-Cu, Al-Cu-La, Al-Cu-La-Sc alloys.</p>
Full article ">Figure 10
<p>DSC curves of Al-Cu, Al-Cu-La, Al-Cu-La-Sc alloys.</p>
Full article ">Figure 11
<p>Intergranular morphology of (<b>a</b>) Al-Cu, (<b>b</b>) Al-Cu-La, (<b>c</b>) Al-Cu-La-Sc alloys.</p>
Full article ">Figure 12
<p>Crystal structure model of intermetallic compounds. (<b>a</b>) Al<sub>2</sub>Cu, (<b>b</b>) AlCu<sub>3</sub>, (<b>c</b>) Al<sub>4</sub>La, (<b>d</b>) Al<sub>3</sub>Sc, (<b>e</b>) AlCuSc.</p>
Full article ">Figure 13
<p>Vibrational heat capacity of different phases at 0–1000 K.</p>
Full article ">
20 pages, 5723 KiB  
Article
Physicomechanical Nature of Acoustic Emission Preceding Wire Breakage during Wire Electrical Discharge Machining (WEDM) of Advanced Cutting Tool Materials
by Sergey N. Grigoriev, Petr M. Pivkin, Mikhail P. Kozochkin, Marina A. Volosova, Anna A. Okunkova, Artur N. Porvatov, Alexander A. Zelensky and Alexey B. Nadykto
Metals 2021, 11(11), 1865; https://doi.org/10.3390/met11111865 - 19 Nov 2021
Cited by 20 | Viewed by 2625
Abstract
The field of applied wire electrical discharge machining (WEDM) is rapidly expanding due to rapidly increasing demand for parts made of hard-to-machine materials. Hard alloys composed of WC, TiC and Co are advanced cutting materials widely used in industry due to the excellent [...] Read more.
The field of applied wire electrical discharge machining (WEDM) is rapidly expanding due to rapidly increasing demand for parts made of hard-to-machine materials. Hard alloys composed of WC, TiC and Co are advanced cutting materials widely used in industry due to the excellent combination of hardness and toughness, providing them obvious advantages over other cutting materials, such as cubic boron nitride, ceramics, diamond or high-speed steel. A rational choice of the WEDM modes is extremely important to ensure the dimensional quality of the manufactured cutting inserts, while roughness of the machined surface on the cutting edge is of great importance with regards to the application of wear-resistant coatings, which increases tool life. However, the stock control systems of CNC WEDM machines, which are based on assessment of electrical parameters such as amperage and voltage, are unable to timely detect conditions at which a threat of wire breakage appears and to prevent wire breakage by stopping the electrode feed and flushing out the interelectrode gap (IEG) when hard alloys with high heat resistance and low heat conductivity, such as WC, TiC and Co composites, are being machined, due to the inability to distinguish the working pulses and pulses that expend a part of their energy heating and removing electroerosion products contaminating the working zone. In this paper, the physicomechanical nature of the WEDM of hard alloy WC 88% + TiC 6% + Co 6% was investigated, and the possibility of using acoustic emission parameters for controlling WEDM stability and productivity were explored. Acoustic emission (AE) signals were recorded in octave bands with central frequencies of 1–3 and 10–20 kHz. It was found that at the initial moment, when the dielectric fluid is virtually free of contaminants, the amplitude of the high-frequency component of the VA signal has its highest value. However, as the contamination of the working zone by electroerosion products increases, the amplitude of the high-frequency component of the AE signal decreases while the low-frequency component increases in an octave of 1–3 kHz. By the time of the wire breakage, the amplitude of the high-frequency component in the octave of 10–20 kHz had reduced by more than 5-fold, the amplitude of the low-frequency component in the octave of 1–3 kHz had increased by more than 2-fold, and their ratio, coefficient Kf, decreased by 12-fold. To evaluate the efficiency of Kf as a diagnostic parameter, the quality of the surface being machined was investigated. The analysis of residual irregularities on the surface at the electrode breakage point showed the presence of deep cracks and craters typical of short-circuit machining. It was also found that the workpiece surface was full of deposits/sticks, whose chemical composition was identical to that of the wire material. The presence of the deposits evidenced heating and melting of the wire due to the increased concentration of contaminants causing short circuits. It was also shown that the wire breakage was accompanied by the “neck” formation, which indicated simultaneous impacts of the local heating of the wire material and tensile forces. Due to the elevated temperature, the mechanical properties the wire material are quickly declining, a “neck” is being formed, and, finally, the wire breaks. At the wire breakage point, sticks/deposits of the workpiece material and electroerosion products were clearly visible, which evidenced a partial loss of the pulses’ energy on heating the electroerosion products and electrodes. A further increase in the contamination level led to short circuits and subsequent breakage of the wire electrode. It was shown that in contrast to the conventional controlling scheme, which is based on the assessment of amperage and voltage only, the analysis of VA signals clearly indicates the risk of wire breakage due to contamination of the working zone, discharge localization and subsequent short circuits. The monotonic dependence of WEDM productivity on AE parameters provides the possibility of adaptive adjustment of the wire electrode feed rate to the highest WEDM productivity at a given contamination level. As the concentration of contaminants increases, the feed rate of the wire electrode should decrease until the critical value of the diagnostic parameter Kf, at which the feed stops and the IEG flushes out, is reached. The link between the AE signals and physicomechanical nature of the WEDM of advanced cutting materials with high heat resistance and low heat conductivity in different cutting modes clearly shows that the monitoring of AE signals can be used as a main or supplementary component of control systems for CNC WEDM machines. Full article
Show Figures

Figure 1

Figure 1
<p>Temperature fields during WEDM in the cases of (<b>a</b>) uniform distribution of discharges over the treated surface; and (<b>b</b>) localization of discharges in a relatively small area. Symbols 1, 2 and 3 denote zones of the electrode-tool, electrode-workpiece and interelectrode gap with the dielectric fluid, respectively.</p>
Full article ">Figure 2
<p>Dependence of the material removal rate (MRR) of the EDM process and the number (percentage of the maximum) of working pulses <span class="html-italic">n<sub>w</sub></span>, idle pulses <span class="html-italic">n<sub>i</sub></span> and short-circuit pulses <span class="html-italic">n<sub>sc</sub></span> on the IEG parameter <span class="html-italic">δ.</span></p>
Full article ">Figure 3
<p>Working area of the Agie Charmilles CUT 1000 OilTech machine with installed accelerometers: 1—electrode- workpiece; 2—electrode- tool; 3—accelerometer and acoustic emission sensors.</p>
Full article ">Figure 4
<p>Comparison of the spectra of AE signals during the processing of hard alloy: the beginning of cutting (1) and just before the breakage of the wire electrode (2): (<b>a</b>) detailed amplitude spectra; (<b>b</b>) 1/3 octave bands with numbers showing the central frequencies of 1/3 octave bands.</p>
Full article ">Figure 5
<p>Changes in the RMS amplitudes of the AE signals in the range of 10–20 kHz (curve 1, (<b>a</b>)), current (curve 2 (<b>a</b>)) and the transfer coefficient Kt (curve 3 (<b>b</b>)) during the period between beginning of operation and the electrode breakage.</p>
Full article ">Figure 6
<p>RMS amplitudes of the AE signals during the solid carbide segment in the frequency ranges. Curve 1: 1–3 kHz, curve 2: 10–20 kHz (<b>a</b>); curve 3: the change in the ratio of lf to hf amplitudes (coefficient Kf) (<b>b</b>).</p>
Full article ">Figure 7
<p>Wire breakage and the “neck” diameter reduced several fold due to melting.</p>
Full article ">Figure 8
<p>Microtexture of the surface being processed. At the initial moment of operation (low concentration of contaminants) (<b>a</b>), and just before the wire breakage (critical level of contamination) (<b>b</b>).</p>
Full article ">Figure 8 Cont.
<p>Microtexture of the surface being processed. At the initial moment of operation (low concentration of contaminants) (<b>a</b>), and just before the wire breakage (critical level of contamination) (<b>b</b>).</p>
Full article ">Figure 9
<p>The surface being machined at the moment of wire breakage: (<b>a</b>) a photo of the surface at the moment of wire breakage; (<b>b</b>) elemental quantitative EDX analysis of the wire melting and breakage zone.</p>
Full article ">Figure 10
<p>The dependence of EDM productivity (<math display="inline"><semantics> <mrow> <mi>MRR</mi> <mo>=</mo> <mi mathvariant="normal">f</mi> <mrow> <mo>(</mo> <mrow> <mi mathvariant="sans-serif">γ</mi> <mo>,</mo> <mi mathvariant="sans-serif">δ</mi> </mrow> <mo>)</mo> </mrow> <mo stretchy="false">)</mo> </mrow> </semantics></math> on the IEG and on the concentration of contaminants (γ<sub>1</sub> &lt; γ<sub>2</sub> &lt; γ<sub>3</sub>).</p>
Full article ">
15 pages, 7616 KiB  
Article
Shearing Characteristics of Cu-Cu Joints Fabricated by Two-Step Process Using Highly <111>-Oriented Nanotwinned Cu
by Jia-Juen Ong, Dinh-Phuc Tran, Shih-Chi Yang, Kai-Cheng Shie and Chih Chen
Metals 2021, 11(11), 1864; https://doi.org/10.3390/met11111864 - 19 Nov 2021
Cited by 14 | Viewed by 2755
Abstract
Cu-Cu bonding has the potential to break through the extreme boundary of scaling down chips’ I/Os into the sub-micrometer scale. In this study, we investigated the effect of 2-step bonding on the shear strength and electrical resistance of Cu-Cu microbumps using highly <111>-oriented [...] Read more.
Cu-Cu bonding has the potential to break through the extreme boundary of scaling down chips’ I/Os into the sub-micrometer scale. In this study, we investigated the effect of 2-step bonding on the shear strength and electrical resistance of Cu-Cu microbumps using highly <111>-oriented nanotwinned Cu (nt-Cu). Alignment and bonding were achieved at 10 s in the first step, and a post-annealing process was further conducted to enhance its bonding strength. Results show that bonding strength was enhanced by 2–3 times after a post-annealing step. We found 50% of ductile fractures among 4548 post-annealed microbumps in one chip, while the rate was less than 20% for the as-bonded counterparts. During the post-annealing, interfacial grain growth and recrystallization occurred, and the bonding interface was eliminated. Ductile fracture in the form of zig-zag grain boundary was found at the original bonding interface, thus resulting in an increase in bonding strength of the microbumps. Full article
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Bonded test vehicle. (<b>b</b>) Layout of the tested vehicle. (<b>c</b>) Enlarged layout of the Kelvin structure at squared area at (<b>b</b>). (<b>d</b>) Schematic of the Kelvin structure in the tested vehicle.</p>
Full article ">Figure 2
<p>(<b>a</b>) Electrodeposition of nt-Cu microbumps by DC current on an 8-inch patterned wafer. The diameter of nt-Cu microbump is 30 µm and the pitch is 80 µm. (<b>b</b>) CMP process of 8” patterned wafers. The bump surface roughness (<span class="html-italic">R</span>q) is below 5 nm. (<b>c</b>) Schematic of test vehicles in this study: 6 × 6 mm<sup>2</sup> for top die and 15 × 15 mm<sup>2</sup> for bottom die. (<b>d</b>) Before the bonding process, bonding surface was cleaned by citric acid and rinsed by deionized water. (<b>e</b>) Each die was then dried with N<sub>2</sub> gas. (<b>f</b>) Top die and bottom die were set on the bonding head and stage to align by alignment marks. The first step bonding under 31 MPa, 47 MPa and 93 MPa compression at 300 °C within 10 s was performed in N<sub>2</sub> ambient.</p>
Full article ">Figure 3
<p>Cross-sections of (<b>a</b>) top die and (<b>b</b>) bottom die microbumps were analyzed by FIB. (<b>c</b>) Bonding surface orientation in normal direction of the nt-Cu microbumps analyzed by EBSD and calculated by OIM in around 40% of &lt;111&gt;-preferred orientation. (<b>d</b>) Cu microbumps before CMP. (<b>e</b>) Cu microbumps after CMP.</p>
Full article ">Figure 4
<p>Process profile of temperature and bonding force vs. bonding time in the first step with an applied bonding force of 93 MPa.</p>
Full article ">Figure 5
<p>(<b>a</b>) Cross-sectional FIB electron (<b>b</b>) ion images of the microbumps bonded at 93 MPa/10 s under 300 °C.</p>
Full article ">Figure 6
<p>Process profile of temperature and bonding force vs. bonding time in the first step with an applied bonding force of 47 MPa.</p>
Full article ">Figure 7
<p>(<b>a</b>) Cross-sectional FIB electron and (<b>b</b>) ion images of the microbumps bonded under 47 MPa/10 s at 300 °C.</p>
Full article ">Figure 8
<p>Process profile of temperature and bonding force vs. bonding time in the first step with an applied bonding force of 31 MPa.</p>
Full article ">Figure 9
<p>(<b>a</b>) Cross-sectional FIB electron and (<b>b</b>) ion images of the microbumps bonded under 31 MPa/10 s at 300 °C.</p>
Full article ">Figure 10
<p>Process profile of temperature and bonding force vs. bonding time under the second step (post-annealing) process.</p>
Full article ">Figure 11
<p>Cross-sectional FIB electron and ion images of the microbumps bonded under (<b>a</b>,<b>b</b>) 93 MPa/10 s, (<b>c</b>,<b>d</b>) 47 MPa/10 s, (<b>e</b>,<b>f</b>) 31 MPa/10 s. All samples were further heat-treated under 47 MPa/1 h/300 °C.</p>
Full article ">Figure 12
<p>Schematic of die shear test. Shear height was set at 200 µm and the shear speed was set at 100 µm/s.</p>
Full article ">Figure 13
<p>Shear strength of the as-bonded and post-annealed samples under various bonding conditions.</p>
Full article ">Figure 14
<p>(<b>a</b>) Brittle and (<b>b</b>) ductile fractures in the microbumps after die shear tests.</p>
Full article ">
16 pages, 6925 KiB  
Article
Effect of Ferritic Morphology on Yield Strength of CGHAZ in a Low Carbon Mo-V-N-Ti-B Steel
by Leping Wang, Huibing Fan, Genhao Shi, Qiuming Wang, Qingfeng Wang and Fucheng Zhang
Metals 2021, 11(11), 1863; https://doi.org/10.3390/met11111863 - 19 Nov 2021
Cited by 6 | Viewed by 1604
Abstract
For investigating the impact of ferritic morphology on yield strength (YS) of the high-heat-input welding induced coarse-grained heat-affected zone (CGHAZ) of a low carbon Mo-V-N-Ti-B steel, a group of particular welding heat inputs were designed to obtain different ferritic microstructures in CGHAZ. The [...] Read more.
For investigating the impact of ferritic morphology on yield strength (YS) of the high-heat-input welding induced coarse-grained heat-affected zone (CGHAZ) of a low carbon Mo-V-N-Ti-B steel, a group of particular welding heat inputs were designed to obtain different ferritic microstructures in CGHAZ. The tensile properties were estimated from typical samples with ferritic microstructures. The mixed microstructures dominated by the intragranular polygonal ferrite (IGPF), the intragranular acicular ferrite (IGAF), and the granular bainite (GB) were obtained at the heat inputs of 35, 65, 85 and 120 kJ/cm, respectively. When the main microstructure changed from IGPF to IGAF and GB, YS increased first and then decreased. The microstructure consisting mainly of IGAF possessed the maximum YS. As the main microstructure changed from IGPF to IGAF and GB, the contribution of grain refinement strengthening to YS was estimated to be elevated remarkably. This means the strength of CGHAZ in a low-carbon steel subjected to the high-heat-input welding could be enhanced by promoting the fine-grained AF and GB formation. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic diagram of the procedures of the thermal processing simulations.</p>
Full article ">Figure 2
<p>Schematical diagram of the lateral section of the simulated sample for the micro-tensile experiment (in mm).</p>
Full article ">Figure 3
<p>Stress-strain curves.</p>
Full article ">Figure 4
<p>Optical micrographs of the simulated samples of (<b>a</b>) 120 kJ/cm, (<b>b</b>) 85 kJ/cm, (<b>c</b>) 65 kJ/cm, and (<b>d</b>) 35 kJ/cm.</p>
Full article ">Figure 5
<p>The SHCCT diagram of thermal simulated simples.</p>
Full article ">Figure 6
<p>TEM micrographs of the microstructure of the simulated samples of (<b>a</b>) 120 kJ/cm, (<b>b</b>) 65 kJ/cm, and (<b>c</b>) 35 kJ/cm, and the M/A manifested by (<b>d</b>) bright field and (<b>e</b>) dark field, and (<b>f</b>) diffraction pattern of the selected area.</p>
Full article ">Figure 7
<p>TEM observation of the precipitates in the simulated samples of (<b>a</b>) 120 kJ/cm, (<b>b</b>) 85 kJ/cm, (<b>c</b>) 65 kJ/cm, and (<b>d</b>) 35 kJ/cm and their EDS analysis results.</p>
Full article ">Figure 8
<p>XRD spectra of the samples with different heat inputs from 120 to 35 kJ/cm.</p>
Full article ">Figure 9
<p>EBSD inverse pole figure for the simulated samples of (<b>a</b>) 120 kJ/cm, (<b>b</b>) 85 kJ/cm, (<b>c</b>) 65 kJ/cm, and (<b>d</b>) 35 kJ/cm with the white and black lines expressing the misorientation tolerance angle in the range of 2–15° and greater than 15°, respectively; image quality maps for the simulated samples of (<b>e</b>) 65 kJ/cm and (<b>f</b>) 35 kJ/cm with the red lines expressing the misorientation tolerance angle greater than or equal 2°.</p>
Full article ">Figure 10
<p>EBSD MED as functions of MTA and the heat input.</p>
Full article ">Figure 11
<p>Typical SEM micrograph of IGAF nucleating possibly at a (Ti,V)(C,N) particle (<b>a</b>) and EDS analysis of the corresponding particle (<b>b</b>).</p>
Full article ">Figure 12
<p>Function relationship between YS of samples at different heat inputs and the MED<sup>−1/2</sup> in the MTA range of 2–15°.</p>
Full article ">Figure 13
<p>Contribution rate of various strengthening factors to the yield strength.</p>
Full article ">
17 pages, 7710 KiB  
Article
A Comparative Investigation of Conventional and Hammering-Assisted Incremental Sheet Forming Processes for AA1050 H14 Sheets
by Harshal Y. Shahare, Abhay Kumar Dubey, Pavan Kumar, Hailiang Yu, Alexander Pesin, Denis Pustovoytov and Puneet Tandon
Metals 2021, 11(11), 1862; https://doi.org/10.3390/met11111862 - 19 Nov 2021
Cited by 5 | Viewed by 2502
Abstract
Incremental Sheet Forming (ISF) is emerging as one of the popular dieless forming processes for the small-sized batch production of sheet metal components. However, the parts formed by the ISF process suffer from poor surface finish, geometric inaccuracy, and non-uniform thinning, which leads [...] Read more.
Incremental Sheet Forming (ISF) is emerging as one of the popular dieless forming processes for the small-sized batch production of sheet metal components. However, the parts formed by the ISF process suffer from poor surface finish, geometric inaccuracy, and non-uniform thinning, which leads to poor part characteristics. Hammering, on the other hand, plays an important role in relieving residual stresses, and thus enhances the material properties through a change in grain structure. A few studies based on shot peening, one of the types of hammering operation, revealed that shot peening can produce nanostructure surfaces with different characteristics. This paper introduces a novel process, named the Incremental Sheet Hammering (ISH) process, i.e., integration of incremental sheet forming (ISF) process and hammering to improve the efficacy of the ISF process. Controlled hammering in the ISF process causes an alternating motion at the tool-sheet interface in the local deformation zone. This motion leads to enhanced material flow and subsequent improvement in the surface finish. Typical toolpath strategies are incorporated to impart the tool movement. The mechanics of the process is further explored through explicit-dynamic numerical models and experimental investigations on 1 mm thick AA1050 sheets. The varying wall angle truncated cone (VWATC) and constant wall angle truncated cone (CWATC) test geometries are identified to compare the ISF and ISH processes. The results indicate that the formability is improved in terms of wall angle, forming depth and forming limits. Further, ISF and ISH processes are compared based on the numerical and experimental results. The indicative statistical analysis is performed which shows that the ISH process would lead to an overall 10.99% improvement in the quality of the parts primarily in the surface finish and forming forces. Full article
(This article belongs to the Special Issue Physical Metallurgy of Light Alloys and Composite Materials)
Show Figures

Figure 1

Figure 1
<p>Schematics of incremental sheet hammering (ISH) process.</p>
Full article ">Figure 2
<p>Schematics of deformation of the workpiece based on linear tool movement with hammering.</p>
Full article ">Figure 3
<p>(<b>a</b>) Schematics of the overlapping region caused due to linear tool movement with hammering (<b>b</b>) Schematics of the basic hammering mechanics.</p>
Full article ">Figure 4
<p>Varying wall angle truncated cone (VWATC) test geometry.</p>
Full article ">Figure 5
<p>Toolpath for the VWATC for (<b>a</b>) ISF process and (<b>b</b>) ISH process.</p>
Full article ">Figure 6
<p>Constant wall angle truncated cone (CWATC) test geometry.</p>
Full article ">Figure 7
<p>Flow stress-strain curves at different strain rates of aluminum alloy AA1050.</p>
Full article ">Figure 8
<p>Numerical model used during simulation of ISF and ISH processes.</p>
Full article ">Figure 9
<p>Experimental setup consisting of (<b>a</b>) dieless manufacturing center (<b>b</b>) forming setup.</p>
Full article ">Figure 10
<p>(<b>a</b>) VWATC formed through ISF process and (<b>b</b>) VWATC formed through ISH process.</p>
Full article ">Figure 11
<p>(<b>a</b>) CWATC formed through ISF process, (<b>a’</b>) Scaled fracture section in CWATC formed through ISF process (<b>b</b>) CWATC formed through ISH process, (<b>b’</b>) Scaled fracture section in CWATC formed through ISH process.</p>
Full article ">Figure 12
<p>3D scanned CWATC components formed with (<b>a</b>) ISF process, (<b>b</b>) ISH process.</p>
Full article ">Figure 13
<p>Material thickness distribution along the sliced section in the formed CWATC component.</p>
Full article ">Figure 14
<p>Material thickness distribution obtained through numerical simulation for the (<b>a</b>) ISF process, (<b>b</b>) ISH process.</p>
Full article ">Figure 15
<p>Comparison of strain values for the components formed through ISF and ISH processes.</p>
Full article ">Figure 16
<p>Surface roughness profiles of components formed through (<b>a</b>) ISF process, (<b>b</b>) ISH process.</p>
Full article ">Figure 17
<p>Forming forces in Z direction during ISF and ISH processes.</p>
Full article ">Figure 18
<p>Experimental statistical analysis of the ISH process with respect to the ISF process.</p>
Full article ">Figure A1
<p>Flowchart of the generalized python code for CWATC.</p>
Full article ">
13 pages, 29693 KiB  
Article
Corrosion Inhibition Properties of Thiazolidinedione Derivatives for Copper in 3.5 wt.% NaCl Medium
by Hassane Lgaz, Sourav Kr. Saha, Han-seung Lee, Namhyun Kang, Fatima Zahra Thari, Khalid Karrouchi, Rachid Salghi, Khalid Bougrin and Ismat Hassan Ali
Metals 2021, 11(11), 1861; https://doi.org/10.3390/met11111861 - 19 Nov 2021
Cited by 10 | Viewed by 2714
Abstract
Copper is the third-most-produced metal globally due to its exceptional mechanical and thermal properties, among others. However, it suffers serious dissolution issues when exposed to corrosive mediums. Herein, two thiazolidinedione derivatives, namely, (Z)-5-(4-methylbenzylidene)thiazolidine-2,4-dione (MTZD) and (Z)-3-allyl-5-(4-methylbenzylidene)thiazolidine-2,4-dione (ATZD), were synthesized [...] Read more.
Copper is the third-most-produced metal globally due to its exceptional mechanical and thermal properties, among others. However, it suffers serious dissolution issues when exposed to corrosive mediums. Herein, two thiazolidinedione derivatives, namely, (Z)-5-(4-methylbenzylidene)thiazolidine-2,4-dione (MTZD) and (Z)-3-allyl-5-(4-methylbenzylidene)thiazolidine-2,4-dione (ATZD), were synthesized and applied for corrosion protection of copper in 3.5 wt.% NaCl medium. The corrosion inhibition performance of tested compounds was evaluated at different experimental conditions using electrochemical impedance spectroscopy (EIS), potentiodynamic polarization curves (PPC) and atomic force microscopy (AFM). EIS results revealed that the addition of studied inhibitors limited the dissolution of copper in NaCl solution, leading to a high polarization resistance compared with the blank solution. In addition, PPC suggested that tested compounds had a mixed-type effect, decreasing anodic and cathodic corrosion reactions. Moreover, surface characterization by AFM indicated a significant decrease in surface roughness of copper after the addition of inhibitors. Outcomes from the present study suggest that ATZD (IE% = 96%) outperforms MTZD (IE% = 90%) slightly, due to the presence of additional –C3H5 unit (–CH2–CH = CH2) in the molecular scaffold of MTZD. Full article
(This article belongs to the Special Issue Surface Coating with Organic-Inorganic Hybrid Materials on Metals)
Show Figures

Figure 1

Figure 1
<p>EIS data for copper in 3.5 wt.% NaCl without and with various concentrations of thiazolidinedione derivatives at 298 K; (<b>a</b>,<b>b</b>) Nyquist plots, (<b>c</b>,<b>d</b>) Bode modulus/Phase angle plots.</p>
Full article ">Figure 2
<p>Electrical equivalent circuits used to fit the EIS data; (<b>a</b>) blank medium, (<b>b</b>) with inhibitors.</p>
Full article ">Figure 3
<p>EIS data for copper in 3.5 wt.% NaCl with 150 ppm of ATZD at 298 K and different immersion times; (<b>a</b>) Nyquist and (<b>b</b>) Bode plots.</p>
Full article ">Figure 4
<p>PPC of copper in 3.5 wt.% NaCl without and with various concentrations of thiazolidinedione derivatives at 298 K; (<b>a</b>): ATZD, (<b>b</b>): MTZD.</p>
Full article ">Figure 5
<p>Langmuir’s isotherm plots for adsorption of inhibitors on copper surface in 3.5 wt.% NaCl at 298 K temperature.</p>
Full article ">Figure 6
<p>AFM results of copper in 3.5 wt.% NaCl without and with 150 ppm of ATZD at 298 K; (<b>a</b>,<b>b</b>): 3D, (<b>c</b>,<b>d</b>): 2D, and (<b>e</b>,<b>f</b>): Roughness of selected area.</p>
Full article ">Scheme 1
<p>General procedure for the synthesis of compounds 3 (MTZD) and 4 (ATZD).</p>
Full article ">
18 pages, 7891 KiB  
Article
Thermographic Analysis of Composite Metallization through Cold Spray
by Asghar Heydari Astaraee, Antonio Salerno, Sara Bagherifard, Pierpaolo Carlone, Hetal Parmar, Antonello Astarita, Antonio Viscusi and Chiara Colombo
Metals 2021, 11(11), 1860; https://doi.org/10.3390/met11111860 - 19 Nov 2021
Cited by 4 | Viewed by 2246
Abstract
Cold Spray is an innovative technology to create coatings through the impact of metallic particles on substrates. Its application to composites’ surfaces is recently attracting the attention of the scientific community thanks to the possibility to functionalize and improve their thermal and wear [...] Read more.
Cold Spray is an innovative technology to create coatings through the impact of metallic particles on substrates. Its application to composites’ surfaces is recently attracting the attention of the scientific community thanks to the possibility to functionalize and improve their thermal and wear properties. Within this context, the generation of the first metal-to-composite layer is fundamental. This work presented an experimental investigation of a composite panel, reinforced with glass fibers and coated with aluminum particles. The coating investigation was carried out through active pulsed thermography, analyzing the thermal response of single and double hatches. The thermal outputs were compared with a standard microscopic analysis, with a critical discussion supporting the identification of factors that influence the thermal response to the pulse: (1) layer’s thickness; (2) cold spray coverage; (3) layer compactness; (4) particle-substrate adhesion; (5) particle’s oxidation; and (6) surface roughness. Full article
(This article belongs to the Special Issue Cold Spray Deposition of Metallic Coatings on Polymers)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematics of the test setup.</p>
Full article ">Figure 2
<p>Extraction from the sprayed panel of the samples <span class="html-italic">S1</span> and <span class="html-italic">S2</span>, for the SEM measurements.</p>
Full article ">Figure 3
<p>Raw and normalized thermal images of the ROI at different time frames after the flash.</p>
Full article ">Figure 4
<p>Raw thermal results: (<b>a</b>) Thermal map of the ROI at t = 2/472 s, with an indication of the processed regions; (<b>b</b>) thermal trend as a function of time, linear scale; (<b>c</b>) thermal trend as a function of time, logarithmic scale; (<b>d</b>) first derivative of the logarithmic Thermal Signal Reconstruction, semi-logarithmic scale; (<b>e</b>) second derivative of the logarithmic Thermal Signal Reconstruction, semi-logarithmic scale.</p>
Full article ">Figure 5
<p>Normalized thermal results: (<b>a</b>) normalized thermal map of the ROI at t = 1/472 s, with an indication of the processed regions; (<b>b</b>) normalized thermal trend as a function of time, linear scale; (<b>c</b>) normalized thermal trend as a function of time, logarithmic scale; (<b>d</b>) first derivative of the normalized logarithmic Thermal Signal Reconstruction, semi-logarithmic scale; (<b>e</b>) second derivative of the normalized logarithmic Thermal Signal Reconstruction, semi-logarithmic scale.</p>
Full article ">Figure 6
<p>Raw thermal data along linear profiles, at t = 2/472 s: (<b>a</b>) profile selection from the thermal map of the ROI. The arrows indicate the origin of each profile, and the white dots are the regions evidenced in the next sub-figures; (<b>b</b>) thermal trend along profile H1; (<b>c</b>) thermal trend along profile H2; (<b>d</b>) thermal trend along profile V1; (<b>e</b>) thermal trend along profile V2.</p>
Full article ">Figure 7
<p>Normalized thermal data along linear profiles, at t = 1/472 s: (<b>a</b>) profile selection from the normalized thermal map of the ROI. The arrows indicate the origin of each profile, and the white dots are the regions evidenced in the next sub-figures; (<b>b</b>) normalized thermal trend along profile H1; (<b>c</b>) normalized thermal trend along profile H2; (<b>d</b>) normalized thermal trend along profile V1; (<b>e</b>) normalized thermal trend along profile V2.</p>
Full article ">Figure 8
<p>Specimen <span class="html-italic">S1</span>, through-thickness analysis: (<b>a</b>) points location; (<b>b</b>–<b>f</b>) SEM-magnified images of the five points.</p>
Full article ">Figure 9
<p>Specimen <span class="html-italic">S2</span>, analysis of the coverage: (<b>a</b>) points location; (<b>b</b>–<b>f</b>) SEM-magnified images of the five points; (<b>g</b>) histogram of the particles’ sizes for points 6 (center of the hatch), 9 (left side), and 10 (right size).</p>
Full article ">Figure 9 Cont.
<p>Specimen <span class="html-italic">S2</span>, analysis of the coverage: (<b>a</b>) points location; (<b>b</b>–<b>f</b>) SEM-magnified images of the five points; (<b>g</b>) histogram of the particles’ sizes for points 6 (center of the hatch), 9 (left side), and 10 (right size).</p>
Full article ">Figure 10
<p>Boxplot diamgram of the oxygen concentrations from the SEM measurements on four regions on the axis of the horizontal and vertical hatches.</p>
Full article ">
15 pages, 6358 KiB  
Article
Parameter Identification of the Yoshida-Uemori Hardening Model for Remanufacturing
by Xuhui Xia, Mingjian Gong, Tong Wang, Yubo Liu, Huan Zhang and Zelin Zhang
Metals 2021, 11(11), 1859; https://doi.org/10.3390/met11111859 - 18 Nov 2021
Cited by 6 | Viewed by 2333
Abstract
The deformation of plastics during production and service means that retired parts often possess different mechanical states, and this can directly affect not only the properties of remanufactured mechanical parts, but also the design of the remanufacturing process itself. In this paper, we [...] Read more.
The deformation of plastics during production and service means that retired parts often possess different mechanical states, and this can directly affect not only the properties of remanufactured mechanical parts, but also the design of the remanufacturing process itself. In this paper, we describe the stress-strain relationship for remanufacturing, in particular the cyclic deformation of parts, by using the particle swarm optimization (PSO) method to acquire the Yoshida-Uemori (Y-U) hardening model parameters. To achieve this, tension-compression experimental data of AA7075-O, standard PSO, oscillating second-order PSO (OS-PSO) and variable weight PSO (VW-PSO) were acquired separately. The influence of particle numbers on the inverse analysis efficiency was studied based on standard PSO. Comparing the results of PSO variations showed that: (1) standard PSO is able to avoid local solutions and obtain Y-U model parameters to the same degree of precision as the OS-PSO; (2) by adjusting section weight, the VW-PSO could improve local fitting accuracy and adapt to asymmetric deformation; (3) by reducing particle numbers to a certain extent, the efficiency of analysis can be improved while also maintaining accuracy. Full article
(This article belongs to the Special Issue Constitutive Modeling of Metallic Materials)
Show Figures

Figure 1

Figure 1
<p>The Y-U hardening model parameters inversion procedure.</p>
Full article ">Figure 2
<p>Finite element model for tension-compression test.</p>
Full article ">Figure 3
<p>Stress-strain curve under cyclic deformation.</p>
Full article ">Figure 4
<p>Intervals for VW-PSO.</p>
Full article ">Figure 5
<p>Stress-strain response curve iteration with standard PSO.</p>
Full article ">Figure 6
<p>Parameter iteration: <span class="html-italic">cb, k, R<sub>sat</sub></span> and <span class="html-italic">sb</span>.</p>
Full article ">Figure 6 Cont.
<p>Parameter iteration: <span class="html-italic">cb, k, R<sub>sat</sub></span> and <span class="html-italic">sb</span>.</p>
Full article ">Figure 7
<p>Simulated stress-strain response curve: GA and standard PSO.</p>
Full article ">Figure 8
<p>Residual error evolution for standard PSO and OS-PSO.</p>
Full article ">Figure 9
<p>Intervals and stress-strain curves with VW-PSO: (<b>a</b>,<b>b</b>) Interval I and corresponding stress-strain curve; (<b>c</b>,<b>d</b>) Interval II and corresponding stress-strain curve; (<b>e</b>,<b>f</b>) Interval III and corresponding stress-strain curve.</p>
Full article ">Figure 9 Cont.
<p>Intervals and stress-strain curves with VW-PSO: (<b>a</b>,<b>b</b>) Interval I and corresponding stress-strain curve; (<b>c</b>,<b>d</b>) Interval II and corresponding stress-strain curve; (<b>e</b>,<b>f</b>) Interval III and corresponding stress-strain curve.</p>
Full article ">Figure 10
<p>Iteration times and simulation times.</p>
Full article ">Figure 11
<p>Residual error evolution for standard PSO with different particle numbers.</p>
Full article ">Figure 12
<p>The bending-leveling experiment and specimen.</p>
Full article ">
20 pages, 4573 KiB  
Article
Grey-Based Taguchi Multiobjective Optimization and Artificial Intelligence-Based Prediction of Dissimilar Gas Metal Arc Welding Process Performance
by Jeyaganesh Devaraj, Aiman Ziout and Jaber E. Abu Qudeiri
Metals 2021, 11(11), 1858; https://doi.org/10.3390/met11111858 - 18 Nov 2021
Cited by 9 | Viewed by 2401
Abstract
The quality of a welded joint is determined by key attributes such as dilution and the weld bead geometry. Achieving optimal values associated with the above-mentioned attributes of welding is a challenging task. Selecting an appropriate method to derive the parameter optimality is [...] Read more.
The quality of a welded joint is determined by key attributes such as dilution and the weld bead geometry. Achieving optimal values associated with the above-mentioned attributes of welding is a challenging task. Selecting an appropriate method to derive the parameter optimality is the key focus of this paper. This study analyzes several versatile parametric optimization and prediction models as well as uses statistical and machine learning models for further processing. Statistical methods like grey-based Taguchi optimization is used to optimize the input parameters such as welding current, wire feed rate, welding speed, and contact tip to work distance (CTWD). Advanced features of artificial neural network (ANN) and adaptive neuro-fuzzy interface system (ANFIS) models are used to predict the values of dilution and the bead geometry obtained during the welding process. The results corresponding to the initial design of the welding process are used as training and testing data for ANN and ANFIS models. The proposed methodology is validated with various experimental results outside as well as inside the initial design. From the observations, the prediction results produced by machine learning models delivered significantly high relevance with the experimental data over the regression analysis. Full article
(This article belongs to the Special Issue Numerical Simulation of Metals Welding Process)
Show Figures

Figure 1

Figure 1
<p>Architecture of the current investigation.</p>
Full article ">Figure 2
<p>Welding apparatus—1. weld machine with the controller; 2. self-build table CNC machine; 3. <span class="html-italic">Z</span>-axis coupled with weld torch; 4. personal computer.</p>
Full article ">Figure 3
<p>Bead geometry, W—width; R—reinforcement; P—penetration; g—root gap.</p>
Full article ">Figure 4
<p>Model of a classical artificial neural network.</p>
Full article ">Figure 5
<p>Structural representation of ANFIS.</p>
Full article ">Figure 6
<p>Macroscopic images of the weld bead: (<b>a</b>) sample DM7; (<b>b</b>) sample C1; (<b>c</b>) sample DM2 (<b>d</b>) sample DM9.</p>
Full article ">Figure 7
<p>S/N ratio results for GRG.</p>
Full article ">Figure 8
<p>ANN output prediction in training, testing, and validating phase versus experimental results.</p>
Full article ">Figure 9
<p>Architecture of developed ANFIS model for predicting the output.</p>
Full article ">Figure 10
<p>Surface plot of proposed ANFIS model for dilution.</p>
Full article ">Figure 11
<p>Membership function for welding current on the Matlab interface.</p>
Full article ">Figure 12
<p>Comparison between experimental and prediction models for runs outside the input experimental design.</p>
Full article ">
14 pages, 7035 KiB  
Article
Masking Effect of LPSO Structure Phase on Wear Transition in Mg97Zn1Y2 Alloy
by Fujun Tao, Hongfei Duan, Lijun Zhao and Jian An
Metals 2021, 11(11), 1857; https://doi.org/10.3390/met11111857 - 18 Nov 2021
Cited by 1 | Viewed by 1372
Abstract
Room- and elevated-temperature wear tests were conducted using a pin-on-disk testing machine to study wear behavior of Mg97Zn1Y2 alloy and role of long-period-stacking-ordered (LPSO) structure phase in mild–severe wear transition (SWT). Variation of wear rate exhibited a three-stage [...] Read more.
Room- and elevated-temperature wear tests were conducted using a pin-on-disk testing machine to study wear behavior of Mg97Zn1Y2 alloy and role of long-period-stacking-ordered (LPSO) structure phase in mild–severe wear transition (SWT). Variation of wear rate exhibited a three-stage characteristic with load at various test temperatures, i.e., a gradual increasing stage, a slightly higher plateau stage, and a rapid rising stage. The wear mechanisms in the three stages were identified using scanning electron microscope (SEM), from which the first stage was confirmed as mild wear, and the other two stages were verified as severe wear. The interdendritic LPSO structure phase was elongated into strips along the sliding direction with Mg matrix deformation in the subsurface, plate-like LPSO structure phase precipitated at elevated temperatures of 150 and 200 °C. The fiber enhancement effect and precipitation effect of LPSO structure phase resulted in a little difference in wear rate between the first and second stages, i.e., a masking effect on SWT. Microstructure and microhardness were examined in the subsurfaces, from which the mechanism for SWT was confirmed to be dynamic recrystallization (DRX) softening. There is an apparently linear correlation between the critical load for SWT and test temperature, indicating that SWT is governed by a common critical DRX temperature. Full article
Show Figures

Figure 1

Figure 1
<p>Optical microphotograph of Mg<sub>97</sub>Zn<sub>1</sub>Y<sub>2</sub> alloy.</p>
Full article ">Figure 2
<p>Wear rate versus applied load: (<b>a</b>) 20–100 °C, (<b>b</b>) 150 and 200 °C, (<b>c</b>) the second stages.</p>
Full article ">Figure 3
<p>SEM microphotographs of worn surfaces at 50 °C under different loads: (<b>a</b>) 20 N, (<b>b</b>) 60 N, (<b>c</b>) 80 N, (<b>d</b>) 100 N, (<b>e</b>)140 N, (<b>f</b>) 160 N.</p>
Full article ">Figure 3 Cont.
<p>SEM microphotographs of worn surfaces at 50 °C under different loads: (<b>a</b>) 20 N, (<b>b</b>) 60 N, (<b>c</b>) 80 N, (<b>d</b>) 100 N, (<b>e</b>)140 N, (<b>f</b>) 160 N.</p>
Full article ">Figure 4
<p>SEM images of worn surfaces at 100 °C (<b>a</b>,<b>b</b>), 150 °C (<b>c</b>,<b>d</b>) and 200 °C (<b>e</b>,<b>f</b>) under different loads: (<b>a</b>) 60 N, (<b>b</b>) 80 N, (<b>c</b>) 20 N, (<b>d</b>) 50 N, (<b>e</b>) 20 N, (<b>f</b>) 40 N.</p>
Full article ">Figure 5
<p>Optical microstructures in the near surface region for sliding at 150 °C under different loads: (<b>a</b>) 40 N, (<b>b</b>) 80 N, (<b>c</b>) 120 N.</p>
Full article ">Figure 6
<p>Optical images of cross-sectional microstructures at 100 °C (<b>a</b>–<b>d</b>) and 200 °C (<b>e</b>–<b>h</b>) under different loads: (<b>a</b>) and (<b>b</b>) 60 N, (<b>c</b>) and (<b>d</b>) 80 N, (<b>e</b>) and (<b>f</b>) 20N, (<b>g</b>) and (<b>h</b>) 40 N.</p>
Full article ">Figure 6 Cont.
<p>Optical images of cross-sectional microstructures at 100 °C (<b>a</b>–<b>d</b>) and 200 °C (<b>e</b>–<b>h</b>) under different loads: (<b>a</b>) and (<b>b</b>) 60 N, (<b>c</b>) and (<b>d</b>) 80 N, (<b>e</b>) and (<b>f</b>) 20N, (<b>g</b>) and (<b>h</b>) 40 N.</p>
Full article ">Figure 7
<p>Microhardness versus depth from surface at 100 °C (<b>a</b>) and 200 °C (<b>b</b>).</p>
Full article ">Figure 8
<p>Critical load versus test temperature at mild–severe wear transition and surface melting states.</p>
Full article ">
16 pages, 4339 KiB  
Article
Linking In Situ Melt Pool Monitoring to Melt Pool Size Distributions and Internal Flaws in Laser Powder Bed Fusion
by Claudia Schwerz and Lars Nyborg
Metals 2021, 11(11), 1856; https://doi.org/10.3390/met11111856 - 18 Nov 2021
Cited by 22 | Viewed by 3999
Abstract
In situ monitoring of the melt pools in laser powder bed fusion (LPBF) has enabled the elucidation of process phenomena. There has been an increasing interest in also using melt pool monitoring to identify process anomalies and control the quality of the manufactured [...] Read more.
In situ monitoring of the melt pools in laser powder bed fusion (LPBF) has enabled the elucidation of process phenomena. There has been an increasing interest in also using melt pool monitoring to identify process anomalies and control the quality of the manufactured parts. However, a better understanding of the variability of melt pools and the relation to the incidence of internal flaws are necessary to achieve this goal. This study aims to link distributions of melt pool dimensions to internal flaws and signal characteristics obtained from melt pool monitoring. A process mapping approach is employed in the manufacturing of Hastelloy X, comprising a vast portion of the process space. Ex situ measurements of melt pool dimensions and analysis of internal flaws are correlated to the signal obtained through in situ melt pool monitoring in the visible and near-infrared spectra. It is found that the variability in melt pool dimensions is related to the presence of internal flaws, but scatter in melt pool dimensions is not detectable by the monitoring system employed in this study. The signal intensities are proportional to melt pool dimensions, and the signal is increasingly dynamic following process conditions that increase the generation of spatter. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic illustration of the method applied for measuring melt pool depth (d) and halfwidth (w/2) in melt pools characteristic of (<b>A</b>) conduction and (<b>B</b>) keyhole melting.</p>
Full article ">Figure 2
<p>Influence of laser scan speed on melt pool geometries and flaw populations in the keyhole regime. Microstructure of specimens manufactured with laser scan speed of: 200 mm/s (<b>A</b>); 400 mm/s (<b>B</b>); 600 mm/s (<b>C</b>); 800 mm/s (<b>D</b>); otherwise identical parameters (nominal laser power 200 W and layer thickness 40 µm). The volume fraction of flaws is indicated. Melt pool boundaries are highlighted for easier visualization. Arrows indicate keyhole pores of irregular morphology. Corresponding flaw size distributions (<b>E</b>) and detailed view for specimens with low flaw content (<b>F</b>). Influence of laser scan speed on melt pool: depths (<b>G</b>); widths (<b>H</b>); aspect ratios (<b>I</b>).</p>
Full article ">Figure 3
<p>Representative sample of melt pool monitoring of specimens with increasing laser scan speed in the keyhole regime, sampled from the topmost layer of each specimen. Laser scan speed of 200 mm/s, 400 mm/s, 600 mm/s, and 800 mm/s and otherwise identical parameters (nominal laser power 200 W and layer thickness 40 µm). (<b>A</b>) Raw signal in temporal x-coordinate. (<b>B</b>) The signal intensity characteristic is the output of a smoothing operation and translation to spatial coordinates. (<b>C</b>) The signal dynamic characteristic highlights regions of high melt pool dynamics.</p>
Full article ">Figure 4
<p>Influence of laser power on melt pool geometries and flaw populations in the keyhole regime. Microstructure of specimens manufactured with laser power of: 100 W (<b>A</b>); 200 W (<b>B</b>); 300 W (<b>C</b>); otherwise identical parameters (nominal laser scan speed 200 mm/s and layer thickness 40 µm). The volume fraction of flaws is indicated. Melt pool boundaries are highlighted for easier visualization. Arrows indicate keyhole porosity of irregular morphology. (<b>D</b>) Corresponding flaw size distributions. Influence of laser power on melt pool: depths (<b>E</b>); widths (<b>F</b>); aspect ratios (<b>G</b>).</p>
Full article ">Figure 5
<p>Representative sample of melt pool monitoring in specimens with increasing laser power in the keyhole regime, sampled from the topmost layer of each specimen. Laser power of 100 W, 200 W, and 300 W and otherwise identical parameters (nominal laser scan speed 200 mm/s and layer thickness 40 µm). (<b>A</b>) Raw signal in temporal x-coordinate. (<b>B</b>) Signal smoothed and translated to spatial coordinates. (<b>C</b>) Signal processed to highlight regions of high melt pool dynamics.</p>
Full article ">Figure 6
<p>Variation on melt pool geometry, melt pool signal characteristics, and incidence of flaws with a layer thickness in the keyhole regime at 100 W and 200 mm/s. Distributions of melt pool depths (<b>A</b>), widths (<b>B</b>), and aspect ratios (<b>C</b>) with varying layer thickness. In the specimens manufactured with layer thickness 20 µm and 40 µm (<b>D</b>), only gas and keyhole pores are observed. For layer thickness of 80 µm, both pores (indicated by the white arrows) and lack of fusion (indicated by the red arrows) are observed (<b>E</b>). The volume fraction of flaws is indicated in (<b>D</b>,<b>E</b>). (<b>F</b>,<b>G</b>) are spatial representations of the intensity and dynamic signal characteristics, respectively.</p>
Full article ">Figure 7
<p>Detail on pore morphology. Keyhole pores (<b>A</b>,<b>B</b>) can present distinct morphologies and sizes. Gas pores (<b>C</b>) are present in all specimens.</p>
Full article ">Figure 8
<p>Influence of laser power on melt pool geometries and flaw populations in the conduction regime. Microstructure of specimens manufactured with a laser power of: 100 W (<b>A</b>); 200 W (<b>B</b>); 300 W (<b>C</b>); with otherwise identical parameters (nominal laser scan speed 1000 mm/s and layer thickness 40 µm). The volume fraction of flaws is indicated. Distribution of melt pool: depths (<b>D</b>); widths (<b>E</b>); aspect ratios (<b>F</b>) for the three levels of laser power. The red dashed lines represent the nominal layer thickness (<b>D</b>) and hatch spacing (<b>E</b>) used in manufacturing.</p>
Full article ">Figure 9
<p>Results from melt pool monitoring of specimens with increasing laser power in the conduction regime sampled from the topmost layer of each specimen. Laser power of 100 W, 200 W, and 300 W, and otherwise identical parameters (nominal laser scan speed 1000 mm/s and layer thickness 40 µm). (<b>A</b>) Raw signal in temporal x-coordinate. Spatial representation of the intensity (<b>B</b>) and dynamic signal characteristics (<b>C</b>).</p>
Full article ">Figure 10
<p>Influence of laser scan speed on melt pool geometries and flaw populations in the conduction regime. Microstructure of specimens manufactured with a laser scan speed of: 1000 mm/s (<b>A</b>); 1200 mm/s (<b>B</b>); 1400 mm/s (<b>C</b>); 1600 mm/s (<b>D</b>); otherwise identical parameters (nominal laser power 300 W and layer thickness 40 µm). The volume fraction of flaws is indicated. Melt pool boundaries are highlighted for easier visualization. Corresponding flaw size distributions (<b>E</b>). Influence of laser scan speed on melt pool: depths (<b>F</b>); widths (<b>G</b>); aspect ratios (<b>H</b>). The red dashed lines represent the nominal layer thickness (<b>F</b>) and hatch spacing (<b>G</b>) used in manufacturing.</p>
Full article ">Figure 11
<p>Detail on the morphology of lack of fusion flaws.</p>
Full article ">Figure 12
<p>Signal intensity characteristics with increasing laser scan speed in the conduction regime, sampled from the topmost layer of each specimen. Laser scan speed 1000 mm/s, 1200 mm/s, 1400 mm/s, and 1600 mm/s and otherwise identical parameters (nominal laser power 300 W and layer thickness 40 µm).</p>
Full article ">Figure 13
<p>Influence of layer thickness on melt pool geometries and flaw populations in the conduction regime. Microstructure of specimens manufactured with layer thickness of: 20 µm (<b>A</b>); 40 µm (<b>B</b>); 80 µm (<b>C</b>); otherwise identical parameters (nominal laser power 200 W and scan speed 1000 mm/s). The volume fraction of flaws is indicated. Distribution of melt pool: depths (<b>D</b>); widths (<b>E</b>); aspect ratios (<b>F</b>) for the three levels of layer thickness. The red dashed lines represent the nominal layer thickness (<b>D</b>) and hatch spacing (<b>E</b>) used in manufacturing.</p>
Full article ">
16 pages, 10059 KiB  
Article
Microstructural Evolution and Electrochemical Behavior of Solution Treated, Hot Rolled and Aged MgDyZnZr Alloy
by Bruno Xavier de Freitas, Leonardo A. Antonini, Paula L. C. T. Cury, Viviane L. F. da Silva, Nabil Chaia, Célia R. Tomachuk, Stéphane Mathieu, Gilberto C. Coelho, Claudinei dos Santos and Carlos A. Nunes
Metals 2021, 11(11), 1855; https://doi.org/10.3390/met11111855 - 18 Nov 2021
Viewed by 1614
Abstract
In order to develop a potential route to fabricate plates and clips for orthopedic applications, a Mg–3.4Dy–0.2Zn–0.4Zr (wt.%) alloy was produced and analyzed in different conditions: solution treated at 525 °C for 3 h, hot rolled and hot rolled and aged at 250 [...] Read more.
In order to develop a potential route to fabricate plates and clips for orthopedic applications, a Mg–3.4Dy–0.2Zn–0.4Zr (wt.%) alloy was produced and analyzed in different conditions: solution treated at 525 °C for 3 h, hot rolled and hot rolled and aged at 250 °C. The aging behavior of the rolled alloy was investigated during isothermal aging at 250 °C, and a significant peak was observed at 10 h. The electrochemical behavior was evaluated in 0.9 wt.% NaCl solution at 37 ± 0.5 °C by potentiodynamic polarization and electrochemical impedance spectroscopy. The 525 °C-3 h and hot rolled specimens exhibited corrosion rates of 2.0 and 1.7 mm/year, respectively. The hot rolled and aged at 250 °C for 10 h specimen presented a grain size of 11.8 ± 1.7 μm with an intense macrotexture of the basal {0002} plane, hardness of 73 ± 3 HV and higher impedance modulus and obtained the highest corrosion resistance with a corrosion rate of 0.9 mm/year. Full article
(This article belongs to the Special Issue Innovations in Metallic Biomaterials)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) SEM/BSE micrograph, (<b>b</b>) XRD pattern and (<b>c</b>) LOM micrograph of the H525 °C-3 h specimen.</p>
Full article ">Figure 2
<p>Schematic directions in the rolled plate and SEM/BSE micrographs (<b>a</b>,<b>c</b>,<b>e</b>) and LOM micrographs (<b>b</b>,<b>d</b>,<b>f</b>) of the rolled specimen.</p>
Full article ">Figure 3
<p>XRD diffractograms of rolled and aged specimens.</p>
Full article ">Figure 4
<p>Aging hardening behavior at 250 °C after hot rolling.</p>
Full article ">Figure 5
<p>SEM/BSE (<b>a</b>,<b>c</b>,<b>e</b>) and LOM micrographs (<b>b</b>,<b>d</b>,<b>f</b>) of aged-10 h specimen; and pole figures of {10<math display="inline"><semantics> <mover> <mn>1</mn> <mo>¯</mo> </mover> </semantics></math>0}, {0002} and {10<math display="inline"><semantics> <mover> <mn>1</mn> <mo>¯</mo> </mover> </semantics></math>1} planes.</p>
Full article ">Figure 6
<p>Open circuit potential curves of H525 °C-3 h, rolled and aged-10 h specimens in 0.9 wt.% NaCl aqueous solution at 37.0 ± 0.5 °C.</p>
Full article ">Figure 7
<p>Potentiodynamic polarization curves of H525 °C-3 h, rolled and aged −10 h specimens in 0.9 wt.% NaCl aqueous solution at 37.0 ± 0.5 °C.</p>
Full article ">Figure 8
<p>Nyquist curves after 30 min (1°EIS), 50 min (2°EIS) and 70 min (3°EIS) of immersion times (<b>a</b>) H525 °C-3 h, (<b>b</b>) rolled and (<b>c</b>) aged-10 h specimens in 0.9 wt.% NaCl aqueous solution at 37.0 ± 0.5 °C.</p>
Full article ">Figure 9
<p>(<b>a</b>) Bode curves and (<b>b</b>) phase angle of H525 °C-3 h, rolled and aged-10 h specimens in 0.9 wt.% NaCl aqueous solution at 37.0 ± 0.5 °C.</p>
Full article ">Figure 10
<p>Equivalent electric circuit used to model the experimental impedance data of MgDyZnZr alloy specimens immersed in 0.9 wt.% NaCl solution at 37 ± 0.5 °C.</p>
Full article ">
10 pages, 4077 KiB  
Article
Wear Behaviors of Stainless Steel and Lubrication Effect on Transitions in Lubrication Regimes in Sliding Contact
by Yoon-Seok Lee, Shunnosuke Yamagishi, Masataka Tsuro, Changwook Ji, Seungchan Cho, Yangdo Kim and Moonhee Choi
Metals 2021, 11(11), 1854; https://doi.org/10.3390/met11111854 - 18 Nov 2021
Cited by 10 | Viewed by 2962
Abstract
The wear behavior of AISI304 stainless steel was investigated under dry, water-, and oil-lubricated conditions. A block-on-disk wear test was conducted in this work, since the test conditions could be controlled easily. For oil-lubricated contact, a significant amount of thin and elongated cutting [...] Read more.
The wear behavior of AISI304 stainless steel was investigated under dry, water-, and oil-lubricated conditions. A block-on-disk wear test was conducted in this work, since the test conditions could be controlled easily. For oil-lubricated contact, a significant amount of thin and elongated cutting chip-like debris was observed. This is attributed to the high lubricating effect of oil. Strain-induced martensitic (SIM) transformation was observed for all AISI304 blocks after the wear test, while AISI304 consisted of a single γ-austenite phase prior to the wear test. The Stribeck curve and the corresponding lubrication regimes were also considered to explain the wear behaviors and lubrication effect of AISI304. In comparison to the dry or water-lubricated conditions, which fall in the boundary lubrication regime at a low rotation speed, it is considered that the high viscosity of the oil-based lubricant causes the lubrication condition to enter the mixed lubrication regime early at a lower speed, thus reducing the specific wear rate over the 100–300 rpm range. Full article
Show Figures

Figure 1

Figure 1
<p>Specifications of (<b>a</b>) block, (<b>b</b>) disk, and (<b>c</b>) rod of experimental setup used for frictional wear test.</p>
Full article ">Figure 2
<p>Electron back-scattered diffraction (EBSD) analysis of AISI304 blocks before wear test: (<b>a</b>) image quality (IQ) maps and (<b>b</b>) corresponding phase maps (PM).</p>
Full article ">Figure 3
<p><span class="html-italic">W</span><sub>s</sub> of AISI304 blocks against HSS disk obtained from wear tests under dry, water-, and oil-lubricated conditions.</p>
Full article ">Figure 4
<p>Scanning electron microscopy (SEM) micrographs of wear tracks on AISI304 blocks at rotation speeds of (<b>a</b>) 100 and (<b>b</b>) 300 rpm, obtained from tests under dry conditions, rotation speeds of (<b>c</b>) 100 and (<b>d</b>) 300 rpm, obtained from tests under water-lubricated conditions, and rotation speeds of (<b>e</b>) 100 and (<b>f</b>) 300 rpm, obtained from tests under oil-lubricated conditions.</p>
Full article ">Figure 5
<p>Morphologies of debris collected at the end of wear tests at a rotation speed of 200 rpm and corresponding energy-dispersive X-ray spectroscopy (EDS) analysis; SEM micrographs of wear debris obtained under (<b>a</b>) dry, (<b>b</b>) water-, and (<b>c</b>) oil-lubricated conditions.</p>
Full article ">Figure 6
<p>EDS analysis of (<b>a</b>) plate-like debris and (<b>b</b>) blocky debris collected at the end of wear tests at a rotation speed of 200 rpm under dry contacts.</p>
Full article ">Figure 7
<p>EBSD analysis of cross-sectioned AISI304 blocks after wear tests: phase maps of blocks at rotation speeds of (<b>a</b>) 100 and (<b>b</b>) 300 rpm obtained from tests under dry contacts, (<b>c</b>) 300 rpm obtained from tests under water-lubricated contacts, and (<b>d</b>) 300 rpm obtained from tests under oil-lubricated contacts.</p>
Full article ">Figure 8
<p>Schematic of the Stribeck curve showing three typical lubrication regimes.</p>
Full article ">
11 pages, 5349 KiB  
Article
Effect of the Hot Deformation Conditions on Structure and Mechanical Properties of AlCr/AlCrSi Powder Composites
by Elena N. Korosteleva, Gennady A. Pribytkov and Victoria V. Korzhova
Metals 2021, 11(11), 1853; https://doi.org/10.3390/met11111853 - 18 Nov 2021
Cited by 1 | Viewed by 1650
Abstract
Aluminum matrix composites usually contain strengthening particles of refractory compounds (SiC, Al2O3) that do not react with the Al matrix. There is a problem in producing the Al matrix composite with inclusion of metals that can generate intermetallic compounds [...] Read more.
Aluminum matrix composites usually contain strengthening particles of refractory compounds (SiC, Al2O3) that do not react with the Al matrix. There is a problem in producing the Al matrix composite with inclusion of metals that can generate intermetallic compounds with aluminum. In this case, a conventional sintering of powder mixtures results in high porosity due to volume growth. That is why some new methods of producing dense Al matrix composites are required. A possibility to create a dense powder Al-based composite containing hard components, such as chromium and silicon, without using the sintering process, is considered. This paper presents study results of structural and mechanical properties of Al-Cr and Al-Cr-Si composites produced by hot compaction of powder mixtures. An analysis of the relationship between mechanical properties and structures of Al-Cr and Al-Cr-Si composites is carried out. Optimal values for thermomechanical processing modes that ensure sufficient strength and plasticity are determined. It is shown that strong bonding of the aluminum particles occurs under hot deformation, and an aluminum matrix is formed that provides acceptable composite bending strength as a result. The presence of chromium and silicon hard inclusions is not a significant obstacle for aluminum plastic flow. Al-Cr and Al-Cr-Si composites produced by hot deformation of the powder mixtures can be used as cathode material for the deposition of wear-resistant nitride coatings on metalworking tools. Full article
(This article belongs to the Special Issue Microstructure/Property Relationship in Metallic Powder Metallurgy)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Typical view of the powders: (<b>a</b>) Al; (<b>b</b>) Cr; (<b>c</b>) Si.</p>
Full article ">Figure 2
<p>Scheme of the two-stage compaction; <span class="html-italic">1</span>—mold matrix; <span class="html-italic">2</span>—upper and bottom punch; <span class="html-italic">3</span>—specimen; (<b>a</b>) cold-pressing of the powder mixture in press molds with diameters of 20–39 mm; (<b>b</b>) compression of heated preform in a press mold with diameter of 40 mm; (<b>с</b>) hot-compacted specimen with diameter of 35 mm.</p>
Full article ">Figure 3
<p>Optical metallography image and XRD patterns of powder composites hot-compacted at 550 °C by 0.5 GPa pressure: (<b>a</b>,<b>c</b>) Al<sub>70</sub>Cr<sub>30</sub>; (<b>b</b>,<b>d</b>) Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub>.</p>
Full article ">Figure 3 Cont.
<p>Optical metallography image and XRD patterns of powder composites hot-compacted at 550 °C by 0.5 GPa pressure: (<b>a</b>,<b>c</b>) Al<sub>70</sub>Cr<sub>30</sub>; (<b>b</b>,<b>d</b>) Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub>.</p>
Full article ">Figure 4
<p>Porosity changes of Al<sub>70</sub>Cr<sub>30</sub> (<b>a</b>) and Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub> (<b>b</b>) composites during the hot compaction process with different processing conditions.</p>
Full article ">Figure 5
<p>Relation between bending strength and hot compression deformation of Al<sub>70</sub>Cr<sub>30</sub> (<b>a</b>) and Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub> (<b>b</b>) powder composites compacted at different temperatures.</p>
Full article ">Figure 6
<p>Relation between plasticity at the bending tests and hot compression deformation of Al<sub>70</sub>Cr<sub>30</sub> (<b>a</b>) and Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub> (<b>b</b>) powder composites compacted at different temperatures.</p>
Full article ">Figure 7
<p>Effect of the hot deformation temperature on aluminum matrix microhardness of Al<sub>70</sub>Cr<sub>30</sub> (<b>a</b>) and Al<sub>65</sub>Cr<sub>25</sub>Si<sub>10</sub> (<b>b</b>) powder composites.</p>
Full article ">Figure 8
<p>SEM image with element analysis of fracture surfaces of Al<sub>70</sub>Cr<sub>30</sub> composites obtained under different conditions of hot compaction: (<b>a</b>) Т = 350 °C, <span class="html-italic">ε<sub>n</sub></span> = 9%; (<b>b</b>) Т = 550 °C, <span class="html-italic">ε<sub>n</sub></span> = 9%; (<b>c</b>) Т = 350 °C, <span class="html-italic">ε<sub>n</sub></span> = 75%; (<b>d</b>) Т = 550 °C, <span class="html-italic">ε<sub>n</sub></span> = 75%.</p>
Full article ">Figure 9
<p>SEM image of fracture surface of Al<sub>65</sub>Sr<sub>25</sub>Si<sub>10</sub> composite hot-compacted under ε = 9% at T = 350 °C (<b>a</b>) and ε = 75% at T = 550 °C (<b>b</b>).</p>
Full article ">
Previous Issue
Next Issue
Back to TopTop