CN114720520B

CN114720520B - A PEI-modified multi-walled carbon nanotube gas sensor and its preparation and application

Info

Publication number: CN114720520B
Application number: CN202210190583.3A
Authority: CN
Inventors: 陈文利; 翁境锋
Original assignee: South China Normal University
Current assignee: South China Normal University
Priority date: 2022-02-28
Filing date: 2022-02-28
Publication date: 2025-07-04
Anticipated expiration: 2042-02-28
Also published as: CN114720520A

Abstract

The invention belongs to the technical field of sensors, and particularly relates to a PEI modified multiwall carbon nanotube gas sensor, and preparation and application thereof. The PEI modified multiwall carbon nanotube gas sensor can accurately detect the volatile organic compounds released by the citrus trees when suffering from citrus yellow dragon disease or early yellow dragon disease, can accurately detect the citrus trees in early stages of suffering from citrus yellow dragon disease, further prevent the citrus trees, and can effectively improve the yield of citrus.

Description

PEI-modified multiwall carbon nanotube gas sensor and preparation and application thereof

Technical Field

The invention belongs to the technical field of sensors. More particularly, to a PEI modified multiwall carbon nanotube gas sensor and preparation and application thereof.

Background

Citrus yellow longdisease (HLB) is known as "cancer" in the global citrus industry, and its spread results in the level of citrus planting area falling to the lowest point in the near modern history of the world, approximately half the peak, and without adequate countermeasures, the citrus industry is faced with a rapid decline in fruit yield and a consequent enormous economic impact. The current method for treating HLB is still immature, so that the timely detection of HLB has become a key problem, and the tree is found and effectively treated at the early stage of the infection of HLB, so that the method is a more effective prevention and control method at present.

It was found that, in comparison to healthy citrus trees, three Volatile Organic Compounds (VOCs) in the leaf volatile gas undergo a significant concentration change in the asymptomatic phase after infection with yellow dragon, the concentration of ethylhexanol significantly decreases, the concentration of linalool and phenylacetaldehyde significantly increases, and the concentration of methyl salicylate also significantly increases in citrus leaves with severe HLB infection.

In light of the above, various portable gas monitoring devices (e.g., E-case) have proven useful for real-time pest monitoring in agricultural and horticultural environments. Methods for detecting gases have been developed including gas chromatography, electrochemiluminescence, raman spectroscopy, liquid chromatography and fluorescence sensors, among which methods related to analytical instruments have the ability to accurately detect specific gases in complex samples, however they also have the disadvantages of large sample preparation amount, expensive and heavy instruments, complicated instrument operation, etc., and are not suitable for real-time detection of gases in actual scenes. Therefore, it is necessary to develop a simple, convenient and real-time gas sensor for early detection of citrus yellow dragon disease.

The most important element of the gas sensor is the gas-sensitive material, most of the gas-sensitive materials of the gas sensor of the current commercial mainstream are metal oxides, but the working temperature required by the metal oxides often reaches hundreds of ℃ or higher, the metal oxides can damage plants with a certain probability during use, and the metal oxides have high energy consumption, are easy to poison, are sensitive to humidity and have lower precision on the volatile matters of the macromolecules of VOC (volatile organic compounds), so the gas sensor is rarely used in the gas test of plants. To solve the above problems, multi-walled carbon nanotubes are often added to gas sensors, which have a larger surface area and more adsorption sites, and the nano-size thereof allows almost all surfaces to be exposed to the environment, improving the sensitivity to VOCs, but the adsorption and reaction of the multi-walled carbon nanotubes to volatile organic compounds are weak. Therefore, few choices are available for detecting early yellow dragon disease in citrus, as chinese patent application discloses a gas sensor that only detects toluene, xylene, methylene chloride, and the application is greatly limited.

Disclosure of Invention

The invention aims to overcome the defect that few choices are available in a method for detecting early yellow dragon disease of a citrus tree, and provides a PEI modified multiwall carbon nanotube gas sensor capable of effectively detecting early yellow dragon disease of the citrus tree.

The invention aims to provide an application of a PEI modified multiwall carbon nanotube gas sensor in detecting citrus yellow dragon disease or catharanthus roseus yellow dragon disease.

It is a further object of the present invention to provide a gas sensitive test system.

It is another object of the present invention to provide a method of detecting citrus yellow dragon disease or vinca yellow dragon disease.

The above object of the present invention is achieved by the following technical solutions:

a PEI modified multi-wall carbon nanotube gas sensor comprises PEI modified multi-wall carbon nanotubes and a resistance detection instrument, wherein the PEI modified multi-wall carbon nanotubes are used for adsorbing volatile organic compounds, and the resistance detection instrument is used for detecting the resistance value of the PEI modified multi-wall carbon nanotubes.

The invention adopts Polyethyleneimine (PEI) to modify the multi-wall carbon nano tube sensor, the PEI is a polymer composed of a plurality of amino repeating units and two carbon aliphatic CH ₂-CH₂ spacer groups, and the PEI not only has a certain gas adsorption capacity, but also can transfer electrons into an electron acceptor (detected gas) through the multi-wall carbon nano tube, so that the resistance value is changed.

The original multi-wall carbon nano tube has fewer defect sites, only a small amount of gas molecules can be adsorbed on the surface in the process of being exposed to the tested gas, and for VOC with larger molecular weight, the adsorption quantity of the original multi-wall carbon nano tube is smaller. The polymeric amine in PEI can maintain the adhesion of partial VOC on the multi-wall carbon nano tube through reversible nucleophilic addition reaction, and meanwhile, in the PEI modification process, the multi-wall carbon nano tube can generate additional defect sites, so that the adsorption sites of the multi-wall carbon nano tube are increased, and the adsorption of the multi-wall carbon nano tube on the VOC is further increased.

Preferably, the volatile organic compound is linalool, phenylacetaldehyde, ethylhexanol, or methyl salicylate.

Preferably, the multi-walled carbon nanotubes are carboxylated or aminated multi-walled carbon nanotubes.

Preferably, the preparation method of the PEI modified multiwall carbon nanotube gas sensor comprises the following steps:

S1, dispersing a multi-wall carbon nano tube in an organic solvent to obtain an ultrasonic multi-wall carbon nano tube dispersion liquid, and uniformly dispersing the multi-wall carbon nano tube dispersion liquid between two metal electrodes on a sensor substrate by adopting a dielectrophoresis arrangement method;

s2, immersing the multi-wall carbon nanotube sensor in a PEI solution completely, standing for 1-2 h under a closed condition, washing and drying to obtain the PEI-modified multi-wall carbon nanotube gas sensor.

Preferably, the multi-walled carbon nanotube dispersion is dripped between two metal electrodes on the sensor substrate.

The invention polarizes the multi-wall carbon nano tube by using the high-frequency alternating electric field of the dielectrophoresis arrangement method, the polarized multi-wall carbon nano tube generates translational motion and rotation moment under the action of the electric field force, and finally the long axis of the multi-wall carbon nano tube is arranged along the direction of the electric field line. The dielectrophoresis arrangement can also lead the multiwall carbon nanotubes to be regularly arranged to obtain a more repeatable result, the arrangement also avoids the agglomeration of the multiwall carbon nanotubes and increases the exposure area of the multiwall carbon nanotubes to gas.

Preferably, in the step S1, the dielectrophoresis arrangement method comprises the steps of carrying out ultrasonic treatment on the multiwall carbon nanotube dispersion liquid for 20-30 min for later use, dripping 10 mug/mL of the multiwall carbon nanotube dispersion liquid after ultrasonic treatment in the center of two metal electrodes when dielectrophoresis arrangement is started, connecting an instrument, adjusting parameters, electrifying for 150-200S, washing and drying to obtain the dielectrophoresis arrangement method.

More preferably, the parameter is adjusted to a frequency of the sinusoidal alternating current signal of 5MHz, peak-to-peak value of 20Vpp.

Preferably, in the step S1, the concentration of the multi-walled carbon nanotube solution is 8-15 μg/mL.

Preferably, in step S1, the time of the ultrasound is 2 hours or more.

Preferably, in step S1, the weight of the PEI is 4-6% of the weight of the PEI solution.

Preferably, in step S1, the organic solvent is one or more of methanol, DMF, DMSO, or ethanol.

The invention further protects application of the PEI modified multiwall carbon nanotube gas sensor in detecting citrus yellow dragon disease or catharanthus roseus yellow dragon disease.

Preferably, the PEI-modified multiwall carbon nanotube gas sensor is further capable of detecting early stage yellow-long disease of citrus.

Preferably, the PEI modified multiwall carbon nanotube gas sensor detects citrus yellow crohn's disease by detecting volatile organic compounds released by citrus trees when suffering from citrus yellow crohn's disease or early stage yellow crohn's disease.

More preferably, the volatile organic compound is ethylhexanol, phenylacetaldehyde, linalool, or methyl salicylate.

The invention further protects a gas-sensitive test system which sequentially comprises a gas chamber, a resistance detection system and a PC end according to the flow direction of a sample, wherein the gas chamber comprises a sample inlet, an air stirrer and the PEI modified multiwall carbon nanotube gas sensor.

Preferably, the sample inlet is used for adding a sample to be detected, the air stirrer is used for uniformly mixing the volatile organic compound volatilized gas with air in the air chamber, the PEI modified multiwall carbon nanotube gas sensor is used for adsorbing the volatile organic compound volatilized gas, the resistance detection system is used for detecting the resistance value of the PEI modified multiwall carbon nanotube gas sensor, and the PC end is used for calculating and displaying the result.

Preferably, the resistance detection system is a singlechip measuring resistance system.

The invention further provides a method for detecting citrus yellow dragon disease or catharanthus roseus yellow dragon disease, which is used for detecting the citrus yellow dragon disease or the catharanthus roseus yellow dragon disease by the gas-sensitive test system.

Preferably, the method for detecting citrus yellow long disease comprises the following steps:

The method comprises the steps of placing blades before and after citrus suffering from yellow dragon disease into an air chamber, uniformly mixing the air released by citrus with air in the air chamber, placing a PEI modified multi-wall carbon nano tube gas sensor into the air chamber for 25-40 minutes, removing, standing for 25-40 minutes, recording the resistance value of the PEI modified multi-wall carbon nano tube gas sensor every 5-8 minutes by a resistance detection system, and calculating and displaying the result at a PC end.

Preferably, the judgment standard of the method is that the resistance value recorded after the resistance of the PEI modified multi-wall carbon nano tube gas sensor is stable in the natural environment with the air humidity of 50% is used as a baseline resistance, and the resistance value after the PEI modified multi-wall carbon nano tube gas sensor adsorbs an object to be detected is positive (diseased yellow dragon disease orange) when the resistance value is higher than the baseline resistance, and is negative (healthy) when the resistance value is lower than the baseline resistance.

The invention has the following beneficial effects:

The PEI modified multiwall carbon nanotube gas sensor can accurately detect the volatile organic compounds released by the citrus trees when suffering from citrus yellow dragon disease or early yellow dragon disease, can accurately detect the citrus trees in early stages of suffering from citrus yellow dragon disease, further prevent the citrus trees, and can effectively improve the yield of citrus.

Drawings

Fig. 1 is a schematic diagram of the preparation flow of the PEI modified multiwall carbon nanotube gas sensor in example 1.

Fig. 2 is a physical diagram and an electrode gap schematic diagram of the sensor substrate prepared in step S1 of example 1, ①、② is a metal electrode region on the sensor substrate.

FIG. 3 is a cross-sectional view of a CNT-COOH sensor and a CNT-NH ₂ sensor.

Fig. 4 is an SEM image of multi-wall carbon nanotubes in the sensors prepared in examples and comparative examples, fig. 4a is an SEM image of multi-wall carbon nanotubes in the CNT sensor prepared in comparative example 1 using the FEI Quanta 250FEG test, fig. 4b is an SEM image of multi-wall carbon nanotubes in the CNT sensor prepared in comparative example 1 using the ZEISS Gemini 500 test, fig. 4c is an SEM image of multi-wall carbon nanotubes in the CNT-COOH sensor prepared in example 1 using the ZEISS Gemini 500 test, and fig. 4d is an SEM image of multi-wall carbon nanotubes in the PEI/CNT-COOH sensor prepared in comparative example 2 using the ZEISS Gemini 500 test.

FIG. 5 is an SEM image of a multiwall carbon nanotube of PEI/CNT-COOH prepared in test example 1.

FIG. 6 is a Raman spectrum of the multi-walled carbon nanotube in the CNT-COOH sensor and the PEI/CNT-COOH sensor prepared in example 1, FIG. 6a is a Raman spectrum of the multi-walled carbon nanotube in the CNT-COOH sensor, and FIG. 6b is a Raman spectrum of the multi-walled carbon nanotube in the PEI/CNT-COOH sensor.

Fig. 7 is a chemical vapor generation and testing system for a test sensor.

FIG. 8 shows the real-time response of the PEI/CNT-COOH sensor obtained in example 1 to four VOCs of different gas phase concentrations, linalool (FIG. 8 a), phenylacetaldehyde (FIG. 8 b), ethylhexanol (FIG. 8 c), methyl salicylate (FIG. 8 d). The grey area indicates the time of exposure of the PEI/CNT-COOH sensor to the volatile, the number below the grey bar indicates the gas phase concentration of the volatile at this time, and the white area indicates the time the PEI/CNT-COOH sensor is recovered in air.

FIG. 9 shows the upper and lower limit concentrations of four VOCs detected by the PEI/CNT-COOH sensor obtained in example 1, linalool (FIG. 9 a), phenylacetaldehyde (FIG. 9 b), ethylhexanol (FIG. 9 c), methyl salicylate (FIG. 9 d) under the same test conditions.

FIG. 10 shows the response of the PEI/CNT-COOH sensor obtained in example 1, the CNT-COOH sensor, and the CNT-NH ₂ sensor obtained in example 2 after 30 minutes of exposure to VOC gas.

FIG. 11 shows the response of the PEI/CNT-COOH sensor of example 1, the CNT-COOH sensor, and the CNT-NH ₂ sensor of example 2 to healthy citrus leaves, yellow dragon disease leaves, 30 minutes after exposure to the citrus leaves.

FIG. 12 shows the real-time response of the PEI/CNT-COOH sensor of example 1 to HLB-bearing citrus leaves and healthy citrus leaves.

FIGS. 13 and 14 show the response of the PEI/CNT-COOH sensor obtained in example 1 to 28 additional leaves.

FIG. 15 shows the real-time response of the CNT-COOH sensor of example 1 to citrus leaves.

FIG. 16 shows the real-time response of the CNT-NH ₂ sensor obtained in example 2 to citrus leaves.

Detailed Description

The invention is further illustrated in the following drawings and specific examples, which are not intended to limit the invention in any way. Unless specifically stated otherwise, the reagents, methods and apparatus employed in the present invention are those conventional in the art.

Reagents and materials used in the following examples are commercially available unless otherwise specified.

A schematic diagram of the preparation flow of the PEI modified multi-wall carbon nanotube gas sensor is shown in FIG. 1:

Example 1 PEI preparation of modified carboxylated multiwall carbon nanotube gas sensor

S1, adopting high phosphorus doped silicon with a 300nm silicon dioxide layer as a substrate, wherein a patterned chromium layer with the thickness of 30nm and a gold layer with the thickness of 100nm are arranged on the substrate and serve as two metal electrodes of the sensor, namely a ①、② area in the figure 2), the interval between the two electrodes is 10 mu m, the overall size of the whole sensor substrate is 4mm multiplied by 7mm multiplied by 0.52mm, and a physical diagram and a schematic diagram are shown in the figure 2.

S2, dispersing carboxylated multi-wall carbon nano tubes in DMF (dimethyl formamide), preparing the concentration to be 10 mug/mL, carrying out water bath ultrasonic treatment for 2 hours at room temperature, carrying out ultrasonic treatment on the carboxylated multi-wall carbon nano tube dispersion liquid for 20 minutes, when dielectrophoresis arrangement is started, using a liquid-transferring gun to remove 10 mug of multi-wall carbon nano tube dispersion liquid (10 mug/mL) and drop the liquid into the centers of two metal Au electrodes on a sensor substrate, then respectively connecting an anode and a cathode at the output end of a function signal generator on the two electrodes of the sensor, regulating parameters of the function signal generator, enabling the frequency of an output sinusoidal alternating current signal to be 5MHz, enabling the peak-to-peak value to be 20V, electrifying for 180 seconds, enabling the multi-wall carbon nano tubes to be orderly arranged in gaps between the two electrodes on the sensor substrate, bridging the two electrodes, closing the function signal generator, removing residual liquid drops on the sensor by using absolute ethyl alcohol after the dielectrophoresis removed, slightly cleaning and then placing the liquid drops on the sensor in a drying box at 70 ℃ for 2 hours, thus obtaining the carboxylated multi-wall carbon nano tube sensor (CNT-COOH sensor shown in a cross section figure of a CNT-3-COOH sensor.

S3, dissolving PEI in methanol to obtain PEI solution, fully immersing the CNT-COOH sensor in the PEI solution, standing for 1h under a closed condition, taking out, cleaning with methanol, and drying in an oven at 70 ℃ for 2h to obtain the PEI modified carboxylated multiwall carbon nanotube sensor (PEI/CNT-COOH sensor).

Example 2 PEI preparation of modified aminated multiwall carbon nanotube gas sensor

S2, dispersing the aminated multi-wall carbon nano tube in DMF, preparing the concentration to be 10 mug/mL, carrying out water bath ultrasonic treatment for 2 hours at room temperature, carrying out ultrasonic treatment on the dispersion liquid of the aminated multi-wall carbon nano tube for 20 minutes, when dielectrophoresis arrangement is started, using a liquid-transferring gun to remove 10 mug of dispersion liquid of the multi-wall carbon nano tube (10 mug/mL) and drop the dispersion liquid of the multi-wall carbon nano tube into the centers of two metal Au electrodes on a sensor substrate, respectively connecting an anode and a cathode at the output end of a function signal generator to the two electrodes of the sensor, regulating parameters of the function signal generator, enabling the frequency of an output sinusoidal alternating current signal to be 5MHz, the peak-to-peak value to be 20V, electrifying for 180 seconds, enabling the multi-wall carbon nano tube to be orderly arranged on the gap between the two electrodes on the sensor substrate, bridging the two electrodes, closing the function signal generator, removing the residual liquid drops on the sensor by using absolute ethyl alcohol after the dielectrophoresis removed, slightly cleaning the residual liquid drops on the sensor, and placing the sensor into a drying box at 70 ℃ for 2 hours after the cleaning moment, so as to obtain the aminated multi-wall carbon nano tube sensor (3962-NH 5326-CNT sensor shown in a cross section figure of a chart of a CNT-figure of 533.

Comparative example 1 preparation of multiwall carbon nanotube gas sensor CNT

S2, dispersing the carboxylated multi-wall carbon nano tube in DMF (dimethyl formamide), preparing the concentration to be 10 mug/mL, performing water bath ultrasonic treatment for 2 hours at room temperature, performing ultrasonic treatment on the carboxylated multi-wall carbon nano tube dispersion liquid for 20 minutes, sucking 10 mu L of multi-wall carbon nano tube dispersion liquid by a pipette, dripping the multi-wall carbon nano tube dispersion liquid into the centers of two electrodes on a sensor substrate, drying in air for a moment, and placing the mixture into a drying box for drying at 70 ℃ for 2 hours to obtain the multi-wall carbon nano tube.

Comparative example 2 PEI preparation of carboxylated multiwall carbon nanotube gas sensor

S2, dispersing carboxylated multiwall carbon nanotubes in DMF (dimethyl formamide), preparing the concentration to be 10 mug/mL, carrying out water bath ultrasonic treatment for 2 hours at room temperature, carrying out ultrasonic treatment on the carboxylated multiwall carbon nanotube dispersion for 20 minutes, when dielectrophoresis arrangement is started, using a liquid-transferring gun to transfer 10 mug of multiwall carbon nanotube dispersion (10 mug/mL) to the centers of two metal Au electrodes on a sensor substrate, then respectively connecting an anode and a cathode at the output end of a function signal generator to the two electrodes of the sensor, regulating parameters of the function signal generator, enabling the frequency of an output sinusoidal alternating current signal to be 5MHz, enabling the peak-to-peak value to be 20V, electrifying for 60 seconds, enabling the multiwall carbon nanotubes to be orderly arranged in the electrode gap on the sensor substrate and bridge the two electrodes of the sensor, after the dielectrophoresis arranged, removing the dielectrophoresis device, lightly cleaning and removing residual liquid drops on the sensor by using absolute ethyl alcohol, and then placing the cleaned drops in a drying box at 70 ℃ for 2 hours, thus obtaining the carboxylated multiwall carbon nanotube sensor (CNT sensor-CNT sensor).

Sensor characterization:

SEM structure characterization As shown in FIG. 4, in the CNT sensor prepared by the dropping method of comparative example 1, a plurality of multi-walled carbon nanotubes are in the shape of plaques and are stacked on each other, and are randomly distributed on the substrate of the CNT sensor (FIG. 4a and FIG. 4 b), and a plurality of areas between the electrodes and the electrode gaps are not deposited with multi-walled carbon nanotubes, so that the utilization rate of the multi-walled carbon nanotubes is very low. The CNT-COOH sensor prepared in example 1 was mainly deposited between the electrode gaps, more multi-walled carbon nanotubes were attracted to the electrode edges and electrode gaps, and more multi-walled carbon nanotubes in the electrode gaps were in contact with each other, extended from each other, and successfully bridged to both electrodes, achieving a better arrangement effect than comparative example 1 (fig. 4 c). The CNT-COOH sensor prepared in comparative example 2 had only a small amount of multi-walled carbon nanotubes attracted to the electrode edges and deposited, and the number of multi-walled carbon nanotubes that could be deposited in the electrode gap and bridge the two electrodes was smaller (fig. 4 d).

The result of the electron microscope of the PEI/CNT-COOH sensor prepared in example 1 is shown in FIG. 5, and it is apparent that PEI covers the multiwall carbon nanotubes in the whole electrode gap, so that only a membranous structure is observed in the electrode gap, the multiwall carbon nanotubes are buried under PEI, and the result also shows that PEI is indeed modified to the multiwall carbon nanotubes.

Raman spectral characterization of CNT-COOH sensor and PEI/CNT-COOH sensor prepared in example 1 were raman-characterized under laser power of 10mW and laser excitation of 532nm, and fig. 6 shows that the characteristic absorption peak at 1345.12cm ^-1, which is caused by lattice defects of curved sheets of multi-walled carbon nanotubes in the CNT-COOH sensor and is generally called D band (disturbing band) corresponding to disordered structures on the walls of multi-walled carbon nanotubes, is a G band at 1581.47cm ^-1, which is influenced by sp2 hybridized structures in the multi-walled carbon nanotubes, is a tubular graphite structure vibration absorption peak caused by chemical bonds such as c= C, C-C, and corresponds to graphite structures on multi-walled carbon nanotubes. The ratio of the integrated areas of the two peaks (ID/IG) can reflect the degree of order (degree of disturbance) of the multi-walled carbon nanotubes, where the value of ID/IG is 1.09 (fig. 6 a). As can be seen from FIG. 6b, the positions of the D band and the G band of the PEI-modified multiwall carbon nanotube sensor slightly shift rightward, which is 1349.88cm ^-1,1584.55cm^-1 respectively, and the intensity of the absorption peak increases a little, and the calculated value of ID/IG is 1.01.

The ID/IG values of the CNT-COOH sensor and the PEI/CNT-COOH sensor are similar and are 1.09 and 1.01 respectively, and the result shows that the PEI modification does not damage the structure of the multi-wall carbon nano tube, and also shows that the PEI does carry out surface coverage on the multi-wall carbon nano tube, so that the ID/IG value is changed.

For the CNT-COOH sensor, the G band was observed at 1581.47cm ^-1, but for the PEI/CNT-COOH sensor, the G band shifted right to 1584.55cm ^-1. The reason for this phenomenon may be that the lone pair electrons of the N atom in PEI may interact with the p electrons of the multiwall carbon nanotubes, and the electron density of the multiwall carbon nanotubes is enhanced due to p-p conjugation, so that the surface polarization degree is improved, and the conductivity of the sensor is enhanced.

Example 3 repeatability and stability test of sensor

The fabricated PEI/CNT-COOH sensors, CNT-NH ₂ sensors were tested for gas sensitivity using a self-made chemical vapor generation and testing system (FIG. 7). The sensor is bonded to the plastic plate carrier through a lead and is connected to a stm32 singlechip (the sensor works under a constant direct current bias of 1V), and a programmed program for monitoring, calculating and storing the current and the resistance of the sensor is stored in the singlechip.

The PEI/CNT-COOH sensor, the CNT-COOH sensor and the CNT-NH ₂ sensor are placed in a natural laboratory environment with the air humidity of 50% at 25 ℃ for about half an hour, and the resistance value at the moment is recorded as a base line resistance after the resistance of each sensor is stable. The required concentrations (in ppm) of diseased citrus and healthy citrus volatiles (linalool, phenylacetaldehyde, ethylhexanol, and methyl salicylate) were calculated using equation (1).

Wherein V _spl represents the volume of the volatile organic compound to be tested injected into the gas chamber by the injector in microliters (μl), d _spl represents the density of the VOC gas to be tested, R is the ideal gas constant (0.0820574587 L.atm. Mol ^-1·K^-1), T represents the laboratory temperature (298K), V _ac represents the total volume of the gas chamber in milliliters (ml), M represents the relative molecular weight of the volatile organic compound to be tested, and P represents the atmospheric pressure (0.992 atm) of the laboratory.

At the beginning of the experiment, each sensor is firstly exposed to VOC with the concentration of 100ppm, if the absolute value of the response of the sensor (the absolute value of the detection result minus the baseline resistance) is smaller than 8%, the VOC concentration is increased, otherwise, the VOC concentration is reduced, when the absolute value of the response of the sensor is within the range of 8% -10%, the VOC concentration is considered to be the lower detection limit concentration of the sensor to the VOC, then a certain concentration of the detected gas is increased, and the response value is observed to determine that the sensor is indeed responsive to the detected gas. Data analysis and baseline correction were performed using Microsoft Excel, GRAPHPAD PRISM, etc. software.

At the same VOC concentration, the absolute value of sensor response |ar| gradually rises with increasing time, and it was observed that |ar| could reach the saturation value within 30 minutes (fig. 8), so 30 minutes were taken as the response time of the sensor to the measured gas environment and the recovery time in air.

And (3) calculating the volume of the volatile organic compound corresponding to the gas concentration of the corresponding volatile organic compound by using the equation (1) (specific numerical values are shown in table 1, table 2, table 3 and table 4), sucking the calculated volume of the volatile organic compound to be detected by using a pipette, then sucking and injecting the volatile organic compound into a gas chamber by using a syringe, turning on a fan, waiting for the complete volatilization of the volatile organic compound and the complete mixing with the air in the gas chamber, and then rapidly placing a sensor in the gas chamber to start a gas-sensitive experiment. The sensor is respectively exposed to volatile organic compound gases with different concentrations for 30 minutes, the resistance value of the current sensor is recorded once every 6 minutes by the singlechip measuring resistance system, then the sensor is transferred to a natural air environment outside the air chamber for 30 minutes to recover, the resistance value of the current sensor is recorded once every 6 minutes by the singlechip measuring resistance system in the recovery process, the PC end calculates and displays data, the same sensor can be exposed to the same VOC with different concentrations (from low to high) for 3 times within 3 hours, and 3 repeated experiments are carried out by using the same sensor to test the repeatability and the stability.

TABLE 1 volume of liquid phase corresponding to linalool gas concentration

V_ac(ml)	V_spl(μl)	d_spl(g/ml)	M(g/mol)	Concentration (ppm)
					420	3.05	0.862	154.25	1
420	15.25	0.862	154.25	5
					420	21.35	0.862	154.25	7
420	30.5	0.862	154.25	10
					420	61	0.862	154.25	20
420	91.5	0.862	154.25	30
					420	122	0.862	154.25	40
420	152.5	0.862	154.25	50
					420	305	0.862	154.25	100
420	610	0.862	154.25	200
					420	1525	0.862	154.25	500
420	2440	0.862	154.25	800
					420	3050	0.862	154.25	1000

TABLE 2 liquid volume for phenylacetaldehyde gas concentration

TABLE 3 liquid volume for ethylhexanol gas concentration

V_ac(mi)	V_spl(μl)	d_spl(g/ml)	M(g/mol)	Concentration n (ppm)
					420	2.67	0.832	130.23	1
420	13.35	0.832	130.23	5
					420	26.7	0.832	130.23	10
420	40.05	0.832	130.23	15
					420	53.4	0.832	130.23	20
420	66.75	0.832	130.23	25
					420	106.8	0.832	130.23	40
420	133.5	0.832	130.23	50
					420	267	0.832	130.23	100
420	534	0.832	130.23	200
					420	1335	0.832	130.23	500
420	2136	0.832	130.23	800
					420	2670	0.832	130.23	1000

TABLE 4 liquid volume for methyl salicylate gas concentration

The stm32 monolithic computer connected with the sensor can transmit the resistance value of the sensor to the PC end in real time, and the equation (2) is used for calculating the response of the sensor to each volatile organic compound:

Where the sensor response is Ar, R ₀ represents the baseline resistance of the sensor, R _i represents the resistance of the sensor after a period of exposure to VOC, and R ₀ and R _i are both in kiloohms (kΩ).

The results show that the PEI/CNT-COOH sensor produced a positive response (FIG. 8 a-c) when exposed to linalool, phenylacetaldehyde, and methyl salicylate (increased resistance) and a negative response (FIG. 8 d) when exposed to ethylhexanol (decreased resistance). The grey area in fig. 8 represents the gas phase concentration of the volatile matter measured at this time when the PEI/CNT-COOH sensor is in the gaseous environment of the volatile organic compound, and the number below the grey area represents the gas phase concentration of the volatile matter measured at this time, so analysis shows that the absolute value of the response of the PEI/CNT-COOH sensor increases correspondingly after the concentration of any of the measured VOC gases increases over a continuous period of time, and the absolute value of the response of the PEI/CNT-COOH sensor has a positive correlation with the measured VOC concentration. The blank area indicates that the PEI/CNT-COOH sensor was recovering in an air environment at this time, and it can be seen that the absolute value of the response of the PEI/CNT-COOH sensor was slowly decreasing, which represents that the PEI/CNT-COOH sensor was very recoverable and repeatable.

When the gas phase concentrations of the test gases were set to 500ppm, 1000ppm and 2000ppm, it was found that the absolute value of response of the PEI/CNT-COOH sensor to ethylhexanol was minimum at the same gas phase concentration (FIG. 8 d), and could only reach 27% at 2000ppm, and the absolute value of response of the PEI/CNT-COOH sensor to linalool was maximum at 500ppm, and could reach 36% at 2000ppm, and 103% at 2000ppm, and the response of the PEI/CNT-COOH sensor to linalool was higher than that of phenylacetaldehyde at the same gas concentration.

Example 4 PEI/sensitivity test of CNT-COOH sensor to VOC

Measuring the lower limit of detection of the PEI/CNT-COOH sensor prepared in example 1, the CNT-COOH sensor and the CNT-NH ₂ sensor prepared in example 2 on the concentrations of linalool, phenylacetaldehyde, methyl salicylate and ethylhexanol, the concentration range of the detected gas is set to 0ppm-1000ppm, and the gas except the gas to be detected can possibly affect the PEI/CNT-COOH sensor, but according to our experimental experience, the response of the sensor caused by air is generally not more than 8%, so that when the lower limit detection of each VOC is carried out, the fluctuation of the absolute value of the response of the sensor is less than 8%, which is considered to be the value fluctuation caused by the air on the PEI/CNT-COOH sensor, and when the absolute value of the response of the sensor in the detected gas environment reaches the range of 8% -10%, the concentration of the detected gas is considered to be the lower limit concentration of the PEI/CNT-COOH sensor on the detected gas.

As shown in FIG. 9, the lower limit of detection of linalool by the PEI/CNT-COOH sensor is 7ppm, and the PEI/CNT-COOH sensor reaches about 55% |Ar| (FIG. 9 a) in a 1000ppm linalool environment; the lower detection limit for phenylacetaldehyde was 9ppm, the lower detection limit for methyl salicylate was 2ppm, the lower detection limit for PEI/CNT-COOH sensor was about 76% at a gas concentration of 1000ppm (FIG. 9 c), the lower detection limit for ethylhexanol was 25ppm, and the lower detection limit for PEI/CNT-COOH sensor was about 23% at a gas concentration of 1000ppm (FIG. 9 d).

From the response curve of FIG. 8, it can be analyzed that the absolute values of the response of the PEI/CNT-COOH sensor to these 4 VOCs at the same gas phase concentration are arranged in the order methyl salicylate > linalool > phenylacetaldehyde > ethylhexanol. The lower limit values of the PEI/CNT-COOH sensor for the 4 VOC detection concentrations are 2ppm of methyl salicylate, 7ppm of linalool, 9ppm of phenylacetaldehyde and 25ppm of ethyl hexanol, respectively, wherein the lower limit of detection of methyl salicylate, linalool and phenylacetaldehyde in response to the higher absolute value range is also lower than that of ethyl hexanol in response to the lower absolute value range, so that the sensitivity of the PEI/CNT-COOH sensor for the 4 VOC can be concluded to be ranked as methyl salicylate > linalool > phenylacetaldehyde > ethyl hexanol. The PEI/CNT-COOH sensor prepared by the invention can not only rapidly respond to the 4 HLB biomarkers, but also reach the minimum detection lower limit of 0-10 ppm level, and has extremely high sensitivity.

The results of FIG. 10 show that the PEI/CNT-COOH sensors reached the highest response values (49%, 35%, 15%, 68%) among the 3 sensors, regardless of the measured gas environment. In the detection of methyl salicylate, the PEI/CNT-COOH sensor reached a maximum response value that was even 4 times the maximum response values of the other two sensors. Overall, the sensitivity of the PEI/CNT-COOH sensor to the 4 volatiles tested herein was far higher than that of the CNT-COOH sensor and the CNT-NH ₂ sensor, which suggests that the PEI/CNT-COOH sensor can more effectively detect the VOC biomarker of citrus yellow dragon disease and can more effectively detect diseased citrus plants than the other two sensors, because the multi-walled carbon nanotubes modified with PEI have more gas adsorption sites and also have stronger gas adsorption capacity, and the polymeric amine structure of PEI with multiple amine groups can also effectively adsorb multiple VOCs such as aldehydes and alcohols.

FIG. 11 shows that the absolute value of the response of the PEI/CNT-COOH sensor is greater than that of the other two sensors, both for diseased and healthy citrus leaf volatiles, and that only the PEI/CNT-COOH sensor has a change trend differential between the responses of healthy and diseased leaves, i.e., a negative response to healthy citrus leaf volatiles and a positive response to diseased citrus leaf volatiles, the remaining two sensors being unable to distinguish diseased and healthy citrus from the change trend of the responses. This result more effectively demonstrates that the PEI/CNT-COOH sensor is more suitable as a sensor for discriminating whether citrus is infected with HLB.

Example 5 PEI/detection of citrus HLB by CNT-COOH sensor

The citrus varieties used herein are sugar oranges, which are obtained from a slightly HLB-infected orchard located in the Guangzhou city of Guangdong in China (113.6122 DEG E,23.135245 DEG N), and a batch of citrus trees planted for 4 years are selected as experimental materials in the orchard, wherein the batch of citrus trees comprises healthy citrus and citrus with HLB.

Currently, a widely accepted method in the laboratory for identifying citrus HLB is based on amplifying a specific 16S rDNA sequence in the HLB bacteria with specific primers, and determining whether and to what extent citrus trees are infected with HLB using Ct values determined by qPCR.

In order to determine whether the PEI/CNT-COOH sensor has the capability of detecting the HLB of citrus, taking citrus leaves as materials, cutting 0.05-0.1g of veins from the leaves after a gas-sensitive experiment, extracting DNA (deoxyribonucleic acid) of the veins, adjusting the concentration of the DNA to 100 ng/. Mu.L, then measuring the Ct value of qPCR (quantitative polymerase chain reaction), wherein the greater the Ct value is, the less the concentration of yellow dragon bacteria of the leaves is, and comparing the response of the PEI/CNT-COOH sensor of the same leaf with the Ct value detection result.

The qPCR method shows that the Ct value of the control sample (ultrapure water used for extracting DNA) is about 34-38, if the Ct value of the sample is lower than that of the blank sample, the sample is considered to be HLB positive, and if the Ct value of the sample is higher than that of the blank sample, the sample is considered to be HLB negative.

3 Healthy citrus leaves and 3 citrus leaves with HLB are picked, 5 leaves are randomly picked from each citrus tree as experimental materials, and only the leaves are cut off during picking, so that mechanical damage is not caused to mesophyll parts of the citrus leaves. The individual leaves were placed in a closed air chamber, the PEI/CNT-COOH sensor was exposed to the volatile air of the leaves for 30 minutes, the resistance was recorded every 6 minutes, the PEI/CNT-COOH sensor was again placed in air for 30 minutes, the resistance was recorded every 6 minutes, and the process was repeated 3 times within 3 hours, similarly to FIG. 8, the gray area was the real-time response of the PEI/CNT-COOH sensor to the volatile air of the leaves, and the white area was the real-time response of the PEI/CNT-COOH sensor to the air.

As shown in FIG. 12, when the PEI/CNT-COOH sensor is exposed to the citrus leaf with HLB, the PEI/CNT-COOH sensor can generate a positive response, the response value can be slowly restored to the baseline when the PEI/CNT-COOH sensor is restored in the air, the response of the PEI/CNT-COOH sensor can change within 0% -30% under the environment of volatilizing gas of the citrus leaf with HLB, and when the PEI/CNT-COOH sensor is exposed to the healthy citrus leaf, the PEI/CNT-COOH sensor can generate a negative response, the response can be slowly increased to the baseline when the PEI/CNT-COOH sensor is restored in the laboratory air with 25 ℃ and 50% humidity, and the response can change by-20% -0%.

Since we used a continuous period of time of real-time response testing equivalent to 3 technical replicates and the trend of the results obtained after all blade material testing remained the same (the real-time response results of the PEI/CNT-COOH sensor for the remaining blades are shown in FIGS. 13, 14), we considered that when a citrus blade was tested by the PEI/CNT-COOH sensor, it was indicated that the citrus blade was yellow-positive if the PEI/CNT-COOH sensor produced a positive response and the response could be maintained at a positive value for a period of time (about 30 minutes) and that the citrus blade was yellow-negative if a negative response was produced and the response could be maintained at a negative value for a period of time (about 30 minutes).

The other two sensors (CNT-COOH sensor, CNT-NH2 sensor) had no very significant regular changes like the PEI/CNT-COOH sensor in response to healthy citrus leaves and citrus leaf volatiles with HLB (fig. 15, 16).

To further demonstrate that PEI/CNT-COOH sensors can distinguish healthy from those with HLB, we designed verification experiments by picking a batch of leaves in each of the healthy and HLB-bearing citrus trees, for a total of 10 citrus trees, using the PEI/CNT-COOH sensor to perform the same gas detection test as above, and then using qPCR to detect the yellow shoot pathogen concentration of the leaves (to detect the Ct value of the leaves). The citrus trees tested have been identified by qPCR with 6 plants (plant 1, plant 3, plant 4, plant 5, plant 9, plant 10) with HLB and 4 healthy plants (plant 2, plant 6, plant 7, plant 8), respectively.

Table 5 is a table comparing the analysis results of PEI/CNT-COOH sensor with the Ct results of qPCR test blade, and the detection results of the sensor in Table 5 are Ar values when the PEI/CNT-COOH sensor reaches the maximum |Ar| within 30 minutes of detecting the blade. It can be seen from Table 5 that all leaves of all healthy plants tested (plant 2, plant 6, plant 7, plant 8) were negative in qPCR results (i.e., ct values were higher than negative control) and also negative in VOC analysis results (i.e., PEI/CNT-COOH sensor produced a negative response).

The detected leaves in the plant 1 are 8 pieces, the detection result of the PEI/CNT-COOH sensor shows that other leaf samples except the leaf 3 are positive, the qPCR result shows that 3 leaf samples (leaf 2, leaf 3 and leaf 4) are negative, when the leaf samples are detected by the PEI/CNT-COOH sensor, only 1 leaf sample shows a negative result, the qPCR result shows that 3 leaf samples (leaf 2, leaf 3 and leaf 4) are negative, the similar situation also shows that in the plant 3, the plant 4, the plant 5 and the plant 9, the situation that one leaf sample in the plant 3 shows that the PEI/CNT-COOH sensor result is positive and the qPCR result is negative, the situation that 3 leaf samples show that the PEI/CNT-COOH sensor result is positive and the qPCR result is negative, and the situation that 2 leaf samples show that the PEI/CNT-COOH sensor result is positive and the qPCR result is negative are found in the plant 9. According to qPCR results, it is determined that plants 3,4,5, 9 and 10 are plants with HLB, and only leaf samples of the plants 10 in the diseased plants are positive in HLB. These results indicate that all leaf samples of healthy plants show negative after PEI/CNT-COOH sensor detection and qPCR detection, and that the leaf samples of diseased plants show positive PEI/CNT-COOH sensor results and negative qPCR results, so that the detection results of PEI/CNT-COOH sensors are closer to the actual conditions in the case of leaf samples.

TABLE 5 comparison of PEI/CNT-COOH sensor detection results with qPCR results

Successful detection of PEI/CNT-COOH sensor in this comparative experiment highlighted the reliability of our fabricated PEI/CNT-COOH sensor detection method. The qPCR method can detect pathogens per se, while the PEI/CNT-COOH sensor is used for detecting the response of host plant VOC analysis after the host is infected with pathogens, because pathogen loads are unevenly distributed in plant tissues, HLB bacteria may exist in low concentration and may fluctuate with time, while citrus leaves not infected with yellow dragon disease may also exceed the leaves infected with HLB pathogens in number in early stages of infection, so that the Ct value of the plant leaves is measured in initial test, the result that part of leaf results are negative, namely, the sample is false negative, so that many citrus trees determined to be not infected continue to become infection sources from months to years after the initial test, our comparative test shows that metabolism of citrus trees infected with HLB has changed, VOC has also changed, and our manufactured PEI/CNT-COOH sensor can detect that under the same sampling amount, the accuracy of our manufactured PEI/CNT-COOH sensor detection method is higher than that of the conventional qPCR detection method. This illustrates that our fabricated PEI/CNT-COOH sensor can be used for detection of early HLB citrus trees.

The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.

Claims

1. A PEI-modified multi-walled carbon nanotube gas sensor, characterized in that it comprises a PEI-modified multi-walled carbon nanotube and a resistance detection instrument, wherein the PEI-modified multi-walled carbon nanotube is used to adsorb volatile organic compounds, and the resistance detection instrument is used to detect the resistance value of the PEI-modified multi-walled carbon nanotube;

The method for preparing the PEI-modified multi-walled carbon nanotubes comprises the following steps:

S1. dispersing multi-walled carbon nanotubes in an organic solvent, ultrasonically dispersing a multi-walled carbon nanotube dispersion, and using a dielectrophoresis arrangement method to uniformly disperse the multi-walled carbon nanotubes between two metal electrodes on a sensor substrate to obtain a multi-walled carbon nanotube sensor;

S2. The multi-walled carbon nanotube sensor was completely immersed in the PEI solution, and allowed to stand for 1 to 2 hours under closed conditions, and then washed and dried to obtain a PEI-modified multi-walled carbon nanotube gas sensor;

In step S1, the steps of the dielectrophoresis arrangement method are as follows: ultrasonically treat the multi-walled carbon nanotube dispersion for 20 to 30 minutes and set aside. At the beginning of the dielectrophoresis arrangement, 10 μg/mL of the ultrasonic multi-walled carbon nanotube dispersion is dropped in the center of two metal electrodes, the instrument is connected, the parameters are adjusted, the power is turned on for 180 seconds, and the mixture is washed and dried.

The volatile organic compound is linalool, phenylacetaldehyde, ethylhexanol or methyl salicylate.

2. Application of the PEI-modified multi-walled carbon nanotube gas sensor according to claim 1 in detecting citrus Huanglongbing or Catharanthus roseus Huanglongbing.

3. The use according to claim 2, characterized in that the PEI-modified multi-walled carbon nanotube gas sensor detects citrus Huanglongbing by detecting volatile organic compounds released when citrus trees are infected with citrus Huanglongbing.

4. A gas-sensitive testing system, characterized in that it includes an air chamber, a resistance detection system, and a PC end in sequence according to the sample flow direction, wherein the air chamber includes an inlet, an air agitator, and the PEI-modified multi-walled carbon nanotube gas sensor according to claim 1.

5. The system according to claim 4 is characterized in that the sample inlet is used to add the sample to be tested, the air agitator is used to evenly mix the gas volatilized by the volatile organic compound with the air in the gas chamber, the PEI-modified multi-walled carbon nanotube gas sensor is used to adsorb the gas volatilized by the volatile organic compound, the resistance detection system is used to detect the resistance value of the PEI-modified multi-walled carbon nanotube gas sensor, and the PC end is used to calculate and display the results.

6. A method for detecting citrus Huanglongbing disease, characterized in that the detection is carried out using the system described in claim 4 or 5.

7. The method according to claim 6, characterized in that the detection method comprises the following steps:

The leaves of citrus before and after being infected with Huanglongbing were placed in an air chamber. After the gas released by the citrus was mixed with the air in the chamber, the PEI-modified multi-walled carbon nanotube gas sensor was placed in the air chamber for 25 to 40 minutes, removed, and allowed to stand for 25 to 40 minutes. The resistance detection system recorded the resistance value of the PEI-modified multi-walled carbon nanotube gas sensor every 5 to 8 minutes, and the results were calculated and displayed on the PC.

8. The method according to claim 7, characterized in that the resistance value recorded after the resistance of the PEI-modified multi-walled carbon nanotube gas sensor is stabilized in a natural environment with an air humidity of 50% is used as the baseline resistance, and when the resistance value of the PEI-modified multi-walled carbon nanotube gas sensor after adsorbing the test object is higher than the baseline resistance, it is positive, and when it is lower than the baseline resistance, it is negative.