A method for improving the sensing selectivity of sensitive materials

Abstract

The present invention discloses a method for improving the sensing selectivity of sensitive materials in the field of materials science and technology. The target gas to be measured is input into the sensitive material database to retrieve the sensitive materials. The various gases of the target gas and interfering gases in practical applications and the sensitive materials are input into the expert database to retrieve the structural data. Based on this, a material surface-gas molecule adsorption model is constructed. By using the first-principles method to simulate the adsorption process and mechanism of gas molecules on the material surface, the essence of the interference of interfering gases on the selective adsorption of sensitive materials-target gases is determined. A surface functionalization scheme is proposed to adjust the types of surface active sites of sensitive materials, thereby regulating the adsorption strength of different gas molecules. The sensing performance of the nanosensor device of the surface-functionalized sensitive material is constructed. The adsorption and sensing performance data can be obtained simply and quickly, reducing the consumption and expenditure of manpower and material resources, saving time, improving the efficiency of the research and development of sensitive materials, and having great practical value.

Description

Technical Field

[0001] The present invention belongs to the technical field of materials science and particularly relates to a method for improving the sensing selectivity of a sensitive material. Background Art

[0002] The integrated development of multiple disciplines has become one of the most prominent features in the development of modern materials science. In particular, computational materials science, which has emerged from the integration with related basic disciplines such as quantum mechanics, condensed matter physics, and computational science and technology, has made it possible the material design concept that combines cross-scale, cross-level, and multiple methods. The previous research idea of studying the application scenarios based on the structure, organization, and properties of materials has been subverted. By means of theoretical simulation and calculation of materials, the performance of materials is directly connected with their composition and structure, with demand as the guidance, which will greatly improve the efficiency of material R & D, reduce the R & D cycle and cost expenditure. This is also an effective method for future new, efficient, and fast advanced materials, and will play a crucial role in promoting the development of China's national economy.

[0003] A gas sensor can sense the composition and concentration of gases in the external environment and can quickly detect various toxic, harmful, flammable, and explosive gases in the external environment. The gas sensor has the advantages of rapid detection, simple operation, low cost, small size, and easy portability, and has broad application prospects and huge market demands in the fields of environmental monitoring, public safety, medical and health, production detection, food safety, and home decoration detection. The sensitive material is the material basis for contacting and sensing the target gas in the gas sensor and is the basis for improving the sensitive performance of the sensor. Preparing high-performance sensitive materials is the core and focus of the development and research of gas sensors. Selectivity is the ability of the sensor to produce a sensing effect on the target gas in the presence of other gases and is one of the most important performance indicators of the sensor.

[0004] The sensor is a basic product in the electronic information industry and the core unit of olfactory sensing in the Internet of Everything and intelligent manufacturing, determining the future intelligent society and intelligent production. The sensor will provide various key information and detection data required for industrial production and social life, and its importance and market opportunities are self-evident. Therefore, countries around the world have continuously increased their investment and R & D in sensors. With the rapid development of the industrial Internet, Industry 4.0, and intelligent manufacturing, high sensitivity, faster speed, high selectivity, and low concentration are required for the performance indicators of sensors. For example, detecting specific VOCs gases with biomarker applications can monitor human health, requiring high sensitivity and selectivity, and the detection limit reaches the ppb level concentration. Developing high-performance gas-sensitive materials with high sensitivity, excellent selectivity, etc. will greatly promote the development of China's intelligent manufacturing and social development. Summary of the Invention

[0005] The object of the present invention is to provide a method for improving the sensing selectivity of a sensitive material, which is characterized in that by constructing an adsorption model of a surface-modified sensitive material-gas molecule and a nano-sensor device, adsorption and sensing performance data can be obtained simply and quickly, and the method specifically includes the following steps:

[0006] (1) Determine the type of sensitive material whose selectivity needs to be improved, and construct a material surface-gas molecule adsorption model: Input the information of the target gas to be detected into the sensitive material database to retrieve the information of the sensitive material, input the information of the target gas, interfering gas and sensitive material in actual application into the expert database, determine the type of sensitive material whose selectivity needs to be improved through retrieval, and construct a material surface-gas molecule adsorption model through the retrieved structural information;

[0007] (2) Clarify the action mechanism of the interfering gas on the sensitive material, and propose a surface functionalization scheme for improving the selective adsorption of the sensitive material-target gas: Calculate and simulate the adsorption process and action mechanism of different gases including the target gas and the interfering gas on the surface of the sensitive material through the first-principles calculation method of quantum mechanics, and the action mechanism includes adsorption energy and electronic structure; Clarify the root cause of the difference in the strength of the action between the target gas and the interfering gas on the surface of the sensitive material, and combine the chemical bond energy data information and experimental synthesis conditions in the expert database to propose a surface functionalization scheme for the selectivity of the sensitive material. The surface functionalization scheme is defects, doping, cluster loading, chemical modification, so as to improve its sensing selectivity for the target gas;

[0008] (3) Screen the functionalization scheme for enhancing the selective adsorption of the target gas, and further simulate the sensing performance of the surface-functionalized sensitive material to the target gas: Construct a surface model of the sensitive material with different functionalization methods, calculate and simulate the adsorption process and action mechanism of different gases including the target gas and the interfering gas on the surface of the sensitive material through the first-principles calculation method of quantum mechanics, and screen out the functionalized surface structure that enhances the selective adsorption of the target gas; Based on the non-equilibrium Green's function-density functional theory method, construct a nano-sensor device model with the surface-functionalized sensitive material surface as the central region, and simulate and calculate the current-voltage curve and sensing response and other sensing performances to the target gas to verify whether it can be applied to the detection of the target gas;

[0009] (4) Correlate the computational simulation with the experiment: Compare the data of the gas zero-point correction energy, adsorption energy, current-voltage curve, and sensitivity with the experimental values, evaluate the error and perform numerical correction; Compare the calculated adsorption-sensing mechanism with the experiment to evaluate whether they match;

[0010] The target gas to be detected includes: N x O y , NH3, CO, SO2, H2S and VOCs.

[0011] The electronic structure of the mechanism of action is bonding, charge transfer, and electron density.

[0012] In step (2), the adsorption process and mechanism of action of different gases including the target gas and interfering gases on the surface of the sensitive material are calculated and simulated by the first-principles calculation method of quantum mechanics, where the adsorption energy E ads The calculation formula is as follows:

[0013] E ads = E mol-sub - E mol - E sub + ΔE ZPE

[0014] where E mol-sub is the energy of the gas molecule adsorbed on the surface of the sensitive material after structural relaxation, E mol and E sub are the energies of the gas molecule and the surface of the sensitive material respectively, and ΔE ZPE is the zero-point energy correction value of the gas molecule.

[0015] In the first-principles calculation method, combined with the actual application scenario of the sensitive material in detecting the target gas and the interference of other gas components on the sensing effect of the sensitive material-target gas, the chemical bonds formed by the interaction of the surface of the sensitive material with some interfering gas molecules are stronger than those with the target gas molecules; through theoretical calculation, the root cause of the poor sensing selectivity of the sensitive material to the target gas can be revealed, which is of great significance for the development of high-performance sensing materials.

[0016] In the first-principles calculation method of quantum mechanics, the adsorption stability of surface-functionalized sensitive materials including defects, doping, cluster loading, and chemical modification is calculated. After screening out the methods that can improve the selectivity of the sensitive material, the sensing performance is tested to verify whether it can meet the performance requirements for detecting the target gas.

[0017] The beneficial effect of the present invention is that by constructing an adsorption model of the surface-modified sensitive material-gas molecule and a nano-sensor device, the adsorption and sensing performance data can be obtained simply and quickly. Compared with the traditional experimental method, it reduces the consumption and expenditure of human and material resources, saves time, and can greatly improve the R & D efficiency of new sensitive materials. Using this method can efficiently and quickly improve the sensing selectivity of the sensitive material;

[0018] Secondly, the present invention uses the first principle combined with the non-equilibrium Green's function method to simulate the influence of different surface functionalization methods on the interaction strength between the surface of the sensitive material and gas molecules at the atomic scale, and can effectively predict and screen surface functionalization methods that enhance the adsorption strength of the sensitive material to the target gas and have excellent sensing performance. Previous scientific research has found that there is a close relationship between the surface structure characteristics of materials and gas molecule adsorption, but it does not explain the reasons for the influence of adsorption and propose a design method for functionalizing the surface of sensitive materials to improve sensing selectivity. The present invention designs and proposes a complete design scheme for optimizing the sensing selectivity of sensitive materials. Combining the information in the expert database, the calculation and simulation method predicts and screens surface functionalization methods that can improve the selective adsorption of the sensitive material to the target gas, and simulates its sensing performance to the target gas by constructing a nano-sensor device model. The adsorption strength of the sensitive material to different gases is obtained, and finally it is verified whether the sensing performance of the surface-functionalized sensitive material to the target gas can be actually applied; the present invention can significantly improve the improvement efficiency of the sensing selectivity of gas-sensitive materials. The method of the present invention has strong practical value for improving the sensing selectivity of gas-sensitive materials and studying the interaction mechanism between the material surface and gas molecules. Brief Description of the Drawings

[0019] Figure 1 Flow chart for improving the sensing selectivity of sensitive materials.

[0020] Figure 2 Adsorption energies of six VOC gas molecules on the Ag-doped graphene surface.

[0021] Figure 3 Adsorption energies of six VOC gas molecules on the Si-doped graphene surface.

[0022] Figure 4 Dual-port nano-sensor models along the (a) armchair and (b) zigzag transport directions, with the left and right electrodes being semi-infinite graphene and connected to the central scattering region where HCHO molecules are adsorbed by Si-doped graphene.

[0023] Figure 5 To verify the current-voltage curves and sensitivities of the Si-doped graphene nano-sensors in the (a) armchair and (b) zigzag transport directions from 0 to 1.0 V. Detailed Description of the Invention

[0024] The purpose of the present invention is to provide a method for improving the sensing selectivity of sensitive materials. The present invention will be described in detail below with reference to the drawings and embodiments.

[0025] As Figure 1The flow chart for improving the sensing selectivity of sensitive materials is shown below. The implemented flow chart includes the following steps: First, input the target gas and information about other gases in the actual application scenario, retrieve the types of sensitive materials whose selectivity needs to be improved from the sensitive material data, and then retrieve information such as various atomic structure parameters and physical and chemical properties of the sensitive materials from the expert database. Construct an adsorption atomic model of gas molecules adsorbed on the surface of the sensitive material, and calculate and simulate to obtain a stable adsorption configuration, the adsorption energy, electronic structure, etc. of the sensitive material to gas molecules through the first principle calculation method of quantum mechanics, revealing the fundamental reason for the difference in adsorption strength between the sensitive material and the target gas and interfering gas molecules on the sensitive material. Retrieve the chemical bond energy data from the expert database and propose a surface functionalization (such as defects, doping, cluster loading, chemical modification, etc.) scheme for the sensitive material surface; then establish a surface-functionalized sensitive material-gas molecule adsorption model, and verify through calculated adsorption energy, etc. whether the proposed surface functionalization scheme can improve the sensing selectivity of the sensitive material to the target gas. Then construct a nano-sensor device model with the surface-functionalized sensitive material as the scattering region, and simulate its current-voltage curve and sensing response to HCHO. According to the above structure, guide the experiment with surface functionalization methods such as defects, doping, cluster loading, chemical modification, etc. to complete the improvement of the sensing selectivity of the sensitive material to the target gas.

[0026] Example

[0027] As Figures 2 - 5 shown; taking Ag-doped graphene as the sensitive material to detect HCHO (formaldehyde) gas as an example, it has a large enough adsorption to HCHO molecules, and the sensitivity at low bias voltage is as high as 900%. However, its selectivity in the application scenario of volatile organic compounds (VOCs) is poor, and it has stronger adsorption to molecules such as olefins and alkynes, interfering with the detection of HCHO and significantly affecting the actual application. Therefore, taking graphene as the sensitive material, a method to improve its sensing selectivity to HCHO in the VOCs application scenario by replacing the doping atoms is as follows. The specific calculation method and structure are as follows:

[0028] (1) Obtain the surface characteristics of Ag-doped graphene and the structural parameters of VOCs molecules: Retrieve the structural characteristics of single-layer graphene and various VOCs molecules (such as CH4, C2H2, C2H4, CH3OH, CH3Cl, and HCHO, etc.) from the expert database, and simulate and calculate the graphene lattice of Ag-doped graphene The height of the doped atom protruding from the graphene plane is consistent with the literature results. The optimized VOCs molecular structure obtained through simulation calculation is also consistent with the literature results. The vacuum layer thickness of various adsorption models is

[0029] (2) Obtain the stable configurations, corresponding adsorption energies, electronic structures, etc. of various VOCs molecules on Ag-doped graphene: Optimize the stable adsorption structures, adsorption energies, electronic structures, etc. of VOCs molecules on Ag-doped graphene through first-principles calculations. The adsorption energy E ads The calculation formula is as follows:

[0030] E ads = E mol-sub - E mol - E sub + ΔE ZPE

[0031] where E mol-sub is the energy of the gas molecule adsorbed on the surface of the sensitive material after structural relaxation, E mol and E sub are the energies of the gas molecule and the surface of the sensitive material respectively, and ΔE ZPE is the zero-point energy correction value of the gas molecule.

[0032] The calculated adsorption energies are as Figure 2 shown: On Ag-doped graphene, the adsorption energy of HCHO is less than that of C2H2 and C2H4, and is close to that of CH3OH. In applications where other VOCs gases are present, alkyne molecules will preferentially occupy the active sites of the doped graphene, preventing the adsorption of HCHO molecules, which will reduce the selectivity for HCHO and affect other properties such as the detection limit and sensitivity. Combining the analysis of results such as electronic structures and charge transfer, it is found that the C-Ag-C ternary bond formed by alkyne gas molecules such as C2H2 and C2H4 with Ag is stronger than the O-Ag-C ternary bond adsorbed by HCHO molecules. It is proposed to use other doped atoms to replace Ag so that its binding with O atoms is stronger than that with C atoms. Searching the expert database, it is found that the bond dissociation energy of the Si-O bond (799.6 kJ / mol) is larger than that of the Si-C bond (451.5 kJ / mol), and it is proposed to use Si to replace Ag-doped graphene so that the bonding of HCHO with Si atoms is stronger than that with alkynes such as C2H2 and C2H4.

[0033] (3) Verify the selective adsorption performance of Si-doped graphene for HCHO molecules in a VOCs environment: Based on the first-principles simulation calculation of quantum mechanics, obtain the height protruding from the graphene plane of Si-doped graphene, which is consistent with the literature results. Optimize the stable adsorption structures, adsorption energies, etc. of VOCs molecules on Si-doped graphene through first-principles calculations. The calculated adsorption energies are as Figure 3As shown in the figure: The adsorption energy of HCHO molecules on Si-doped graphene is the most negative among the six VOCs gases, much stronger than the adsorption of C2H2, C2H4, and CH3OH. The adsorption energies of C2H2 and C2H4 are greater than -0.50 eV, turning into physical adsorption. The interference of alkenynes and alkynes to HCHO is even smaller, and the selectivity of Si-doped graphene as a sensitive material for HCHO sensing is further enhanced.

[0034] (4) Construct Si-doped graphene as a nano-sensor device and simulate its sensing performance for HCHO molecules: Based on the density functional theory combined with the non-equilibrium Green's function method, construct a nano-sensor device with intrinsic graphene as the left and right electrodes and Si-doped graphene as the central scattering region. Since the graphene lattice has structural anisotropy, there are two typical transport directions of current after applying voltage - armchair and zigzag (as Figure 5 shown). Simulate its current-voltage curve, sensitivity, etc. for HCHO molecules. The sensitivity calculation formula is as follows:

[0035] S = (I0 - I) / I × 100%

[0036] where I0 is the initial current of the sensor and I is the current after the sensor adsorbs HCHO molecules. As Figure 5 shown, the adsorption of HCHO molecules makes the current flowing through the sensor increase, and there is a large difference in the current before and after adsorption. The sensitivity to HCHO can reach 40% at low bias voltage, which can meet the actual application requirements.

[0037] Trimethylsilyl and n-hexane are used as the precursors of Si and C respectively. The precursor liquid is transported to the chemical vapor deposition reactor through argon, and a large-area Si-doped graphene sheet can be grown on the Cu foil. Finally, the Si-doped graphene sheet is connected and encapsulated with metal electrodes and tested to detect HCHO gas. When Si-doped graphene maintains the adsorption strength for HCHO, but has weak adsorption for other VOCs gases, that is, the selectivity of HCHO is enhanced and the sensing current signal is relatively sensitive. Using the present invention, it is possible to quickly guide the experiment to complete the optimization of the enhanced selectivity of the sensitive material through surface functionalization methods such as defects, doping, cluster loading, chemical modification, etc.

Claims

1. A method for improving the sensing selectivity of a sensitive material, characterized in that, By constructing an adsorption model of surface-modified sensitive material - gas molecules and a nano-sensor device, adsorption and sensing performance data can be obtained simply and quickly, which specifically includes the following steps: (1) Determine the type of sensitive material whose selectivity needs to be improved and construct an adsorption model of material surface - gas molecules: Input the information of the target gas to be detected into the sensitive material database to retrieve the information of the sensitive material. Input the information of the target gas, interfering gas, and sensitive material in the actual application into the expert database. Determine the type of sensitive material whose selectivity needs to be improved through retrieval, and construct an adsorption model of material surface - gas molecules based on the retrieved structural information; (2) Clarify the action mechanism of the interfering gas on the sensitive material and propose a surface functionalization scheme to improve the selective adsorption of the sensitive material - target gas: Calculate and simulate the adsorption process and action mechanism of different gases including the target gas and interfering gas on the surface of the sensitive material through the first-principles calculation method of quantum mechanics. The action mechanism includes adsorption energy and electronic structure; clarify the fundamental reason for the difference in the strength of the action between the target gas and the interfering gas on the surface of the sensitive material. Combine the chemical bond energy data information in the expert database and the experimental synthesis conditions to propose a surface functionalization scheme for the selectivity of the sensitive material. The surface functionalization scheme is defects, doping, cluster loading, and chemical modification to improve its sensing selectivity for the target gas; (3) Screen the functionalization scheme that enhances the selective adsorption of the target gas and further simulate the sensing performance of the surface-functionalized sensitive material for the target gas: Construct a surface model of the sensitive material with different functionalization methods. Calculate and simulate the adsorption process and action mechanism of different gases including the target gas and interfering gas on the surface of the sensitive material through the first-principles calculation method of quantum mechanics. Screen out the functionalized surface structure that enhances the selective adsorption of the target gas; Based on the non-equilibrium Green's function - density functional theory method, construct a nano-sensor device model with the surface-functionalized sensitive material surface as the central region, and simulate and calculate the current-voltage curve and sensing response and other sensing performances for the target gas to verify whether it can be applied to the detection of the target gas; (4) Correlate computational simulation with experiments: Compare the data of gas zero-point correction energy, adsorption energy, current-voltage curve, and sensitivity with the experimental values, evaluate the error and perform numerical correction; Compare the calculated adsorption-sensing mechanism with the experiment to evaluate whether they match.

2. The method for improving the sensing selectivity of a sensitive material according to claim 1, characterized in that, The target gas to be detected includes: N x O y , NH3, CO, SO2, H2S, and VOCs.

3. The method for improving the sensing selectivity of a sensitive material according to claim 1, characterized in that, The electronic structure of the said action mechanism is bonding, charge transfer, and electron density.

4. The method for improving the sensing selectivity of a sensitive material according to claim 1, characterized in that, In the step (2), the adsorption process and mechanism of different gases including the target gas and the interfering gas on the surface of the sensitive material are calculated and simulated by the first principle calculation method of quantum mechanics, where the adsorption energy E ads The calculation formula is as follows: E ads = E mol-sub - E mol - E sub + ΔE ZPE Among which E mol-sub is the energy of the gas molecules adsorbed on the surface of the sensitive material after structural relaxation, E mol and E sub are the energies of the gas molecules and the surface of the sensitive material respectively, and ΔE ZPE is the zero-point energy correction value of the gas molecules.

5. The method for improving the sensing selectivity of a sensitive material according to claim 1, characterized in that, The first-principles calculation method of quantum mechanics, combined with the actual application scenario of the sensitive material in detecting the target gas and the interference of other gas components on the sensing effect of the sensitive material - target gas, is that the chemical bond formed by the interaction between the surface of the sensitive material and some interfering gas molecules is stronger than that with the target gas molecules; Through theoretical calculation, the fundamental reason for the poor sensing selectivity of the sensitive material for the target gas can be revealed, which is of great significance for the development of high-performance sensing materials.

6. The method for improving the sensing selectivity of a sensitive material according to claim 1, characterized in that, The first principle calculation method of quantum mechanics performs adsorption stability calculations on sensitive materials with surface functionalization including defects, doping, cluster loading, and chemical modification. After screening out methods that can improve the selectivity of the sensitive materials, the sensing performance is tested to verify whether it can meet the performance requirements for detecting target gases.

Images