A sensor structure for discriminating different molecular weight gases and a simulation method

Abstract

The application discloses a sensor structure and a simulation method for distinguishing different molecular weight gases, the sensor structure comprising a semiconductor nanotube array and an electrode, the electrode being in contact with the top and bottom of the semiconductor nanotube array, and the nanotube diameter being smaller than the mean free path of the gas to be detected; the simulation method comprising: establishing an axisymmetric two-dimensional section geometric model of a single nanotube structure in the semiconductor nanotube array by using a finite element simulation software, adding a semiconductor and a free molecule flow physical field interface, setting material properties and boundary conditions, dividing a grid and analyzing the diffusion of different molecular weight gases and the sensor response process by using a transient solver; and the application realizes the distinction of the sensor to different molecular weight gases through different diffusion processes in the nanotube with a diameter smaller than the mean free path of the gas to be detected and different response results of the sensor, and solves the problem of poor gas distinguishing ability of the semiconductor gas sensor in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of gas detection and sensors, and in particular to a sensor structure and a simulation method for distinguishing gases of different molecular weights. Background Art

[0002] Gas sensors are widely used in industrial safety, environmental monitoring, healthcare, and other fields. In applications involving the detection of multi-component gases (such as toxic and harmful gases generated in industrial production, flammable and explosive gases in potentially hazardous environments, and symptomatic gases exhaled by patients in medical diagnosis), sensors must possess strong resolution and high detection efficiency for different types of gases (especially gases with similar functional groups). Therefore, developing gas sensor structures that can quickly and accurately distinguish gases of different molecular weights is of great significance for ensuring production environment safety and assisting medical diagnosis.

[0003] Commonly used gas sensors are classified into electrochemical, catalytic combustion, optical, and semiconductor types. Among them, semiconductor gas sensors have advantages such as high sensitivity, fast response, low cost, and strong integration, but their gas resolution capabilities are limited.

[0004] The sensing process of semiconductor gas sensors can be divided into the gas dynamics process of the gas to be measured diffusing to the surface of the sensitive material, and the semiconductor process of the semiconductor resistance change caused by the adsorption / desorption of the gas on the semiconductor surface.

[0005] Existing research has largely focused on the adsorption and desorption of gases on semiconductor surfaces, neglecting the diffusion process before the gases reach the surface. However, strategies that alter the adsorption sites of gases on semiconductor surfaces are primarily effective for distinguishing gas molecules with distinct functional groups; gases with similar functional groups are fundamentally difficult to distinguish.

[0006] Previous studies on gas dynamics have shown that gases diffuse differently in nanostructures than in free space. When the mean free path of a gas is greater than the pore size of the nanostructure, gas molecules undergo Knudsen diffusion, and the diffusion coefficient is related to the gas molecular weight. However, this diffusion characteristic has not yet been combined with sensor response to discriminate between gases of different molecular weights.

[0007] Therefore, how to propose a sensor structure and simulation method for distinguishing gases of different molecular weights to intuitively reflect the gas diffusion process within the structure and its impact on the transient response of the sensor is a technical problem that needs to be solved urgently. Summary of the Invention

[0008] Invention purposes: In view of the deficiencies in the prior art, the purpose of the present application is to provide a sensor structure and simulation method for distinguishing different molecular weight gases, which utilizes the different diffusion processes of different gases to be detected in nanotubes with a tube diameter smaller than the average free path and the different response results of the sensor, realizes the distinction of the sensor for different molecular weight gases, and solves the problem of poor distinguishing ability of the semiconductor gas sensor for gases with similar functional groups in the prior art.

[0009] Technical solutions: The purpose of the present application is realized by the following technical solutions:

[0010] The sensor structure for distinguishing different molecular weight gases of the present application comprises a semiconductor nanotube array and an electrode, the electrode being in contact with the top and bottom of the semiconductor nanotube array; the nanotube tube diameter in the semiconductor nanotube array is smaller than the average free path of the gas to be detected.

[0011] The simulation method for distinguishing different molecular weight gases of the present application is implemented by the sensor structure for distinguishing different molecular weight gases, and comprises the following steps:

[0012] (1) An axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in the semiconductor nanotube array is established in the finite element simulation software COMSOL, a rectangle representing the outer contour of the nanotube is drawn with the axis as the axis of symmetry, and a tube structure representing the inner contour of the nanotube is drawn inside the rectangle with the axis as the axis of symmetry, the space enclosed by the tube structure and the axis is the gas diffusion space, the tube longitudinal wall is parallel to the outer contour of the nanotube, and the distance between the tube longitudinal wall and the outer contour of the nanotube represents the wall thickness of the nanotube, the tube diameter is smaller than the average free path of the gas to be detected;

[0013] (2) Semiconductor physical field interface and free molecule flow physical field interface are added in the finite element simulation software COMSOL;

[0014] (3) Material settings are made for the axisymmetric two-dimensional cross-sectional geometric model of the single nanotube structure in the finite element simulation software COMSOL;

[0015] (4) The surface charge density of the inner wall of the semiconductor nanotube, the analytical doping model and the doping concentration of the semiconductor nanotube material, the metal contact type and the terminal voltage of the contact surface between the semiconductor and the electrode are set in the semiconductor physical field in the finite element simulation software COMSOL; wherein the surface charge density of the inner wall of the semiconductor nanotube is:

[0016] ρ s =-e_const*(scd-fmf.N_ads_G1 / (2e3))

[0017] Wherein, ρ sis the surface charge density, e_const is the basic charge, scd is the number of active adsorption sites per unit area on the material surface, and fmf.N_ads_G1 is the number of adsorbed molecules per unit area.

[0018] (5) In the free molecular flow physics field of the finite element simulation software COMSOL, the molecular weight of the gas to be detected, the surface temperature of the gas diffusion space, the type and boundary conditions of the inner wall of the nanotube, the initial values ​​of the incident gas molecular flux, pressure, number density, and the storage tank pressure boundary conditions are set; among them, the inner wall type of the nanotube is adsorption / desorption, and the initial adsorption concentration n is ads,0,G1 = 0, additional molar flux Γ G1 =0, the adhesion coefficient is:

[0019] S G1 =sc*(1-fmf.n_ads_G1 / n)

[0020] Among them, S G1 is the adhesion coefficient, sc is the adhesion coefficient when there is no site occupancy, fmf.n_ads_G1 is the number of moles of adsorbed molecules per unit area, and n is the number of moles of active adsorption sites per unit area on the material surface;

[0021] The desorption rate is: D G1 =fmf.n_ads_G1 / τ

[0022] Among them, D G1 is the desorption rate, and τ is the desorption time constant.

[0023] The initial value of the incident molecular flux is G G1 =0, the initial value of pressure is p G1 =0, the initial value of number density is n G1 =0.

[0024] The pressure boundary condition of the storage tank is: p 0,G1 =1e5*per

[0025] Among them, p 0,G1 is the storage tank pressure, and per is the concentration of the gas to be detected (in ppm).

[0026] (6) Meshing the axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in the finite element simulation software COMSOL, determining the meshing sequence type, and setting the mesh unit shape and size;

[0027] (7) In the finite element simulation software COMSOL, the simulation time unit, time step and tolerance in the transient solver are configured, the free molecular flow physics interface and the semiconductor physics interface are selected as the physics interfaces to be calculated, and an auxiliary scan of the concentration of the gas to be detected is added. The number of molecules adsorbed per unit area on the inner wall of the nanotube and the sensor response value in the set time step are simulated and calculated; by comparing the diffusion process of gases with different molecular weights in the nanotubes and the simulation results of the different responses of the sensor to gases with different molecular weights, gases with different molecular weights are distinguished.

[0028] In step (3), the semiconductor nanotube material is set as the semiconductor material for the gas sensor.

[0029] Preferably, the semiconductor nanotube material in step (3) is set to anatase titanium dioxide.

[0030] The analytical doping model of the semiconductor nanotube material in step (4) is donor doping (n-type).

[0031] In step (4), the metal contact type between the semiconductor and the electrode contact surface is an ideal ohmic contact, the terminal voltage V0 at the top of the material is 0V, and the terminal voltage V1 at the bottom is greater than 0V.

[0032] In step (6), the meshing sequence type used for the axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure is a physical field controlled mesh, the mesh shape is a triangular mesh, and the mesh size is refined.

[0033] In step (7), the molecular weights of different gases to be detected are set to simulate the input of gases with different molecular weights, and steps (1) to (7) are repeated. By comparing the diffusion process of gases with different molecular weights in the nanotubes and the simulation results of the different responses of the sensor to gases with different molecular weights, gases with different molecular weights are distinguished.

[0034] Working Principle: The sensor structure of the present invention distinguishes gases of different molecular weights by the following method: when the nanotube diameter is smaller than the mean free path of the gas being detected, the gas's diffusion coefficient and diffusion rate are inversely proportional to the 0.5 power of the gas's molecular weight. Gases with smaller molecular weights diffuse faster than gases with larger molecular weights within nanotubes with diameters smaller than the mean free path of the gas being detected. Therefore, during gas detection, the sensor's response to gases with smaller molecular weights is greater than that to gases with larger molecular weights within the same timeframe. For gases with smaller molecular weights, more gas molecules enter the nanotubes at the same time, resulting in a faster and larger sensor response.

[0035] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0036] (1) The sensor structure and simulation method of the present invention are used to distinguish gases of different molecular weights. The sensor distinguishes gases of different molecular weights by utilizing the different diffusion processes of different gases to be detected in nanotubes with diameters smaller than their mean free paths and the different response results of the sensors. The sensor has a simple and flexible structure and strong practicality.

[0037] (2) The simulation of the gas diffusion and sensor response process of the nanotube sensor structure of the present invention can intuitively and clearly verify the effectiveness of the sensor structure in distinguishing different gases, saving experimental costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the structure of the sensor for distinguishing gases of different molecular weights according to the present invention;

[0039] Figure 2 FIG. 1 is an axisymmetric two-dimensional cross-sectional geometric model diagram of a single nanotube structure in a semiconductor nanotube array according to an embodiment of the present invention;

[0040] Figure 3 Schematic diagram of a meshing method for an axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure according to an embodiment of the present invention;

[0041] Figure 4 This is a simulated cloud diagram of the number of gas molecules adsorbed per unit area on the inner wall of the nanotube after passing hydrogen, methane, and ethane gases with a concentration of 1 ppm for 40 ms, 60 ms, 80 ms, and 100 ms, respectively, in an embodiment of the present invention;

[0042] Figure 5 This is a simulated cloud diagram of the number of gas molecules adsorbed per unit area on the inner wall of the nanotube after hydrogen, methane, and ethane gases with a concentration of 100 ppm were introduced for 4ms, 6ms, 8ms, and 10ms, respectively, in an embodiment of the present invention;

[0043] Figure 6 Graphs showing the time-domain response of a single nanotube sensor to (a) hydrogen, (b) methane, and (c) ethane at concentrations of 1 ppm, 10 ppm, 100 ppm, and 1000 ppm, according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] like Figure 1 Figure 2 shows a schematic diagram of the sensor structure for distinguishing gases of different molecular weights according to the present invention, comprising a semiconductor nanotube array 1 and electrodes 2. The diameter of the nanotubes in semiconductor nanotube array 1 is smaller than the mean free path of the gas to be detected, and the positive and negative electrodes of electrode 2 contact the top and bottom surfaces of the semiconductor nanotube array, respectively.

[0045] Figure 2This is a diagram of an axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in a semiconductor nanotube array provided by an embodiment of the present invention. This embodiment is modeled and simulated using the COMSOL 5.4 simulation platform. An axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in a semiconductor nanotube array is established. A rectangle representing the outer contour of the nanotube is drawn with the axis as the axis of symmetry. A tube structure representing the inner contour of the nanotube is drawn inside the rectangle with the axis as the axis of symmetry. The space enclosed by the tube structure and the axis is the gas diffusion space. The longitudinal wall of the tube is parallel to the outer contour of the nanotube, and the distance between the longitudinal wall and the outer contour of the nanotube represents the wall thickness of the nanotube.

[0046] In this embodiment, the nanotube has a diameter of 25 nm, a wall thickness of 25 nm, and a length of 500 nm. The detection object is a small molecule gas with a concentration of 1-1000 ppm. The tube diameter is smaller than the mean free path of the gas to be detected.

[0047] The nanotube material is the software default anatase titanium dioxide.

[0048] The surface charge density of the inner wall of the nanotube is:

[0049] ρ s =-e_const*(scd-fmf.N_ads_G1 / (2e3))

[0050] Among them, ρ s is the surface charge density, e_const is the basic charge, scd is the number of active adsorption sites per unit area on the material surface, and fmf.N_ads_G1 is the number of adsorbed molecules per unit area; in this embodiment, scd = 3.01e16 m -2 .

[0051] The analytical doping model of the nanotube material is donor doping (n-type); in this embodiment, the donor concentration N D0 =3e18m -3 .

[0052] The metal contact type between the semiconductor and the electrode contact surface is an ideal ohmic contact, the terminal voltage V0 at the top of the material is 0V, and the terminal voltage V1 at the bottom is greater than 0V; in this embodiment, the terminal voltage V1 is 0.1V.

[0053] To verify the effectiveness of the nanotube structure of the present invention in distinguishing gases of different molecular weights (including gases with similar functional groups), this example uses hydrogen, methane, and ethane as examples. In the Free Molecular Flow physics interface, the molecular weights of the gases to be detected are set to 0.002 kg / mol, 0.016 kg / mol, and 0.030 kg / mol, respectively.

[0054] The inner wall type of the nanotube is adsorption / desorption, and the initial adsorption concentration nads,0,G1 = 0, additional molar flux Γ G1 =0, the adhesion coefficient is:

[0055] S G1 =sc*(1-fmf.n_ads_G1 / n)

[0056] Among them, S G1 is the adhesion coefficient, sc is the adhesion coefficient when there is no site occupation, fmf.n_ads_G1 is the number of moles of adsorbed molecules per unit area, and n is the number of moles of active adsorption sites per unit area on the material surface; in this embodiment, sc = 0.01, n = 1e-4 mol / m 2 ;

[0057] The desorption rate is:

[0058] D G1 =fmf.n_ads_G1 / τ

[0059] Among them, D G1 is the desorption rate, τ is the desorption time constant; in this embodiment, τ = 1s;

[0060] The initial value of the incident molecular flux is G G1 =0, the initial pressure value is p G1 =0, the initial value of number density is n G1 =0;

[0061] The pressure boundary condition of the storage tank is:

[0062] p 0,G1 =1e5*per

[0063] Among them, p 0,G1 is the storage tank pressure, and per is the concentration of the gas to be detected (in ppm).

[0064] The axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure is meshed. The meshing sequence type used is the physical field controlled mesh, the mesh shape is the triangular mesh, and the mesh size is the refined mesh.

[0065] Figure 3 Schematic diagram of a meshing method for an axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in an embodiment of the present invention.

[0066] Configure the simulation time unit, time step, and tolerance in the transient solver, select the physics interface to be calculated, and add an auxiliary scan of the gas concentration to be detected. In this embodiment, the time unit is ms, the time step is range(0,1,9)range(10,10,90)range(100,100,2000), and the tolerance is physics-controlled. Select the free molecular flow physics interface and the semiconductor physics interface as the physics interfaces to be calculated. The parameter value list for the gas concentration to be detected per is 10^{range(-6,0.2,-3)}. Simulate and calculate the number of molecules adsorbed per unit area on the inner wall of the nanotube and the sensor response value in the set time step.

[0067] Figure 4 and Figure 5 The following are the simulated cloud diagrams of the number of gas molecules adsorbed per unit area on the inner wall of the nanotube after 40ms, 60ms, 80ms, and 100ms of hydrogen, methane, and ethane gases with a concentration of 1ppm and 4ms, 6ms, 8ms, and 10ms of hydrogen, methane, and ethane gases with a concentration of 100ppm, respectively. It can be seen from the diagrams that there is a significant difference in the diffusion speed of the three gases with different molecular weights in the nanotubes. In the same time, the gas with a smaller molecular weight diffuses faster and has a larger adsorption amount on the inner wall of the nanotube. This distribution is reflected in the sensor response, as shown in Figure 1. Figure 6 As shown in the time domain response curve of the sensor, for the same concentration of the gas to be tested, the sensor's response to the gas with a small molecular weight is not only larger in amplitude but also faster in process, which intuitively demonstrates the superiority of the sensor structure provided by the present invention in distinguishing gases with different molecular weights.

Claims

1. A simulation method for distinguishing gases of different molecular weights, characterized by: The invention adopts a sensor structure for distinguishing gases of different molecular weights, wherein the sensor structure comprises a semiconductor nanotube array (1) and electrodes (2); the electrodes (2) are in contact with the top and bottom of the semiconductor nanotube array (1); the diameter of the nanotubes in the semiconductor nanotube array (1) is smaller than the mean free path of the gas to be detected; The simulation method comprises the following steps: (1) An axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in a semiconductor nanotube array (1) is established in the finite element simulation software COMSOL. A rectangle representing the outer contour of the nanotube is drawn with the axis as the axis of symmetry, and a tube structure representing the inner contour of the nanotube is drawn inside the rectangle with the axis as the axis of symmetry; the space enclosed by the tube structure and the axis is the gas diffusion space; the longitudinal wall of the tube is parallel to the outer contour of the nanotube, the distance between the longitudinal wall of the tube and the outer contour of the nanotube represents the wall thickness of the nanotube, and the diameter of the nanotube is smaller than the mean free path of the gas to be detected; (2) Add semiconductor physics interface and free molecular flow physics interface to the finite element simulation software COMSOL; (3) Material settings for the axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in the finite element simulation software COMSOL; (4) In the semiconductor physics field of the finite element simulation software COMSOL, the surface charge density of the inner wall of the semiconductor nanotube, the analytical doping model and doping concentration of the semiconductor nanotube material, the metal contact type and terminal voltage of the contact surface between the semiconductor and the electrode are set; the surface charge density of the inner wall of the semiconductor nanotube is: ρ s =-e_const*(scd-fmf.N_ads_G1 / (2e3)) Among them, ρ s is the surface charge density, e_const is the basic charge, scd is the number of active adsorption sites per unit area on the material surface, and fmf.N_ads_G1 is the number of adsorbed molecules per unit area; (5) In the free molecular flow physics field of the finite element simulation software COMSOL, the molecular weight of the gas to be detected, the surface temperature of the gas diffusion space, the type and boundary conditions of the inner wall of the nanotube, the initial values ​​of the incident gas molecular flux, pressure, number density, and the storage tank pressure boundary conditions are set; among them, the inner wall type of the nanotube is adsorption / desorption, and the initial adsorption concentration n is ads,0,G1 = 0, additional molar flux Γ G1 =0, the adhesion coefficient is: S G1 =sc*(1-fmf.n_ads_G1 / n) Among them, S G1 is the adhesion coefficient, sc is the adhesion coefficient when there is no site occupancy, fmf.n_ads_G1 is the number of moles of adsorbed molecules per unit area, and n is the number of moles of active adsorption sites per unit area on the material surface; The desorption rate is: D G1 =fmf.n_ads_G1 / τ Among them, D G1 is the desorption rate, τ is the desorption time constant; The initial value of the incident molecular flux is G G1 =0, the initial value of pressure is p G1 =0, the initial value of number density is n G1 =0; The pressure boundary condition of the storage tank is: p 0,G1 =1e5*per Among them, p 0,G1 is the storage tank pressure, per is the concentration of the gas to be detected; (6) Meshing the axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in the finite element simulation software COMSOL, determining the meshing sequence type, and setting the mesh unit shape and size; (7) In the finite element simulation software COMSOL, the simulation time unit, time step and tolerance in the transient solver are configured, the free molecular flow physics interface and the semiconductor physics interface are selected as the physics interfaces to be calculated, and an auxiliary scan of the concentration of the gas to be detected is added. The number of molecules adsorbed per unit area on the inner wall of the nanotube and the sensor response value in the set time step are simulated and calculated; by comparing the diffusion process of gases with different molecular weights in the nanotubes and the simulation results of the different responses of the sensor to gases with different molecular weights, gases with different molecular weights are distinguished.

2. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (3), the semiconductor nanotube material is set as the semiconductor material for the gas sensor.

3. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (3), the semiconductor nanotube material is set to anatase titanium dioxide.

4. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (4), the analytical doping model of the semiconductor nanotube material is n-type donor doping.

5. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (4), the metal contact type between the semiconductor and the electrode contact surface is an ideal ohmic contact, the terminal voltage V0 at the top of the material is 0V, and the terminal voltage V1 at the bottom is greater than 0V.

6. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (6), the meshing sequence type used for the axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure is the physical field controlled mesh.

7. The simulation method for distinguishing gases of different molecular weights according to claim 6, wherein: The shape of the grid is a triangular grid.

8. The simulation method for distinguishing gases of different molecular weights according to claim 6, wherein: The mesh size is refined.

9. The simulation method for distinguishing gases of different molecular weights according to claim 1, wherein: In step (7), the molecular weights of different gases to be detected are set to simulate the input of gases with different molecular weights, and steps (1) to (7) are repeated. By comparing the diffusion process of gases with different molecular weights in the nanotubes and the simulation results of the different responses of the sensor to gases with different molecular weights, gases with different molecular weights are distinguished.

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