Sensor structure for distinguishing gases with different molecular weights and simulation method

Abstract

The invention discloses a sensor structure for distinguishing gases with different molecular weights and a simulation method, the sensor structure comprises a semiconductor nanotube array and electrodes, the electrodes are in contact with the top and the bottom of the semiconductor nanotube array, and the diameter of the nanotube is smaller than the average free path of a gas to be detected; the simulation method comprises the following steps of: establishing an axisymmetric two-dimensional section geometric model of a single nanotube structure in the semiconductor nanotube array through finite element simulation software, adding a semiconductor and free molecular flow physical field interface, setting material attributes and boundary conditions, and establishing a two-dimensional section geometric model of the single nanotube structure in the semiconductor nanotube array; and dividing grids and analyzing diffusion of gases with different molecular weights and a sensor response process through a transient solver. Through different diffusion processes in the nanotubes with the tube diameter smaller than the average free path of the to-be-detected gas and different response results of the sensor, the sensor can distinguish gases with different molecular weights, and the problem that a semiconductor gas sensor in the prior art is poor in gas distinguishing capacity is solved.

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, medical health and other fields. In the application scenarios of detecting multi-component gases (such as toxic and harmful gases generated in industrial production, flammable and explosive gases in potentially dangerous environments, and symptomatic gases exhaled by patients in medical diagnosis), sensors need to have strong resolution and high detection efficiency for different types of gases (especially gases with similar functional groups). Therefore, the development of a gas sensor structure that can quickly and accurately distinguish gases of different molecular weights is of great significance for ensuring the safety of the production environment and assisting medical diagnosis.

[0003] Commonly used gas sensors are divided into electrochemical type, catalytic combustion type, optical type, semiconductor type, etc. Among them, semiconductor gas sensors have the advantages of high sensitivity, fast response, low cost, strong integration, etc., but their gas resolution ability is 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] Most existing studies focus on the adsorption / desorption of gases on the surface of semiconductor materials, while ignoring the diffusion process of gases before they come into contact with the surface. However, the strategy of changing the adsorption sites of gases on the surface of semiconductor materials is mainly effective for distinguishing gas molecules with different functional groups, and it is difficult to distinguish gases with similar functional groups from a basic principle.

[0006] Existing studies on gas dynamics have shown that the diffusion of gas in nanostructures is different from that in free space. When the mean free path of the gas is greater than the pore size of the nanostructure, the gas molecules will undergo Knudsen diffusion, and the gas diffusion coefficient is related to the gas molecular weight. However, this diffusion characteristic has not yet been combined with sensor response to distinguish 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] Purpose of the invention: In view of the deficiencies in the prior art, the purpose of the present invention is to propose a sensor structure and simulation method for distinguishing gases of different molecular weights, utilizing the different diffusion processes of different gases to be detected in nanotubes whose diameters are smaller than their mean free paths and the different response results of the sensors, thereby realizing the sensor's distinction between gases of different molecular weights and solving the problem in the prior art that semiconductor gas sensors have poor resolution for gases with similar functional groups.

[0009] Technical solution: The purpose of the present invention is achieved through the following technical solutions:

[0010] The sensor structure of the present invention for distinguishing gases of different molecular weights comprises a semiconductor nanotube array and electrodes, wherein the electrodes are in contact with the top and bottom of the semiconductor nanotube array; the diameter of nanotubes in the semiconductor nanotube array is smaller than the mean free path of the gas to be detected.

[0011] The simulation method for distinguishing gases of different molecular weights of the present invention is implemented by a sensor structure for distinguishing gases of different molecular weights. The simulation method comprises the following steps:

[0012] (1) An axisymmetric two-dimensional cross-sectional geometric model of a single nanotube structure in a 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 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. The tube diameter is smaller than the mean free path of the gas to be detected.

[0013] (2) Add semiconductor physics interface and free molecular flow physics interface to the finite element simulation software COMSOL;

[0014] (3) Material settings for the axisymmetric two-dimensional cross-sectional geometric model of a 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 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 of 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] Among them, 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 physical 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 of the inner wall of the nanotube and its boundary conditions, the initial value of the incident gas molecular flux, pressure, number density, and the storage tank pressure boundary condition are set; among which, the type of the inner wall of the nanotube is adsorption / desorption, and the initial adsorption concentration n 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 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 surface of the material;

[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 to 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; 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 a semiconductor material for a gas sensor.

[0029] Preferably, the semiconductor nanotube material in step (3) is 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 >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 in the following way: when the diameter of the nanotube is smaller than the mean free path of the gas to be detected, the diffusion coefficient and diffusion speed of the gas are inversely proportional to the 0.5 power of the gas molecular weight. The diffusion speed of the gas with a small molecular weight in the nanotube whose diameter is smaller than the mean free path of the gas to be detected is faster than that of the gas with a large molecular weight. Therefore, when performing gas detection, the sensor's response value to the gas with a small molecular weight is larger than that to the gas with a large molecular weight in the same time. For the gas with a small molecular weight, more gas molecules enter the nanotube at the same time, which is reflected in the sensor response, that is, the sensor's response process to the gas with a small molecular weight is faster and has a larger amplitude.

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

[0036] (1) The sensor structure and simulation method for distinguishing gases of different molecular weights of the present invention utilize the different diffusion processes of different gases to be detected in nanotubes whose diameters are smaller than their mean free paths and the different response results of the sensors to achieve the sensor's distinction of gases of different molecular weights. The structure is simple and flexible and the practicability is strong.

[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 This is a schematic diagram of the structure of a sensor for distinguishing gases of different molecular weights according to the present invention;

[0039] Figure 2 It 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 A 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;

[0041] Figure 4 The 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 1 ppm are respectively introduced for 40 ms, 60 ms, 80 ms and 100 ms in the embodiment of the present invention;

[0042] Figure 5 The 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 respectively introduced for 4ms, 6ms, 8ms and 10ms in the embodiment of the present invention;

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

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

[0045] Figure 2It is an axisymmetric two-dimensional cross-sectional geometric model diagram of a single nanotube structure in a semiconductor nanotube array provided by an embodiment of the present invention. This embodiment is modeled and simulated by using the COMSOL5.4 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, 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 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 of the tube 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 tube length of 500 nm. The detection object is a small molecule gas with a concentration of 1-1000 ppm, and 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] In order 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), in this embodiment, hydrogen, methane, and ethane are taken as examples, and 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, in the free molecular flow physical field interface.

[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 surface of the material; 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 refined.

[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 physical field 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 physical field control; select the free molecular flow physical field interface and the semiconductor physical field interface as the physical field interfaces to be calculated; the parameter value list of the gas concentration per to be detected is 10^{range(-6,0.2,-3)}; simulate and calculate the number of molecules adsorbed per unit area of ​​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 figure that there is a significant difference in the diffusion speed of the three gases with different molecular weights in the nanotube. In the same time, the gas with a small 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, such as Figure 6 As shown in the sensor time domain response curve, 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 sensor structure for distinguishing gases of different molecular weights, characterized in that: It comprises a semiconductor nanotube array (1) and an electrode (2); the electrode (2) is in contact with the top and bottom of the semiconductor nanotube array (1); and the diameter of the nanotubes in the semiconductor nanotube array (1) is smaller than the mean free path of the gas to be detected.

2. A simulation method for distinguishing gases of different molecular weights, characterized in that: The simulation method is implemented by using the sensor structure for distinguishing gases of different molecular weights as claimed in claim 1, and 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 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) 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 semiconductor-electrode contact surface are set in the semiconductor physical field of the finite element simulation software COMSOL; 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 physical 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 of the inner wall of the nanotube and its boundary conditions, the initial value of the incident gas molecular flux, pressure, number density, and the storage tank pressure boundary condition are set; among which, the type of the inner wall of the nanotube is adsorption / desorption, and the initial adsorption concentration n 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 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 surface of the material; 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 to 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; 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.

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

4. The simulation method for distinguishing gases of different molecular weights according to claim 2, characterized in that: In step (3), the semiconductor nanotube material is set to anatase titanium dioxide.

5. The simulation method for distinguishing gases of different molecular weights according to claim 2, characterized in that: In step (4), the analytical doping model of the semiconductor nanotube material is n-type donor doping.

6. The simulation method for distinguishing gases of different molecular weights according to claim 2, characterized in that: 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 >0V.

7. The simulation method for distinguishing gases of different molecular weights according to claim 2, characterized in that: 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.

8. The simulation method for distinguishing gases of different molecular weights according to claim 7, characterized in that: The shape of the grid is a triangular grid.

9. The simulation method for distinguishing gases of different molecular weights according to claim 7, characterized in that: The mesh size is refined.

10. The simulation method for distinguishing gases of different molecular weights according to claim 2, characterized in that: 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.

Images