A transistor-type spectral sensor for laser spectrometer

Abstract

The present invention discloses a transistor-type spectral sensor applied to a laser spectrometer, which belongs to the field of laser spectrum detection technology, and uses an "electric" grid instead of a grating as a whole to construct a spectral sensor with a p-i-n transistor heterojunction as the core. The spectral sensor developed by the present invention can use the electric grid voltage to perform spectroscopic collection of lasers of different bands, and use a deep learning method to achieve multi-component laser spectrum addressing and reconstruction; construct a high-performance spectrally adjustable p-i-n transistor heterojunction to improve the characteristics of laser dynamic response, thereby reducing the nonlinear distortion, attenuation and frequency shift of laser signals in high-frequency and high-speed environments; realize the sensor to split lasers of different bands, quickly reconstruct the laser spectrum, and collect data in time for analysis and processing.

Description

Technical Field

[0001] The invention belongs to the technical field of laser spectrum detection, and in particular relates to a transistor-type spectrum sensor applied to a laser spectrometer. Background Art

[0002] Based on the development and innovation of spectral sensors, spectral technology has also achieved long-term and rapid development. The characteristic absorption frequency of substances can be extracted through infrared spectroscopy technology. Currently, transistor light sensors have been applied in multi-component wide-spectrum non-dispersive infrared (NDIR) technology and spectroscopic Fourier transform infrared spectroscopy (FTIR) technology.

[0003] These methods can make full use of the high-precision spectral resolution capability of Fourier infrared spectrometers and the fast test speed of plasmon devices, taking into account real-time gas component identification and high-precision concentration resolution density (800zeptomole / um2). However, due to the weak interaction between the silicon carbon rods and high-pressure mercury lamps commonly used in Fourier spectrometers and gas molecules, large light scattering losses, difficulty in high-frequency signal detection, and short optical path, it will be difficult to further improve the test accuracy of the sensor system. Summary of the invention

[0004] In view of the deficiencies in the prior art, an object of the present invention is to provide a transistor-type spectrum sensor for use in a laser spectrometer.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A transistor-type spectral sensor comprises a gate, a source, a P-type semiconductor material layer, an N-type semiconductor material layer and a drain, wherein there is a voltage difference between the gate and the source, the source is connected to the P-type semiconductor material layer, the P-type semiconductor material layer is connected to the N-type semiconductor material layer, and the N-type semiconductor material layer is connected to the drain;

[0007] The P-type semiconductor material layer and the N-type semiconductor material layer form a pin transistor heterojunction, and the gate is an electric gate, and the gate voltage can be changed.

[0008] Furthermore, the P-type semiconductor material layer uses materials including nickel oxide, cuprous oxide, cobalt oxide, chromium trioxide, tin oxide and cuprous sulfide.

[0009] Furthermore, the N-type semiconductor material layer is made of materials including lead selenide, vanadium pentoxide, chromium trioxide, titanium oxide, tungsten trioxide and iron trioxide.

[0010] Furthermore, the gate voltage can obtain multiple optimal center detection wavelength states.

[0011] Furthermore, the P-type semiconductor material layer and the N-type semiconductor material layer have electronic conductivity.

[0012] Beneficial effects of the present invention:

[0013] 1. The sensor of the present invention realizes the tuning effect of the central wavelength of the spectral sensor. The high-performance spectrally adjustable pin transistor heterojunction is used to improve the characteristics of the laser response and reduce the nonlinear distortion, attenuation and frequency shift of the laser signal. P-type and N-type semiconductor materials with obvious absorption peaks, high carrier mobility, direct narrow band gap (0.28-0.41eV), good photoconductivity and electronic conductivity in the infrared band are selected to form the heterojunction.

[0014] 2. The sensor of the present invention realizes automatic spectral addressing and reconstruction. Through the convolution effect within the spectral response, a gate voltage and spectral response relationship model is established. The deep learning method is used to select characteristic bands to establish a sample correction model, and other samples are used to verify the generalization ability of the model, thereby performing laser spectral addressing and reconstruction to achieve high-precision, multi-band laser measurement.

[0015] 3. The sensor of the present invention realizes precise control of gate voltage. By taking advantage of the polarization-sensitive characteristics of heterojunctions under different gate voltages, linear polarized light detection measurements are performed on photodetectors to measure the relationship between the polarization angle and photocurrent of devices under different wavelength lasers and different gate voltages. By comparing the anisotropic current ratio of the fitting curves of lasers of different wavelengths, the gate voltage with the strongest corresponding laser photoelectric response is found, ensuring the accuracy of the output signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 This is a schematic diagram of the structure of the transistor-type spectral sensor in the present invention.

[0018] Figure 2 It is a schematic diagram of the design and manufacture of the pin transistor heterojunction spectrum detector in the present invention;

[0019] Figure 3 It is a schematic diagram of the energy band arrangement structure of the pin heterostructure in the present invention;

[0020] Figure 4 It is a step-by-step manufacturing process diagram and structure diagram of the "electric grid" type spectral transistor type sensor of the present invention;

[0021] Figure 5 is a graph showing the relationship between photocurrent and polarization angle in the present invention;

[0022] Figure 6 It is a graph of the output characteristic curve and the transfer characteristic curve of the heterojunction phototransistor in the present invention;

[0023] Figure 7 It is a photoelectric response characteristic diagram in the present invention.

[0024] Figure 8 It is a conceptual diagram of deep learning of neural network in the present invention;

[0025] Fig. 9 This is the gas second harmonic detection diagram of the present invention

[0026] Explanation of the reference numerals: 1. gate electrode; 2. source electrode; 3. P-type semiconductor material layer; 4. N-type semiconductor material layer; 5. drain electrode. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] See also Figures 1 to 9 As shown, the present invention proposes a transistor-type spectral sensor applied to a laser spectrometer, including a heterojunction formed by P-type and N-type semiconductor materials, combined with an inner convolution effect, and using neural network deep learning to perform spectral addressing and recombination models.

[0029] The present invention is based on the pin laser response heterostructure, uses an "electric" gate instead of a grating, uses electrofluid inkjet printing technology to prepare a transistor array, and cooperates with laser packaging and slicing to develop a single-transistor laser spectrum sensor. Each incident laser can not only distinguish the spectrum at its exclusive gate voltage value, but also has good anti-interference performance. Through the convolution effect within the spectral response, a gate voltage spectrum effect relationship model is established, and the laser spectrum addressing and reconstruction are performed using the deep learning method.

[0030] The present invention can perform second harmonic acquisition and tuning on multi-band laser spectrum signals, and its working process is as follows: first, spectrum addressing and band locking are performed, and then the mixed laser signal is detected in the infrared band, and finally, the low frequency is filtered out by using the optoelectronic interconnected inter-frequency circuit, the second harmonic is tuned out, and the next band is continuously scanned, and finally the second harmonic detection of multi-band laser is realized.

[0031] like Figure 1As shown, the structure of the present invention comprises, from bottom to top, a gate 1, a source 2, a P-type semiconductor material layer 3, an N-type semiconductor material layer 4 and a drain 5. There is a voltage difference between the gate 1 and the source 2. The source 2 is connected to the P-type semiconductor material layer 3, the P-type semiconductor material layer 3 is connected to the N-type semiconductor material layer 4, and the N-type semiconductor material layer 4 is connected to the drain 5.

[0032] The P-type semiconductor material layer 3 and the N-type semiconductor material layer 4 form a pin transistor heterojunction. The gate 1 is given different voltages, and the heterojunction exhibits polarization sensitivity. The energy band arrangement and the detection band change. When a laser of a certain characteristic wavelength is incident on the heterojunction, the gate voltage obtains the optimal central detection wavelength state. On this basis, the dynamic response characteristics of the laser response are obtained, and a device gate voltage-spectral response relationship model is established in combination with the convolution effect within the spectral response. A convolution kernel is formed inside the heterojunction. The device gate voltage-spectral response relationship model is combined with a convolutional neural network algorithm (CNN) model, and a characteristic band is selected to establish a sample correction model. The convolution kernel is verified by an algorithm test, and the tuning of the central wavelength of the spectral sensor and the reconstruction and addressing of the laser spectrum are completed.

[0033] Furthermore, the materials used for the P-type semiconductor material layer 3 include but are not limited to nickel oxide NiO, cuprous oxide Cu2O, cobalt oxide CoO, chromium trioxide Cr2O3, tin oxide SnO, cuprous sulfide Cu2S

[0034] Furthermore, the materials used for the N-type semiconductor material layer 4 include but are not limited to lead selenide PbSe, vanadium pentoxide V2O5, chromium trioxide CrO3, titanium oxide TiO2, tungsten trioxide WO3, and iron trioxide Fe2O3.

[0035] Furthermore, the gate 1 uses an "electric" gate instead of a photogate, and the gate voltage can be changed

[0036] Furthermore, the gate voltage can obtain multiple optimal center detection wavelength states

[0037] Furthermore, by using exclusive gate voltage values ​​for different incident lasers, laser splitting in different bands, interference reduction and rapid reconstruction of the laser spectrum can be achieved.

[0038] Furthermore, the device gate voltage-spectral response relationship model includes wavelength (λ), gate voltage (V G ), photocurrent (I(λ, VG)) data set matrix

[0039] Furthermore, the sample correction model includes an input layer, a convolutional layer, a pooling layer, a fully connected layer and an output layer.

[0040] like Figure 2As shown, the present invention starts from enhancing the light response and gate control efficiency, explores the influence of the heterojunction characteristics and structure of the phototransistor channel on spectral detection, studies the negative differential effect in the nano heterojunction channel, surface plasmons, and FP tuning oscillation and other light-electric coupling mechanisms, and constructs a high-performance spectrally tunable pin transistor heterojunction to improve the characteristics of laser response, thereby reducing the nonlinear distortion, attenuation and frequency shift of the laser signal. By using the heterojunction band gap control in the transistor channel, it is proposed to use an "electric" gate instead of a grating to achieve the tuning effect of the central wavelength of the spectral sensor, perform spectral splitting, and achieve spectral reconstruction through deep learning methods.

[0041] like Figure 3 As shown, the present invention selects P-type 3 and N-type semiconductor material layers 4 with obvious absorption peaks, high carrier mobility, direct narrow band gap (0.28-0.41eV), good photoconductivity and electronic conductivity in the infrared band to form a heterojunction. The spectral response of the heterojunction device is flexible and controllable. When the detector is regulated by different gate voltages, the energy band arrangement of the heterojunction interface will change accordingly, and the detection band will also change accordingly.

[0042] like Figure 4 As shown, the step-by-step manufacturing process of the present invention is as follows: the source electrode 2 is prepared by electrofluidic inkjet printing on the back-doped silicon oxide wafer, and the P-type semiconductor layer 3 is prepared by an eccentric spin coating process. The nanowires are arranged in an orderly manner, so that the device has better polarization characteristics. The amorphous N-type semiconductor material layer 4 is deposited to a thickness of 50nm using a mask through an alternating current (AC) magnetron sputtering system as the photosensitive layer of the device. Finally, the drain electrode 5 is prepared by electrofluidic inkjet printing, and the gate 1, source 2 and drain 5 of the device should be obtained by annealing at 150°C for 30 minutes. The prepared photodetection transistor has high detection speed, wide modulation bandwidth, and high device response, and achieves photoelectric performance of >1×1014Jones and above 106A / W in the laser infrared band.

[0043] like Figure 5 As shown, the heterojunction exhibits polarization sensitivity under different gate voltages, and linear polarized light detection measurements are performed on the photodetector to measure the relationship between the polarization angle and photocurrent of the device under different wavelength lasers and different gate voltages. The incident light is 940nm, and the polar coordinate diagram of the photocurrent as a function of the polarization angle under the conditions of gate voltages of 3v, 5v and 10v is selected. The anisotropic photocurrent ratios are 1.04, 1.05 and 1.54, respectively. It can be seen that when the gate voltage is 10v, it has better polarization sensitivity characteristics, and the anisotropic current ratio of the fitting curve is larger, proving that when Vg=10v, the photoelectric response to the 940nm laser is stronger and has good anti-interference. The work relies on the experimental 850-1700nm supercontinuum laser, and cooperates with a monochromator to collect the spectral response signals of the device under different gate voltage conditions. As Figure 8The wavelength (λ), gate voltage (V G ), photocurrent (I(λ, VG)). The deep learning process of the spectral sensor will be determined by the spectral signal responsivity R, the photocurrent response I of different gate voltages, and the incident light power P. Using the aforementioned test data set and the intrinsic relationship function of the photocurrent spectral response, the matrix equation is constructed:

[0044]

[0045] like Figure 6 and Figure 7 As shown in Figure 1, the photocurrent response speed under the gate voltage (Vg) changes from ~0V to 20V, with a step size of ~0.5V (Vds = 0V, 1Hz LD switching). The isochromatic line diagram of the photocurrent (Iph) response matrix is ​​shown in Figure 1. Figure 7 As shown in (b), the Iph value is obvious under positive gate voltage. Figure 7 (a) shows a typical dynamic photoswitching behavior extracted at 940nm with a gate bias section. When Vg increases to 20V, the photocurrent (Iph) rises from 5.4nA to 55.3nA. The rise time and fall time can reach ~80ms (detailed pulses in the inset), showing a sudden photoresponse behavior and excellent reproducibility. It is worth mentioning that no dynamic photocurrent can be observed under incident illumination at 640nm, and excellent photocurrent is obtained under the same light intensity and gate bias and 940nm illumination. We attribute this effect to the relaxation effect. Figure 7 (c) The responsivity curve shows that the photoresponse is more sensitive to 940nm infrared incident and can be close to 160A / W, which can be calculated by R=Iph / Pin.

[0046] like Figure 8 As shown, when a laser of a certain characteristic wavelength is incident on the heterojunction spectral detector, the gate voltage obtains the state of the optimal central detection wavelength, and the laser is collected at different gate voltage values, which is divided into light of different bands. On this basis, the dynamic response characteristics of the laser response are obtained, and a device gate voltage-spectral response relationship model is established. Combined with the convolutional neural network algorithm (CNN) model, the characteristic band is selected to establish a sample correction model, and other samples are used to verify the generalization ability of the model. It mainly includes input layer, convolution layer, pooling layer, fully connected layer and output layer. The gate voltage-dependent laser spectral response matrix can be further applied to laser spectral addressing, and the spectral signal can be reconstructed within the range of 3-5nm near the central wavelength. At the same time, the low error of the addressing peak position of the laser spectral sensor (~0.5nm) and the wide working bandwidth in the near infrared (~850nm-1700nm) are taken into account.

[0047] The work uses a transistor-type spectral detector and a supercontinuum laser to test and draw a spectral mapping diagram of the photocurrent, and continues to use the convolution kernel to build a CNN neural network for the data set of gate voltage and incident laser signals in different bands. Based on the existing detector system, the present invention will use a gate voltage adjustable spectral sensor to further improve the detection accuracy, and realize an ultra-high-precision laser spectral detection system by demodulating multi-band second harmonics, and cooperate with various intelligent recognition algorithms to expand the system's related applications.

[0048] Fig. 9 For gas second harmonic detection, Figure 7 (a) is the data diagram of the second harmonic of the mixed gas displayed on the host computer. At this time, the NO concentration is 20 μL·L -1 , H2S is 40μL·L -1 , NH3 is 12μL·L -1 , NO2 is 30μL·L -1 , C2H2 is 10μL·L -1 , CO2 is 7μL·L -1 , CH4 is 25μL·L -1 , HCL is 10μL·L -1 When eight lasers are working at the same time, the system controls the bandpass filter to perform time-sharing filtering and extraction, and transmits the second harmonic data to the host computer for real-time display in sequence according to the filtering order, thus realizing real-time display of eight-channel spectra of different gases. Figure 7 (b) is the second harmonic of the gradient concentration of nitrogen dioxide from 30 to 100 μL·L-1. Figure 7 (c) Hydrogen sulfide 30-100 μL·L -1 The second harmonic of the gradient concentration, Figure 7 (d) Methane 20-100 μL·L -1 By comparing the second harmonic of the gradient concentration, it can be found that the greater the gas concentration, the greater the peak-to-peak value of the second harmonic.

[0049] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0050] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0051] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0052] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0053] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0054] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0055] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A transistor-type spectrum sensor used in a laser spectrometer, comprising: The device comprises a gate electrode (1), a source electrode (2), a P-type semiconductor material layer (3), an N-type semiconductor material layer (4) and a drain electrode (5); a voltage difference exists between the gate electrode (1) and the source electrode (2); the source electrode (2) is connected to the P-type semiconductor material layer (3); the P-type semiconductor material layer (3) is connected to the N-type semiconductor material layer (4); and the N-type semiconductor material layer (4) is connected to the drain electrode (5); The P-type semiconductor material layer (3) and the N-type semiconductor material layer (4) form a pin transistor heterojunction, the pin transistor heterojunction exhibits polarization sensitivity under different gate voltages, the amorphous N-type semiconductor material layer (4) serves as a photosensitive layer of the device, the gate (1) is an electric gate, and the gate voltage can be changed; The P-type semiconductor material layer (3) is made of nickel oxide, cuprous oxide, cobalt oxide, chromium oxide, tin oxide or cuprous sulfide; The N-type semiconductor material layer (4) is made of materials including lead selenide, vanadium pentoxide, chromium trioxide, titanium oxide, tungsten trioxide or iron trioxide.

2. A transistor-type spectrum sensor for use in a laser spectrometer according to claim 1, characterized in that: The gate voltage can obtain multiple optimal center detection wavelength states.

3. The transistor-type spectrum sensor used in a laser spectrometer according to claim 1, characterized in that: The P-type semiconductor material layer (3) and the N-type semiconductor material layer (4) have electronic conductivity.

4. A laser spectrometer, characterized in that: The laser spectrometer comprises the transistor-type spectral sensor according to any one of claims 1-3.

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