Mid-infrared spectrum analysis system and method base on metasurface computational reconstruction

Abstract

Embodiments of the present application relate to the technical field of spectrum analysis, and provide a mid-infrared spectrum analysis system and method based on a metasurface computational reconstruction. The mid-infrared spectrum analysis system comprises a metasurface core layer, a substrate, and a photoelectric detector array. The metasurface core layer and the substrate are stacked, and the metasurface core layer is provided with a metasurface structure array. The metasurface structure array comprises a plurality of metasurface structures, and spectrum responses of the plurality of metasurface structures are different. A spectrum response set of all of the metasurface structures in the metasurface structure array is a transmission matrix. The metasurface core layer is arranged above the photoelectric detector array, the photoelectric detector array comprises a plurality of photoelectric detectors, and the plurality of photoelectric detectors have one-to-one correspondence to the plurality of metasurface structures. The photoelectric detectors are configured to receive an optical signal generated by mid-infrared incident light to be measured after passing through the corresponding metasurface structures, and perform computational reconstruction on the basis of the transmission matrix of the metasurface structure array and the optical signal, to obtain spectrum information of the mid-infrared incident light to be measured.

Description

A mid-infrared spectral analysis system and method based on metasurface computational reconstruction Technical Field

[0001] The present application relates to the field of spectral analysis technology, and in particular to a mid-infrared spectral analysis system and method based on metasurface computational reconstruction. Background Art

[0002] Spectra are important parameters for studying the interaction between energy and matter, such as in biochemical research and gas composition analysis. The mid-infrared band, which spans 2 to 20 μm, is an electromagnetic waveband. Because this band contains an atmospheric transparency window and contains peaks for thermal radiation, molecular characteristics, and functional group absorption, it is widely used in infrared thermal imaging observations, material composition analysis, and free-space communications.

[0003] Currently, most research on miniaturized spectrometers focuses on the visible and near-infrared spectral ranges, while mid-infrared spectrometers are often implemented as benchtop spectrometers using discrete components. Traditional benchtop spectrometers typically rely on bulky dispersive optics, long optical pathlengths, detector arrays, and piezoelectric moving parts. However, the development of miniaturized spectrometers is becoming increasingly popular in a variety of handheld, portable, and integrated applications, including crop analysis, food production line monitoring, and marine science research.

[0004] While existing laboratory benchtop spectrometer systems offer the highest resolution and spectral range, miniaturized optical spectrometers offer distinct advantages over these systems, such as on-site and instantaneous measurements, where portability, low power consumption, and reduced size are more critical than resolution. Therefore, achieving compact, real-time mid-infrared spectral analysis has become a hot topic.

[0005] Summary of the Invention

[0006] The purpose of the embodiments of the present application is to provide a mid-infrared spectral analysis system and method based on metasurface computational reconstruction, which can reduce the size of the mid-infrared spectral analysis and reduce power consumption, realize real-time mid-infrared spectral analysis, and improve the technical effect of convenience.

[0007] In a first aspect, an embodiment of the present application provides a mid-infrared spectroscopy analysis system based on metasurface computational reconstruction, comprising a metasurface core layer, a substrate, and a photodetector array;

[0008] The metasurface core layer and the substrate are stacked, and the metasurface core layer is provided with a metasurface structure array, the metasurface structure array includes a plurality of metasurface structures, and the spectral responses of the plurality of metasurface structures are different, and the spectral response set of all metasurface structures in the metasurface structure array is a transmission matrix;

[0009] The metasurface core layer is arranged above the photodetector array, and the photodetector array includes multiple photodetectors, and the multiple photodetectors correspond one-to-one to the multiple metasurface structures; the photodetectors are used to receive the optical signal generated after the mid-infrared incident light to be measured passes through the corresponding metasurface structure, and perform calculation and reconstruction based on the transmission matrix of the metasurface structure array and the optical signal to obtain the spectral information of the mid-infrared incident light to be measured.

[0010] In the above-mentioned implementation process, the mid-infrared spectral analysis system based on metasurface computational reconstruction introduces a metasurface structure array, which includes a plurality of metasurface structures with different spectral responses. Thus, the corresponding metasurface structure is designed by utilizing the characteristics of the metasurface that can introduce spatially varying electromagnetic or optical responses and mold the wavefront into an arbitrary shape, so as to achieve different spectral responses to the mid-infrared incident light, so that the photodetector array can obtain different photocurrents within the mid-infrared band. Due to the miniaturization of the metasurface and the real-time response of the detector, the spectral data of the mid-infrared incident light is obtained through transmission matrix processing, thereby realizing small, ultra-fine and real-time mid-infrared spectral analysis. Thus, the mid-infrared spectral analysis system based on metasurface computational reconstruction can reduce the size of the mid-infrared spectral analysis and reduce power consumption, realize real-time mid-infrared spectral analysis, and improve the technical effect of convenience.

[0011] Furthermore, the metasurface structure is a metasurface structure of a preset matrix grid model, and the preset matrix grid model includes a plurality of grids, each grid representing an etching state and a retention state of the metasurface structure.

[0012] Furthermore, the shape of the metasurface structure is one or more of a circular hole, a cylinder, a square, and a polygon.

[0013] Furthermore, the material of the metasurface structure is a chalcogenide material.

[0014] Furthermore, the substrate is a mid-infrared transparent medium substrate, and the material of the substrate is one or more of calcium fluoride, barium fluoride, magnesium fluoride, silicon, sapphire, and zinc oxide.

[0015] In a second aspect, an embodiment of the present application provides a mid-infrared spectral analysis method based on metasurface computational reconstruction, which is applied to the mid-infrared spectral analysis system based on metasurface computational reconstruction described in any one of the first aspects, and the mid-infrared spectral analysis method includes:

[0016] Traverse each metasurface structure in the metasurface core layer and process the traversed metasurface structures:

[0017] irradiating the metasurface structure with a calibration incident light, and obtaining transmission spectrum information of the calibration incident light after passing through the metasurface structure;

[0018] After the traversal is completed, multiple transmission spectrum information corresponding to multiple metasurface structures is obtained;

[0019] generating a transmission matrix according to the plurality of transmission spectrum information;

[0020] Integrating a metasurface structure array above a photodetector array, wherein the plurality of metasurface structures in the metasurface structure array corresponds one-to-one to the plurality of photodetectors in the photodetector array;

[0021] Irradiating the mid-infrared incident light to be measured onto the metasurface core layer, each photodetector generates a photocurrent signal based on the metasurface structure, and obtaining multiple photocurrent signals;

[0022] Calculation and reconstruction are performed based on the transmission matrix and the multiple photocurrent signals to obtain spectral information of the mid-infrared incident light to be measured.

[0023] Furthermore, the transmission matrix is ​​an m-row × n-column transmission matrix, where m represents the number of metasurface structures in the metasurface core layer, and n represents the number of sampling points for the mid-infrared incident light to be measured. The calculation formula of the photocurrent signal is:

[0024] Among them, I i is the photocurrent generated by the i-th metasurface structure, F(λ) is the spectral information of the mid-infrared incident light to be measured, λ is the wavelength of light, λ1 is the wavelength of the first sampling point of the mid-infrared incident light to be measured, λn is the wavelength of the n-th sampling point of the mid-infrared incident light to be measured, and Ri(λ) is the spectral response function corresponding to the i-th metasurface structure.

[0025] Furthermore, the step of performing calculation and reconstruction based on the transfer matrix and the multiple photocurrent signals to obtain spectral information of the incident mid-infrared light to be measured includes:

[0026] The spectrum information F(λ) of the incident mid-infrared light to be measured is sparsely represented as F(λ)=β(λ)k using basis functions, and the calculation formula of the photocurrent signal is discretized to obtain the discrete processing formula:

[0027] Wherein, βj(λj) is the expanded basis function corresponding to the j-th sampling point of the mid-infrared incident light to be measured, kj is the correlation coefficient vector corresponding to the j-th sampling point of the mid-infrared incident light to be measured, and Riij(λj) is the spectral response function corresponding to the i-th metasurface structure and the j-th sampling point of the mid-infrared incident light to be measured;

[0028] Regularization processing is performed according to the discrete processing formula to obtain the regularization processing formula:

[0029] Solving the regularization processing formula based on a preset regularization algorithm and the transfer matrix to obtain regularization parameters and correlation vector coefficients;

[0030] The spectrum information of the incident mid-infrared light to be measured is obtained according to the regularization parameter, the correlation vector coefficient and the basis function.

[0031] Furthermore, the regularization processing formula is:

[0032] Where α is the regularization parameter, R is the transfer matrix, k is the correlation coefficient vector, β is the basis function, and I is the photocurrent.

[0033] Furthermore, the step of irradiating the calibration incident light onto the metasurface structure and obtaining transmission spectrum information of the calibration incident light after passing through the metasurface structure includes:

[0034] The calibration incident light is focused and irradiated onto the metasurface structure through one or more optical lenses such as a reflector, a plano-convex lens, and an objective lens to obtain transmission spectrum information of the calibration incident light after passing through the metasurface structure.

[0035] Other features and advantages disclosed in the present application will be described in the following description, or some features and advantages can be inferred or determined without doubt from the description, or can be learned by implementing the above-mentioned technology disclosed in the present application.

[0036] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0038] FIG1 is a schematic structural diagram of a mid-infrared spectroscopy analysis system based on metasurface computational reconstruction provided in an embodiment of the present application;

[0039] FIG2 is a schematic diagram of the shape of a first metasurface structure provided in an embodiment of the present application;

[0040] FIG3 is a schematic diagram of the shape of a second metasurface structure provided in an embodiment of the present application;

[0041] FIG4 is a schematic diagram of the shape of a third metasurface structure provided in an embodiment of the present application;

[0042] FIG5 is a schematic diagram of the shape of a fourth metasurface structure provided in an embodiment of the present application;

[0043] FIG6 is a schematic diagram of the shape of a fifth metasurface structure provided in an embodiment of the present application;

[0044] FIG7 is a schematic diagram of a process of a mid-infrared spectroscopy analysis method based on metasurface computational reconstruction according to an embodiment of the present application;

[0045] FIG8 is a schematic flow chart of another mid-infrared spectroscopy analysis method based on metasurface computational reconstruction provided in an embodiment of the present application;

[0046] FIG9 is a schematic diagram of the spectrum reconstruction effect provided by an embodiment of the present application.

[0047] Icons: metasurface structure 101; metasurface core layer 102; substrate 103; photodetector array 104. DETAILED DESCRIPTION

[0048] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0049] In this application, terms such as "upper," "lower," "left," "right," "front," "back," "top," "bottom," "inner," "outer," "center," "vertical," "horizontal," "transverse," and "longitudinal" indicate positions or locations based on the positions or locations shown in the accompanying drawings. These terms are primarily intended to better describe this application and its embodiments and are not intended to limit the devices, elements, or components indicated to having a specific orientation, or to being constructed or operated in a specific orientation.

[0050] Furthermore, some of the above terms may be used to express other meanings besides indicating a position or location. For example, the term "on" may also be used to indicate a dependency or connection in certain circumstances. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances.

[0051] Furthermore, the terms "installed," "disposed," "provided with," "connected," and "connected" should be interpreted broadly. For example, they can refer to fixed connections, removable connections, or integral structures; mechanical connections or point connections; direct connections, indirect connections through an intermediary, or internal communication between two devices, elements, or components. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances.

[0052] Furthermore, the terms "first," "second," and the like are primarily used to distinguish between different devices, elements, or components (which may or may not be of the same type and configuration) and are not intended to indicate or imply the relative importance or quantity of the devices, elements, or components indicated. Unless otherwise specified, "plurality" means two or more.

[0053] The embodiment of the present application provides a mid-infrared spectral analysis system and method based on metasurface computational reconstruction, which can be applied to real-time mid-infrared spectral analysis; the mid-infrared spectral analysis system based on metasurface computational reconstruction introduces a metasurface structure array, which includes a plurality of metasurface structures with different spectral responses; thereby, the corresponding metasurface structure is designed by utilizing the characteristics of the metasurface that can introduce spatially varying electromagnetic or optical responses and mold the wavefront into an arbitrary shape, so as to achieve different spectral responses to mid-infrared incident light, so that the photodetector array can obtain different photocurrents within the mid-infrared band; due to the miniaturization of the metasurface and the real-time response of the detector, the spectral data of the mid-infrared incident light is obtained through transmission matrix processing, thereby realizing small, ultra-fine and real-time mid-infrared spectral analysis; thereby, the mid-infrared spectral analysis system based on metasurface computational reconstruction can reduce the size of the mid-infrared spectral analysis and reduce power consumption, realize real-time mid-infrared spectral analysis, and improve the technical effect of convenience.

[0054] Please refer to Figure 1, which is a schematic structural diagram of a mid-infrared spectroscopy analysis system based on metasurface computational reconstruction provided in an embodiment of the present application. The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction includes a metasurface core layer 102, a substrate 103, and a photodetector array 104;

[0055] Exemplarily, the metasurface core layer 102 and the substrate 103 are stacked, and the metasurface core layer 102 is provided with a metasurface structure array, the metasurface structure array includes a plurality of metasurface structures 101, and the spectral responses of the plurality of metasurface structures 101 are different, and the spectral response set of all the metasurface structures 101 in the metasurface structure array is a transmission matrix;

[0056] Exemplarily, the metasurface core layer 102 is arranged above the photodetector array 104, and the photodetector array 104 includes multiple photodetectors, and the multiple photodetectors correspond one-to-one to the multiple metasurface structures 101; the photodetectors are used to receive the optical signal generated after the mid-infrared incident light to be measured passes through the corresponding metasurface structure, and perform calculation and reconstruction based on the transmission matrix and optical signal of the metasurface structure array 104 to obtain the spectral information of the mid-infrared incident light to be measured.

[0057] Exemplarily, the material of the metasurface structure 101 is a chalcogenide material.

[0058] In some embodiments, the metasurfaces are all chalcogenide materials, including but not limited to GeSbS materials, As2Se3, As2S3 and other chalcogenide compounds; in the present application, chalcogenide materials have many advantages in the mid-infrared band. First, chalcogenide materials have a spectrum that absorbs a large wavelength range including the mid-infrared band. This enables chalcogenide materials to be used to manufacture optical devices covering the entire mid-infrared band. Secondly, chalcogenide materials have high nonlinear optical effects and can produce a large optical response in the mid-infrared band. Finally, chalcogenide materials have high chemical and thermal stability and can operate stably at high temperatures and in harsh environments. Therefore, the spectral response of the metasurface structure on this material covers the 2um-20um band.

[0059] Exemplarily, the substrate 103 is a mid-infrared transparent medium substrate, and the material of the substrate 103 is one or more of calcium fluoride, barium fluoride, magnesium fluoride, silicon, sapphire, and zinc oxide; in other words, the substrate can be a mid-infrared transparent medium such as calcium fluoride, barium fluoride, magnesium fluoride, silicon, sapphire, and zinc oxide.

[0060] For example, the metasurface structures on the metasurface core layer 102 include, but are not limited to, circular holes, cylinders, squares, and polygons. Alternatively, an inverse design algorithm can be used to first determine the design goal (e.g., low cross-correlation coefficients for the spectral response matrices of the various metasurface structures), and then iteratively optimize the structural parameters in the computational software until the optimal metasurface structure and parameters are found. The photodetector array is configured to receive photocurrent generated by mid-infrared light.

[0061] Please refer to Figures 2 to 6. Figure 2 is a schematic diagram of the shape of the first supersurface structure provided in an embodiment of the present application, Figure 3 is a schematic diagram of the shape of the second supersurface structure provided in an embodiment of the present application, Figure 4 is a schematic diagram of the shape of the third supersurface structure provided in an embodiment of the present application, Figure 5 is a schematic diagram of the shape of the fourth supersurface structure provided in an embodiment of the present application, and Figure 6 is a schematic diagram of the shape of the fifth supersurface structure provided in an embodiment of the present application.

[0062] Exemplarily, the shape of the metasurface structure is one or more of a circular hole, a cylinder, a square, and a polygon.

[0063] Exemplarily, as shown in FIG6 , the metasurface structure is a metasurface structure of a preset matrix grid model, which includes a plurality of grids, each grid representing an etching state and a retention state of the metasurface structure; optionally, black represents etching and white represents retention.

[0064] In some embodiments, the structural design of the metasurface in the present invention is other than simple regular patterns (as shown in FIG. 2 to FIG. 5 );

[0065] Optionally, an inverse design algorithm is used to minimize the cross-correlation coefficients of the spectral response functions of the metasurface structures. The specific design steps are as follows:

[0066] 1. Determine the design goals and clarify the operating wavelength and optical performance;

[0067] 2. Then the core layer is meshed to generate a 100×100 mesh model. The mesh is represented by 1 and 0, which correspond to etching and retention respectively.

[0068] 3. A 100×100 grid is randomly arranged with 1s and 0s to simulate the physical parameters of the device. Based on the design goals and simulation results of the device, appropriate optimization algorithms are selected, such as topology optimization, shape optimization, and intelligent algorithms. These algorithms will automatically adjust the structure and parameters of the device to achieve the best optical performance. The simulation results are compared to meet the requirements of the computational reconstruction algorithm and the mid-infrared band. One of the reverse-designed metasurface structures is shown in Figure 6.

[0069] In some embodiments, in combination with the metasurface structure of the preset matrix grid model shown in FIG6 , the preparation method thereof is exemplified as follows:

[0070] After determining the optimal metasurface parameters, a core layer is first grown on a substrate, followed by a spun-on coating. Electron beam lithography is then used to create a computer-generated structural pattern on the chip. A scanning electron microscope is then controlled to provide an electron beam to expose the sample surface, breaking the molecular bonds in the photoresist in the exposed areas and creating new materials. Inductively coupled plasma etching is then used. A high-frequency electric field in the etcher ionizes the reactive gas, generating a plasma. This plasma reacts with the sample, corroding the surface and removing the photoresist and thin films in non-photoresist areas. Using interface mechanics or chemical reactions, the metasurface unit cell is transferred through three main steps: peeling, alignment, and bonding. The unit cell of this metasurface structure is approximately 1mm×1mm, meeting the requirements for miniaturization.

[0071] Please refer to Figure 7, which is a flow chart of a mid-infrared spectral analysis method based on metasurface computational reconstruction provided in an embodiment of the present application. The mid-infrared spectral analysis method based on metasurface computational reconstruction is applied to the mid-infrared spectral analysis system based on metasurface computational reconstruction shown in Figures 1 to 6. The method includes the following steps:

[0072] S100: traverse each metasurface structure in the metasurface core layer and process the traversed metasurface structures: irradiate the metasurface structure with a calibration incident light, and obtain transmission spectrum information after the calibration incident light passes through the metasurface structure;

[0073] S200: After the traversal is completed, multiple transmission spectrum information corresponding to multiple metasurface structures is obtained;

[0074] S300: Generate a transmission matrix based on multiple transmission spectrum information;

[0075] S400: integrating a metasurface structure array above a photodetector array, wherein a plurality of metasurface structures in the metasurface structure array correspond one-to-one to a plurality of photodetectors in the photodetector array;

[0076] S500: irradiating the mid-infrared incident light to be measured onto the metasurface core layer. Each photodetector generates a photocurrent signal based on the metasurface structure, thereby obtaining multiple photocurrent signals.

[0077] S600: Perform calculation and reconstruction based on the transmission matrix and the multiple photocurrent signals to obtain spectral information of the mid-infrared incident light to be measured.

[0078] Please refer to Figure 8, which is a flow chart of another mid-infrared spectroscopy analysis method based on metasurface computational reconstruction provided in an embodiment of the present application.

[0079] For example, the transmission matrix is ​​an m-row × n-column transmission matrix, where m represents the number of metasurface structures in the metasurface core layer, and n represents the number of sampling points for the mid-infrared incident light to be measured. The calculation formula for the photocurrent signal is:

[0080] Among them, Ii is the photocurrent generated by the corresponding i-th metasurface structure, F(λ) is the spectral information of the mid-infrared incident light to be measured, λ represents the wavelength of light, λ1 represents the wavelength of the first sampling point of the mid-infrared incident light to be measured, λn represents the wavelength of the n-th sampling point of the mid-infrared incident light to be measured, and Ri(λ) is the spectral response function corresponding to the i-th metasurface structure.

[0081] Exemplarily, S600: performing computational reconstruction based on the transmission matrix and the plurality of photocurrent signals to obtain spectral information of the incident mid-infrared light to be measured includes:

[0082] S610: The spectrum information F(λ) of the incident mid-infrared light to be measured is sparsely represented as F(λ)=β(λ)k using basis functions, and the calculation formula of the photocurrent signal is discretized to obtain a discrete processing formula:

[0083] Wherein, βj(λj) is the expanded basis function corresponding to the j-th sampling point of the mid-infrared incident light to be measured, kj is the correlation coefficient vector corresponding to the j-th sampling point of the mid-infrared incident light to be measured, and Riij(λj) is the spectral response function corresponding to the i-th metasurface structure and the j-th sampling point of the mid-infrared incident light to be measured;

[0084] S620: Perform regularization processing according to the discrete processing formula to obtain a regularization processing formula:

[0085] S630: Solve the regularization processing formula based on the preset regularization algorithm and the transfer matrix to obtain the regularization parameter and the correlation vector coefficient;

[0086] S640: Obtaining spectral information of the mid-infrared incident light to be measured according to the regularization parameter, the correlation vector coefficient, and the basis function.

[0087] For example, the regularization algorithm is combined with the transfer matrix R to solve the regularization parameter, obtain the correlation vector coefficient, and then multiply it by the basis function to obtain the spectral information of the incident mid-infrared light to be measured.

[0088] For example, the regularization formula is:

[0089] Where α is the regularization parameter, R is the transfer matrix, k is the correlation coefficient vector, β is the basis function, and I is the photocurrent.

[0090] Exemplarily, the step of irradiating the calibration incident light onto the metasurface structure and obtaining transmission spectrum information of the calibration incident light after passing through the metasurface structure includes:

[0091] The calibration incident light is focused and irradiated onto the metasurface structure through one or more optical lenses such as a reflector, a plano-convex lens, and an objective lens to obtain the transmission spectrum information of the calibration incident light after passing through the metasurface structure.

[0092] In some implementation scenarios, in conjunction with Figures 1 to 8 , the mid-infrared spectroscopy analysis method based on metasurface computational reconstruction provided in the embodiments of the present application may be implemented in the following steps:

[0093] 1. After the metasurface structure is fabricated, it is necessary to perform actual measurement and calibration of the metasurface structure. Using incident light of a known spectrum, the light is focused onto only one metasurface structure on the chip through optical lenses such as reflectors, plano-convex lenses, and objective lenses. The actual transmission spectrum is calibrated with a photodetector and compared with the simulated transmission spectrum.

[0094] 2. Move the chip so that light traverses different locations on the chip. Then, the actual transmission spectra of different metasurface unit structures on the metasurface chip are transmitted to the computer to form a transmission matrix.

[0095] The computer establishes a one-to-one correspondence between wavelength and spatial intensity distribution through multiple metasurface units with different spectral responses. After learning is completed, the metasurface chip is integrated above the photodetector array.

[0096] 3. The photodetectors corresponding to the different metasurface units then need to be calibrated to represent the photocurrent generated by each unit, and the corresponding measured photocurrent is transmitted to the computer. The time required to measure the photocurrent depends on the detector frame rate;

[0097] 4. The set of all metasurface array spectral responses in the metasurface array is the transfer matrix R. The transfer matrix R is m rows by n columns, where m represents the number of distinct metasurface units and n represents the number of sampling points for the incident light. The transfer matrix is ​​often underdetermined, requiring a combination of various computational reconstruction algorithms to solve it. Reconstruction of the input spectrum F(λ) is achieved by solving an underdetermined linear system of equations with n unknown wavelength points λn and m measured values ​​Im.

[0098] After the incident light passes through the metasurface chip and hits the photodetector, it generates a photocurrent, which can be expressed as:

[0099] where is the spectral response function of different metasurface units, is the incident spectrum, and is the photocurrent generated by the corresponding metasurface unit. During the learning and calibration process, the transfer matrix R, the set of spectral responses of all units, was obtained. The incident spectral function is sparsely represented using different basis functions (e.g., based on dictionary learning or a sparse representation of a random transfer matrix such as a Gaussian function). Since this system of equations is linear, it can be discretized into the following form:

[0100] Where is the expanded basis function, / >; is the correlation coefficient vector; the problem of solving the above linear equation can be simplified to the following optimization problem:

[0101] where is the regularization parameter. We then use the regularization algorithm and deep learning, combined with the transfer matrix R, to solve the above optimization problem by measuring the photocurrent I. We solve for the regularization parameter and obtain the correlation vector coefficient, which is then multiplied by the basis function to obtain the spectral information of the incident light.

[0102] Therefore, the spectral information can be obtained through the algorithm based on the obtained photocurrent information, as shown in FIG9 , which is a schematic diagram of the spectral reconstruction effect provided by an embodiment of the present application, and a comparison diagram of the actual incident spectral information and the reconstructed spectral information, which is the case when the incident light is a double peak;

[0103] The mid-infrared spectroscopy analysis system provided by the embodiments of the present application realizes miniaturized, real-time and high-precision mid-infrared spectroscopy analysis.

[0104] For example, the mid-infrared spectral analysis system and method provided in the embodiments of the present application, compared with traditional mid-infrared spectrometers, combine deep learning, regularization and other reconstruction algorithms, and have the advantages of fast detection speed, ultra-fine spectral resolution, and miniaturization. It can identify high resolution and fast wide spectrum in the range of 2um-20um, and can be widely used in applications such as gas sensing analysis.

[0105] In all embodiments of the present application, "big" and "small" are relative, "more" and "less" are relative, and "up" and "down" are relative. The expressions of such relative terms will not be elaborated in the embodiments of the present application.

[0106] It should be understood that the phrases “in this embodiment,” “in an embodiment of the present application,” or “as an optional implementation” mentioned throughout the specification mean that specific features, structures, or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, “in this embodiment,” “in an embodiment of the present application,” or “as an optional implementation” appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in one or more embodiments in any suitable manner. Those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required for the present application.

[0107] In the various embodiments of the present application, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0108] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A mid-infrared spectroscopy analysis system based on metasurface computational reconstruction, characterized in that: including a metasurface core layer, a substrate, and a photodetector array; The metasurface core layer and the substrate are stacked, and the metasurface core layer is provided with a metasurface structure array, the metasurface structure array includes a plurality of metasurface structures, and the spectral responses of the plurality of metasurface structures are different, and the spectral response set of all the metasurface structures in the metasurface structure array is a transmission matrix; The metasurface core layer is arranged above the photodetector array, and the photodetector array includes a plurality of photodetectors, and the plurality of photodetectors correspond one-to-one to the plurality of metasurface structures; the photodetector is used to receive the optical signal generated after the mid-infrared incident light to be measured passes through the corresponding metasurface structure, and perform calculation and reconstruction according to the transmission matrix of the metasurface structure array and the optical signal to obtain the spectral information of the mid-infrared incident light to be measured.

2. The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction according to claim 1, characterized in that: The super surface structure is a super surface structure of a preset matrix grid model, and the preset matrix grid model includes a plurality of grids, each grid representing an etching state and a retention state of the super surface structure.

3. The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction according to claim 1 or 2, characterized in that: The shape of the super surface structure is one or more of a circular hole, a cylinder, a square, and a polygon.

4. The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction according to claim 1, characterized in that: The material of the super surface structure is a chalcogenide material.

5. The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction according to claim 1, characterized in that: The substrate is a mid-infrared transparent medium substrate, and the material of the substrate is one or more of calcium fluoride, barium fluoride, magnesium fluoride, silicon, sapphire, and zinc oxide.

6. A mid-infrared spectroscopy analysis method based on metasurface computational reconstruction, characterized in that: The mid-infrared spectroscopy analysis system based on metasurface computational reconstruction according to any one of claims 1 to 5, wherein the mid-infrared spectroscopy analysis method comprises: Traversing each metasurface structure in the metasurface core layer, and processing the traversed metasurface structure: irradiating the calibrated incident light to the metasurface structure, and obtaining transmission spectrum information of the calibrated incident light after passing through the metasurface structure; After the traversal is completed, multiple transmission spectrum information corresponding to multiple metasurface structures is obtained; Generate a transmission matrix according to the plurality of transmission spectrum information; Integrating a metasurface structure array above a photodetector array, wherein a plurality of metasurface structures in the metasurface structure array correspond one-to-one to a plurality of photodetectors in the photodetector array; The incident mid-infrared light to be measured is irradiated onto the core layer of the metasurface, and each photodetector generates a photocurrent signal based on the metasurface structure to obtain a plurality of photocurrent signals; Calculation and reconstruction are performed based on the transmission matrix and the multiple photocurrent signals to obtain spectral information of the mid-infrared incident light to be measured.

7. The mid-infrared spectroscopy analysis method based on supersurface computational reconstruction according to claim 6, characterized in that: The transmission matrix is ​​a transmission matrix of m rows×n columns, where m represents the number of metasurface structures in the metasurface core layer, and n represents the number of sampling points of the mid-infrared incident light to be measured. The calculation formula of the photocurrent signal is: Among them, I i is the photocurrent generated by the i-th metasurface structure, F(λ) is the spectral information of the mid-infrared incident light to be measured, λ represents the light wavelength, λ1 represents the light wavelength of the first sampling point of the mid-infrared incident light to be measured, λn represents the light wavelength of the n-th sampling point of the mid-infrared incident light to be measured, and Ri(λ) is the spectral response function corresponding to the i-th metasurface structure.

8. The mid-infrared spectroscopy analysis method based on supersurface computational reconstruction according to claim 7, characterized in that: The step of performing calculation reconstruction based on the transmission matrix and the multiple photocurrent signals to obtain the spectral information of the mid-infrared incident light to be measured comprises: The spectrum information F(λ) of the mid-infrared incident light to be measured is sparsely represented as F(λ)=β(λ)k using basis functions, and the calculation formula of the photocurrent signal is discretized to obtain a discrete processing formula: Where βj(λj) is the basis function of the jth sampling point corresponding to the mid-infrared incident light to be measured, k j is the correlation coefficient vector corresponding to the jth sampling point of the mid-infrared incident light to be measured, Rij(λj) is the spectral response function corresponding to the i-th metasurface structure and the jth sampling point of the mid-infrared incident light to be measured Regularization processing is performed according to the discrete processing formula to obtain the regularization processing formula: The regularization processing formula is solved based on the preset regularization algorithm and the transfer matrix to obtain Regularization parameter, correlation vector coefficient; The spectral information of the incident mid-infrared light to be measured is obtained according to the regularization parameter, the correlation vector coefficient and the basis function.

9. The mid-infrared spectroscopy analysis method based on supersurface computational reconstruction according to claim 8, characterized in that: The regularization processing formula is: Where α is the regularization parameter, R is the transfer matrix, k is the correlation coefficient vector, β is the basis function, and I is the photocurrent.

10. The mid-infrared spectroscopy analysis method based on supersurface computational reconstruction according to claim 6, characterized in that: The step of irradiating the calibration incident light onto the metasurface structure and obtaining transmission spectrum information of the calibration incident light after passing through the metasurface structure comprises: The calibration incident light is focused and irradiated onto the metasurface structure through one or more of a reflector, a plano-convex lens, and an objective lens to obtain transmission spectrum information of the calibration incident light after passing through the metasurface structure.

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