Spectrometer, spectrum reconstruction method and device and electronic equipment

Abstract

The invention provides a spectrograph, a spectrum reconstruction method and device and electronic equipment, and relates to the field of spectrum analysis. The spectrograph comprises a chip and a peripheral circuit, the chip comprises a photoelectric response layer, a gate layer and an electrode lead-out layer, and a target semiconductor is arranged in the photoelectric response layer; the photoelectric response layer is used for converting an incident spectrum into a photocurrent signal; the gate layer is used for changing the photoelectric response characteristic of the target semiconductor and covers the upper and lower surfaces of the photoelectric response layer; the electrode lead-out layer is used for outputting the photocurrent signal to external equipment, and the external equipment is used for reconstructing an incident spectrum according to the photocurrent signal and the photoelectric response characteristic of the target semiconductor; the peripheral circuit is used for maintaining the chip to work. According to the invention, the semiconductor with adjustable photoelectric response characteristics is used as the core of the photoelectric response layer, so that the spectrometer has the spectral analysis capability from infrared to terahertz wave bands, does not need to depend on a huge optical assembly and a precise mechanical displacement assembly, and can effectively solve the problems in the prior art.

Description

Technical Field

[0001] This application relates to the field of spectral analysis, and more particularly to a spectrometer, a spectral reconstruction method, an apparatus, and an electronic device. Background Technology

[0002] The infrared to terahertz band covers a key spectral region from molecular vibrations to weak intermolecular interactions, forming a continuous information channel for resolving the structure and microscopic dynamics of matter. This band contains rich molecular characteristic absorptions and low-frequency resonance modes, which are crucial not only for materials composition analysis, biomolecular recognition, and lattice dynamics research, but also for demonstrating unique advantages in various applications such as biomedicine, space remote sensing imaging, and non-destructive testing in industrial production, becoming an important spectral window connecting basic science and applied technology.

[0003] Currently, the mainstream implementation schemes for spectrometers include dispersive (e.g., grating spectrometers), filtered (e.g., narrowband filtered spectrometers), and interferometric (e.g., Fourier transform infrared spectrometers). Compared to the diverse types of visible light spectrometers, infrared to terahertz spectrometers are mainly interferometric, relying on a high-precision moving platform to acquire interference fringes that evolve over time, and then obtaining the spectrum through Fourier transform. Traditional infrared to terahertz spectrometers typically contain large optical components and precise mechanical displacement components, which cannot meet the demands for low cost and portability in fields such as biomedical detection, environmental monitoring, and spectral imaging. Summary of the Invention

[0004] This application provides a spectrometer, a spectral reconstruction method, an apparatus, and an electronic device to address the shortcomings of existing spectrometers in the infrared to terahertz band, which, due to their large optical components and sophisticated mechanical displacement components, cannot meet the demands for low cost and portability in fields such as biomedical detection, environmental monitoring, and spectral imaging.

[0005] This application provides a spectrometer, including a chip and peripheral circuitry. The chip includes a photoresponse layer, a gate layer, and an electrode lead-out layer. A target semiconductor is disposed in the photoresponse layer. The photoelectric response layer is used to convert the incident spectrum into a photocurrent signal; The gate layer is used to change the photoelectric response characteristics of the target semiconductor by adjusting the band structure of the photoelectric response layer. The gate layer covers the upper and lower surfaces of the photoelectric response layer. The gate layer generates an electrostatic field by applying a voltage thereon. The electrostatic field is used to break the symmetry inside the target semiconductor to change the size of the band gap of the target semiconductor, thereby changing the photoelectric response characteristics of the target semiconductor. The electrode lead-out layer is used to output the photocurrent signal to an external device, and the external device is used to reconstruct the incident spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor. The peripheral circuitry is used to maintain the operation of the chip. According to the spectrometer provided in this application, a dielectric material is further disposed in the photoresponse layer, the dielectric material being used to encapsulate the target semiconductor.

[0006] According to the spectrometer provided in this application, the medium is boron nitride.

[0007] According to the spectrometer provided in this application, the electrode lead-out layer is respectively disposed on the left and right sides of the photoelectric response layer.

[0008] According to the spectrometer provided in this application, the target semiconductor is bilayer graphene.

[0009] This application also provides a spectral reconstruction method based on the above-mentioned spectrometer, including: Acquire the photocurrent signal generated by the spectrometer under the target spectrum illumination; The target spectrum is reconstructed based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

[0010] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the spectral reconstruction method as described above.

[0011] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the spectral reconstruction method as described above.

[0012] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the spectral reconstruction method as described above.

[0013] This application provides a spectrometer, including a chip and peripheral circuitry. The chip comprises a photoresponse layer, a gate layer, and an electrode lead-out layer. A target semiconductor is disposed in the photoresponse layer. The photoresponse layer is used to convert the incident spectrum into a photocurrent signal. The gate layer is used to modify the photoresponse characteristics of the target semiconductor and covers the upper and lower surfaces of the photoresponse layer. The electrode lead-out layer is used to output the photocurrent signal to an external device, which reconstructs the incident spectrum based on the photocurrent signal and the photoresponse characteristics of the target semiconductor. The peripheral circuitry is used to maintain the chip's operation. This application uses a target semiconductor with adjustable photoresponse characteristics as the core of the photoresponse layer, enabling the spectrometer to perform spectral analysis from the infrared to the terahertz band. Furthermore, compared to traditional infrared to terahertz spectrometers, the spectrometer of this application does not require bulky optical components and precise mechanical displacement components, possessing advantages such as simple structure, small size, portability, and low cost. It can better meet the needs of biomedical detection, environmental monitoring, and spectral imaging fields for low-cost and portable spectrometers. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the structure of a spectrometer shown in one embodiment of this application.

[0016] Figure 2 This is a flowchart illustrating a spectral reconstruction method according to an embodiment of this application.

[0017] Figure 3 This is a schematic diagram of the structure of a photoelectric response measurement system according to an embodiment of this application.

[0018] Figure 4 This is a schematic diagram illustrating a photoelectric response function according to an embodiment of this application.

[0019] Figure 5 This is a schematic diagram of a photoelectric response matrix shown in one embodiment of this application.

[0020] Figure 6 This is a schematic diagram of the spectral reconstruction results of polytetrafluoroethylene shown in one embodiment of this application.

[0021] Figure 7 This is a schematic diagram of the spectral reconstruction results of polyethylene-vinyl acetate shown in one embodiment of this application.

[0022] Figure 8 This is a structural block diagram of a spectral reconstruction device shown in one embodiment of this application.

[0023] Figure 9 This is a schematic diagram of the physical structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] To address the limitations of traditional infrared to terahertz spectrometers, which contain bulky optical components and intricate mechanical displacement mechanisms, thus failing to meet the demands for low cost and portability across various fields, this application provides a computational infrared to terahertz spectrometer, the structure of which is as follows: Figure 1 As shown. Figure 1 This is a schematic diagram of the structure of a spectrometer shown in one embodiment of this application.

[0026] Reference Figure 1 The spectrometer of this application includes a chip and peripheral circuitry. The chip includes a photoresponse layer, a gate layer, and an electrode lead-out layer. The photoresponse layer contains a target semiconductor.

[0027] The photoresponse layer is used to convert the incident spectrum into a photocurrent signal.

[0028] Among them, the incident spectrum refers to the light wave emitted from the light source, which, after interacting with the sample under test (e.g., being selectively absorbed by the sample), finally reaches and illuminates the surface of the photoelectric response layer, containing rich wavelength and corresponding intensity information.

[0029] Specifically, the principle by which the photoresponse layer converts the incident spectrum into a photocurrent signal is as follows: When the incident spectrum shines on the photoresponse layer, photons in the spectrum with energy greater than the band gap of the target semiconductor will be absorbed by the target semiconductor. This energy is used to excite electrons in the semiconductor's valence band to jump to the conduction band, thereby generating freely moving electron-hole pairs. Under the action of the electric field applied by the peripheral circuit, these photoexcited electrons and holes will undergo directional movement and be collected by the electrodes, forming a macroscopically measurable current, i.e., photocurrent. Since the photoresponse layer simultaneously receives incident light of all wavelengths, the final output photocurrent signal is the sum of the currents generated by all effective photons (with energy greater than the band gap).

[0030] The gate layer is used to change the photoelectric response characteristics of the target semiconductor. The gate layer covers the upper and lower surfaces of the photoelectric response layer.

[0031] The photoelectric response characteristics of the target semiconductor refer to the set of inherent physical laws governing how the target semiconductor, as the core photosensitive unit, converts the energy of incident photons into electrical signals. The photoelectric response characteristics comprehensively describe how and to what extent the target semiconductor responds to light, mainly including: 1) spectral response characteristics, i.e., the functional relationship between the photoelectric conversion efficiency (the efficiency of generating photocurrent) and the incident light wavelength or wavenumber; 2) light intensity response characteristics, i.e., the dependence between the generated photocurrent signal and the incident light intensity; and 3) tunability, i.e., the property that the spectral response characteristics themselves can be actively modulated and changed by external physical parameters (such as voltage, magnetic field, temperature, stress, etc.).

[0032] In this application, the photoelectric response characteristics of the target semiconductor are tunable, meaning that the photoelectric response behavior of the target semiconductor is not static but can be actively controlled and changed. Specifically, the gate layer of this application can change the photoelectric response characteristics of the target semiconductor by adjusting (e.g., applying voltage) the band structure of the photoelectric response layer.

[0033] In this application, the gate layer serves as the control electrode. By applying a voltage to it, a strong electrostatic field perpendicular to the device plane is generated. This electric field penetrates the insulating dielectric layer and directly acts on the target semiconductor of the photoresponse layer. This electric field can break the internal symmetry of the target semiconductor, change the size of its band gap, and thus achieve the control of the target semiconductor's band structure. Since the photoelectric response behavior of a semiconductor, especially its sensitivity to certain wavelengths of light (i.e., the spectral response function), is essentially determined by its band structure, this application can directly change the photon absorption threshold and absorption efficiency of the target semiconductor by altering its band gap, thereby changing the photoelectric response characteristics of the target semiconductor.

[0034] In this application, the use of a target semiconductor with tunable photoelectric response characteristics is fundamental to achieving broadband (infrared to terahertz band) spectral analysis capabilities. The fundamental reason is that a conventional detector with a fixed response can only integrate the entire incident spectrum into a single, undecipherable current value. If the optical response characteristics of the target semiconductor can be altered, then by actively modulating the band structure of the target semiconductor (e.g., applying voltage), the target semiconductor can generate a series of photoelectric response functions with distinct spectral characteristics (i.e., low correlation), and an integrated photocurrent value can be measured under each photoelectric response function. Mathematically, this is equivalent to transforming an unsolvable multi-unknown, single-equation problem into a fully informative multi-unknown, multi-equation linear system. As long as this series of photoelectric response functions can effectively cover the infrared to terahertz band, this linear system can contain sufficient information, ultimately allowing the target spectrum within the infrared to terahertz band to be solved using computational reconstruction algorithms.

[0035] The electrode lead-out layer is used to output the photocurrent signal to an external device, which is used to reconstruct the incident spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor.

[0036] In this application, the electrode lead-out layer is communicatively connected to an external device. The external device can read the photocurrent signal from the spectrometer, and then reconstruct the incident spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor.

[0037] In one embodiment, the electrode lead-out layers are respectively disposed on the left and right sides of the photoresponse layer, such as... Figure 1 As shown, when the gate layers cover the upper and lower surfaces of the photoresponse layer, and the electrode lead-out layers are respectively disposed on the left and right sides of the photoresponse layer, the entire structure is equivalent to a dual-gate controlled diode. The upper and lower gates can apply a vertical electric field to the middle semiconductor layer, and the left and right electrode lead-out layers are equivalent to the source and drain, respectively, and their function is to lead the current signal generated by the semiconductor layer to the external collection circuit. Therefore, through this design, a stable signal output channel can be provided for the photocurrent generated in the photoresponse layer, thereby realizing effective electrical driving and signal readout of the photoresponse layer.

[0038] Peripheral circuitry is used to maintain the chip's operation.

[0039] In this application, all circuits in the spectrometer other than the chip are collectively referred to as peripheral circuits. These peripheral circuits maintain stable chip operation and enable the basic functions of the spectrometer. The structure of the peripheral circuits can be configured according to actual needs, and this application does not impose any restrictions on this.

[0040] In summary, this application provides a spectrometer, including a chip and peripheral circuitry. The chip comprises a photoresponse layer, a gate layer, and an electrode lead-out layer. A target semiconductor is disposed in the photoresponse layer. The photoresponse layer is used to convert the incident spectrum into a photocurrent signal. The gate layer is used to modify the photoresponse characteristics of the target semiconductor and covers the upper and lower surfaces of the photoresponse layer. The electrode lead-out layer is used to output the photocurrent signal to an external device, which reconstructs the incident spectrum based on the photocurrent signal and the photoresponse characteristics of the target semiconductor. The peripheral circuitry is used to maintain the chip's operation. This application uses a target semiconductor with adjustable photoresponse characteristics as the core of the photoresponse layer, enabling the spectrometer to perform spectral analysis from the infrared to the terahertz band. Furthermore, compared to traditional infrared to terahertz spectrometers, the spectrometer of this application does not require bulky optical components and precise mechanical displacement components, possessing advantages such as simple structure, small size, portability, and low cost. It can better meet the needs of biomedical detection, environmental monitoring, and spectral imaging fields for low-cost and portable spectrometers.

[0041] An existing technology provides an on-chip infrared spectroscopy analysis system based on electric field modulation. The chip comprises, from top to bottom, a substrate layer, a semiconductor nanofilm, and a top electrode layer. The semiconductor nanofilm is a sandwich structure consisting of an upper dielectric layer, a semiconductor layer, and a lower dielectric layer, arranged sequentially from top to bottom. Both the substrate layer and the top electrode layer are connected to a probe station and external circuitry via metal electrodes for spectral testing. The upper and lower dielectric layers are boron nitride or aluminum oxide thin film dielectric materials, the semiconductor layer is a black phosphorus film, the top electrode layer is an electrode film transparent to the detection band, and the substrate layer is a highly doped silicon dioxide substrate. The process of spectral reconstruction based on this on-chip infrared spectroscopy analysis system is as follows: First, constructing the photoelectric response function matrix. By modulating the Franz-Keldysh effect of electron-hole plasma / electron-hole liquid in the semiconductor material using an electric field, band-edge absorption is controlled, thereby obtaining a series of different photoelectric response functions; Second, measuring the photoelectric response signal, using a continuous laser to obtain the photocurrent of the infrared spectroscopy analysis chip. With the applied electric displacement vector Size variation and wavelength The spectral response spectra between them are Then, by diagonalizing the spectral response matrix and differentiating the photocurrent with respect to the electric displacement vector, the following relationship is obtained, and the measured spectrum is then solved. : .

[0042] However, the spectral reconstruction scheme based on the above-mentioned on-chip infrared spectral analysis system has the following problems: First, this scheme constructs an tunable response function by modulating the band-edge absorption characteristics of black phosphorus material using an external electric field. However, band-edge absorption modulation typically results in a gradual change in photoelectric response and low wavelength differentiation, leading to highly similar spectral shapes among different photoelectric response functions, making it difficult to construct a photoelectric response matrix with low correlation. To alleviate this problem, an approximately diagonalized photoelectric response matrix can be constructed by differentiating the photocurrent with respect to electric field parameters (such as the electric displacement vector), thereby reducing the linear correlation between photoelectric response functions and simplifying the spectral reconstruction solution process mathematically. However, such derivative operations are inherently sensitive to noise and rely on complex signal processing.

[0043] Second, this scheme uses black phosphorus as the semiconductor active layer material, relies on an external electric field to modulate its band-edge absorption characteristics, and uses a mid-infrared continuous laser to complete the spectral testing in the 2.5-4.8 μm band. However, due to the intrinsic band gap and excitation mechanism of black phosphorus, its spectral response capability is significantly attenuated in longer wavelength regions (especially the far-infrared and terahertz bands), making it difficult to achieve effective coverage.

[0044] Third, this scheme uses black phosphorus as the core material. Black phosphorus is extremely sensitive to oxygen and moisture, and is prone to oxidation and structural degradation. It requires an inert atmosphere and multi-layer encapsulation to maintain stability, which significantly increases the complexity of device fabrication and packaging. At the same time, the thickness of black phosphorus is difficult to control precisely, the material has poor uniformity, and it faces problems such as unstable wafer sources and low repeatability during mass production, which restricts its practical application in large-scale integrable spectroscopic devices.

[0045] Fourth, the solution uses a mid-infrared continuous laser as the incident light source to ensure sufficient light intensity and wavelength resolution. However, such lasers are expensive and the system is complex, which limits the deployment of practical applications.

[0046] To address the aforementioned issues, this application employs bilayer graphene as the target semiconductor, which effectively overcomes the shortcomings of using black phosphorus as the core semiconductor material. The specific reasons are as follows: Regarding the first issue mentioned above, this application achieves effective modulation of the photoelectric response function of the target semiconductor in the wavelength dimension by precisely controlling the band structure and band gap of bilayer graphene. The photoelectric response functions under different band gap conditions exhibit significant differences in peak position, shape, and intensity, naturally forming a set of low-correlation, programmable photoelectric response functions. A well-structured photoelectric response observation matrix can be obtained without additional diagonalization processing. This characteristic significantly improves the reversibility, robustness, and simplicity of the spectral reconstruction process and system implementation.

[0047] Regarding the second question mentioned above, this application, based on bilayer graphene material, enables the spectrometer to possess photoelectric response capabilities from a wide band in the infrared range to a potential extension to the terahertz band by precisely controlling its band structure and band gap. This is significantly superior to the limitations of existing black phosphorus systems in terms of material bandwidth and spectral extension.

[0048] Regarding the third issue mentioned above, this application employs bilayer graphene as the control material. Graphene exhibits excellent chemical stability and structural reliability in atmospheric environments, avoiding complex packaging processes and making it suitable for conventional micro / nano fabrication processes. Furthermore, graphene thin-layer structures have high uniformity, and the fabrication technologies (such as mechanical exfoliation and CVD) are mature, providing good wafer-source consistency and integration compatibility. This significantly improves the consistency and scalability of device fabrication, meeting the development needs of large-area, arrayed spectral chips.

[0049] Regarding the fourth issue mentioned above, this application utilizes the broadband absorption characteristics of bilayer graphene in the infrared band. By precisely controlling its band structure and band gap, programmable design of the photoelectric response function can be achieved. Under ordinary blackbody radiation light source irradiation, a clear, distinguishable, and low-correlation photoelectric response function can be generated, which can significantly simplify the system configuration and improve the universality and practicality of the spectrometer.

[0050] The spectrometer provided in this application uses bilayer graphene as the core of the photoelectric response layer, enabling the chip itself to possess dual functions of spectral filtering and photoelectric detection. It eliminates the need for external detectors such as CMOS or complex heterogeneous device arrays. By precisely controlling the band structure of the bilayer graphene through voltage application to the gate layer, continuous and flexible changes in photoelectric response characteristics can be achieved on a single device. This allows a single structure and voltage modulation technique to replace the functions of multiple devices with different structures in traditional technologies. Secondly, the spectrometer provided in this application primarily covers the mid-infrared molecular fingerprint region. Utilizing the excellent broadband absorption and electrically tunable characteristics of bilayer graphene in this band, it can highly sensitively capture and identify the characteristic absorption fingerprints of molecules, thereby achieving precise spectral analysis of complex chemical components.

[0051] In conjunction with the above embodiments, in one implementation, a dielectric material is further disposed in the photoresponse layer. The dielectric material is used to encapsulate the target semiconductor, thereby protecting the target semiconductor from the influence of the external environment while significantly reducing internal charge scattering and significantly improving the stability, photoelectric conversion efficiency and performance of the photoresponse layer.

[0052] In one embodiment, in conjunction with the above embodiments, the medium is boron nitride.

[0053] In this application, boron nitride can be selected as the dielectric, which can suppress charge scattering to the maximum extent, fully preserve and give full play to the target semiconductor's ultra-high carrier mobility and excellent intrinsic optoelectronic properties.

[0054] In summary, this application provides a computational infrared to terahertz spectrometer, whose chip structure consists of multiple functional regions, including: (1) a core photoresponse layer, which is a (low-dimensional) semiconductor material coated with a dielectric material, constituting a core structural unit with tunable photoresponse capability; (2) a top gate layer, which is an infrared to terahertz band transparent electrode structure covering the surface of the photoresponse layer, used to regulate the band structure of the (low-dimensional) semiconductor material; and (3) a preset electrode lead-out structure, used to connect the spectrometer to external devices to realize the reading and analysis of photocurrent signals. Among them, the structure of the core photoresponse layer can be a bilayer graphene coated with a dielectric material (e.g., boron nitride), and the top gate layer can be a few-layer graphite or graphene with infrared to terahertz band transparency. In actual implementation, in addition to bilayer graphene, any semiconductor material whose photoresponse characteristics can be actively regulated can be used as the target semiconductor in the photoresponse layer. In addition, the dielectric material used to coat the target semiconductor can be other materials besides boron nitride, depending on actual needs.

[0055] This application employs a target semiconductor with adjustable photoelectric response characteristics as the core of the photoelectric response layer, enabling the spectrometer to perform spectral analysis from the infrared to the terahertz band. Furthermore, compared to traditional infrared to terahertz spectrometers, the spectrometer of this application does not require bulky optical components and precise mechanical displacement components, possessing advantages such as simple structure, small size, low cost, and portability. It can better meet the needs of biomedical detection, environmental monitoring, and spectral imaging fields for low-cost and portable spectrometers.

[0056] This application also provides a spectral reconstruction method based on the above-mentioned spectrometer, such as... Figure 2 As shown. Figure 2 This is a flowchart illustrating a spectral reconstruction method according to an embodiment of this application. (Refer to...) Figure 2 The spectral reconstruction method of this application may include the following steps: Step 100: Acquire the photocurrent signal generated by the spectrometer under the target spectrum illumination.

[0057] Step 200: Based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer, the target spectrum is reconstructed.

[0058] In this application, the spectrometer achieves spectral reconstruction based on the following model: in, For wavelength, For the spectrometer regarding wavelength The photoelectric response function (used to reflect photoelectric response characteristics). For the unknown incident spectrum with respect to wavelength Intensity distribution, This is the photoelectric response signal (photocurrent signal) of the spectrometer to the incident spectrum.

[0059] The photoelectric response functions of the spectrometer under different control conditions are used to construct a photoelectric response matrix. Then the photoelectric response signal can be expressed in matrix form. The incident spectrum can be reconstructed by solving the inverse problem of this linear model. .

[0060] This application employs a target semiconductor with adjustable photoelectric response characteristics as the core of the photoelectric response layer, enabling the spectrometer to perform spectral analysis from the infrared to the terahertz band. Secondly, compared to traditional infrared to terahertz spectrometers, the spectrometer of this application does not require bulky optical components and precise mechanical displacement components, possessing advantages such as simple structure, small size, low cost, and portability. This makes the spectral reconstruction method based on the spectrometer of this application simple to implement and highly efficient.

[0061] In this application, the photoelectric response functions of different channels together constitute the incident spectrum. To photoelectric response signal The mapping relationship between them. The wavelength coverage and distribution characteristics of the photoelectric response function determine the spectrometer's ability to perceive different spectral features, thus directly affecting the incident spectrum. The reconstructable wavelength range. Generally, the number of photoelectric response functions is far less than the number of wavelength-resolved points in the spectrum to be reconstructed. The inverse problem solution is an underdetermined inverse problem, characterized by non-unique solutions and sensitivity to noise. Therefore, constructing a set of low-correlation photoelectric response functions (characterized by the Pearson correlation coefficient) can improve the photoelectric response matrix. The reversibility and effective number of channels (i.e., the quantitative representation of photoelectric response characteristics) are improved to enhance the robustness of solving the underdetermined inverse problem. Therefore, a set of flexibly adjustable, wide-range, and low-correlation photoelectric response functions is constructed, thereby forming a well-structured photoelectric response matrix. This is the core and key element in the design of computational reconstructive spectrometers.

[0062] In view of the above considerations, this application provides a method for controlling the photoelectric response characteristics of (low-dimensional) semiconductor materials. By controlling the band gap size and carrier concentration of the (low-dimensional) semiconductor material, its intrinsic response characteristics to the incident light field are changed, thereby achieving highly robust and flexible control of the photoelectric response function, and thus constructing a low-correlation photoelectric response matrix. .

[0063] Specifically, in one embodiment, the photoelectric response characteristics of the target semiconductor are determined by the following steps: The response intensity of the target semiconductor to incident light of different wavelengths at multiple different band gaps was obtained, and multiple curves of response intensity as a function of wavelength were obtained. Based on multiple curves, the photoelectric response characteristics of the target semiconductor are determined.

[0064] In this application, a photoelectric response matrix is ​​obtained. The process is as follows: Step 1: Maintain the target semiconductor (e.g., bilayer graphene) within the band gap Below, the photoelectric response of the target semiconductor is measured using a Fourier transform infrared spectrometer to obtain the photocurrent signal. The measurement system is as follows: Figure 3 As shown. Figure 3 This is a schematic diagram of the structure of a photoelectric response measurement system according to an embodiment of this application.

[0065] Figure 3 A Fourier transform infrared spectroscopy system for calibrating or testing spectroscopic instruments (target semiconductors) is demonstrated. Broadband infrared light emitted from a light source is collimated and focused by an off-axis parabolic mirror, passes through a thin-film sample (typically with an air background during photoelectric response matrix calibration), and then enters a Michelson interferometer. A beam splitter within the interferometer splits the beam in two, directing it towards a fixed mirror and a linearly moving mirror, respectively. The two beams reflect and then rejoin, generating interference. Finally, the modulated beam carrying interference information is focused onto the spectroscopic instrument located within a cryogenic chamber (to provide a stable low-temperature operating environment). In this calibration setup, the core function of the spectroscopic instrument is as a high-sensitivity detector, converting the received optical interference signal into a photocurrent signal for Fourier transform analysis in real time. The second step involves performing a Fourier transform on the measured photocurrent signal to obtain the current bandgap. Below, the photoelectric response function of the target semiconductor to incident light, such as Figure 4 As shown. Figure 4 This is a schematic diagram illustrating a photoelectric response function according to an embodiment of this application.

[0066] The curve of response intensity versus wavelength mentioned above is the photoelectric response function.

[0067] exist Figure 4In (a), photocurrent intensity refers to the intensity of the photocurrent signal actually generated and measured by the photodetector (i.e., the spectroscopic instrument) after receiving light from the interferometer. Normalization means that all intensity values ​​are scaled proportionally so that their maximum value or central peak value is 1. Optical path difference (OPD) is a physical quantity in Fourier transform spectrometers, referring to the difference in path lengths traveled by two beams of light passing through the moving and fixed mirrors in the interferometer when they re-converge. The unit is millimeters (mm). Figure (a) shows how the photocurrent intensity changes with the optical path difference, i.e., the interferogram. Figure 4 In (b), intensity refers to the relative intensity of the spectral signal at each wavenumber point after performing a Fourier transform on the interferogram in (a). It reflects the sensitivity of the spectrometer to light at different wavenumbers or the intensity of transmitted light. Wavenumber is defined as the reciprocal of wavelength, representing the number of waves contained within a unit length (usually 1 cm). The unit is the reciprocal of centimeters (cm). -1 Wavenumber is directly proportional to energy; the higher the value, the higher the energy of the light. Figure 4 (b) represents a photoelectric response function, which is derived from... Figure 4 (a) shows the original photocurrent interferogram signal obtained by Fourier transform.

[0068] Step 3: Adjust the band gap of the target semiconductor sequentially. Repeat the above steps to obtain a series of different band gaps. The photoelectric response functions are used to form the photoelectric response matrix, as shown below. Figure 5 As shown. Figure 5 This is a schematic diagram of a photoelectric response matrix shown in one embodiment of this application. Figure 4 The photoelectric response function in is Figure 5 It is drawn as a row vector of the photoelectric response matrix.

[0069] exist Figure 5 In semiconductors, the energy band gap (Eg) represents the minimum energy required for an electron to transition from the valence band to the conduction band. The unit is meV (millielectron volt). Figure 5 The color intensity at any point represents the photoelectric response intensity of the spectrometer at that point under the corresponding combination of band gap and wavenumber.

[0070] This application modulates the band structure of a target semiconductor, gradually opening its original zero bandgap. At different bandgap levels, the target semiconductor exhibits high robustness and low correlation in its photoelectric response to the incident light field. By changing the bandgap of the target semiconductor, a series of different photoelectric response functions can be obtained, thereby constructing a photoelectric response matrix. .

[0071] This application obtains a series of photoelectric response functions that are significantly different from each other in terms of spectral characteristics by actively and continuously controlling the band gap of the target semiconductor. The inherent low correlation between these functions ensures that the constructed photoelectric response matrix can fundamentally guarantee the stability and uniqueness of the solution to the inverse spectral problem, thereby enabling high-fidelity, high signal-to-noise ratio spectral analysis.

[0072] In conjunction with the above embodiments, in one implementation, before step 200, the method further includes: Acquire the background photocurrent signal generated by the spectrometer under background spectral illumination; Accordingly, step 200 may include: The initial target spectrum is reconstructed based on the photoelectric response characteristics and photocurrent signal; The background spectrum is reconstructed based on the photoelectric response characteristics and the background photocurrent signal; The target spectrum is obtained based on the initial target spectrum and the background spectrum.

[0073] In this application, air absorption spectroscopy is used to perform self-calibration on the spectroscopic instrument (target semiconductor) to achieve better spectral reconstruction results. Specifically, based on the photoelectric response characteristics and background photocurrent signal, when reconstructing the background spectrum, the background photocurrent signal is first obtained. The process of obtaining the background photocurrent signal is as follows: The band gap of the target semiconductor is adjusted sequentially as follows: This is consistent with the bandgap data used in the photoelectric response matrix construction process. In each bandgap... Below, the target semiconductor is recorded in the air background spectrum. The photoelectric response signal generated below The background photoelectric response signal vector is obtained as follows: When reconstructing the background spectrum based on the photoelectric response characteristics and the background photocurrent signal, the photocurrent signal is first obtained. The process of obtaining the photocurrent signal is as follows: A sample material is introduced between the light source and the spectroscopic instrument in the optical path. Because the sample material has distinct absorption characteristics in the infrared band, its transmission spectrum contains multiple characteristic absorption peaks. Therefore, the incident spectrum reaching the spectroscopic instrument after being modulated by the sample material... Compared to the background spectrum of air, absorption dips appear within a specific wavenumber range, reflecting the absorption characteristics of the sample material.

[0074] Similarly, the band gap of the target semiconductor is adjusted sequentially as follows: This is consistent with the bandgap data used in the photoelectric response matrix construction process. In each bandgap... Below, the recording spectrometer records the incident spectrum modulated by the absorption of the sample material. The photoelectric response signal generated below The photoelectric response signal vector is obtained as follows: After obtaining the background photoelectric response signal vector Photoelectric response signal vector After that, it can be based on and photoelectric response matrix The background spectrum was reconstructed based on... and photoelectric response matrix The initial target spectrum is obtained through reconstruction. In this application, the initial target spectrum is represented as... The background spectrum is represented as .

[0075] In practical implementation, the target spectrum is obtained based on the initial target spectrum and the background spectrum, and can be: and The result of the division is taken as the absorption spectrum of the sample material, i.e., the target spectrum.

[0076] In this application, if the sample material is polytetrafluoroethylene (PTFE), which has representative infrared absorption characteristics, the reconstruction result of the target spectrum is as follows: Figure 6 As shown. If the sample material is polyethylene-vinyl acetate (EVA), the reconstruction result of the target spectrum is as follows. Figure 7 As shown, the reconstruction results of both sample materials were compared with the measurement results of a commercial Fourier transform spectrometer. Figure 6 This is a schematic diagram of the spectral reconstruction results of polytetrafluoroethylene shown in one embodiment of this application. Figure 7 This is a schematic diagram of the spectral reconstruction results of polyethylene-vinyl acetate shown in one embodiment of this application.

[0077] Depend on Figure 6As can be seen, the spectral reconstruction results (solid line) of polytetrafluoroethylene (PTFE) obtained by the spectrometer of this application show extremely high consistency with the spectral reconstruction results (dashed line) of a commercial Fourier transform infrared spectrometer (in industry standard) in multiple dimensions such as the position of key characteristic absorption peaks, peak shape profile, and relative intensity. Therefore, the spectrometer of this application has a reliable ability to accurately identify and analyze complex molecules using spectra.

[0078] Depend on Figure 7 As can be seen, even for EVA materials with more complex and denser characteristic absorption peaks than PTFE, the spectrometer described in this application can still accurately reconstruct its spectral fingerprint. The reconstruction results are highly consistent with the measurement data of industry-standard commercial FTIR spectrometers across the entire wavelength range. This indicates that the spectral reconstruction technology described in this application is not only effective for single materials, but also has the versatility to reliably perform spectral analysis on a variety of different chemical substances.

[0079] In this application, considering the background spectrum during spectral reconstruction enables systematic error correction and signal normalization. The background spectrum contains all non-sample-introduced interference signals, such as the non-uniform spectral distribution of the light source, the characteristic absorption of water vapor and carbon dioxide in the air, and the response deviations of the instrument's optical components and detectors themselves. By dividing the sample reconstructed spectrum (initial target spectrum) by the background reconstructed spectrum (background spectrum), these shared systematic and environmental artifacts can be effectively eliminated. This allows for the separation and extraction of a pure spectrum that reflects only the intrinsic absorption or transmission characteristics of the sample, greatly improving the accuracy, comparability, and reliability of the final spectral results.

[0080] In conjunction with the above embodiments, in one implementation, step 200 may include: Based on the Gaussian basis function, photocurrent signal, and photoelectric response characteristics of the target semiconductor, the expression for the target spectrum is obtained; The target spectrum is obtained by solving the expression using a Tikhonov regularization algorithm based on generalized cross-validation.

[0081] Specifically, the process of reconstructing the spectrum may include: Step 1: Gorsky expansion.

[0082] The target spectrum to be reconstructed is obtained using Gaussian basis functions. Expand the spectrum to be reconstructed. It can be represented as a linear combination of a set of Gaussian functions, i.e.: At discrete wavelength points The above is recorded as: Right now: in, Represents the expansion coefficients of different Gaussian functions. Let Gausky's function be the matrix containing the values ​​of the Gausky function, and its matrix elements be... Indicates the first The Gaussian function at the wavelength point The value on.

[0083] Substitute into the linear inversion model Then we have: Further notes The problem can then be transformed into solving the following linear system: Step 2: Tikhonov regularization based on generalized cross-validation.

[0084] Specifically, using the Tikhonov regularization method, the objective function after introducing the regularization term is: Among them, the regularization parameter The trade-off between the smoothness of the control solution and the goodness of fit is addressed. To achieve unsupervised parameter selection, this application employs Generalized Cross Validation (GCV) to automatically select the optimal regularization factor. Its evaluation function is defined as follows: To reduce computational complexity, when dealing with matrices... Perform singular value decomposition Then, the trace term in the above formula can be simplified to: in For matrix singular values, For matrix Rank.

[0085] Finally, through traversal And find the minimum value of the GCV function to determine the optimal regularization parameters. According to the optimal regularization parameters The minimum value of the objective function can be obtained by solving for it, and the expansion coefficients at which the objective function reaches its minimum value can be calculated. As the optimal expansion coefficient Finally, based on the optimal expansion coefficients... The reconstructed spectrum is obtained and expressed as follows: Step 3: Self-calibration of spectroscopic instruments and spectral reconstruction The absorption spectra of the sample materials were analyzed using the Gaussian expansion and the Tikhonov regularization method based on generalized cross-validation. With the background spectrum of air Reconstruction is performed to obtain the initial target spectrum. and background spectrum .

[0086] This application provides a stable, robust, and automated solution framework for the inherent ill-posed, underdetermined, and inverse problem in spectral reconstruction. Specifically, Gaussian basis functions fundamentally reduce the solution complexity and uncertainty by performing a low-dimensional parameterization expansion of the spectrum. Next, Tikhonov regularization effectively suppresses measurement noise interference and ensures the uniqueness and stability of the reconstruction results by introducing smoothness constraints. Finally, generalized cross-validation automatically finds the optimal balance parameters for the regularization process to avoid result distortion. The synergistic effect of these three methods ultimately achieves high-fidelity recovery of physically real, smooth, and reliable target spectra from a small number of noisy indirect measurement signals.

[0087] exist Figure 4 In this study, the bandgap tuning range of the target semiconductor was 82 to 118 meV, with data measured at 70 points. In practical implementation, the bandgap tuning range is not limited to 82 to 118 meV, nor is it limited to measuring only 70 points. Under certain conditions, a larger bandgap tuning range allows for a wider wavelength coverage, more measurement points, and higher resolution spectral reconstruction.

[0088] In this application, the photoelectric response layer of the spectrometer is constructed using a high-k dielectric material, which can expand the tunable range of the band gap and reduce the lower limit of the reconfigurable wavelength, thereby obtaining a larger spectral coverage.

[0089] Reference Figure 6 or Figure 7 As shown, the spectral reconstruction experiment of PTFE and EVA materials was carried out at 80K. In actual implementation, other temperatures can also be used. Within a certain range, the lower the temperature, the larger the upper limit of the reconstructable wavelength; the higher the temperature, the stronger the intrinsic photoelectric response of bilayer graphene and the higher the signal-to-noise ratio.

[0090] Reference Figure 6 or Figure 7 As shown, the experimental spectral reconstruction of PTFE and EVA materials spans approximately 10.5–16.7 μm (approximately 600–960 cm⁻¹). -1 The main limitation is the filter and light source used in the experimental setup. Using a longer wavelength filter and a high-power light source can achieve a longer wavelength range coverage at low temperatures.

[0091] The spectral reconstruction apparatus provided in this application is described below. The spectral reconstruction apparatus described below can be referred to in correspondence with the spectral reconstruction method described above.

[0092] Figure 8 This is a structural block diagram of a spectral reconstruction device according to an embodiment of this application. (Refer to...) Figure 8 The spectral reconstruction apparatus 800 of this application may include: The acquisition module 801 is used to acquire the photocurrent signal generated by the spectrometer under the illumination of the target spectrum; The reconstruction module 802 is used to reconstruct the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

[0093] According to the spectral reconstruction apparatus 800 provided in this application, the photoelectric response characteristics of the target semiconductor are determined by the following steps: obtaining the response intensity of the target semiconductor to incident light of different wavelengths at multiple different band gaps, and obtaining multiple curves showing the change of response intensity with wavelength; and determining the photoelectric response characteristics of the target semiconductor based on the multiple curves.

[0094] According to the spectral reconstruction device 800 provided in this application, the acquisition module 801 is further configured to: acquire the background photocurrent signal generated by the spectrometer under background spectral illumination; the reconstruction module is specifically configured to: reconstruct an initial target spectrum based on the photoelectric response characteristics and the photocurrent signal; reconstruct a background spectrum based on the photoelectric response characteristics and the background photocurrent signal; and obtain the target spectrum based on the initial target spectrum and the background spectrum.

[0095] According to the spectral reconstruction apparatus 800 provided in this application, the reconstruction module 802 is specifically used to: obtain an expression for the target spectrum based on the Gaussian basis function, the photocurrent signal, and the photoelectric response characteristics of the target semiconductor; and solve the expression using a Tikhonov regularization algorithm based on generalized cross-validation to obtain the target spectrum.

[0096] Figure 9 This is a schematic diagram of the physical structure of an electronic device according to an embodiment of this application. Figure 9As shown, the electronic device may include a processor 910, a communications interface 920, a memory 930, and a communication bus 940, wherein the processor 910, the communications interface 920, and the memory 930 communicate with each other via the communication bus 940. The processor 910 can call logical instructions in the memory 930 to execute a spectral reconstruction method, which includes: acquiring a photocurrent signal generated by the spectrometer under target spectral illumination; and reconstructing the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

[0097] Furthermore, the logical instructions in the aforementioned memory 930 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0098] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the spectral reconstruction method provided by the above methods. The method includes: acquiring a photocurrent signal generated by a spectrometer under target spectral illumination; and reconstructing the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

[0099] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the spectral reconstruction method provided by the above methods, the method comprising: acquiring a photocurrent signal generated by a spectrometer under illumination of a target spectrum; and reconstructing the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

[0100] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0101] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A spectrometer, characterized in that, The device includes a chip and peripheral circuitry. The chip includes a photoresponse layer, a gate layer, and an electrode lead-out layer. The photoresponse layer contains a target semiconductor. The photoelectric response layer is used to convert the incident spectrum into a photocurrent signal; The gate layer is used to change the photoelectric response characteristics of the target semiconductor by adjusting the band structure of the photoelectric response layer. The gate layer covers the upper and lower surfaces of the photoelectric response layer. The gate layer generates an electrostatic field by applying a voltage thereon. The electrostatic field is used to break the symmetry inside the target semiconductor to change the size of the band gap of the target semiconductor, thereby changing the photoelectric response characteristics of the target semiconductor. The electrode lead-out layer is used to output the photocurrent signal to an external device, and the external device is used to reconstruct the incident spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor. The peripheral circuitry is used to maintain the operation of the chip.

2. The spectrometer according to claim 1, characterized in that, The photoresponse layer also includes a medium for encapsulating the target semiconductor.

3. The spectrometer according to claim 2, characterized in that, The medium is boron nitride.

4. The spectrometer according to claim 1, characterized in that, The electrode lead-out layers are respectively disposed on the left and right sides of the photoresponse layer.

5. The spectrometer according to any one of claims 1-4, characterized in that, The target semiconductor is bilayer graphene.

6. A spectral reconstruction method based on the spectrometer according to any one of claims 1-5, characterized in that, include: Acquire the photocurrent signal generated by the spectrometer under the target spectrum illumination; The target spectrum is reconstructed based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

7. The spectral reconstruction method according to claim 6, characterized in that, The photoelectric response characteristics of the target semiconductor are determined through the following steps: The response intensity of the target semiconductor to incident light of different wavelengths at multiple different band gaps was obtained, resulting in multiple curves showing the change of response intensity with wavelength. The photoelectric response characteristics of the target semiconductor are determined based on multiple curves.

8. The spectral reconstruction method according to claim 6, characterized in that, Before the target spectrum is obtained through reconstruction, the method further includes: Acquire the background photocurrent signal generated by the spectrometer under background spectral illumination; The step of reconstructing the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer includes: Based on the photoelectric response characteristics and the photocurrent signal, the initial target spectrum is reconstructed. Based on the photoelectric response characteristics and the background photocurrent signal, the background spectrum is reconstructed. The target spectrum is obtained based on the initial target spectrum and the background spectrum.

9. A spectral reconstruction device, characterized in that, include: The acquisition module is used to acquire the photocurrent signal generated by the spectrometer under the illumination of the target spectrum; The reconstruction module is used to reconstruct the target spectrum based on the photocurrent signal and the photoelectric response characteristics of the target semiconductor in the photoelectric response layer of the spectrometer.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the spectral reconstruction method as described in any one of claims 6 to 8.

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