A computationally reconstructed spectral detector based on an array of perovskite tunable optical filters

Abstract

The application provides a kind of based on perovskite tunable filter array computing reconstruction type spectral detector, belongs to spectral detector technical field, including perovskite filter array, photosensitive camera and the host computer with spectral computing reconstruction module;The light spectrum to be measured is incident to perovskite filter array and is selectively absorbed, and then directly to photosensitive camera, converts the transmitted light signal into electrical signal, and the output gray image is acquired and processed by the host computer, and the spectral reconstruction is completed by the spectral computing reconstruction module.The application utilizes the specific absorption characteristics of perovskite materials with different components to different wavelengths of light, and uses perovskite filter array to realize the function of spectrometer.Combining the system response matrix and the system response result vector, the spectral reconstruction is realized by the spectral computing reconstruction algorithm.The application can greatly reduce the size of the spectrometer to micron level, and reduce the difficulty and cost of preparation, and can change the perovskite filter array for different detection needs, and improve the compatibility of spectral detector.

Description

Technical Field

[0001] This invention belongs to the field of spectroscopic detector technology, specifically relating to a computationally reconstructable spectroscopic detector based on a perovskite tunable filter array. Background Technology

[0002] Spectrometers are key devices in many fields of materials analysis and environmental analysis, used to detect the intensity distribution of incident light at different wavelengths. Their basic principle is as follows: A spectral dispersive platform converts the incident light from a mixed-wavelength beam into a spectral detection plane where the wavelengths can be spatially distributed. Then, through a photosensitive element and a controllable slit, single-wavelength light components are detected multiple times and converted into electrical signals. Finally, each electrical signal is mapped one-to-one with the original spectral signal, thereby constructing the detected spectral information.

[0003] With the development of spectroscopic detectors, they are gradually shifting towards civilian applications. Therefore, proposing a spectroscopic detector that meets the requirements of civilian use, miniaturization, simplicity, and low cost is of great practical value. Currently, most spectroscopic detectors use the principle of light dispersion for spectral dispersion, but this changes the original optical path direction. Under the condition of using the same photosensitive element, the detection accuracy of this scheme is strongly correlated with the size of the dispersion space; a larger dispersion space usually achieves higher detection accuracy. Therefore, while pursuing high accuracy, it is difficult to miniaturize the size of the spectroscopic detector, with the smallest size typically ranging from centimeters to decimeters. At the same time, this scheme has high requirements for the accuracy of the dispersion element and system calibration. Therefore, there is a need to propose a miniaturized, low-cost, and easily fabricated spectroscopic detector. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention proposes a computational reconstruction spectral detector based on a perovskite tunable filter array. By adjusting the composition of each filter unit in the perovskite filter array, each filter unit has different spectral absorption characteristics, thereby changing the spectral information transmitted through the perovskite filter array and realizing the function of light dispersion. After being collected by a photosensitive camera, the spectrum is reconstructed through a spectral calculation and reconstruction algorithm. This invention reduces the size of the spectral detector while reducing the manufacturing cost and difficulty.

[0005] The specific technical solution of this invention is as follows:

[0006] A computational reconstruction spectral detector based on a perovskite tunable filter array, characterized in that it comprises a perovskite filter array, a photosensitive camera, and a host computer arranged sequentially, wherein the host computer includes a spectral calculation and reconstruction module;

[0007] The spectrum to be measured is incident on a perovskite filter array. After selective absorption by the perovskite filter array, it is directly incident on a photosensitive camera. The photosensitive camera converts the transmitted light signal of the spectrum to be measured into an electrical signal and outputs a grayscale image. The host computer acquires and processes the grayscale image, and performs spectral reconstruction of the spectrum to be measured through a spectral calculation and reconstruction module to obtain the reconstruction result (reconstructed spectrum).

[0008] Furthermore, the perovskite filter array comprises n arrays arranged based on Cs. 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3. Filter units for perovskite material thin films, by designing different ratios of Cs 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3 Perovskite material thin film (tuning the light absorption band gap) to obtain filter units with different light absorption, so that the spectral detection range of the perovskite filter array includes the spectrum range to be measured; where 0≤x, y≤1, and x+y≤1, and n is a positive integer.

[0009] Furthermore, the maximum detection band of the computationally reconstructed spectrophotometer is 398–775 nm, and the absorption band edge energy range is 1.6–3.11 eV.

[0010] Furthermore, the size of the filter unit covers at least 3×3 pixels of the photosensitive camera.

[0011] Furthermore, each filter unit of the perovskite filter array can be adaptively adjusted and replaced according to different spectral detection requirements.

[0012] Furthermore, the photosensitive camera includes a protective glass, a photosensitive element, and a control and power supply circuit; wherein, the protective glass is fixed on the back of the perovskite filter array to protect the photosensitive element; the photosensitive element is used to convert the transmitted light signal of the spectrum to be measured into an electrical signal; the control and power supply circuit is used to control the on / off state of the photosensitive element and data transmission, convert the electrical signal obtained by the photosensitive element into grayscale value, and obtain and output a grayscale image.

[0013] Furthermore, the functions of the host computer include: turning on the photosensitive camera, turning off the photosensitive camera, sending configuration parameter commands to the photosensitive camera, acquiring the grayscale image output by the photosensitive camera, calculating the average grayscale value of the region corresponding to each filter unit in the grayscale image, constructing a system response result vector based on the average grayscale value of each region, constructing a system response matrix, and using the spectral calculation and reconstruction module to perform spectral reconstruction of the spectrum to be measured.

[0014] Furthermore, the system response matrix is ​​constructed as follows: based on the absorbance of each filter unit in the perovskite filter array, the absorbance matrix of the perovskite filter array is constructed and converted into the corresponding transmittance matrix. Then, the quantum efficiency is obtained according to the datasheet of the photosensitive camera. The transmittance matrix is ​​multiplied by the quantum efficiency to obtain the system response matrix. Here, the transmittance matrix represents the proportion of the transmitted light signal that can be transmitted after the spectrum to be measured passes through different filter units to the original spectrum to be measured. The quantum efficiency of the photosensitive camera represents the proportion of the transmitted light signal received by the photosensitive element that can be converted into an electrical signal. Multiplying the two can represent the proportion of the spectrum to be measured that can be converted into an electrical signal in the photosensitive unit region under the corresponding different filter units.

[0015] Furthermore, the transmittance matrix is ​​a two-dimensional matrix, where one dimension represents the number of each filter unit in the perovskite filter array, and the other dimension represents the transmittance of the corresponding filter unit for different wavelengths of light.

[0016] Furthermore, the spectral calculation and reconstruction module reconstructs the spectrum of the target spectrum using the least squares method based on non-negative Tikhonov regularization constraints, based on the system response matrix and the system response result vector.

[0017] The beneficial effects of this invention are as follows:

[0018] This invention proposes a computational reconstruction-type spectrometer based on a perovskite tunable filter array. By adjusting the composition of each filter unit in the perovskite filter array, each filter unit has different spectral absorption characteristics, thereby changing the spectral information transmitted through the perovskite filter array and achieving the function of light dispersion. After being acquired by a photosensitive camera, the light signal to be measured is converted into an electrical signal. Combining the system response matrix and the system response result vector, the spectrum is reconstructed through a spectral computational reconstruction algorithm. Compared with traditional spectrometers based on dispersive elements, this invention can significantly reduce the dispersion space size to the micrometer level. Secondly, due to the use of low-cost and easily fabricated perovskite material thin films, the cost of spectral detection data can be significantly reduced. Thirdly, due to the replaceable design, the perovskite filter array can be changed for different detection needs without changing the photosensitive camera, thereby improving the compatibility of the spectrometer. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the workflow of the computational reconstructive spectroscopic detector based on a perovskite tunable filter array proposed in Embodiment 1 of the present invention.

[0020] Figure 2 This is a schematic diagram of the spectral dispersive principle of the computational reconstructive spectrometer based on a perovskite tunable filter array proposed in Embodiment 1 of the present invention.

[0021] Figure 3 The light absorption characteristics of perovskite filters 1-8, calibrated by ultraviolet-visible-near-infrared absorption spectroscopy, as proposed in Example 1 of this invention;

[0022] Figure 4 The light absorption characteristics of perovskite filters 9-16 as calibrated by ultraviolet-visible-near-infrared absorption spectroscopy as proposed in Example 1 of this invention;

[0023] Figure 5 The light absorption characteristics of perovskite filters 17-24 calibrated by ultraviolet-visible-near-infrared absorption spectroscopy as proposed in Example 1 of this invention;

[0024] Figure 6 The light absorption characteristics of perovskite filters No. 25-32, calibrated by ultraviolet-visible-near-infrared absorption spectroscopy, as proposed in Example 1 of this invention;

[0025] Figure 7 The light absorption characteristics of perovskite filters No. 33-40, calibrated by ultraviolet-visible-near-infrared absorption spectroscopy, as proposed in Example 1 of this invention;

[0026] Figure 8 The light absorption characteristics of perovskite filters 41-48 calibrated by ultraviolet-visible-near-infrared absorption spectroscopy as proposed in Example 1 of this invention;

[0027] Figure 9 The light absorption characteristics of perovskite filters 49-56 calibrated by ultraviolet-visible-near-infrared absorption spectroscopy as proposed in Example 1 of this invention;

[0028] Figure 10 The light absorption characteristics of perovskite filters No. 57-60, calibrated by ultraviolet-visible-near-infrared absorption spectroscopy, as proposed in Example 1 of this invention;

[0029] Figure 11 This is the spectrum reconstruction result of a xenon lamp with a center wavelength of 500 nm and a width of 27 nm in Example 1 of the present invention;

[0030] Figure 12 This is a schematic diagram of the three-dimensional structure of the perovskite filter array and the photosensitive camera mentioned in Embodiment 1 of the present invention. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in conjunction with the following specific embodiments and with reference to the accompanying drawings.

[0032] The following non-limiting embodiments are intended to enable those skilled in the art to more fully understand the present invention, but do not limit the invention in any way.

[0033] Example 1

[0034] This embodiment provides a computationally reconstructed spectral detector based on a perovskite tunable filter array, and the workflow is as follows: Figure 1 As shown, a perovskite filter array, a photosensitive camera, and a host computer are arranged in sequence, and the host computer includes a spectral calculation and reconstruction module.

[0035] The perovskite filter array comprises n=60 arrays arranged based on Cs. 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3. A filter unit for a perovskite material thin film, wherein 0 ≤ x, y ≤ 1, and x + y ≤ 1; the Cs 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y The preparation method of perovskite thin films is as follows: N,N-dimethylformamide (DMF) and dimethyl sulfoxide (DMSO) solvents are prepared in a 1:1 volume ratio to obtain a precursor solvent, which is divided into three parts for later use; CsI, MAI, and PbI2 powders are taken in a 1:9:10 molar ratio, stirred for 3 hours to dissolve in the precursor solution, and filtered to obtain CsI. 0.1 MA 0.9 PbI3 solution; CsBr, MABr, and PbBr2 powders were taken in a molar ratio of 1:9:10, stirred for 3 hours to dissolve in the precursor solution, and then filtered to obtain CsBr2. 0.1 MA 0.9 PbBr3 solution; CsCl, MACl, and PbCl2 powders were taken in a molar ratio of 1:9:10, stirred for 3 hours to dissolve in the precursor solution, and then filtered to obtain CsCl2 solution. 0.1 MA 0.9 PbCl3 solution; Cs were taken in the ratio of x:y:(1-xy) 0.1 MA 0.9 PbCl3 solution, Cs 0.1 MA 0.9 PbBr3 solution and Cs 0.1 MA 0.9Sixty spin-coating solutions with different ratios were prepared using PbI3 solution, with x and y values ​​set as shown in Table 1. Each of the 60 spin-coating solutions was shaken and mixed thoroughly. Using a solvent-free solution method in a glove box, the spin-coating solutions were applied to flexible polyethylene naphthalate (PEN) substrates. The spin-coating speed was set to 3000 rpm, and the spin-coating time to 30 s. At the 10th second, nitrogen gas was used to directly blow away excess solvent to accelerate evaporation. After spin-coating, the films were annealed and crystallized on a 100℃ heating stage for 20 min, ultimately yielding 60 perovskite material films with different ratios.

[0036] Table 1. Values ​​of x and y for 60 perovskite thin films with different formulations

[0037]

[0038]

[0039] For Cs 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3. For perovskite thin films, the larger the value of x, the stronger the absorption band-edge energy and the shorter the wavelength; conversely, the larger the value of 1-xy, the weaker the absorption band-edge energy and the longer the wavelength. Wherein, Cs 0.1 MA 0.9 The absorption band-edge energy of PbCl3 is approximately 3.11 eV, which corresponds to a wavelength of about 398 nm; Cs 0.1 MA 0.9 The absorption band-edge energy of PbBr3 is approximately 2.27 eV, which corresponds to a wavelength of about 546 nm; Cs 0.1 MA 0.9 The absorption band-edge energy of PbI3 is approximately 1.6 eV, corresponding to a wavelength of around 775 nm. By designing Cs with different ratios... 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3 Perovskite material thin film, to obtain filter units with different light absorption, so that the spectral detection range of the perovskite filter array includes the spectrum range to be measured.

[0040] The absorbance of 60 prepared perovskite thin films was determined by UV-Vis-NIR absorption spectroscopy. The absorbance distribution of each perovskite thin film is shown in the figure below. Figures 3-10As shown, the absorbance of each perovskite film was converted into transmittance in numerical order, and the absorbance and transmittance matrices of the perovskite filter array were constructed. A 1×1.5mm section was cut from each perovskite film using a physical cutting method. 2 Small thin-film filters of a certain size are used as filter units.

[0041] The photosensitive camera includes a protective glass, a photosensitive element, and a control and power supply circuit. Each filter unit is fixed to the protective glass in numerical order, forming a perovskite filter array. The protective glass protects the photosensitive element. The spectrum to be measured is incident on the perovskite filter array, selectively absorbed, and then directly incident on the photosensitive camera. The photosensitive element converts the transmitted light signal of the spectrum into an electrical signal. The control and power supply circuit controls the on / off state of the photosensitive element and data transmission, converts the electrical signal obtained by the photosensitive element into grayscale values, and obtains and outputs a grayscale image.

[0042] The functions of the host computer include: turning on the photosensitive camera, turning off the photosensitive camera, sending configuration parameter commands to the photosensitive camera, acquiring the grayscale image output by the photosensitive camera, calculating the average grayscale value of the region corresponding to each filter unit in the grayscale image, constructing a system response result vector based on the average grayscale value of each region, constructing a system response matrix, and using the spectral calculation and reconstruction module to perform spectral reconstruction of the spectrum to be measured.

[0043] The spectral splitting principle of this embodiment is as follows: Figure 2 As shown, a xenon lamp source with a center wavelength of 500 nm and a width of 27 nm is used as the spectrum to be measured. The spectrum is incident perpendicularly onto the obtained perovskite filter array. After selective absorption by the perovskite filter array, it is incident perpendicularly onto the photosensitive camera. The absorbance matrix of the perovskite filter array is converted into the corresponding transmittance matrix T.

[0044]

[0045] Among them, T i (λ j ), 1≤i≤n, 1≤j≤m are the wavelengths of the i-th filter unit. j The transmittance of light; m is the calibration accuracy of the transmittance matrix, which affects the spectral resolution of the spectral detection.

[0046] The host computer sends configuration commands to the photosensitive camera, setting its parameters. Then, it sends start or stop commands to cause the camera to acquire a grayscale image of the light response and store it in its data buffer. The host computer also sends data acquisition commands to the camera, which then transmits the data from its buffer to the host computer. The quantum efficiency Q is obtained according to the camera's datasheet.

[0047]

[0048] Since the quantum efficiency of any pixel in a photosensitive camera is the same, the system response R of the region corresponding to the i-th filter unit is... i It can be represented as:

[0049] R i =T i ·Q=[Q(λ1)T i (λ1) … Q(λ m )T i (λ m )]

[0050] Among them, T i This represents the i-th row vector of the transmittance matrix T;

[0051] R i According to T i By concatenating the components in the same order, we can obtain the system response matrix R:

[0052]

[0053] Where, Q(λ) j ), 1≤j≤m represents the wavelength of the photosensitive camera. j The quantum efficiency of light; R i (λ j ), 1≤i≤n, 1≤j≤m are the wavelengths of the i-th filter unit. j The intensity of light that can be converted into electrical signals;

[0054] After receiving the data, the host computer first segments the grayscale image according to the distribution of each filter unit in the perovskite filter array. Specifically, grayscale image preprocessing is performed using grayscale image binarization and threshold segmentation combined with binarization to distinguish regions with and without filter units. Then, a connected component algorithm is used for block segmentation, ensuring a one-to-one correspondence between corresponding blocks in the grayscale image and their calibrated absorbance values. Next, an erosion algorithm is used to filter out potentially damaged pixels around the filter units to avoid errors caused by these pixels. Finally, grayscale value filtering and averaging are performed within each filter unit's block to obtain the system response output for each filter unit, collectively forming the system response result vector I = [I1 … I n ] T , where I i , 1≤i≤n represents the grayscale response result of the block corresponding to the i-th filter unit;

[0055] The spectral calculation and reconstruction module reconstructs the spectrum of the target spectrum using the least squares method based on non-negative Tikhonov regularization constraints, based on the system response matrix R and the system response result vector I. The system response matrix R and the system response result vector I have the following relationship:

[0056] R·X=I

[0057]

[0058] Where X represents the spectral information to be measured; x(λ) j ), 1≤j≤m is the wavelength of λ j The intensity of light.

[0059] The reconstruction result (reduced spectrum) of this embodiment is as follows: Figure 11 As shown, the center wavelength of the reconstructed result is 503 nm and the width is 26 nm, which is basically consistent with the actual information of the spectrum to be measured.

[0060] In this embodiment, the photosensitive camera used is an MV-CA050-20UM industrial camera, and the three-dimensional structure after being combined with the perovskite filter array is as follows. Figure 12 As shown; the photosensitive element is an OnSemi PYTHON5000 sensor, with a resolution of 2592×2048 and a pixel size of 4.8μm×4.8μm; the square array is a perovskite filter array. The host computer is directly connected to the photosensitive camera via USB to send commands such as "callback" and "capture a frame". After the host computer sends the "callback" command, the photosensitive camera establishes communication with the host computer, confirming a normal connection; after the host computer sends the "capture a frame" command, it first controls the photosensitive camera to start detection, and after collecting one frame in the data buffer, it stops detection and sends the data stored in the buffer back to the host computer.

[0061] The above description is merely a specific embodiment of the present invention. Any feature disclosed in this specification may be replaced by other equivalent or similar features unless otherwise specified. All disclosed features, or steps in all methods or processes, may be combined in any way except for mutually exclusive features and / or steps.

Claims

1. A computationally reconstructable spectral detector based on a perovskite tunable filter array, characterized in that, The system comprises a perovskite filter array, a photosensitive camera, and a host computer arranged sequentially. The host computer includes a spectral calculation and reconstruction module. The perovskite filter array comprises n arrays arranged based on Cs. 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3. Filter units for perovskite material thin films, by designing different ratios of Cs 0.1 MA 0.9 Pb(Cl x Br y I 1-x-y )3. Perovskite material thin film, to obtain filter units with different light absorption, so that the spectral detection range of the perovskite filter array includes the spectrum range to be measured; where 0≤x,y≤1, and x+y≤1, and n is a positive integer; The spectrum to be measured is incident on a perovskite filter array. After selective absorption by the perovskite filter array, it is directly incident on a photosensitive camera. The photosensitive camera converts the transmitted light signal of the spectrum to be measured into an electrical signal and outputs a grayscale image. The host computer acquires and processes the grayscale image, and performs spectral reconstruction of the spectrum to be measured through a spectral calculation and reconstruction module to obtain the reconstruction result.

2. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 1, characterized in that, The maximum detection band of the computationally reconstructed spectrophotometer is 398~775 nm, and the absorption band edge energy range is 1.6~3.11 eV.

3. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 1, characterized in that, The size of the filter unit covers at least 3×3 pixels of the camera.

4. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 1, characterized in that, The photosensitive camera includes a protective glass, a photosensitive element, and a control and power supply circuit. The protective glass is fixed to the back of the perovskite filter array to protect the photosensitive element. The photosensitive element is used to convert the transmitted light signal of the spectrum to be measured into an electrical signal. The control and power supply circuit is used to control the on / off state of the photosensitive element and the data transmission, convert the electrical signal obtained by the photosensitive element into grayscale value, and obtain and output a grayscale image.

5. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 1, characterized in that, The functions of the host computer include: turning on the photosensitive camera, turning off the photosensitive camera, sending configuration parameter commands to the photosensitive camera, acquiring the grayscale image output by the photosensitive camera, calculating the average grayscale value of the region corresponding to each filter unit in the grayscale image, constructing a system response result vector based on the average grayscale value of each region, constructing a system response matrix, and using the spectral calculation and reconstruction module to perform spectral reconstruction of the spectrum to be measured.

6. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 5, characterized in that, The process of constructing the system response matrix is ​​as follows: based on the absorbance of each filter unit in the perovskite filter array, construct the absorbance matrix of the perovskite filter array, convert it into the corresponding transmittance matrix, then obtain the quantum efficiency according to the datasheet of the photosensitive camera, and multiply the transmittance matrix with the quantum efficiency to obtain the system response matrix.

7. The computationally reconstructable spectroscopic detector based on a perovskite tunable filter array according to claim 1, characterized in that, The spectral calculation and reconstruction module reconstructs the spectrum of the target spectrum using the least squares method based on the system response matrix and the system response result vector, and employs a non-negative Tikhonov regularization constraint.

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