Micro LED micro display module color conversion method and system based on quantum dots

Abstract

The invention relates to the technical field of micro display modules, and discloses a micro LED micro display module color conversion method and system based on quantum dots. Comprising the following steps: performing multi-temperature multi-power spectrum acquisition on a red quantum dot material and a green quantum dot material in a Micro LED micro display module to generate a quantum dot color conversion parameter mapping table; an ink-jet printing device is controlled to deposit a quantum dot material on the Micro LED blue light backboard, and a quantum dot color conversion layer structure is formed; monitoring the spectrum expression in a temperature change environment, and generating a temperature compensation control instruction; according to the method, the blue light LED driving current, the quantum dot layer temperature and the packaging pressure parameters of the Micro LED micro-display module are adjusted in real time, the color stability of the Micro LED micro-display module is kept, the color point drift of the quantum dot Micro LED micro-display module in a wide temperature range is effectively controlled, and the high color gamut coverage rate and the color accuracy can be kept under different brightness conditions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of micro display modules, and particularly relates to a Micro LED micro display module color conversion method and system based on quantum dots. BACKGROUND

[0002] With the rapid development of display technology, Micro LED micro display technology has become a research focus in the high-end display field due to its high brightness, high contrast ratio and ultra-long service life. As an important implementation path for Micro LED full-color display, quantum dot-based color conversion technology uses the excellent narrow-band light-emitting characteristics and high quantum efficiency of quantum dot materials to significantly expand the display color gamut and simplify the manufacturing process. However, in the actual preparation process, the response of quantum dot materials to blue light excitation shows a high degree of nonlinearity, and quantum dot materials of different concentrations, different particle sizes and different encapsulation processes show complex spectral variation rules at different temperatures and excitation intensities, which makes it difficult for traditional spectral characterization methods to accurately predict the color performance in actual displays, resulting in problems such as color point drift and regional color non-uniformity.

[0003] The prior art has obvious limitations in processing quantum dot color conversion. Traditional methods usually only optimize the quantum dot response under a single blue light injection power condition, ignoring the comprehensive influence of the dynamic changes of blue light LED brightness on the red and green quantum dot light-emitting efficiency ratio in the actual display process. Especially under high brightness display conditions, quantum dot materials are prone to saturation effect and light quenching phenomenon, resulting in a decrease in color reproduction accuracy. In addition, quantum dot materials are sensitive to temperature changes and will produce spectral drift at different working temperatures, and the prior art lacks an effective temperature adaptability adjustment mechanism, making it difficult to ensure color consistency under different environmental conditions. SUMMARY

[0004] The present application provides a Micro LED micro display module color conversion method and system based on quantum dots, which effectively controls the color point drift of quantum dot Micro LED micro display modules within a wide temperature range and maintains high color gamut coverage and color accuracy under different brightness conditions.

[0005] In a first aspect, the present application provides a Micro LED micro display module color conversion method based on quantum dots, which includes: Performing multi-temperature and multi-power spectrum acquisition on red quantum dot materials and green quantum dot materials in a Micro LED micro display module under 460nm blue light excitation to generate a quantum dot color conversion parameter mapping table; The quantum dot color conversion parameter mapping table is used to control an inkjet printing device to deposit quantum dot material on a Micro LED blue light backboard to form a quantum dot color conversion layer structure. The spectral performance of the quantum dot color conversion layer structure under a temperature change environment is monitored to generate a temperature compensation control instruction. The temperature compensation control instruction is used to adjust the blue light LED drive current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module in real time, and the display image output by the Micro LED micro display module is subjected to color mapping processing to maintain the color stability of the Micro LED micro display module.

[0006] In a second aspect, the present application provides a quantum dot-based Micro LED micro display module color conversion system, which comprises: A collection module is configured to collect the multi-temperature and multi-power spectra of red quantum dot material and green quantum dot material in a Micro LED micro display module under 460nm blue light excitation to generate a quantum dot color conversion parameter mapping table. A deposition module is configured to control an inkjet printing device to deposit quantum dot material on a Micro LED blue light backboard according to the quantum dot color conversion parameter mapping table to form a quantum dot color conversion layer structure. A monitoring module is configured to monitor the spectral performance of the quantum dot color conversion layer structure under a temperature change environment to generate a temperature compensation control instruction. An adjustment module is configured to use the temperature compensation control instruction to adjust the blue light LED drive current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module in real time, and to perform color mapping processing on the display image output by the Micro LED micro display module to maintain the color stability of the Micro LED micro display module.

[0007] The technical scheme provided by the application performs spectrum collection and characteristic matrix construction on red and green quantum dot materials under multiple temperature and multiple power conditions, so that the system can comprehensively master the nonlinear response characteristics of quantum dots in the actual working environment, and accurately predict the color conversion efficiency and color purity of the quantum dots. Based on the response data of the quantum dot material, the color conversion nonlinear characteristics under different excitation intensities are detected, and a color conversion parameter mapping table containing a temperature correction factor is generated, effectively overcoming the defects of traditional methods in considering the saturation effect of quantum dots under high brightness display conditions. Through systematic deposition parameter optimization and edge compensation printing strategy, uniform deposition of the quantum dot color conversion layer is realized, and the edge spectrum shift problem caused by uneven thickness of the quantum dot layer in traditional technology is solved, so that the color difference between the edge and center areas of the display area is controlled within a smaller range. Through the spectrum correction algorithm of wavelet transform and the adaptive gain compensation mechanism, the peak position and half peak width changes caused by temperature changes are corrected in real time, so that the color point drift of the quantum dot Micro LED micro display module in a wide temperature range is effectively controlled. Using the multi-layer perception target dynamic programming model to adjust the blue light LED drive current, quantum dot layer temperature and packaging pressure parameters in real time, the saturation effect and light quenching phenomenon under high display brightness are effectively suppressed, and the color reproduction ability under high brightness display conditions is significantly improved. Through the chrominance data feedback of the built-in light sensor to perform automatic aging compensation, the color shift caused by aging after quantum dot packaging is corrected in real time, ensuring that the Micro LED micro display module can still maintain stable color output after long-term aging test, prolonging the service life of the equipment. By constructing a lookup table of the RGB color space in the partition and introducing a quantum dot excitation intensity compensation factor, accurate color mapping covering low, medium and high brightness intervals is realized, so that the display system can maintain high color gamut coverage and color accuracy under different brightness conditions. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor based on these drawings.

[0009] Figure 1 The flowchart of the quantum dot-based Micro LED micro display module color conversion method provided by the embodiment of the application is shown. Figure 2 The structural schematic block diagram of the quantum dot-based Micro LED micro display module color conversion system provided by the embodiment of the application is shown. DETAILED DESCRIPTION

[0010] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0011] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may change based on actual circumstances.

[0012] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0013] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0014] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0015] See also Figure 1 , Figure 1 A schematic diagram of the process of color conversion of a Micro LED micro display module based on quantum dots provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the quantum dot-based Micro LED micro-display module color conversion method provided in the embodiment of the present application includes steps S100 to S600.

[0016] Step S100: Under 460nm blue light excitation, multi-temperature and multi-power spectrum acquisition is performed on the red quantum dot material and the green quantum dot material in the Micro LED micro display module to generate a quantum dot color conversion parameter mapping table; It is understood that the execution subject of the present invention can be a quantum dot-based Micro LED micro-display module color conversion system, or a terminal or server, which is not limited here. The embodiment of the present invention is described by taking the server as the execution subject as an example.

[0017] Specifically, based on the physical and optical properties of quantum dot materials, the red and green quantum dot materials used in the micro display module are classified, and a high-resolution screening mechanism is established for raw material batch differences, particle size distribution, surface ligand parameters, and other parameters. Combined with the emission peak, half-height width, quantum efficiency and other spectral parameters, a plurality of classified quantum dot samples are obtained. Each set of classified quantum dot samples is placed in a high-precision temperature control system, and a temperature gradient environment is established by gradually covering the working temperature range through a step-by-step temperature adjustment program. Under the above temperature control conditions, a high-stability 460nm blue light excitation source is used to apply different excitation powers to the classified quantum dot materials at each temperature node. The multi-power gradient excitation can comprehensively reveal the color conversion response limit of quantum dot materials in the actual working range, and reflect the influence of excitation intensity on the emission efficiency, peak shift and color purity change, and obtain representative quantum dot excitation states. Through a high-sensitivity, wide dynamic range spectrophotometer or a high-precision spectral analyzer, the emission spectrum of each sample under each set of temperature and power parameter combinations is collected, and the original spectral data matrix covering the full temperature and power range is obtained. To ensure the authenticity and scientificity of the data, during the spectral data acquisition process, the excitation light intensity, environmental stray light background and system response curve parameters are simultaneously collected, and the original data are preprocessed by denoising, background subtraction and response correction. The original spectral data of the quantum dots are analyzed by multi-parameter spectral analysis, and the key response data of the quantum dots, such as luminous intensity, main emission peak wavelength, half-width, emission integral intensity, and color coordinate change, are obtained. Combined with principal component analysis, nonlinear fitting or multivariate regression data processing methods, the changes in the luminescence mechanism of quantum dots at different temperatures and different excitation intensities are analyzed. Especially focusing on the nonlinear response phenomena of quantum dot materials under high excitation power, such as saturation effect, luminescence quenching, thermal-induced peak shift and color purity decrease, and using these analysis results, a multi-dimensional mathematical model describing the luminescence behavior of quantum dots is established. The quantitative mapping relationship between all quantum dot materials in temperature, power, excitation intensity and spectral response is sorted out, and a quantum dot color conversion parameter mapping table is formed.

[0018] In this embodiment, the light intensity and wavelength distribution of all collected red and green quantum dot materials under different excitation power conditions are systematically calculated and analyzed, the main emission peak, half-height width and total light intensity at each power point are extracted, and the quantitative relationship curve between excitation intensity and luminous efficiency is drawn based on this, and the quantum dot excitation intensity-luminous efficiency curve is obtained. Based on the temperature-intensity influence factor table, the above test is repeated for each group of quantum dot samples in the full temperature range. By comparing the changes in light intensity under different temperature conditions at the same excitation power, the inhibitory or enhancing effect of temperature on quantum dot luminous efficiency is measured and recorded in the form of relative change rate, and the temperature-intensity influence factor table is generated, which reflects the thermal sensitivity of quantum dot light emission. Select the test environment that meets the standard to test the actual color display of the above quantum dot materials. The specific method is to accurately position and drift analyze the color points of each group of samples under different excitation powers and different temperatures by standard CIE1931 color coordinate system, and combined with spectral analysis, the data set reflecting the color coordinate drift of quantum dot materials under actual driving conditions is obtained, and the saturation effect and light quenching phenomenon of quantum dots under high power excitation conditions are revealed. For example, when the excitation intensity is extremely high, the luminous efficiency tends to be flat or even decreases, and the emission peak position appears blue shift or red shift, the color purity decreases, and the overall performance of the color reproduction ability decreases. Through comparative analysis, a compensation parameter model in the high excitation interval is established, and a high brightness compensation parameter set is obtained, which includes specific adjustment factors for correcting color coordinate drift, peak position shift and efficiency loss. Combine the high brightness compensation parameter set with the color conversion efficiency data obtained at each excitation intensity point to form a multi-dimensional, multi-working condition cross-mapping quantum dot color conversion parameter mapping table.

[0019] Step S200, according to the quantum dot color conversion parameter mapping table, control the inkjet printing equipment to deposit quantum dot material on the Micro LED blue backlight panel to form a quantum dot color conversion layer structure; Specifically, based on the description of the color conversion efficiency and spectral characteristics of red and green quantum dot materials under different excitation intensities, temperatures and structure thicknesses in the color conversion parameter mapping table, red and green quantum dot inks are prepared. In the ink preparation process, the dispersion of quantum dots, the polarity of the solvent, the viscosity, and the compatibility of the surface ligand are considered to ensure that the quantum dot materials remain highly dispersed and stable in the ink. According to the requirements of the mapping table for the best color conversion effect, combined with the micro-display pixel structure, color gamut coverage and target luminous efficiency, the key process parameters of inkjet printing are reasonably set, including the temperature of the nozzle, the piezoelectric driving voltage, the ink droplet spacing, the number of printing layers, etc. These parameter combinations aim to achieve the optimal material deposition thickness, uniformity and spatial resolution. After completing the preset of quantum dot ink and parameter combination, relying on a high-precision inkjet printing platform, quantum dot inkjet deposition experiments are carried out on the specified area of the Micro LED blue backlight panel. During the experiment, the nozzle temperature is precisely adjusted to ensure the rheological properties of the ink and the quality of the droplet formation, and an appropriate piezoelectric driving voltage is used to control the droplet volume and speed, so that multiple groups of quantum dot deposition test samples are prepared under the cooperation of different ink droplet spacings and printing layer numbers. To avoid the degradation of quantum dots by water and oxygen in the air, all deposited samples need to be heat treated in a nitrogen-protected environment after transfer. The heat treatment process can promote the ordered arrangement and dense bonding between the quantum dots and the substrate, while removing solvent residues and surface impurities, obtaining a quantum dot color conversion test layer with a dense structure, a smooth surface, and stable physical and chemical properties. The color conversion performance of all heat-treated test layers is measured under 460 nm blue light excitation, including the luminous intensity, spectral distribution, peak position, color coordinate consistency of the quantum dot layer, and its uniformity at different spatial positions. By comparing and analyzing with the target performance parameters in the mapping table, the optimal deposition parameters that can ensure high color gamut coverage and high conversion efficiency, while considering the thermal stability and optical uniformity, are selected. The selected optimal deposition parameters are applied to the actual large-area printing process of the Micro LED blue backlight panel to precisely deposit quantum dot materials on a large scale, and finally form a quantum dot color conversion layer structure with a dense structure, uniform layer thickness and controllable spectral characteristics.

[0020] Step S300, monitor the spectral performance of the quantum dot color conversion layer structure under temperature change environment, and generate temperature compensation control instructions; Specifically, the prepared and optimized quantum dot color conversion layer structure is loaded on the Micro LED micro display module, and during the experiment or production stage, a high-precision temperature control module is integrated to orderly adjust the working environment temperature of the module by gradient, so that the module experiences a complete test sequence from low temperature to high temperature or even extreme temperature. In this process, a miniature high-sensitivity spectral acquisition device is synchronously carried, and for each temperature node, the emission spectrum data of the quantum dot color conversion layer under the excitation of the Micro LED is collected in real time. Through the cyclic test of continuous temperature conditions, the peak intensity, main emission wavelength and spectral distribution of the quantum dot light emission are obtained, and the drift of the quantum dot material light emission peak position at different temperatures is captured, that is, the quantum dot peak temperature drift data is recorded. Based on the collected large amount of real-time spectrum and temperature data, the influence law of temperature rise or fall on the quantum dot emission wavelength is analyzed by establishing a quantitative temperature-peak drift mapping relationship. With the increase of temperature, the quantum dot emission peak position will appear different degrees of red shift or blue shift, the peak intensity will weaken or the distribution width will increase, resulting in obvious drift of color purity and color coordinates. Through fitting and regression analysis, a mathematical model describing the change trend of the main emission peak of the quantum dot at different temperatures is obtained, which serves as the basic data structure for temperature compensation. In order to improve the correction accuracy, the real-time spectrum data is decomposed by wavelet transform, and the original signal is decomposed into multi-scale and multi-component frequency domain features, so as to extract the temperature-related spectral change details. On this basis, combined with the temperature-peak drift mapping relationship, a set of temperature adaptive spectral correction parameters are generated by calculating the change amplitude and direction of each component at different temperatures. These parameters include the main emission peak correction factor, and also include multi-dimensional correction quantities such as brightness attenuation compensation and color coordinate offset correction. The temperature adaptive spectral correction parameters are fused with the real-time monitored environment temperature data, and the adaptive gain compensation mechanism is used to dynamically adjust the driving current of the Micro LED blue light excitation source, the output of the quantum dot layer temperature control device, and even the packaging pressure and other hardware parameters, so as to realize the rapid compensation of the quantum dot material light emission state, and make the output spectrum stable within the target color interval. Through the linkage mechanism of real-time monitoring, feature extraction and adaptive compensation, temperature compensation control instructions are generated and fed back to the driving and control system of the micro display module.

[0021] Step S400, real-time adjusting the blue light LED driving current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module by using the temperature compensation control instructions, and performing color mapping processing on the display image output by the Micro LED micro display module, to maintain the color stability of the Micro LED micro display module.

[0022] Specifically, based on the temperature compensation control instruction, a multi-layer perception target dynamic programming model for quantum dot photoluminescence characteristics is established. The dynamic programming model is composed of a state perception network, an action generation network, and a reward evaluation network, forming an intelligent closed-loop regulation system for full-process adaptive regulation. In each display cycle, the current input display content brightness distribution map and the actual quantum dot light intensity distribution map are sent into the state perception network as multi-dimensional input information for feature extraction and fusion. The state perception network uses deep convolution and attention mechanism to quantitatively model the global and local optical response, color distribution, and spatial non-uniformity, and outputs a state feature vector that can fully represent the current display state and environmental conditions. The state feature vector is input into the action generation network for processing. The action generation network uses a dual-channel deep neural network architecture to continuously optimize and search the hardware adjustable parameter space, including blue LED driving current, quantum dot layer temperature, and packaging pressure. Based on the historical response of spectrum, temperature, and color gamut drift, the optimal adjustment trend is predicted. The network output is a set of initial action space parameters, which are used to drive the physical execution unit of the Micro LED module for real-time adjustment. The feedback data such as adjusted spectrum, brightness, and color uniformity are collected in real time to form parameter adjustment evaluation results. The parameter adjustment evaluation results are input into the reward evaluation network. Based on the reinforcement learning strategy, the reward evaluation network evaluates the actual effect of each parameter adjustment in real time according to the multi-dimensional indicators such as color accuracy, color gamut coverage, visual consistency, and energy efficiency before and after adjustment, and dynamically updates the reward function weight to ensure that the model can continuously tend to be optimal. Through multiple rounds of optimization and feedback reinforcement of the above closed-loop network, the dynamic programming model efficiently outputs the optimal parameter regulation strategy, realizing dynamic optimization of parameter combination. According to the optimal parameter regulation strategy obtained, the blue LED driving current is precisely adjusted based on the current brightness and color distribution characteristics of the input image, to compensate for the brightness fluctuation caused by the change of quantum dot light efficiency with temperature. The quantum dot layer temperature control equipment is intelligently set to offset the thermal peak position drift and color gamut shift, and the packaging pressure is adjusted to maintain the stability and light consistency of the quantum dot layer physical structure. The real-time adaptive adjustment of all hardware parameters is interrelated with the brightness and color content of the input image, ensuring that the output color remains stable and accurate even in extreme display scenarios such as high brightness and high color saturation. At the same time, through the dynamic optimized control parameter combination, combined with the real-time color mapping processing module, each frame of display image output by the Micro LED module is corrected in real time for color coordinates, automatically compensating for the slight color deviation caused by environmental temperature change or material aging, so that the display color gamut remains stable within the preset standard range.

[0023] In this embodiment, under standard observation conditions, high-precision chroma measurement is performed on the display image output by the Micro LED micro display module. The actual chroma value of each frame of image is continuously monitored by a dedicated colorimeter or an embedded high-sensitivity spectral sensor, and the actual display chroma value collected is compared with the theoretical design chroma value pixel by pixel, and the chroma value deviation data of each display point is calculated. Taking these chroma value deviations as the core input, combined with the color gamut response characteristics of quantum dot materials, a basic color correction model is constructed. This model includes the nonlinear relationship between the chroma value deviation and the target chroma, and can realize multi-dimensional color error mapping for different color intervals, different pixel positions and different environmental brightness conditions. After establishing the basic color correction model, the mechanism of dynamic optimization control parameters is introduced, and the quantum dot excitation intensity compensation factor is embedded into the correction model according to the change rule of quantum dot excitation intensity in different brightness intervals of the Micro LED micro display module. In this way, the influence of hardware adjustment parameters such as blue LED driving current, quantum dot layer temperature and packaging pressure in actual operation is considered comprehensively, and the adaptive dynamic update of the color mapping model is realized. Through this step, the system can effectively compensate for the quantum dot color deviation caused by the change of excitation intensity in high-brightness display, strong backlight environment or scenes with significant light-dark contrast, so that the color mapping model can cover a wider range of working conditions, significantly improving the accuracy and consistency of color gamut restoration. At the same time, a standard white test image is configured inside the Micro LED micro display module, and the display chroma value of the standard white image is collected by the built-in light sensor regularly, and the test display chroma value is compared with the initial display chroma value obtained at the time of factory shipment or first calibration in real time, and the chroma difference between the two is calculated. This chroma difference is the key input of the real-time correction instruction of the model, which is automatically fed back to the color mapping processing system for correcting and updating the current comprehensive color mapping model parameters. Through the periodic and automatic chroma monitoring and correction instruction generation mechanism, the system can adaptively adjust the color compensation parameters in different running stages, different environmental temperatures and different aging degrees, and can effectively cope with the color shift phenomenon of quantum dot materials caused by factors such as aging, thermal drift or external stress changes in the long-term working process. With the continuous input of the real-time correction instruction of the model, the comprehensive color mapping model can continuously optimize its internal parameters, realize automatic compensation for quantum dot packaging aging, material attenuation and environmental influence, and guarantee the color restoration ability and long-term display stability of the Micro LED micro display module in various application scenarios.

[0024] In the embodiment of the present application, the red and green quantum dot materials are subjected to spectrum collection and characteristic matrix construction under multiple temperature and power conditions, so that the system can comprehensively master the nonlinear response characteristics of quantum dots in the actual working environment, and accurately predict the color conversion efficiency and color purity of quantum dots. Based on the quantum dot material response data, the color conversion nonlinear characteristics under different excitation intensities are detected, and a color conversion parameter mapping table containing a temperature correction factor is generated, effectively overcoming the defects of traditional methods in considering the saturation effect of quantum dots under high brightness display conditions. Through systematic deposition parameter optimization and edge compensation printing strategy, uniform deposition of the quantum dot color conversion layer is realized, and the edge spectrum shift problem caused by uneven thickness of the quantum dot layer in traditional technology is solved, so that the color difference between the edge and center areas of the display area is controlled within a smaller range. Through the spectrum correction algorithm of wavelet transform and the adaptive gain compensation mechanism, the peak position and half peak width changes caused by temperature changes are corrected in real time, so that the color point drift of the quantum dot Micro LED micro display module in a wide temperature range is effectively controlled. Using the multi-layer perception target dynamic programming model to adjust the blue LED drive current, quantum dot layer temperature and packaging pressure parameters in real time, the saturation effect and light quenching phenomenon under high display brightness are effectively suppressed, and the color reproduction ability under high brightness display conditions is significantly improved. Through the chrominance data feedback of the built-in light sensor to perform automatic aging compensation, the color shift caused by aging after quantum dot packaging is corrected in real time, ensuring that the Micro LED micro display module can still maintain stable color output after long-term aging test, prolonging the service life of the equipment. By constructing a lookup table of the RGB color space in partitions and introducing a quantum dot excitation intensity compensation factor, accurate color mapping covering low, medium and high brightness intervals is realized, so that the display system can maintain high color gamut coverage and color accuracy under different brightness conditions.

[0025] In a specific embodiment, the process of step S100 can specifically include the following steps: The red quantum dot material and the green quantum dot material in the Micro LED micro display module are classified to obtain graded quantum dot material samples; The graded quantum dot material samples are placed in a temperature control system, and a temperature gradient is adjusted to obtain quantum dot material test environments under different temperature conditions; The graded quantum dot material samples are subjected to 460 nm blue light excitation based on the quantum dot material test environments under different temperature conditions to obtain quantum dot excitation states under multiple power conditions; The quantum dot excitation states under multiple power conditions are subjected to spectrum collection to obtain quantum dot original spectrum data, and the quantum dot original spectrum data are subjected to multi-parameter spectrum analysis to obtain quantum dot material response data; Based on quantum dot material response data, color conversion nonlinear response characteristics of quantum dots under different excitation intensities are detected, and a quantum dot color conversion parameter mapping table is generated.

[0026] Specifically, red and green quantum dot materials are classified according to their basic physical properties and optical performance. This classification not only relies on the preliminary physical screening of material sources and synthesis batches, but also relies on high-resolution particle size analyzers and high-sensitivity spectrometers to comprehensively detect quantum dot samples of different batches, different particle sizes, and different dispersities. Particle size distribution directly affects the emission peak position and quantum efficiency of quantum dots, while dispersity and the choice of surface ligands affect the uniformity, photoluminescence efficiency, and stability of quantum dots during ink preparation and deposition. Therefore, a large number of quantum dot raw materials are subjected to particle size statistical analysis to remove large particle agglomerates and fine particle impurities, ensuring that the selected materials have a narrow particle size distribution, high uniformity, and that each batch passes the preliminary test of emission spectrum to screen core indicators such as main emission peak position, full width at half maximum, and quantum efficiency. For red and green quantum dots, separate classification standards are established for each material system, such as grouping red quantum dots by main emission wavelength (e.g., 630-640 nm, 640-650 nm, etc.) and grouping green quantum dots by 530-540 nm and 540-550 nm to ensure that the classified samples are representative, comparable, and batch traceable. After completing the preliminary classification, the environmental adaptability test is entered. The classified quantum dot material samples are placed in a high-precision temperature control system, which has a wide temperature range, high temperature control accuracy, and fast and stable response capability. Common temperature control platforms include program-controlled hot tables, miniature environmental chambers, or temperature cycling boxes, which can achieve simultaneous temperature testing of multiple samples. Before formal testing, the samples are standardized, such as using the same ink dispersant, dilution concentration, and support substrate to avoid external variables affecting the optical response. In the temperature control system, the temperature is gradually increased or decreased by step or continuous temperature change to create a quantum dot material test environment under different temperature conditions. After setting the temperature control nodes, the excitation response test is performed. In the experiment, a high-stability blue light excitation source with a strictly limited wavelength of 460 nm is used to apply different power levels of excitation light to each classified quantum dot material sample. For example, multiple power levels are selected to excite each batch of samples at each temperature node, and the excitation power, incident angle, and light source uniformity are recorded. The quantum dot luminescence process under blue light excitation will produce complex changes due to the nonlinear response of the material itself, temperature-related behavior, and excitation intensity saturation effect. To avoid data collection errors, the light source output and spectrometer detection sensitivity are calibrated before each collection to ensure the consistency and comparability of the data under different batches and conditions. The emission spectrum of each group of quantum dot samples under different excitation powers and temperature nodes is collected by a high-sensitivity, wide dynamic range spectrophotometer or array-type spectrometer. The raw spectral data includes basic information such as complete emission intensity curves, main emission peak wavelength, full width at half maximum, and integrated luminescence intensity.After data acquisition, systematic multi-parameter spectral analysis is performed for each set of raw spectral data, including conventional statistics and comparison of peak position, intensity, and half-height width, and combined with multi-dimensional data analysis methods such as principal component analysis for dimensionality reduction of the data set, or nonlinear fitting methods (such as Gaussian peak fitting, Lorentzian decomposition, etc.) for separation and quantification of peak shape changes and superposition phenomena. Synchronous acquisition of environmental light background, substrate reflection light, material self-absorption and other multiple correction data, and deducting the corresponding system error and background noise in the data processing flow, to ensure that the quantum dot material response data truly reflects the intrinsic optical properties of the material. Based on the quantum dot material response data, the color conversion nonlinear response characteristics of quantum dots under different excitation intensities are detected. Since the luminescent efficiency and main emission peak position of quantum dots do not change linearly with excitation intensity or temperature, but there is a threshold effect, saturation behavior, thermal quenching and photobleaching effect under blue light excitation, therefore, data analysis not only needs to calculate the response curve of luminescent intensity to excitation power, but also should combine the main emission peak position drift, integrated luminescent efficiency drop and color coordinate change under each temperature condition, to establish a multi-dimensional relationship model of quantum dot temperature-excitation power-emission response. The peak position drift, luminescent saturation critical point and luminescent efficiency limit of the same material under different power excitation and temperature environment are fitted and analyzed, for example, under high excitation power, it is observed that the emission efficiency of quantum dot material tends to saturation or even decreases in the opposite direction, or the peak position red shift and half-height width widening phenomenon occurs, which all need to be quantitatively described by mathematical model. Especially in the high temperature and high power interval, pay attention to the complex behaviors of quantum dot material such as photobleaching, material self-heating and structure distortion, and introduce compensation factors or adaptive adjustment coefficients in data modeling. Through full induction, statistics and modeling of all spectral and response data of the graded samples under all temperature and power combinations, a quantum dot color conversion parameter mapping table is generated. This mapping table covers the core parameters of red and green quantum dot materials under different temperatures and different excitation intensities, such as luminescent intensity, peak position, color coordinate, conversion efficiency, saturation point, color drift and response lag.

[0027] In a specific embodiment, the step of detecting the color conversion nonlinear response characteristics of quantum dots under different excitation intensities based on quantum dot material response data can specifically include the following steps: Based on the quantum dot material response data, the luminescent intensity and wavelength distribution relationship of red quantum dots and green quantum dots under each power point is calculated to obtain a quantum dot excitation intensity-luminescent efficiency curve; Using the quantum dot excitation intensity-luminescent efficiency curve, the luminescent intensity change rate of quantum dots under different temperature conditions is measured to obtain a temperature-intensity influence factor table; Based on the temperature-intensity influence factor table, actual color display testing of quantum dot materials in a standard test environment is performed to obtain quantum dot color coordinate drift data; By using the quantum dot color coordinate drift data, the influence of the saturation effect and the light quenching phenomenon of the quantum dots under high excitation power on the color restoration is analyzed, a high brightness compensation parameter set is obtained, and the high brightness compensation parameter set is combined with the color conversion efficiency data under different excitation intensities to obtain a quantum dot color conversion parameter mapping table.

[0028] Specifically, based on the quantum dot material response data, the key parameters of each group of red and green quantum dot materials, such as the peak value of luminescent intensity, emission wavelength, and emission spectrum width, are extracted under each set blue light excitation power point. The experiment includes low, medium, and high multi-grade excitation intensity intervals, covering the whole process from sub-threshold excitation to high-intensity saturation and even super-intensity quenching. In the data processing stage, the quantum dot excitation intensity-luminescent efficiency curve is drawn with excitation power as the horizontal coordinate and quantum dot luminescent intensity as the vertical coordinate. The fitting algorithm (such as polynomial fitting, exponential fitting, and piecewise linear) is used to describe the trend of luminescent efficiency with excitation power. As the excitation power gradually increases, the quantum dot material luminescent intensity will go through the initial linear increase zone, the secondary decreasing gain zone, and the final saturation or even decline zone. The characteristics of each section are determined by the excitation cross section, non-radiative recombination process, and energy level structure of the material. By analyzing the slope change, saturation point inflection point position, limiting luminescent efficiency, and emission wavelength shift with excitation intensity of each curve, the energy conversion mechanism and color conversion stability of quantum dots are revealed. Using the quantum dot excitation intensity-luminescent efficiency curve, the luminescent intensity change rate of quantum dots under different temperature conditions is measured. The above power scanning experiment is repeated at different temperature nodes, and the luminescent intensity change at each temperature is normalized with the reference temperature. In the data processing stage, the luminescent intensity change rate at different temperatures for each excitation power point is normalized to obtain a multi-dimensional temperature-intensity influence factor table. This table uses temperature and excitation intensity as indexes and outputs the corresponding luminescent intensity change percentage or decay coefficient. Based on the temperature-intensity influence factor table, the actual color display test in the standard test environment is entered. According to the display industry standards, quantum dot materials are prepared into standard pixel structures or films in a controlled environment, and their actual color coordinates (such as CIE 1931 xy coordinates) under different excitation intensities and temperatures are measured through Micro LED module excitation. The shift of color coordinates directly reflects the changes in material spectrum shape, emission peak, and width, as well as the influence of each excitation power and temperature condition on color reproduction ability. To make the data representative, multiple rounds of testing are conducted on different material samples in the full color gamut and multi-luminance interval to obtain the quantum dot color coordinate shift dataset, revealing the blue shift, red shift, or width increase of quantum dot luminescent peak under high excitation power, as well as the contraction of color gamut coverage under extreme conditions, which manifests as slight or even obvious deviation of the actual output color of the display panel. After analyzing the quantum dot color coordinate shift data, the saturation effect and light quenching phenomenon of materials under high excitation power are quantitatively evaluated. Quantum dots are prone to saturation, where the luminescent intensity growth tends to plateau or even decrease, and some materials may experience a sudden drop in emission efficiency or rapid degradation (light quenching) due to excessive blue light energy, which will have an irreversible impact on color reproduction.By statistical analysis of the excitation intensity threshold of these phenomena, the color coordinate offset amplitude and the recovery (i.e. whether the original luminescent characteristics can be returned after the excitation intensity is reduced), a high brightness compensation parameter set is established. The parameter set includes the luminescent intensity correction factor corresponding to the excitation intensity, the color coordinate drift correction amount, the spectral compensation weighting coefficient, etc., which is used to guide how to dynamically correct the output color by adjusting the blue light LED drive current, the quantum dot temperature control system and the packaging pressure during the actual work of the module, and to maximize the elimination of color deviation and efficiency loss caused by saturation and quenching. The high brightness compensation parameter set and the color conversion efficiency data under different excitation intensities are integrated, all experimental and theoretical models are integrated, and a quantum dot color conversion parameter mapping table is constructed. This mapping table is stored in a multi-dimensional data structure, including the luminous efficiency, main peak wavelength and color coordinates under each excitation intensity and temperature node, and the compensation factors of saturation, quenching and temperature drift are linked, to realize the dynamic color adjustment capability of the Micro LED micro display module under various display environments, brightness requirements and temperature conditions.

[0029] In a specific embodiment, the process of performing step S200 can specifically include the following steps: According to the quantum dot color conversion parameter mapping table, quantum dot ink is prepared using red quantum dot materials and green quantum dot materials, and quantum dot deposition parameters including jet temperature, piezoelectric driving voltage, droplet spacing and printing layer number are created using the quantum dot ink; Based on the quantum dot deposition parameter combination, quantum dot inkjet deposition experiments are performed on the Micro LED blue backlight panel to obtain quantum dot deposition test samples; The quantum dot deposition test samples are subjected to heat treatment in a nitrogen environment to obtain stable quantum dot color conversion test layers, and the color conversion performance of the stable quantum dot color conversion test layers under 460nm blue light excitation is measured to obtain optimal deposition parameters; The deposition process of quantum dot materials is performed on the Micro LED blue backlight panel using the optimal deposition parameters to obtain a quantum dot color conversion layer structure.

[0030] Specifically, the quantum dot color conversion parameter mapping table marks the luminescent efficiency, main emission wavelength, color coordinate change, excitation nonlinearity and saturation point position of red and green quantum dots under different excitation power, temperature, layer thickness, material ratio and other working conditions, and the compensation parameters, temperature drift, packaging pressure and other key factors are included in the correction system. In the quantum dot ink preparation stage, according to the optimal material ratio and concentration suggested by the mapping table, the red quantum dots and green quantum dots are dispersed in high-purity, low-volatility and highly compatible solvents with inkjet technology, such as cyclohexanone, NMP, toluene, etc. The selection of the solvent should have good surface tension, appropriate viscosity and high boiling point characteristics, and be supplemented with an appropriate amount of dispersant and surfactant to prevent quantum dot aggregation and material precipitation. The concentration of quantum dot solution needs to be adjusted repeatedly through optical density and optical rotation tests to ensure that high color purity and saturation can be achieved during inkjet deposition, and that pore plugging or uneven deposition does not occur due to excessive concentration. After completing the basic preparation of quantum dot ink, according to the parameter mapping table combined with the technical specifications of inkjet printing equipment, the deposition parameter group is set, including nozzle temperature, piezoelectric drive voltage, ink droplet spacing and printing layer number. The nozzle temperature control is directly related to the rheological properties and atomization quality of the ink, which needs to be maintained in the range of 30~60℃ to optimize the formation of ink droplets, while avoiding thermal decomposition of quantum dots. The piezoelectric drive voltage determines the volume, speed and jetting stability of the ink droplets, which needs to be calibrated under different nozzle models to ensure uniform droplet distribution under high-frequency driving. The ink droplet spacing is precisely adjusted according to the spreading ability and surface energy characteristics of quantum dot materials. Too small spacing will lead to material accumulation and local thickening, while too large spacing will result in missing printing and empty spots, ultimately affecting color conversion uniformity and display consistency. The printing layer number needs to be dynamically adjusted according to the material absorption thickness and target conversion efficiency, using a multi-layer superposition strategy to improve optical density and color saturation, but strict avoidance of layer interface scattering and stress accumulation is required. Under the guidance of the optimized parameter combination, quantum dot ink is gradually deposited on the surface of Micro LED blue backlight panel through the inkjet printing process. In the early stage of the experiment, the step method or orthogonal experimental design is used to observe and record the deposition behavior, ink droplet spreading, drying rate and surface tension under different parameter combinations. Non-destructive testing is performed on the thickness uniformity, surface roughness, edge burr and other indicators of the deposited layer using optical microscopes, three-dimensional white light interferometers and other instruments to select the sample group with the best flatness and density. All quantum dot test samples after deposition are immediately subjected to heat treatment in an inert nitrogen atmosphere. The heat treatment temperature and time need to be set in combination with the thermal stability range of quantum dot materials and the heat resistance limit of the substrate to promote solvent evaporation, dispersant removal and mutual rearrangement of quantum dots, while improving the physical bonding strength and chemical stability of the quantum dot and the substrate interface. The nitrogen protection environment is crucial because oxygen and moisture in the air can easily cause quantum dot surface oxidation and degradation, affecting color conversion efficiency and long-term life. After heat treatment, all quantum dot color conversion test layers are measured for system performance under standard 460nm blue light excitation.The performance measurement needs to cover the luminous intensity, the main peak wavelength, the half-height width, the color coordinates and other conventional parameters, and the spatial uniformity test, the excitation efficiency mapping, the thickness-efficiency correlation analysis and other tests are carried out on the entire deposition layer. With the aid of two-dimensional imaging spectrometer, area array camera and high-resolution excitation probe, the conversion efficiency and color coordinate consistency at different positions and different layer thicknesses are obtained. By comparing with the theoretical optimal value in the quantum dot color conversion parameter mapping table one by one, combined with multiple sets of experimental data for multivariate statistical regression, the optimal deposition parameters that can obtain the highest color restoration, the maximum luminous efficiency and the minimum thickness fluctuation under the specific jet temperature, piezoelectric voltage, droplet spacing and layer number are screened out. The optimal deposition parameters are used to deposit quantum dot materials on the Micro LED blue backlight. With the aid of automatic inkjet printing equipment and real-time quality monitoring system, precise control and dynamic correction are performed on each pixel and each emission area to prevent small cumulative errors caused by material distribution deviation and equipment fluctuation. After deposition, nitrogen heat treatment and batch spectrum detection are performed again to ensure that all areas of the color conversion layer reach the target standard, and finally the quantum dot color conversion layer structure is obtained.

[0031] In a specific embodiment, the process of performing step S300 can specifically include the following steps: Load the quantum dot color conversion layer structure on the Micro LED micro display module, and perform gradient adjustment of the working temperature to obtain a test sequence under multiple temperature conditions; Perform real-time spectrum acquisition on the test sequence under multiple temperature conditions to obtain quantum dot real-time spectrum data and quantum dot peak temperature drift data, and calculate the quantum dot temperature-peak drift mapping relationship according to the quantum dot peak temperature drift data; Based on the quantum dot temperature-peak drift mapping relationship, perform wavelet transform decomposition on the quantum dot real-time spectrum data to obtain temperature adaptability spectrum correction parameters, and perform adaptive gain compensation according to the temperature adaptability spectrum correction parameters and the real-time monitored environmental temperature data to obtain temperature compensation control instructions.

[0032] Specifically, the quantum dot color conversion layer structure is loaded on the Micro LED micro display module. The loading process ensures that the quantum dot layer fully adheres to the Micro LED light-emitting area without air bubbles or mechanical stress accumulation. High-transparency, high-temperature-resistant encapsulation materials are used to achieve effective physical protection and optical coupling, avoiding interface reflection loss and stray light interference. After loading, the experimental platform integrates a high-precision temperature control unit, which realizes continuous or stepwise adjustment of the environmental temperature through programmed scheduling. The temperature control unit has a wide range of high-resolution temperature control capabilities and simultaneously records the actual surface and internal temperature of the module. Each temperature node is set considering the thermal stability limit of quantum dot materials and the safe operating range of Micro LED drive circuits to avoid material failure or electrical performance degradation caused by extreme temperatures. After entering the test sequence under multiple temperature conditions, the real-time acquisition of quantum dot emission spectra under Micro LED excitation is performed at each temperature node through a high-sensitivity spectral acquisition system. The spectral acquisition equipment has a wide dynamic response, high signal-to-noise ratio, and high spectral resolution, allowing it to accurately record the changes in quantum dot light intensity, main emission peak wavelength, half-width, and spectral shape during transient temperature changes. To improve the overall coverage and representativeness of the data, the spectral uniformity of different spatial positions (such as the center, edge, and hot spot area) is considered in the experiment, and a two-dimensional array spectrometer is used for full-module imaging measurement. The real-time spectral data collected, especially the wavelength, intensity, and spectral pattern of the main emission peak as a function of temperature, are the core basis for subsequent modeling and compensation. During the entire temperature scanning process, the main emission peak position of the quantum dots at each temperature node is compared with the initial (reference temperature) state, and the peak temperature drift data of the quantum dots are calculated and stored. This drift is characterized by redshift, intensity attenuation, or spectral width increase at high temperatures, and the specific amplitude is related to the size distribution, synthetic ligand, and encapsulation method of the quantum dot material. Based on the large amount of temperature-peak drift data sets obtained above, statistical analysis, curve fitting, or polynomial regression methods are used to establish the temperature-peak drift mapping relationship of the quantum dots. To improve the dynamic adaptability of the compensation model and its sensitivity to local abnormal drift, wavelet transform decomposition is introduced to the real-time acquired quantum dot spectral data. Wavelet transform simultaneously expands the original signal in time and frequency domains, achieving multi-scale decomposition of spectral details and overall trends under temperature disturbance. By separating different frequency components such as main peak drift, side peak enhancement, and spectral width change, the spectral feature components highly correlated with temperature changes are extracted. These components are analyzed in conjunction with the established temperature-peak drift mapping relationship to refine the extraction of temperature-adaptive spectral correction parameters, such as peak position correction, intensity normalization factor, and spectral distortion compensation coefficient. The temperature-adaptive spectral correction parameters and real-time monitored environmental temperature data are jointly input into the adaptive gain compensation algorithm.The algorithm adopts proportional-integral-derivative control, fuzzy control or adaptive adjustment mechanism based on neural network, and links the change amount of the environmental temperature with the spectral shift data to dynamically output compensation instructions. Specifically, under high temperature conditions, the Micro LED blue light excitation power is automatically increased or the local temperature control unit of the quantum dot layer is adjusted, or the stress compensation of the quantum dot light emitting center is realized through fine adjustment of the packaging stress. In addition, the actual driving current is dynamically fine-tuned to optimize the excitation intensity and light-emitting efficiency matching, ensuring that the main emission peak and color coordinates of the output are always stable in the design target range even when the external temperature fluctuates greatly. Through the above steps, temperature compensation control instructions are generated and automatically fed back to the hardware drive and color mapping module of the Micro LED micro display module.

[0033] In a specific embodiment, the process of performing step S400 can specifically include the following steps: Based on the temperature compensation control instructions, a multi-layer perception target dynamic programming model for quantum dot photoluminescence characteristics is constructed, which includes a state perception network, an action generation network and a reward evaluation network; The luminance distribution map of the current display content and the quantum dot light intensity distribution map are input into the state perception network for processing to obtain a state feature vector; The state feature vector is input into the action generation network for double-channel deep neural network analysis to obtain an initial action space parameter group, and the Micro LED micro display module is adjusted based on the initial action space parameter group to obtain a parameter adjustment evaluation result; The parameter adjustment evaluation result is input into the reward evaluation network to perform quantum dot color conversion dynamic regulation and optimization to obtain an optimal parameter regulation strategy of the Micro LED micro display module; According to the optimal parameter regulation strategy, the blue LED driving current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module are adjusted in real time in combination with the luminance and color distribution characteristics of the input image to obtain a dynamically optimized control parameter combination; The display image output by the Micro LED micro display module is color-mapped through the dynamically optimized control parameter combination to maintain the color stability of the Micro LED micro display module.

[0034] Specifically, a multi-layer perception target dynamic programming model for quantum dot photoluminescence characteristics is constructed based on temperature compensation control instructions. The core structure includes a state perception network, an action generation network, and a reward evaluation network. The state perception network serves as the input layer of the entire dynamic programming model, responsible for comprehensive perception and representation of the current display content and quantum dot light-emitting state. The system real-time acquires the brightness distribution map of the current display content (i.e., the brightness distribution of the input image in space) and the actual quantum dot light intensity distribution map (obtained through integrated light sensors or imaging spectrometers), which are used as multi-dimensional data inputs. After normalization, feature extraction, and noise reduction preprocessing, environmental noise and extreme pixel interference are eliminated. The brightness distribution and light intensity spatial features are analyzed at multiple scales using convolution layers, normalization layers, and attention mechanisms in deep neural networks, extracting global uniformity, local anomalies, light-dark contrast, spatial color gamut offset, and other information, and fusing them into a high-dimensional state feature vector. The state feature vector is input into the action generation network, which uses a dual-channel deep neural network structure, divided into a parameter regulation channel and a behavior prediction channel. The parameter regulation channel extracts the influence of adjustable parameters on output performance from the feature vector, and predicts the parameter combination range suitable for the current state by integrating the historical response data of the current module's temperature, excitation current, packaging stress, and quantum dot light-emitting efficiency. The behavior prediction channel considers the possible trends in the future display cycles, and based on deep reinforcement learning or recurrent neural networks, simulates the response path of the system output under different parameter adjustments, and predicts the stability and robustness of the strategy. The network outputs an initial action space parameter set, including the adjustment amplitude of the blue LED drive current, the target temperature setting of the quantum dot layer temperature control unit, and the packaging pressure fine-tuning strategy. These parameters are reflected in the actual light-emitting performance of the Micro LED module after being issued to the hardware through the device driver layer. By collecting feedback data such as brightness distribution, color gamut response, and main emission peak drift after parameter adjustment, the evaluation results of parameter adjustment are obtained, which are fed back to the reward evaluation network. The reward evaluation network, as the optimization decision unit in the multi-layer model, quantitatively scores the actual effect of each parameter adjustment based on key indicators such as optical performance, energy consumption, and color consistency. The network uses a multi-objective evaluation mechanism to convert color gamut coverage, brightness uniformity, energy efficiency improvement, and color restoration accuracy into a weighted reward function, and dynamically updates the weights to adapt to different display content and application scenarios. For parameter strategies with good performance, the network gives higher rewards and promotes them as the preferred choice for subsequent decisions. For poor combinations, the strategy priority is reduced, and abnormal fluctuations, rapid aging, and excessive energy consumption are marked as risk events to prompt the system to automatically avoid them. Through continuous trial-and-error, adjustment, evaluation, and feedback iterations, the reward evaluation network can guide the model strategy to quickly converge to the global optimal solution, outputting the globally optimal parameter regulation strategy.The model regulates the strategy of the optimal parameters output by the current reward evaluation network, combines the brightness and color distribution characteristics of the real-time input image, and adjusts the hardware parameters of the Micro LED micro display module in linkage. According to the display content such as high brightness, strong contrast, color saturation and the like, the blue light LED driving current is automatically increased, and meanwhile, the temperature sensing and quantum dot temperature control unit are combined to realize dynamic balance of the temperature of the quantum dot layer, so as to eliminate the color gamut shrinkage and peak shift under high temperature; if long-time high-brightness operation or local area abnormal heating is detected, the real-time packaging pressure is adjusted to optimize the heat conduction path, so as to prevent material aging and structural damage. All the adjustment parameters form a dynamic optimization control parameter combination, which is sent to the display control module and the hardware driving layer by the system, so as to realize instantaneous response and frame-by-frame adjustment. On the basis of the above regulation, real-time color mapping processing of the output display image is combined. The optimized parameter combination and the quantum dot color conversion mapping table are used to dynamically correct the brightness and color coordinates of each pixel, automatically compensate for the slight color deviation caused by temperature, power and pressure fluctuations, and keep each frame of display image in the designed color gamut and target color space.

[0035] In an embodiment, the process of performing color mapping processing on the display image output by the Micro LED micro display module by the parameter combination of dynamic optimization control to maintain the color stability of the Micro LED micro display module can specifically include the following steps: Performing colorimetric measurement on the display image output by the Micro LED micro display module under standard observation conditions, calculating the colorimetric value deviation data of the actual display colorimetric value and the theoretical colorimetric value, and performing color mapping using the colorimetric value deviation data to obtain a basic color correction model; Based on the parameter combination of dynamic optimization control, the quantum dot excitation intensity in different brightness intervals is introduced into the basic color correction model to obtain a comprehensive color mapping model; A light sensor is installed inside the Micro LED micro display module to collect the test display colorimetric value of the standard white test image, and the difference between the test display colorimetric value and the initial display colorimetric value is calculated for automatic updating to obtain model real-time correction instructions; According to the model real-time correction instructions, the parameters of the comprehensive color mapping model are dynamically updated, and the color deviation caused by aging of the quantum dot after packaging is automatically compensated and adjusted to maintain the color stability of the Micro LED micro display module.

[0036] Specifically, under the standard observation light source and observation angle consistent with CIE or industry standards, the chromaticity of the display image output by the Micro LED micro display module is measured. This step relies on a high-sensitivity, wide-band response spectrophotometer or an embedded spectral sensor network to collect the output chromaticity values of each pixel, each block, and each scene in all directions and frame by frame. The system is automatically calibrated before and after each measurement to eliminate environmental interference, equipment drift, and other non-ideal error sources. During each batch and each stage of the display task, the actual display chromaticity values measured are compared with the theoretical target chromaticity values (i.e., the ideal color coordinates defined by the image content color management standard at the time of factory shipment or according to the image content color management standard). The actual display deviation is quantified using indicators such as ΔE or color coordinate difference. After statistical processing of the chromaticity value deviation data of all pixels or regions, the data is input into the color mapping algorithm module. The deviation distribution is modeled using least squares, polynomial fitting, matrix transformation, or machine learning algorithms to extract global and local color drift trends and abnormal points, and to build a basic color correction model. This model establishes a mapping relationship between the physical chromaticity output space of the Micro LED micro display module and the target color space, providing a mathematical basis and response mechanism for subsequent real-time correction and compensation. As the system continuously adapts to actual working scenarios and content types, the basic color correction model integrates dynamic optimization control parameters. The quantum dot excitation intensity in different brightness intervals directly affects the quantum dot light-emitting efficiency, peak shift, color gamut width, and primary color coordinate distribution. Based on the real-time running physical adjustment parameters of the module, such as blue LED drive current, quantum dot layer temperature, and packaging pressure, as well as local brightness information of different pixels or regions, a quantum dot excitation intensity compensation factor is introduced as a new weight parameter and embedded in the basic color correction model. Through this step, the model not only reflects the standard color mapping in a static environment, but also has the ability to adaptively compensate for color in complex display scenarios such as high brightness, strong contrast, and large dynamic range, thereby evolving into a highly dynamic comprehensive color mapping model. In terms of model closed-loop feedback mechanism, to ensure the real-time performance and self-learning ability of the system, a high-precision light sensor array is integrated inside the Micro LED micro display module. The system periodically or at each boot self-check, operation anomaly detection, and other nodes automatically calls the standard white test image, drives the display in full white, gray scale, and full black scenes by the controller, and accurately collects the actual display chromaticity values of each pixel or region through the built-in light sensor. The standard white test display chromaticity values collected will form a corresponding difference with the module factory shipment, last global correction, or theoretical ideal value. These differences constitute real-time correction instructions for the model, reflecting the dynamic shift trend of the system's color performance after long-term operation, material aging, and environmental temperature changes.In view of the inevitable aging phenomenon of quantum dot materials and packaging systems under long-term high-intensity driving, such as red shift of the main emission peak, brightness attenuation, color gamut shrinkage and other problems, the system needs to integrate a specific aging compensation algorithm in the model correction and mapping update process. The algorithm combines multi-dimensional data such as cumulative running time, historical temperature curve, chroma shift rate, etc., through the establishment of a mathematical model of physical aging and color shift, dynamically adjusts the compensation factor for each pixel and each display area, and automatically optimizes the color mapping weight, so as to realize the stable output of color in the life cycle of the display terminal without affecting the response speed and energy efficiency of the system. The entire color mapping and compensation system maintains the color stability of the Micro LED micro display module through the closed-loop process of continuous measurement-modeling-compensation-re-measurement-re-optimization.

[0037] Please refer to Figure 2 , Figure 2 The structure of the Micro LED micro display module color conversion system 200 based on quantum dots provided by the embodiment of the present application is shown in the structure schematic block diagram as shown in Figure 2 The Micro LED micro display module color conversion system 200 based on quantum dots includes: The acquisition module 210 is used for multi-temperature and multi-power spectrum acquisition of red quantum dot materials and green quantum dot materials in the Micro LED micro display module under 460nm blue light excitation, and generates a quantum dot color conversion parameter mapping table; The deposition module 220 is used for controlling the inkjet printing equipment to deposit quantum dot materials on the Micro LED blue light backboard according to the quantum dot color conversion parameter mapping table, and forms a quantum dot color conversion layer structure; The monitoring module 230 is used for monitoring the spectral performance of the quantum dot color conversion layer structure in the temperature change environment, and generating a temperature compensation control instruction; The adjustment module 240 is used for adjusting the blue light LED drive current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module in real time by using the temperature compensation control instruction, and performing color mapping processing on the display image output by the Micro LED micro display module, and maintaining the color stability of the Micro LED micro display module.

[0038] Through the synergistic cooperation of the above components, the spectral collection and characteristic matrix construction of red and green quantum dot materials under multiple temperature and power conditions enable the system to comprehensively master the nonlinear response characteristics of quantum dots in the actual working environment, accurately predict the color conversion efficiency and color purity of quantum dots. Based on the response data of quantum dot materials, the color conversion nonlinear characteristics under different excitation intensities are detected, and a color conversion parameter mapping table containing a temperature correction factor is generated, effectively overcoming the defects of traditional methods in considering the saturation effect of quantum dots under high brightness display conditions. Through systematic deposition parameter optimization and edge compensation printing strategies, uniform deposition of the quantum dot color conversion layer is realized, solving the edge spectrum shift problem caused by uneven thickness of the quantum dot layer in traditional technology, and controlling the color difference between the edge and center areas of the display area within a smaller range. Through the spectral correction algorithm of wavelet transform and the adaptive gain compensation mechanism, the changes in peak position and half peak width caused by temperature changes are corrected in real time, so that the color point drift of the quantum dot Micro LED micro display module in a wide temperature range is effectively controlled. Using the multi-layer perception target dynamic programming model to adjust the blue LED drive current, quantum dot layer temperature and packaging pressure parameters in real time, the saturation effect and light quenching phenomenon under high display brightness are effectively suppressed, and the color reproduction ability under high brightness display conditions is significantly improved. Through the chrominance data feedback of the built-in light sensor to execute automatic aging compensation, the color shift caused by aging after quantum dot packaging is corrected in real time, ensuring that the Micro LED micro display module can still maintain stable color output after long-term aging test, prolonging the service life of the equipment. By constructing the lookup table of the RGB color space in the partition and introducing the quantum dot excitation intensity compensation factor, accurate color mapping covering low, medium and high brightness intervals is realized, so that the display system can maintain high color gamut coverage and color accuracy under different brightness conditions.

[0039] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, system and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0040] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application or the entire or part of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0041] The above-described embodiments are merely used to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some of the technical features; and these modifications or replacements do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A color conversion method for a Micro LED micro display module based on quantum dots, characterized in that: include: Under 460nm blue light excitation, multi-temperature and multi-power spectrum acquisition is performed on the red and green quantum dot materials in the Micro LED micro-display module to generate a quantum dot color conversion parameter mapping table; Controlling an inkjet printing device to deposit quantum dot material on the Micro LED blue light backplane according to the quantum dot color conversion parameter mapping table to form a quantum dot color conversion layer structure; monitoring the spectral performance of the quantum dot color conversion layer structure under a temperature-changing environment and generating temperature compensation control instructions; The temperature compensation control instructions are used to adjust the blue LED driving current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module in real time, and color mapping processing is performed on the display image output by the Micro LED micro display module to maintain the color stability of the Micro LED micro display module.

2. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 1, characterized in that: The method involves collecting multi-temperature and multi-power spectra of the red quantum dot material and the green quantum dot material in the Micro LED micro display module under 460nm blue light excitation to generate a quantum dot color conversion parameter mapping table, including: Classify the red quantum dot materials and green quantum dot materials in the Micro LED micro display module to obtain graded quantum dot material samples; Placing the graded quantum dot material samples in a temperature control system, performing temperature gradient adjustment, and obtaining quantum dot material test environments under different temperature conditions; Based on the quantum dot material test environment under different temperature conditions, the graded quantum dot material samples were excited by 460nm blue light to obtain the quantum dot excitation state under multiple power conditions; Performing spectral acquisition on the quantum dot excitation state under the multiple power conditions to obtain original spectral data of the quantum dots, and performing multi-parameter spectral analysis on the original spectral data of the quantum dots to obtain quantum dot material response data; The color conversion nonlinear response characteristics of the quantum dots under different excitation intensities are detected based on the quantum dot material response data, and a quantum dot color conversion parameter mapping table is generated.

3. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 2, characterized in that: The detecting the color conversion nonlinear response characteristics of the quantum dots under different excitation intensities based on the quantum dot material response data and generating a quantum dot color conversion parameter mapping table includes: Based on the response data of the quantum dot material, the relationship between the luminous intensity and wavelength distribution of the red quantum dots and the green quantum dots at each power point is calculated to obtain a quantum dot excitation intensity-luminous efficiency curve; Using the quantum dot excitation intensity-luminous efficiency curve, the luminous intensity change rate of the quantum dots under different temperature conditions is measured to obtain a temperature-intensity influence factor table; Based on the temperature-intensity influence factor table, actual color display testing is performed on the quantum dot material in a standard test environment to obtain quantum dot color coordinate drift data; The quantum dot color coordinate drift data is used to analyze the influence of the saturation effect and light quenching phenomenon of quantum dots under high excitation power on color reproduction, and a high-brightness compensation parameter set is obtained. The high-brightness compensation parameter set is combined with the color conversion efficiency data under different excitation intensities to obtain a quantum dot color conversion parameter mapping table.

4. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 1, characterized in that: The method of controlling an inkjet printing device to deposit quantum dot material on a Micro LED blue light backplane according to the quantum dot color conversion parameter mapping table to form a quantum dot color conversion layer structure includes: According to the quantum dot color conversion parameter mapping table, quantum dot ink is prepared using red quantum dot material and green quantum dot material, and a quantum dot deposition parameter combination including nozzle temperature, piezoelectric drive voltage, ink drop spacing, and number of printing layers is created using the quantum dot ink; Based on the quantum dot deposition parameter combination, a quantum dot inkjet deposition experiment was performed on a Micro LED blue light backplane to obtain a quantum dot deposition test sample; Thermally treating the quantum dot deposition test sample in a nitrogen environment to obtain a stable quantum dot color conversion test layer, and measuring the color conversion performance of the stable quantum dot color conversion test layer under 460nm blue light excitation to obtain optimal deposition parameters; The optimal deposition parameters are used to deposit quantum dot materials on the Micro LED blue light backplane to obtain a quantum dot color conversion layer structure.

5. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 1, characterized in that: The monitoring of the spectral performance of the quantum dot color conversion layer structure under a temperature change environment and generating a temperature compensation control instruction includes: The quantum dot color conversion layer structure is mounted on a Micro LED micro-display module, and a gradient adjustment of the operating temperature is performed to obtain a test sequence under multiple temperature conditions; Performing real-time spectrum acquisition on the test sequence under the multiple temperature conditions to obtain quantum dot real-time spectrum data and quantum dot peak temperature drift data, and calculating a quantum dot temperature-peak drift mapping relationship based on the quantum dot peak temperature drift data; Based on the quantum dot temperature-peak drift mapping relationship, the real-time spectral data of the quantum dots is decomposed by wavelet transform to obtain temperature-adaptive spectral correction parameters, and adaptive gain compensation is performed according to the temperature-adaptive spectral correction parameters and the real-time monitored ambient temperature data to obtain temperature compensation control instructions.

6. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 1, characterized in that: The method comprises: using the temperature compensation control instruction to adjust the blue LED driving current, quantum dot layer temperature, and packaging pressure parameters of the Micro LED micro display module in real time, and performing color mapping processing on the display image output by the Micro LED micro display module to maintain the color stability of the Micro LED micro display module, including: Building a multi-layer perception target dynamic programming model for quantum dot photoluminescence characteristics based on the temperature compensation control instruction, the multi-layer perception target dynamic programming model including a state perception network, an action generation network, and a reward evaluation network; Inputting the brightness distribution map of the currently displayed content and the quantum dot luminous intensity distribution map into the state perception network for processing to obtain a state feature vector; Inputting the state feature vector into the action generation network for dual-channel deep neural network analysis to obtain an initial action space parameter group, and using the initial action space parameter group to adjust parameters of the Micro LED micro display module to obtain a parameter adjustment evaluation result; Inputting the parameter adjustment evaluation results into the reward evaluation network to perform dynamic control optimization of quantum dot color conversion to obtain the optimal parameter control strategy for the Micro LED micro display module; According to the optimal parameter control strategy, combined with the brightness and color distribution characteristics of the input image, the blue LED drive current, quantum dot layer temperature, and packaging pressure parameters of the Micro LED micro display module are adjusted in real time to obtain a dynamically optimized control parameter combination; Through the combination of parameters controlled by dynamic optimization, color mapping processing is performed on the display image output by the Micro LED micro display module to maintain the color stability of the Micro LED micro display module.

7. The color conversion method of a quantum dot-based Micro LED micro-display module according to claim 6, characterized in that: The method of performing color mapping processing on the display image output by the Micro LED micro display module by using the parameter combination of the dynamic optimization control to maintain the color stability of the Micro LED micro display module includes: Performing chromaticity measurement on the display image output by the Micro LED micro-display module under standard observation conditions, calculating the chromaticity value deviation data between the actual displayed chromaticity value and the theoretical chromaticity value, and performing color mapping using the chromaticity value deviation data to obtain a basic color correction model; Based on the parameter combination of the dynamic optimization control, a quantum dot excitation intensity compensation factor is introduced into the basic color correction model for the quantum dot excitation intensity in different brightness ranges to obtain a comprehensive color mapping model; Installing a light sensor inside the Micro LED micro display module to collect the test display chromaticity value of the standard white test image, and calculating the difference between the test display chromaticity value and the initial display chromaticity value for automatic update to obtain a real-time model correction instruction; According to the real-time correction instructions of the model, the parameters of the comprehensive color mapping model are dynamically updated, and automatic compensation adjustment is performed for the color shift caused by aging after quantum dot encapsulation to maintain the color stability of the Micro LED micro display module.

8. A quantum dot-based Micro LED micro-display module color conversion system, characterized in that: A method for performing color conversion of a quantum dot-based Micro LED micro-display module according to any one of claims 1 to 7, comprising: The acquisition module is used to collect multi-temperature and multi-power spectra of the red and green quantum dot materials in the Micro LED micro-display module under 460nm blue light excitation, and generate a quantum dot color conversion parameter mapping table; A deposition module is used to control an inkjet printing device to deposit quantum dot material on the Micro LED blue light backplane according to the quantum dot color conversion parameter mapping table to form a quantum dot color conversion layer structure; A monitoring module, configured to monitor the spectral performance of the quantum dot color conversion layer structure under a temperature-changing environment and generate temperature compensation control instructions; The adjustment module is used to use the temperature compensation control instructions to adjust the blue light LED driving current, quantum dot layer temperature and packaging pressure parameters of the Micro LED micro display module in real time, and perform color mapping processing on the display image output by the Micro LED micro display module to maintain the color stability of the Micro LED micro display module.

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