Wide-color-gamut low-blue-light display screen system with adaptive light field regulation and control

Abstract

The invention provides a self-adaptive wide-color-gamut low-blue-light display screen system. The self-adaptive wide-color-gamut low-blue-light display screen system comprises a four-primary-color Micro-LED array and a perovskite quantum dot stabilizing layer. According to the system, image signals are mapped through a nerve driving module, the blue light peak value is dynamically adjusted through a bio-optical engine, the partition inhibition coefficient beta (x, y, t) is calculated based on the pupil diameter and the watching duration, and the blue light harm is reduced to the RG0 level. The yellow light chip fills up the RGB color gamut gap, the quantum dot layer ensures the color accuracy, the initial blue light wavelength avoids a harmful wave band of 415-455nm, and collaborative optimization of a wide color gamut and low blue light is achieved.

Description

Technical Field

[0001] This application relates to the field of visual display, and more particularly to a wide color gamut low blue light display system with adaptive light field modulation. Background Technology

[0002] With the development of display technology, users' demands for screen color performance and eye protection are increasing. Traditional displays typically use an RGB three-primary-color architecture, which, while meeting basic color display requirements, has significant shortcomings in the following aspects:

[0003] Color gamut limitations: Traditional sRGB or AdobeRGB color gamuts cannot cover a wider range of colors (such as DCI-P3), affecting color accuracy in professional imaging, medical diagnosis and other scenarios.

[0004] Blue light hazards: The short-wavelength blue light (415–455nm) from traditional LED backlights can easily cause visual fatigue and may interfere with the body's biological rhythms (such as melatonin secretion).

[0005] Energy efficiency issues: Wide color gamut displays typically require higher brightness or more complex color management, leading to increased power consumption and affecting the battery life of mobile devices.

[0006] Therefore, there is an urgent need for a display technology solution that can achieve a balance between wide color gamut, low blue light, and high energy efficiency. Summary of the Invention

[0007] The purpose of this application is to provide a wide color gamut low blue light display system.

[0008] According to one aspect of this application, an adaptive light field modulation wide color gamut low blue light display system is provided, comprising:

[0009] The four-primary-color Micro-LED array consists of independently packaged blue, green, yellow, and red LED chips, among which:

[0010] The peak emission wavelength of the yellow light chip is 530–600 nm;

[0011] A perovskite quantum stabilizing layer is directly attached to the light-emitting surface of the Micro-LED array. The stabilizing layer contains a CsPbBr3-CsPbI3 gradient quantum dot film, which is used to control the emission wavelength shift of the Micro-LED within ±2nm range.

[0012] The neural drive module maps input image data into four primary color drive current signals through a spiking neural network.

[0013] The bio-optics adaptive engine dynamically calculates the blue light suppression coefficient β(x,y,t) of each zone based on real-time pupil diameter data and viewing duration, and adjusts the peak wavelength of the blue light unit to 460–470nm accordingly.

[0014] In one specific embodiment, the perovskite quantum stable layer is formed as a continuous thin film with a thickness of no more than 5 μm. After being continuously exposed to an aging environment at 85°C and 85% relative humidity for 1000 hours, the color coordinate offset Δu'v' of the Micro-LED array is less than 0.002.

[0015] In one specific embodiment, the spiking neural network driving module:

[0016] Receive input image data in standard RGB format and convert the input image data into a pulse frequency modulation signal;

[0017] The four primary color driving currents are calculated using a programmable 4×4 synaptic weight matrix W, where the driving current Ik of the k-th primary color satisfies: Ik=∑j=14Wkj·Sj(t);

[0018] Output optimized four-primary-color drive current signals.

[0019] In one specific embodiment, the formula for calculating the partitioned blue light suppression coefficient β(x,y,t) is as follows:

[0020] β(x,y,t)=α·Apupil(x,y,t)Amax+(1-α)·e-tviewτ

[0021] Where α is the physiological weighting coefficient, and 0.5≤α≤0.8, Apupil is the real-time pupil area, Amax is the maximum pupil area, tview is the continuous viewing duration, and τ is the time decay constant, which satisfies: 1h≤τ≤3h.

[0022] In one specific embodiment, the spectral half-width of both the yellow light unit and the green light unit is ≤25nm, and a distributed Bragg reflector layer is provided between them to suppress spectral crosstalk.

[0023] In one specific embodiment, the perovskite quantum dot stabilizing layer is formed using an aerosol jet printing process and has an Al2O3 / fluororesin dual-layer encapsulation structure.

[0024] In one specific embodiment, the synaptic weight matrix W is dynamically updated through pulse time-dependent plasticity rules, and the hardware implementation adopts a ReRAM-based in-memory computing architecture.

[0025] In one specific embodiment, the bio-optical adaptive engine further includes:

[0026] Millimeter-wave radar module is used to detect the user's distance and dynamically adjust the screen brightness accordingly;

[0027] A skin conductance sensor is used to monitor the user's fatigue state and trigger a reduction in blue light intensity.

[0028] In one specific embodiment, the perovskite quantum dot stabilizing layer further includes a calibration method:

[0029] After quantum dot film deposition, the actual emission wavelength λ_meas of each pixel region was measured;

[0030] Compare with the target wavelength λ_target;

[0031] When |λ_meas-λ_target|>3nm, a compensation current ΔI_k is injected through the neuromorphic driving module:

[0032] ΔI_k=η·(λ_meas-λ_target)·I_k

[0033] Where η is the wavelength-to-current conversion coefficient, and 0.05 ≤ η ≤ 0.1 nm -1 ,

[0034] The compensated emission wavelength is controlled within the range of λ_target±2nm.

[0035] Therefore, this application presents an adaptive light field-controlled wide color gamut low blue light display system. By introducing a yellow light chip, it directly fills the gap in the yellow region of the RGB three primary colors in the CIE chromaticity diagram. Combined with the broad-spectrum coverage of green and red light chips, it expands the color gamut. Furthermore, the perovskite quantum dot stabilization layer, through gradient component design, locks the Micro-LED wavelength offset within ±2nm, ensuring color accuracy. It is worth noting that its low blue light control logic sets the initial peak wavelength of the blue light chip to 430-480nm, avoiding the harmful 415-455nm band. The bio-optical engine dynamically shifts the blue light peak and provides real-time feedback on the user's physiological state through pupil area. Furthermore, by combining a viewing duration attenuation factor to generate a β(x,y,t) coefficient, the blue light hazard index is ultimately reduced to the RG0 exemption level. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0037] Figure 1This is the execution logic diagram of a wide color gamut low blue light display system with adaptive light field modulation.

[0038] Figure 2 A unit summary diagram of a wide color gamut low blue light display system with adaptive light field modulation;

[0039] Figure 3 This is a unit coverage diagram of a four-primary-color Micro-LED array.

[0040] Explanation of icon numbers:

[0041] 100. A wide color gamut low blue light display system with adaptive light field modulation; 10. Four-primary-color Micro-LED array; 20. Perovskite quantum stabilizing layer; 30. Neural drive module; 40. Bio-optical adaptive engine; 1. Blue light chip; 2. Green light chip; 3. Yellow light chip; 4. Red light chip. Detailed Implementation

[0042] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings. Preferred embodiments of this application are shown in the drawings. However, this application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the disclosure of this application.

[0043] It should be noted that when a component is said to be "fixed to" another component, it can be directly attached to the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0045] Please refer to Figures 1-3 One embodiment of this application provides a wide color gamut low blue light display system 100 with adaptive light field modulation, comprising:

[0046] The four-primary-color Micro-LED array 10 consists of independently packaged blue light chip 1, green light chip 2, yellow light chip 3, and red light chip 4, wherein:

[0047] The peak emission wavelength of the yellow light chip 3 is 530–600 nm;

[0048] A perovskite quantum stabilizing layer 20 is directly attached to the light-emitting surface of the Micro-LED array. The stabilizing layer contains a CsPbBr3-CsPbI3 gradient composition quantum dot film, which is used to control the emission wavelength shift of the Micro-LED within ±2nm range.

[0049] The neural drive module 30 maps the input image data into four primary color drive current signals through a spiking neural network;

[0050] The Bio-Optics Adaptive Engine 40 dynamically calculates the blue light suppression coefficient β(x,y,t) of the zone based on real-time acquired pupil diameter data and viewing duration, and adjusts the peak wavelength of the blue light unit to 460–470nm accordingly.

[0051] Furthermore, in this embodiment, it should be noted that the technical objective is achieved through the coordinated operation of the following core components:

[0052] Blue light chip 1: Made of InGaN material, with a native peak wavelength of 450nm (unadjusted).

[0053] Green LED Chip 2: Based on GaN, with a peak emission rate of 535±2nm (half-width ≤25nm).

[0054] Huangguang Chip 3: Utilizes AlInGaP quaternary material, with a peak wavelength of 560nm (covering the critical range of 530–600nm).

[0055] Red LED chip 4: AlInGaP material, peak wavelength 620nm

[0056] Employing a diamond pixel arrangement (BYGR unit cycle), with a minimum pixel pitch of 20μm.

[0057] The CsPbBr3 (green region) gradient transitions continuously to the CsPbI3 (red region), with a thickness of 3.2 μm.

[0058] In the bonding process, the LEDs are directly bonded to the surface of the Micro-LED array using vacuum lamination technology in a nitrogen glove box, with an interface porosity of <0.1%.

[0059] It should be noted that the quantum dots generate a Stokes shift after being excited by the Micro-LED, which converts the 450nm output of the blue light chip 1 to 460nm (after adjustment), while stabilizing the wavelength shift of other chips.

[0060] Furthermore, the signal processing flow of the neural drive module 30 is as follows:

[0061] The RGB input image is decomposed into three channels: R / G / B, and a time-series signal S is generated through pulse frequency modulation. j (t)(j=1,2,3).

[0062] Initialize a 4×4 synaptic weight matrix W, where W B3 =0.62 (blue light weight), W Y1 =0.41 (compensation for yellow light against red light).

[0063] Its current output satisfies:

[0064] I k =∑ j＝1 4 W kj ·S j (t) Generates four primary color driving currents with a delay of <2ms.

[0065] In this embodiment, a four-primary-color array (diamond-shaped arrangement, 20μm spacing) composed of blue (InGaN-based, 450nm), green (GaN-based, 535±2nm), yellow (AlInGaP-based, 560nm), and red (AlInGaP-based, 620nm) Micro-LED chips is used to achieve ±2nm wavelength stability. This is combined with a CsPbBr3-CsPbI3 gradient quantum dot stabilization layer (3.2μm thick, vacuum-pressed bonding). Furthermore, a four-primary-color driving module based on a pulse neural network (4×4 synaptic weight matrix, response latency <2ms) and a bio-optics adaptive engine 40 (real-time pupil monitoring and blue light suppression coefficient β calculated based on viewing time) are used to achieve 118% DCI-P3 color gamut coverage and 465±2nm low-harm blue light (B(λ)=1.2mW / cm²). 2 The technology achieves a Δu'v'<0.002 effect after 1000 hours of aging ( / sr), while reducing power consumption by 22% and visual fatigue index by 57%.

[0066] In one specific embodiment, the perovskite quantum stable layer 20 forms a continuous thin film with a thickness not exceeding 5 μm. After being continuously exposed to an aging environment at 85°C and 85% relative humidity for 1000 hours, the color coordinate offset Δu'v' of the Micro-LED array is less than 0.002.

[0067] Furthermore, the perovskite quantum dot stabilizing layer is formed into a continuous film of ≤5μm using an aerosol jet printing process (the thickness of traditional quantum dot layers is usually ≥15μm). This thickness design improves the light conversion efficiency to 92% while significantly reducing the internal stress of the film.

[0068] In one specific embodiment, the spiking neural network driving module:

[0069] Receive input image data in standard RGB format and convert the input image data into a pulse frequency modulation signal;

[0070] The four primary color driving currents are calculated using a programmable 4×4 synaptic weight matrix W, where the driving current Ik of the k-th primary color satisfies: Ik=∑j=14Wkj·Sj(t);

[0071] Output optimized four-primary-color drive current signals.

[0072] Furthermore, by converting standard RGB input data into a pulse sequence encoded according to the brightness ratio (maximum frequency 100kHz), and using a 4×4 synaptic weight matrix optimized by a genetic algorithm to achieve DCI-P3 color gamut coverage ≥97% and 6500K white point balance, and completing the drive current calculation within 10ns based on the ReRAM in-memory computing architecture, a comprehensive performance breakthrough was achieved, with the average color difference ΔE* reduced to 0.9, system power consumption only 0.28mW / kpixel, and support for a 480Hz refresh rate, keeping the motion image ghosting index below 0.8%.

[0073] Furthermore, in this embodiment, the luminance value (CjCj) of the standard RGB input data is encoded into a pulse frequency signal in a proportional manner. Color gamut expansion is achieved using a 4×4 synaptic weight matrix (WkjWkj) optimized by a genetic algorithm—where matrix elements are constrained by DCI-P3 coverage ≥ 97% and white point balance (∑Wk1·xk ≥ 0.704 ∑Wk1·xk ≥ 0.704 and: W·R:W·G:W·B:W·

[0074] Y = 0.30:0.59:0.11:0.00W·R:W·G:W·B:W·Y = 0.30:0.59:0.11:0.00), and based on the physical characteristics of the ReRAM in-memory computing architecture:

[0075] (Drive current Ik=VDD·∑jGkjIk=VDD·∑jGkj, conductance Gkj∝WkjGkj∝Wkj) The four primary color current calculations are completed within 10ns, ultimately achieving a synergistic optimization of average color difference ΔE*≤0.9, system power consumption of 0.28mW / kilopixel and 480Hz refresh rate. Its core lies in pulse event driving to reduce ineffective power consumption, while in-memory computing eliminates data transfer energy consumption, reducing the motion image ghosting index to 0.8%.

[0076] In one specific embodiment, the formula for calculating the partitioned blue light suppression coefficient β(x,y,t) is as follows:

[0077] β(x,y,t)=α·Apupil(x,y,t)Amax+(1-α)·e-tviewτ

[0078] Where α is the physiological weighting coefficient, and 0.5≤α≤0.8, Apupil is the real-time pupil area, Amax is the maximum pupil area, tview is the continuous viewing duration, and τ is the time decay constant, which satisfies: 1h≤τ≤3h.

[0079] Furthermore, the algorithm design for the partitioned blue light suppression coefficient β(x,y,t) is based on the human eye's biological rhythm and light adaptation mechanism. The real-time pupil area reflects the light intensity received by the retina (the smaller the pupil, the stronger the ambient light). It is sampled at 120Hz through infrared imaging, and α∈[0.5,0.8] is used to adjust the physiological signal weights.

[0080] The duration of continuous viewing triggers an exponential decay of blue light intensity. The decay constant τ∈[1,3]h matches the human melatonin secretion cycle. The weighted synthesis of these two factors achieves the adaptive logic of "enhancing blue light suppression in strong light environments and dynamically weakening blue light during long-term viewing".

[0081] In one specific embodiment, the spectral half-width of both the yellow light unit and the green light unit is ≤25nm, and a distributed Bragg reflector layer is provided between them to suppress spectral crosstalk.

[0082] Furthermore, the yellow light unit adopts the AlGaInP material system, and the tunable emission peak of 530-600nm is achieved by controlling the quantum well width. The green light unit is based on InGaN material, and the full width at half maximum (FWHM) is compressed to ≤25nm by stress-compensated epitaxy. The distributed Bragg reflector (DBR) is composed of 15 pairs of SiO2 / TiO2 alternating thin films, with a reflectivity >99.5%.

[0083] Furthermore, its crosstalk suppression mechanism is that the DBR layer is located between the yellow-green light units, its bandgap is designed to be 540-580nm, and the oblique evaporation process is used to extend the reflection angle to ±30°. Its unit spacing is optimized to less than 50μm, and with the help of the microlens array, it achieves a light extraction efficiency of more than 85%.

[0084] In one specific embodiment, the perovskite quantum dot stabilizing layer is formed using an aerosol jet printing process and has an Al2O3 / fluororesin dual-layer encapsulation structure.

[0085] Furthermore, the aerosol printing process and dual-layer encapsulation design, while ensuring the high optical performance of quantum dot films, significantly improve environmental stability and process feasibility, providing key technological support for the mass production of Micro-LED displays. In particular, the Al2O3 / fluororesin dual-layer structure achieves a water and oxygen barrier performance of 1.2 × 10⁻⁶. -6 g / m 2 / day.

[0086] In one specific embodiment, the synaptic weight matrix W is dynamically updated through pulse time-dependent plasticity rules, and the hardware implementation adopts a ReRAM-based in-memory computing architecture.

[0087] Furthermore, by deeply integrating the plasticity mechanism of biological neurons with the physical characteristics of memristors, a display driving system with self-learning capabilities was constructed. After 1000 hours of continuous operation, the system maintained a DCI-P3 color gamut coverage of 98.2% ± 0.3%, and power consumption exhibited a self-optimizing decrease of 5.7% over time, providing a hardware foundation for adaptive display systems. In particular, the analog computing characteristics of ReRAM devices enabled the energy consumption for color gamut conversion to be only 1 / 840th that of traditional digital circuits, offering significant advantages in low-power scenarios such as VR / AR.

[0088] In one specific embodiment, the bio-optical adaptive engine 40 further includes:

[0089] Millimeter-wave radar module is used to detect the user's distance and dynamically adjust the screen brightness accordingly;

[0090] A skin conductance sensor is used to monitor the user's fatigue state and trigger a reduction in blue light intensity.

[0091] Furthermore, a bio-physical dual-modal sensing network was constructed using the phase difference ranging principle (distance resolution ±1.5cm) of a 60GHz FMCW millimeter-wave radar and multi-band impedance detection (10Hz-1kHz) of skin conductance response (GSR). Based on a Bayesian probabilistic framework, the joint probability estimation of user distance and fatigue state was achieved, and the blue light suppression intensity was dynamically adjusted. Ultimately, while ensuring color fidelity of ΔE < 1.5, the visual fatigue index was reduced by 41% (verified by the PERCLOS standard), while maintaining adaptive display control with 98% DCI-P3 color gamut coverage.

[0092] In one specific embodiment, the perovskite quantum dot stabilizing layer further includes a calibration method:

[0093] After quantum dot film deposition, the actual emission wavelength λ_meas of each pixel region was measured;

[0094] Compare with the target wavelength λ_target;

[0095] When |λ_meas-λ_target|>3nm, a compensation current ΔI_k is injected through the neuromorphic driving module:

[0096] ΔI_k=η·(λ_meas-λ_target)·I_k

[0097] Where η is the wavelength-to-current conversion coefficient, and 0.05 ≤ η ≤ 0.1 nm-1 ,

[0098] The compensated emission wavelength is controlled within the range of λ_target±2nm.

[0099] Furthermore, by integrating a miniature fiber optic spectrometer to monitor the emission wavelength of the quantum dots in real time, the wavelength-to-current conversion coefficient η (0.05-0.1 nm) is dynamically adjusted based on a gradient descent optimization algorithm. -1 By combining the temperature compensation model λ_target(T)=λ0+κ(T-T0) (κ=0.03nm / ℃) with the aging compensation function η(t)=η0(1-0.02·e^(-t / 5000)), a fully closed-loop wavelength control system was constructed, ultimately achieving wavelength stability of ±1.3nm and white point shift of Δu'v'<0.001, enabling the quantum dot display to maintain 14-bit color depth accuracy and over 98.8% DCI-P3 color gamut coverage within a 50,000-hour working life.

[0100] Therefore, this application discloses an adaptive light field-controlled wide color gamut low blue light display system 100. By introducing a yellow light chip 3, it directly fills the gap in the yellow region of the RGB three primary colors in the CIE chromaticity diagram. Combined with the broad-spectrum coverage of the green light chip 2 and the red light chip 4, the color gamut is expanded. Furthermore, the perovskite quantum dot stabilizing layer, through gradient component design (CsPbBr3-CsPbI3), locks the Micro-LED wavelength offset within ±2nm, ensuring color accuracy. It is worth noting that its low blue light control logic sets the initial peak wavelength of the blue light chip 1 to 430-480nm, avoiding the harmful 415-455nm band. The bio-optical engine dynamically shifts the blue light peak and provides real-time feedback on the user's physiological state through pupil area. Furthermore, by combining the viewing duration attenuation factor to generate a β(x,y,t) coefficient, the blue light hazard index is ultimately reduced to the RG0 exemption level.

[0101] The embodiments described above are merely examples of several implementations of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the scope of protection of this application.

Claims

1. A wide color gamut low blue light display system with adaptive light field modulation, characterized in that, include: The four-primary-color Micro-LED array consists of independently packaged blue, green, yellow, and red LED chips, among which: The peak emission wavelength of the yellow light chip is 530–600 nm; A perovskite quantum stabilizing layer is directly attached to the light-emitting surface of the Micro-LED array. The stabilizing layer contains a CsPbBr3-CsPbI3 gradient quantum dot film, which is used to control the emission wavelength shift of the Micro-LED within ±2nm range. The neural drive module maps input image data into four primary color drive current signals through a spiking neural network. The bio-optics adaptive engine dynamically calculates the blue light suppression coefficient β(x,y,t) of each zone based on real-time pupil diameter data and viewing duration, and adjusts the peak wavelength of the blue light unit to 460–470nm accordingly.

2. The adaptive light field modulation wide color gamut low blue light display system according to claim 1, characterized in that, The perovskite quantum stable layer forms a continuous thin film with a thickness of no more than 5 μm. After being continuously exposed to an aging environment at 85°C and 85% relative humidity for 1000 hours, the color coordinate offset Δu'v' of the Micro-LED array is less than 0.

002.

3. The adaptive light field modulation wide color gamut low blue light display system according to claim 1, characterized in that, The spiking neural network driving module: Receive input image data in standard RGB format and convert the input image data into a pulse frequency modulation signal; The four primary color driving currents are calculated using a programmable 4×4 synaptic weight matrix W, where the driving current Ik of the k-th primary color satisfies: Ik=∑j=14Wkj·Sj(t); Output optimized four-primary-color drive current signals.

4. The adaptive light field modulation wide color gamut low blue light display system according to claim 1, characterized in that, The formula for calculating the blue light suppression coefficient β(x,y,t) of the partition is as follows: β(x,y,t)=α·Apupil(x,y,t)Amax+(1-α)·e-tviewτ Where α is the physiological weighting coefficient, and 0.5≤α≤0.8, Apupil is the real-time pupil area, Amax is the maximum pupil area, tview is the continuous viewing duration, and τ is the time decay constant, which satisfies: 1h≤τ≤3h.

5. The adaptive light field modulation wide color gamut low blue light display system according to claim 1, characterized in that, The spectral half-width of both the yellow and green light units is ≤25nm, and a distributed Bragg reflector layer is provided between them to suppress spectral crosstalk.

6. The adaptive light field modulation wide color gamut low blue light display system according to claim 2, characterized in that, The perovskite quantum dot stabilizing layer is formed using an aerosol jet printing process and has an Al2O3 / fluororesin dual-layer encapsulation structure.

7. The adaptive light field modulation wide color gamut low blue light display system according to claim 3, characterized in that, The synaptic weight matrix W is dynamically updated through pulse time-dependent plasticity rules, and the hardware implementation adopts a ReRAM-based in-memory computing architecture.

8. The adaptive light field modulation wide color gamut low blue light display system according to claim 1, characterized in that, The bio-optical adaptive engine also includes: Millimeter-wave radar module is used to detect the user's distance and dynamically adjust the screen brightness accordingly; A skin conductance sensor is used to monitor the user's fatigue state and trigger a reduction in blue light intensity.

9. A wide color gamut low blue light display system with adaptive light field modulation according to claim 2, characterized in that, The perovskite quantum dot stabilizing layer also includes a calibration method: After quantum dot film deposition, the actual emission wavelength λ_meas of each pixel region was measured; Compare with the target wavelength λ_target; When |λ_meas-λ_target|>3nm, a compensation current ΔI_k is injected through the neuromorphic driving module: ΔI_k=η·(λ_meas-λ_target)·I_k Where η is the wavelength-to-current conversion coefficient, and 0.05 ≤ η ≤ 0.1 nm -1 , The compensated emission wavelength is controlled within the range of λ_target±2nm.

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