Light source transition area gradient light-emitting display screen based on photonic crystal

Abstract

The invention provides a light source transition area gradient light-emitting display screen based on a photonic crystal, which relates to the technical field of display screens and comprises a photonic crystal substrate, a light source module, a driving module, a feedback module and a data processing control end, the photonic crystal substrate is a silicon-based and polymer-based two-dimensional photonic crystal and is installed on a core optical layer of the display screen, non-uniform periodic gradient structures are periodically distributed on the surface of the photonic crystal substrate, the periodic change range is 50-200 nanometers, and a point defect microcavity array, a chiral structure, a sub-wavelength columnar metasurface array and a waveguide bending structure are embedded in the substrate. Aiming at the defects in the aspect of light field regulation and control in the prior art, smooth gradual change of a light field at a sub-wavelength level is realized through the non-uniform periodic gradient structure (the period is 50-200 nanometers) of the photonic crystal substrate, the point defect microcavity array and the waveguide bending structure; the problem of abrupt change of light intensity caused by traditional pixel-level brightness adjustment is solved.

Description

Technical Field

[0001] This invention relates to the field of display technology, specifically to a gradient light-emitting display screen based on a photonic crystal in the light source transition region. Background Technology

[0002] With the widespread application of display technology in consumer electronics, medical imaging, and automotive dashboards, gradient light emission in the light source transition zone is a crucial element for improving visual comfort and display quality. Its smoothness and precision directly determine the screen's contrast, color reproduction, and user experience. In existing technologies, gradient light emission in the light source transition zone mainly employs pixel array-based brightness gradation control or simple optical modulation assisted by filters. This method is simple in structure and low in cost, and is currently the mainstream solution for LED and OLED displays. Meanwhile, researchers are also attempting to introduce backlight partitioning or software algorithms to simulate and optimize the light field, aiming to improve gradient parameters and enhance display effects through numerical means.

[0003] However, existing technologies still have the following problems:

[0004] First, in terms of light field control, traditional methods rely on pixel-level brightness adjustment, which leads to abrupt changes in light intensity in the transition zone and makes it impossible to achieve a smooth gradient at the subwavelength level. When the displayed content is complex, brightness jumps or blurred boundaries are likely to occur, affecting visual continuity.

[0005] Secondly, in terms of multidimensional control, existing systems lack coordinated optimization of chroma, polarization and phase, and only perform single brightness modulation. They cannot handle the light field distribution in dynamic scenes, resulting in uneven color or polarization distortion. Especially in flexible or transparent displays, they cannot adapt to bending or changes in ambient light.

[0006] Therefore, a gradient light-emitting display screen based on photonic crystals in the light source transition region is needed to solve the above problems. Summary of the Invention

[0007] Technical problems to be solved

[0008] To address the shortcomings of existing technologies, this invention provides a gradient light-emitting display screen with a light source transition region based on photonic crystals, thus solving the problems of existing technologies.

[0009] Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solution: a gradient light-emitting display screen based on a photonic crystal light source transition region, comprising a photonic crystal substrate, a light source module, a driving module, a feedback module, and a data processing control terminal;

[0011] The photonic crystal substrate is a silicon-based or polymer-based two-dimensional photonic crystal, which is installed in the core optical layer of the display screen. The surface has a non-uniform periodic gradient structure with a periodic variation range of 50 to 200 nanometers. The substrate contains a microcavity array with embedded point defects, a chiral structure, a subwavelength columnar metasurface array, and a waveguide bending structure. A thin film heater array is provided below the substrate.

[0012] The light source module consists of a broadband LED and a laser light source, which is installed at the input end of the display screen and coupled to the waveguide of the photonic crystal substrate via an optical fiber.

[0013] The driving module includes a piezoelectric actuator, a transparent electrode, a lithium niobate electro-optic modulator, a MEMS actuator, and a thin-film heater. The piezoelectric actuator is embedded inside the photonic crystal substrate for dynamically controlling the periodic gradient. The transparent electrode covers the surface of the microcavity array for controlling the microcavity resonant frequency. The lithium niobate electro-optic modulator is integrated into the waveguide and chiral structure region for controlling the optical path folding and polarization state. The MEMS actuator is distributed on the metasurface array for controlling the phase distribution. The thin-film heater array is mounted on the bottom of the substrate for controlling the thermal field distribution.

[0014] The feedback module includes a light intensity sensor, a polarization sensor, a phase sensor, and a temperature sensor, which are distributed at a spacing of 100 micrometers × 100 micrometers at the output end of the photonic crystal substrate, installed on the light field output layer of the display screen, and connected to the data processing control end via optical fiber.

[0015] The data processing control terminal is an integrated circuit module installed on the back panel of the display screen. It includes a piezoelectric drive circuit, an electro-optic drive circuit, a MEMS drive circuit, and a thermo-optic drive circuit. A display screen is provided at the bottom to display light field data, polarization data, and optimization reports.

[0016] Preferably, the photonic crystal substrate is manufactured using silicon-based photonic integration technology; the data processing control terminal includes a control system, the adjustment process of which includes a non-uniform periodic gradient modulation process, a microcavity array local enhancement process, a dynamic optical field folding optimization process, a spin photonic crystal polarization control process, a photonic crystal metasurface phase control process, an adaptive thermo-optical coupling optimization process, an optical field data acquisition process, an environmental interference correction process, and a resource dynamic allocation process, and all processes in the control system are executed through the data processing control terminal.

[0017] Preferably, the light field data acquisition process acquires light field intensity and polarization state data in the transition zone in real time through light intensity sensors and polarization sensors. The light intensity sensors and polarization sensors are arranged in an array with a spacing of 100 micrometers × 100 micrometers and transmitted to the data processing control terminal through optical fiber at a microsecond frequency. A dynamic sampling algorithm is used to optimize the sampling frequency according to the ambient light intensity and temperature.

[0018] The non-uniform periodic gradient modulation process interacts with the optical field data acquisition process, providing periodic modulation data to the adaptive thermo-optical coupling optimization process.

[0019] The microcavity array local enhancement process interacts with the optical field data acquisition process, providing resonant data to the adaptive thermo-optical coupling optimization process.

[0020] The dynamic light field folding optimization process interacts with the light field data acquisition process, providing optical path data to the adaptive thermo-optical coupling optimization process.

[0021] The spin photonic crystal polarization control process interacts with the optical field data acquisition process to provide polarization data to the adaptive thermo-optical coupling optimization process.

[0022] The photonic crystal metasurface phase modulation process interacts with the optical field data acquisition process, providing phase data to the adaptive thermo-optical coupling optimization process.

[0023] The environmental interference correction process interacts with the optical field data acquisition process, providing correction data to the adaptive thermo-optical coupling optimization process.

[0024] The adaptive thermo-optical coupling optimization process uses a weighted fusion algorithm to integrate period, resonance, optical path, polarization, phase, and correction data to optimize the optical field parameters in the transition region.

[0025] The dynamic resource allocation process interacts with all other processes to optimize resource allocation.

[0026] Preferably, the non-uniform periodic gradient modulation process dynamically adjusts the periodic distribution of the photonic crystal through a piezoelectric actuator, with the periodic variation range being 50 to 200 nanometers, generating a transition region optical field with an intensity gradient greater than 20%.

[0027] The non-uniform periodic gradient modulation process generates periodic tuning parameters through analysis of 30 days of historical light field data, supports online updates to adapt to ambient light intensity and display requirements, and is combined with a thin-film heater array to assist in periodic stability control.

[0028] Preferably, the microcavity array local enhancement process applies an electric field through transparent electrodes, modulates the refractive index change to be greater than 0.15, dynamically adjusts the microcavity resonant frequency, and generates local optical field enhancement, with a Q factor ranging from 1000 to 5000.

[0029] The microcavity array local enhancement process combines 7-day, 14-day, and 30-day optical field data analysis to dynamically optimize the microcavity resonance parameters, generating resonance data consisting of refractive index changes, resonant frequencies, light intensity, and Q-factor ranges for the adaptive thermo-optical coupling optimization process.

[0030] Preferably, the dynamic optical field folding optimization process adjusts the periodic refractive index gradient or waveguide bending structure within the photonic crystal using a lithium niobate electro-optic modulator, dynamically changing the optical path folding path length to generate a nonlinear optical field gradient, with a switching time of less than 500 nanoseconds.

[0031] The dynamic optical field folding optimization process optimizes folding parameters by analyzing 30 days of historical optical field data. It sends optical path data to 3F once per cycle, which includes path length and distribution values, and then transmits it to the adaptive thermo-optical coupling optimization process.

[0032] Preferably, the spin photonic crystal polarization modulation process uses a chiral photonic crystal structure and a lithium niobate electro-optic modulator to apply an electric field of less than 3 volts per micrometer, dynamically switching the polarization state from linear polarization to circular polarization.

[0033] The polarization control process analyzes 30 days of historical polarization data, optimizes polarization state parameters, generates polarization data containing polarization type and chromaticity distribution, and transmits it to the adaptive thermo-optical coupling optimization process.

[0034] Preferably, the photonic crystal metasurface phase modulation process adjusts the metasurface phase distribution through a subwavelength columnar metasurface array and a MEMS actuator, with the column height varying from 10 to 50 nanometers, generating a phase gradient greater than π / 2.

[0035] The metasurface phase modulation process analyzes 30 days of historical phase data, optimizes phase distribution parameters, generates phase data containing gradient and light intensity values, and transmits it to the adaptive thermo-optical coupling optimization process.

[0036] Preferably, the environmental interference correction process collects environmental data through temperature sensors, light intensity sensors, and humidity sensors, and updates the interference factor weights using a dynamic filtering algorithm, with initial weights of 0.45 for temperature, 0.35 for light intensity, and 0.2 for humidity.

[0037] The dynamic filtering algorithm optimizes the weight distribution through a 30-day learning cycle, supports interference correction across environmental changes, and transmits the correction results to the adaptive thermo-optical coupling optimization process.

[0038] Preferably, the adaptive thermo-optical coupling optimization process applies a local thermal field through a thin-film heater array, modulates the refractive index change of the photonic crystal to be greater than 0.1, and optimizes the photonic bandgap distribution;

[0039] The adaptive thermo-optical coupling optimization process analyzes 30 days of historical light field data to generate an optimization report that includes light intensity, colorimetry, and stability, supporting high-resolution display, flexible display, and transparent display scenarios.

[0040] The data processing control terminal uses a time series analysis algorithm to analyze the light field, polarization, and power consumption data of the past 30 days, and generates a performance report that includes the system's operating status and optimization suggestions. When the light field fluctuation exceeds 1.5%, an early warning is triggered and the resource allocation ratio is adjusted.

[0041] The resource dynamic allocation process receives real-time power consumption, computational latency, and data throughput data from each process. Based on 30 days of historical operating data, it uses a resource optimization algorithm to predict resource demand for the next 4 hours and dynamically adjusts the allocation ratio: 35% for the optical field data acquisition process, 20% for the non-uniform periodic gradient modulation process, and 15% for the microcavity array local enhancement process.

[0042] The resource optimization algorithm supports fault self-diagnosis. When a sensor fault is detected, the faulty module is automatically isolated, and a diagnostic report containing the fault type, scope of impact, and recovery suggestions is generated and transmitted to the data processing control terminal.

[0043] It should be noted that in each process, when transmitting data, it is best to ensure that the light does not jump around randomly, with fluctuations of less than 1% within 30 days, that is, to ensure stability.

[0044] Beneficial effects

[0045] This invention provides a gradient light-emitting display screen with a transition region based on a photonic crystal. It has the following advantages:

[0046] 1. This invention addresses the shortcomings of existing technologies in light field manipulation by employing a non-uniform periodic gradient structure (period 50 to 200 nanometers) on a photonic crystal substrate, a point-defect microcavity array, and a waveguide bending structure to achieve smooth, gradual changes in the light field at the subwavelength level. This overcomes the abrupt changes in light intensity caused by traditional pixel-level brightness adjustments. Under complex display content, the piezoelectric actuator dynamically adjusts the period to generate a transition zone light field with a light intensity gradient greater than 20%, avoiding brightness jumps and boundary blurring. This significantly improves visual continuity and image quality, making it particularly suitable for high-resolution display scenarios such as smartphone screens, enhancing the user's visual experience.

[0047] 2. To address the limitations of multidimensional modulation, this invention utilizes a chiral structure and a lithium niobate electro-optic modulator to synergistically control the polarization state, dynamically switching from linear polarization to circular polarization. Combined with a subwavelength cylindrical metasurface array and a MEMS actuator to optimize the phase distribution (gradient greater than π / 2), it achieves multidimensional synergistic modulation of chromaticity, polarization, and phase, resolving the color inhomogeneity and polarization distortion caused by single brightness modulation. In flexible or transparent displays, the thin-film heater array and environmental interference correction process adapt to bending or changes in ambient light, ensuring consistent light field distribution and meeting the adaptability requirements of wearable devices or augmented reality glasses. Attached Figure Description

[0048] Figure 1 This is a diagram showing the light field distribution of the photonic crystal display screen modulation control mechanism of the present invention.

[0049] Figure 2 This is a dynamic resource allocation diagram for the system of the present invention;

[0050] Figure 3 This is a light intensity fluctuation monitoring and early warning diagram of the present invention;

[0051] Figure 4 This is a partial intensity diagram of the present invention;

[0052] Figure 5 This is a system framework diagram of the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Specific Implementation Example 1:

[0055] like Figures 1 to 5 As shown, a photonic crystal-based gradient light-emitting display screen with a transition region includes a photonic crystal substrate, a light source module, a driving module, a feedback module, and a data processing control terminal.

[0056] This display utilizes the photonic bandgap, slow-light effect, localized field enhancement, and interference characteristics of photonic crystals to achieve ultra-smooth, multi-dimensional gradient light emission in the light source transition region. Through integrated hardware components and control system processes, combined with multi-physics field driving and closed-loop feedback mechanisms, it ensures dynamic control of light intensity, chromaticity, polarization, and phase, breaking through the pixel-level abrupt changes or simple brightness adjustment methods of traditional displays, such as pixel-by-pixel control, pulse width modulation, or filters. The system workflow begins with the light source input, undergoes multi-dimensional optical control of the photonic crystal substrate, is powered by the driving module, monitored in real-time by the feedback module, and the data processing control terminal executes algorithm optimization, ultimately outputting a smooth transition region light field to achieve high-resolution, flexible, or transparent display scenarios. The following details the composition, installation location, working principle of each structural component, as well as the execution method of the control process, data transmission, and utilization method, ensuring complete resource allocation.

[0057] Detailed description of system architecture components:

[0058] The core of the system consists of a photonic crystal substrate, a light source module, a driving module, a feedback module, and a data processing and control terminal. It is manufactured using silicon-based photonic integration technology, ensuring high precision, compact integration, and low power consumption, with total power consumption controlled below 50 milliwatts. The overall size of the display screen is less than 500 square millimeters, and it is divided into a core optical layer, an input terminal, a light field output layer, and a backplane layer. The installation positions of each component are clearly defined to ensure efficient collaboration.

[0059] Photonic crystal substrate:

[0060] The photonic crystal substrate is the optical core of the system. It is a two-dimensional photonic crystal based on silicon or polymer, with a thickness of 1 to 5 micrometers, and is fabricated using silicon-based photonic integration technology. The fabrication process includes substrate preparation on a silicon or polymer substrate, photolithography to define the periodic structure, chemical vapor deposition to embed optical elements, plasma etching to form the array, and chemical mechanical polishing to ensure flatness of less than 1 nanometer. A non-uniform periodic gradient structure is distributed on the substrate surface, with the period gradually changing from 50 nanometers in the central region to 200 nanometers at the edge, and the spacing changing by about 10 nanometers per millimeter. The light transmission efficiency is controlled by the spatial distribution of the photonic bandgap. The narrow bandgap in the central region results in high transmission efficiency, while the wide bandgap in the edge region suppresses light transmission, forming an initial light intensity gradient. A microcavity array with point defects is embedded inside the substrate. Point defects with a diameter of 200 to 500 nanometers are introduced into the periodic structure to form a high Q-factor resonant cavity with a Q-factor range of 1000 to 5000. The resonance effect amplifies the intensity of specific wavelengths of light, achieving localized optical field enhancement. Chiral structures are helical or asymmetric periodic arrays, ranging in size from 100 to 300 nanometers, with asymmetric apertures or spacing, supporting photon spin-orbit coupling and modulating polarization states, such as converting linear polarization to circular polarization. Subwavelength columnar metasurface arrays consist of columnar units, 10 to 50 nanometers high and 50 to 100 nanometers in diameter, which modulate the direction and intensity of light propagation through geometric phase control, creating a phase gradient greater than π / 2. Waveguide curved structures are curved waveguide paths with radii of 1 to 5 micrometers, utilizing periodic refractive index gradients to form multiple reflection paths and optimize the nonlinear optical field distribution. A transparent oxide thin-film heater array, made of indium tin oxide (ITO), 100 nanometers thick, is bonded to the bottom surface of the substrate and distributed in each micro-region with a spacing of 100 micrometers. It generates a localized thermal field through resistance heating, with temperature variations of 5 to 50 degrees Celsius, modulating the refractive index and optimizing thermo-optical coupling.

[0061] A photonic crystal substrate is mounted on the core optical layer of the display, located at the geometric center of the display and covering the entire display area, for example, 10 mm × 10 mm. It is fixed on the top and bottom by a 0.1 mm thick transparent glass or polymer protective layer. A point-defect microcavity array and chiral structure are embedded in the middle layer of the substrate at a depth of 0.5 to 1 micrometer. A subwavelength columnar metasurface array is distributed on the top surface of the substrate at a thickness of 0.2 micrometers. A waveguide bending structure is embedded in the bottom layer of the substrate at a depth of 1 to 2 micrometers. A thin-film heater array is attached to the bottom surface of the substrate and in direct contact with the backsheet layer to ensure efficient heat conduction. The substrate receives the optical signal input from the light source module, with a wavelength of 400 to 800 nanometers. An initial light intensity distribution is formed through a non-uniform periodic gradient. The microcavity array enhances the local light intensity, the chiral structure modulates the polarization state, the metasurface shapes the phase, the waveguide folds the optical path, and the thin-film heater fine-tunes the refractive index, ultimately outputting a multidimensional light field.

[0062] Light source module:

[0063] The light source module is a broadband LED or laser light source, covering wavelengths from 400 to 800 nanometers or monochromatic tunable wavelengths, with a power of 5 to 20 milliwatts. It adopts standard optoelectronic device packaging and has a size of approximately 1 mm × 1 mm. It is coupled to the waveguide of the photonic crystal substrate via an optical fiber with a refractive index-matched silicon-based waveguide of 50 micrometers in diameter, achieving a coupling efficiency greater than 80% and providing stable light input. The light source module is installed at the input end of the display screen, located on the left edge of the core optical layer. It is connected to the substrate waveguide port via 10 to 20 optical fibers arranged at a spacing of 100 micrometers. The optical fibers are fixed within an input end optical coupling slot with a depth of 0.5 mm to ensure efficient injection of the optical signal. The light source module emits a broadband or monochromatic light signal, which is transmitted through the optical fiber into the substrate waveguide, providing initial light energy for subsequent optical field modulation. The data processing control terminal adjusts the light source intensity via current control, with a current range of 0.1 to 1 milliamp to adapt to different display requirements.

[0064] Driver module:

[0065] The drive module comprises multiphysics drive elements with a total power consumption of 20 to 40 milliwatts, integrated into the core optical layer and backplane layer. The piezoelectric actuator, made of lead zirconate titanate (LZT), measures 50 μm × 50 μm and generates mechanical strain by applying a voltage of 0 to 5 volts, with deformation ranging from 1 to 10 nanometers, dynamically adjusting the substrate period. The transparent electrode is a 50-nanometer thick indium tin oxide (ITO) thin film, which modulates the resonant frequency by applying an electric field of 0 to 3 volts per micrometer to change the microcavity's refractive index. The lithium niobate electro-optic modulator, a 100 μm × 100 μm thin-film device, adjusts the refractive index through electro-optic effects, controlling optical path folding and polarization states. The MEMS actuator, a 50 μm × 50 μm micromechanical system, adjusts the metasurface pillar height by electrostatic or thermal actuation, varying from 10 to 50 nanometers, controlling the phase distribution. The thin-film heater array, a 100-nanometer thick ITO thin film, generates a thermal field through resistance heating, modulating the substrate's refractive index. Piezoelectric actuators are embedded in the middle layer of the photonic crystal substrate at a depth of 0.5 to 1 micrometer, arranged in an array with a spacing of 100 micrometers and aligned with the periodic structural units. Transparent electrodes cover the top layer of the substrate's microcavity array region with a coverage of more than 90%, and are bonded to the substrate surface through a deposition process. Lithium niobate electro-optic modulators are integrated into the waveguide and chiral structure region inside the substrate at a depth of 1 to 2 micrometers, with their paths defined by photolithography. MEMS actuators are distributed on the top layer of the substrate's metasurface array, with one actuator installed below each columnar unit. A thin-film heater array is bonded to the bottom surface of the substrate, located between the core optical layer and the backplane layer, ensuring efficient heat conduction. These driving elements are powered and controlled by the driving circuitry of the data processing control terminal, enabling multi-physics field coordinated modulation.

[0066] Feedback module:

[0067] The feedback module comprises a light intensity sensor, a polarization sensor, a phase sensor, and a temperature sensor, employing silicon photodiodes, polarization-sensitive photodetectors, interferometric detectors, and thermistors, respectively. These sensors are arrayed at a 100μm × 100μm spacing at the output end of the photonic crystal substrate and mounted on the light field output layer of the display screen. The total number of sensors ranges from 100 to 1000, depending on the screen size. The light intensity sensor has a resolution of 0.1%, the polarization sensor has a resolution of 1 degree, the phase sensor has a resolution of π / 100, and the temperature sensor has a resolution of 0.1 degrees Celsius. It monitors the light field output data in real time and connects to the data processing control unit via a 50μm diameter optical fiber, achieving microsecond-level transmission rates and closed-loop feedback. The feedback module is mounted on the light field output layer atop the core optical layer, adjacent to the substrate output end. The sensor array is fixed to the surface of the output layer using photolithography and deposition processes, directly contacting the protective layer to ensure efficient light signal capture.

[0068] Data processing control terminal:

[0069] The data processing control unit is an integrated circuit module mounted on the backplane layer of the display screen, located below the core optical layer. It includes piezoelectric drive circuits, electro-optic drive circuits, MEMS drive circuits, and thermo-optic drive circuits, which control the piezoelectric voltage, electric field strength, actuation signal, and heating current, respectively. A small display screen with a resolution of 320×240 is located at the bottom of the backplane layer, used to display light field data, polarization data, and optimization reports. The data processing control unit uses an embedded processor, such as a field-programmable gate array (FPGA), to execute algorithms, process sensor data, and generate drive signals, with a total power consumption of less than 10 milliwatts. The data processing control unit is connected to the drive module via an internal circuit bus and to the feedback module via optical fiber. It is integrated on the circuit board of the backplane layer, measuring approximately 5 mm × 5 mm and 0.5 mm thick, and is fixed using an adhesive process to ensure stable signal transmission.

[0070] The photonic crystal substrate is manufactured using silicon-based photonic integration technology to ensure high-precision integration. The data processing and control unit executes nine processes through the hardware of the drive module and feedback module: non-uniform periodic gradient modulation, microcavity array local enhancement, dynamic optical field folding optimization, spin photonic crystal polarization control, photonic crystal metasurface phase control, adaptive thermo-optical coupling optimization, optical field data acquisition, environmental interference correction, and dynamic resource allocation. The data transmission method is that the raw data collected by the sensor is transmitted to the data processing and control unit through optical fiber at a microsecond rate. The data processing and control unit uses this data to perform algorithm processing, generates an optimized signal, and feeds it back to the drive module through the circuit bus to realize the gradual output of the optical field.

[0071] Detailed explanation of system control process:

[0072] The control system comprises nine coordinated processes, all executed through a data processing control terminal. Data transmission utilizes fiber optics and a circuit bus. The feedback module's sensors collect raw data on light intensity, polarization, phase, and temperature, transmitting this data via fiber optics to the data processing control terminal. The terminal stores 30 days of historical data in its internal memory, combines this data with real-time data for algorithmic analysis, generates optimized parameters, and feeds them back to the drive module via the circuit bus, forming a closed-loop control system to ensure a smooth, multi-dimensional light field output in the transition zone.

[0073] Non-uniform periodic gradient modulation process:

[0074] The data processing control unit receives real-time light intensity data from the light field data acquisition process and analyzes the current light intensity gradient. If the gradient is less than 20%, the data processing control unit combines 30 days of historical light field data analysis to generate periodic tuning parameters. A voltage of 0 to 5 volts is applied to the piezoelectric actuator via a piezoelectric drive circuit to generate mechanical strain, adjusting the period of the photonic crystal substrate from 50 nanometers to 200 nanometers, forming a transition region light field with a light intensity gradient greater than 20%. The periodic modulation data, including the change and gradient value, interacts with the light field data acquisition process and is transmitted to the data processing control unit via a circuit bus, providing it to the adaptive thermo-optical coupling optimization process for global fusion. The thin-film heater array applies current through a thermo-optical drive circuit to control temperature changes from 5 to 50 degrees Celsius, assisting in periodic stability. The response time is less than 100 microseconds, supporting online parameter updates to adapt to ambient light intensity and display requirements.

[0075] Microcavity array local enhancement process:

[0076] The data processing control unit acquires local light intensity data from the light field data acquisition process. If the enhancement is insufficient, it analyzes historical light field data from 7, 14, and 30 days to calculate the electric field intensity signal. Modulating the refractive index change to be greater than 0.15, an electric field of 0 to 3 volts per micrometer is applied to the transparent electrode via an electro-optic drive circuit. This adjusts the microcavity resonant frequency, with a Q factor ranging from 1000 to 5000, generating local light field enhancement. The resonant data, including refractive index change, resonant frequency, light intensity value, and Q factor range, interacts with the light field data acquisition process and is transmitted to the data processing control unit via a circuit bus. This data is then provided to the adaptive thermo-optical coupling optimization process for multi-dimensional fusion, generating control results that include light intensity, wavelength range, and stability.

[0077] Dynamic light field folding optimization process:

[0078] The data processing control unit analyzes 30 days of historical light field data. If the nonlinear gradient is not smooth, it calculates the electric field signal and applies it to the lithium niobate electro-optic modulator via an electro-optic drive circuit. This adjusts the periodic refractive index gradient within the photonic crystal or the waveguide bending structure, changing the optical path folding path length. The switching time is less than 500 nanoseconds, generating a nonlinear light field gradient. The optical path data, including path length and distribution values, interacts with the light field data acquisition process and is transmitted to the data processing control unit via a circuit bus. This data is then provided to the adaptive thermo-optic coupling optimization process, generating control results that include light intensity distribution, nonlinear gradient, and stability.

[0079] Spin photonic crystal polarization modulation process;

[0080] The data processing control unit acquires data from the polarization sensor and analyzes it in conjunction with 30 days of historical polarization data. If the polarization switching is not optimized, and the applied electric field is less than 3 volts per micrometer, the lithium niobate electro-optic modulator is adjusted via an electro-optic drive circuit. Combined with the chiral photonic crystal structure, the polarization state is dynamically switched from linear polarization to circular polarization. The polarization data, including polarization type and chromaticity distribution, interacts with the light field data acquisition process and is transmitted to the data processing control unit via a circuit bus. This data is then provided to the adaptive thermo-optic coupling optimization process for chromaticity enhancement, generating control results that include polarization type, light intensity, and chromaticity distribution.

[0081] Phase modulation process of photonic crystal metasurface:

[0082] The data processing control unit analyzes 30 days of historical phase data. If the phase distribution is not fine, it calculates an actuation signal, applies it to the MEMS actuator via a MEMS driving circuit, and adjusts the height of the subwavelength columnar metasurface array by 10 to 50 nanometers to generate a phase gradient greater than π / 2. The phase data, including gradient and light intensity values, interacts with the optical field data acquisition process and is transmitted to the data processing control unit via a circuit bus. This data is then provided to the adaptive thermo-optical coupling optimization process to generate control results that include phase, light intensity, and stability.

[0083] Environmental interference correction process:

[0084] The data processing control unit collects environmental data through temperature, light intensity, and humidity sensors. It employs a dynamic filtering algorithm to update the weights of interference factors, with initial weights of 0.45 for temperature, 0.35 for light intensity, and 0.2 for humidity. The weight distribution is optimized through a 30-day learning cycle to correct environmental interference in the light field data, such as refractive index shifts caused by temperature changes. The corrected data interacts with the light field data acquisition process and is transmitted via fiber optic cable to the data processing control unit, providing support for an adaptive thermo-optical coupling optimization process that enables correction across environmental variations.

[0085] Adaptive thermo-optical coupling optimization process:

[0086] The data processing control unit employs a weighted fusion algorithm to integrate periodic, resonance, optical path, polarization, phase, and correction data. Combined with 30 days of historical light field data analysis, it calculates the heating signal, which is applied to the thin-film heater array via a thermo-optical driving circuit. This generates a localized thermal field, modulating a refractive index change greater than 0.1, thus optimizing the photon bandgap distribution. The fused data generates an optimization report, supporting high-resolution, flexible, or transparent display scenarios. This report is transmitted to the data processing control unit via a circuit bus, ensuring optimal output of light intensity, color, and stability.

[0087] Light field data acquisition process:

[0088] Light intensity and polarization sensors are distributed at a 100 μm × 100 μm spacing on the light field output layer to collect real-time data on light field intensity and polarization state in the transition zone. A dynamic sampling algorithm optimizes the sampling frequency based on ambient light intensity and temperature. The data is transmitted to the data processing control terminal via optical fiber at microsecond-level frequencies. The collected data is used for feedback optimization in various processes and interacts with other processes via a circuit bus, providing real-time light field information.

[0089] Dynamic resource allocation process:

[0090] The data processing control unit receives real-time power consumption, computational latency, and data throughput data for each process. It employs a resource optimization algorithm based on 30 days of historical operating data to predict resource requirements for the next 4 hours, dynamically adjusting the allocation ratio to ensure a total of 100% allocation: 35% for the optical field data acquisition process, 20% for the non-uniform periodic gradient modulation process, 15% for the microcavity array local enhancement process, 10% for the dynamic optical field folding optimization process, 8% for the spin photonic crystal polarization modulation process, 7% for the photonic crystal metasurface phase modulation process, 3% for the adaptive thermo-optical coupling optimization process, and 2% for the environmental interference correction process. The algorithm supports fault self-diagnosis, automatically isolating modules when sensor faults are detected and generating a diagnostic report containing the fault type, impact range, and recovery suggestions, which is transmitted to the data processing control unit's display screen via the internal bus. The resource allocation ratio is dynamically adjusted according to the computational complexity and real-time requirements of each process. For example, optical field data acquisition requires more resources due to high-frequency sampling, while thermo-optical coupling optimization requires fewer resources due to global fusion. The algorithm ensures balanced allocation and optimizes system efficiency by analyzing historical power consumption and latency data. Specific Implementation Example 2:

[0092] like Figures 1 to 5 As shown, the control system of this display relies on the collaborative work of multiple algorithms, including dynamic sampling, weighted fusion, time series analysis, dynamic filtering, and resource optimization algorithms, to ensure ultra-smooth, multi-dimensional gradual control of light field intensity, chromaticity, polarization, and phase. These algorithms run at the data processing control end, processing sensor data and historical data from the feedback module to generate optimized signals to drive the hardware module, achieving dynamic optimization of the light field in the transition zone. The following details the input data, output results, specific calculation steps, and applications of each algorithm in the system:

[0093] Dynamic sampling algorithm:

[0094] Input data: Real-time light field intensity and polarization state data collected by light intensity sensor and polarization sensor, ambient light intensity and temperature data, and historical light field data for 30 days.

[0095] Output: Optimized sensor sampling frequency, ranging from 1 microsecond to 100 microseconds.

[0096] Calculation steps: The data processing control unit receives real-time light field data transmitted via optical fiber from the light intensity sensor and polarization sensor. It analyzes changes in ambient light intensity and temperature, and combines this with 30 days of historical light field data to assess the light field fluctuation trend. If the ambient light intensity change is greater than 10% or the temperature change is greater than 5 degrees Celsius, the algorithm increases the sampling frequency to capture rapid changes; if the light field is stable, the algorithm decreases the frequency to reduce power consumption. The algorithm calculates the fluctuation threshold based on historical data and adjusts the sampling interval to ensure data acquisition accuracy and efficiency.

[0097] System Application: This algorithm is applied to the optical field data acquisition process, optimizing the sampling frequency of the light intensity sensor and polarization sensor. The sensors are distributed in the optical field output layer at a spacing of 100 μm × 100 μm. The data is transmitted to the data processing control terminal at a microsecond rate through optical fiber. This provides real-time input for non-uniform periodic gradient modulation, microcavity array local enhancement, dynamic optical field folding optimization, spin photonic crystal polarization control, photonic crystal metasurface phase control, and adaptive thermo-optical coupling optimization processes, ensuring the dynamic response of optical field control.

[0098] Weighted fusion algorithm:

[0099] Input data: periodic modulation data (period variation and light intensity gradient), resonance data (Q factor and local light intensity), optical path data (folding path length and distribution), polarization data (polarization type and chromaticity distribution), phase data (phase gradient and light intensity), environmental correction data (temperature, light intensity, humidity weights), and 30-day historical light field data.

[0100] Output results: Optimized light field parameters, including light intensity, chromaticity, polarization, and phase distribution.

[0101] Calculation Steps: The data processing control unit receives data transmitted from each process via the circuit bus and integrates period, resonance, optical path, polarization, phase, and correction data. The algorithm analyzes 30 days of historical light field data to determine the contribution weight of each data point to light field optimization. The initial weights are: period 0.3, resonance 0.2, optical path 0.15, polarization 0.15, phase 0.1, and correction 0.1. The weights are dynamically adjusted based on real-time light field fluctuations; for example, the period weight is increased when the light intensity gradient is less than 20%, and the polarization weight is increased when the chromaticity deviation is greater than 5%. The algorithm fuses the data to generate an optimization signal, which is sent to the drive module to adjust the refractive index and optical path distribution of the photonic crystal substrate.

[0102] System Application: This algorithm is applied to the adaptive thermo-optical coupling optimization process, integrates multi-dimensional data, optimizes the photon bandgap distribution, applies a local thermal field through a thin-film heater array, modulates the refractive index change to be greater than 0.1, generates a smooth light field output, supports high-resolution, flexible or transparent display scenarios, and the optimized signal is transmitted to the drive module through the circuit bus.

[0103] Time series analysis algorithms:

[0104] Input data: 30 days of historical light field, polarization and power consumption data, and real-time light field fluctuation data.

[0105] Output: Performance report, including system running status, optimization suggestions, and warning signals.

[0106] Calculation steps: The data processing control unit stores 30 days of historical data in its internal memory, analyzes the time-series trends of light field, polarization, and power consumption, and identifies periodic fluctuations and anomalies. If the real-time light field fluctuation exceeds 1.5%, the algorithm triggers an alert and generates a report containing the cause of the fluctuation and adjustment suggestions. The algorithm predicts light field stability based on historical data, calculates optimization parameters, such as adjusting the voltage or current of the drive module, and sends them to the drive circuit. The report is visualized on a backplane display screen with a resolution of 320×240.

[0107] System Application: This algorithm is applied to the data processing control terminal to monitor system operation status, generate performance reports, trigger early warnings, and adjust resource allocation ratios to ensure optical field stability. Report data is transmitted via the internal bus to the dynamic resource allocation process, optimizing resource allocation across each process.

[0108] Dynamic filtering algorithm:

[0109] Input data: Real-time environmental data (temperature, light intensity, humidity) collected by temperature sensor, light intensity sensor and humidity sensor, 30 days of historical environmental data, and initial interference factor weights (temperature 0.45, light intensity 0.35, humidity 0.2).

[0110] Output: Optimized interference factor weights, corrected light field data.

[0111] Calculation Steps: The data processing control unit receives environmental data transmitted from the sensor via optical fiber and analyzes the interference of temperature, light intensity, and humidity changes on the light field, such as refractive index shift caused by temperature changes. Based on 30 days of historical data, the algorithm optimizes the weight distribution through a learning cycle. The initial weights are 0.45 for temperature, 0.35 for light intensity, and 0.2 for humidity. When temperature fluctuations exceed 5 degrees Celsius, the temperature weight is increased; when ambient light intensity changes exceed 10%, the light intensity weight is increased. The algorithm corrects interference in the light field data, generates corrected data, and transmits it to the adaptive thermo-optical coupling optimization process.

[0112] System Application: This algorithm is applied to the environmental interference correction process to correct the impact of the environment on the light field data. The data is transmitted to the data processing control terminal through optical fiber and provided to the adaptive thermo-optical coupling optimization process to ensure the stability of the light field output. It is suitable for display scenarios with changing environments.

[0113] Resource optimization algorithms:

[0114] Input data: Real-time power consumption, computational latency, and data throughput data for each process, and 30 days of historical operation data.

[0115] Output results: Resource allocation ratio (total 100%), including optical field data acquisition process 35%, non-uniform periodic gradient modulation process 20%, microcavity array local enhancement process 15%, dynamic optical field folding optimization process 10%, spin photonic crystal polarization control process 8%, photonic crystal metasurface phase control process 7%, adaptive thermo-optical coupling optimization process 3%, environmental interference correction process 2%, and fault diagnosis report.

[0116] Calculation steps: The data processing control terminal receives real-time power consumption, latency, and throughput data from each process, transmits them via the circuit bus, and predicts resource requirements for the next 4 hours based on 30 days of historical operating data. The algorithm analyzes the computational complexity and real-time requirements of each process and allocates resources accordingly: 35% for optical field data acquisition due to high-frequency sampling; 20% for non-uniform periodic gradient modulation due to high-precision mechanical drive; 15% for microcavity array local enhancement due to electric field modulation; 10% for dynamic optical field folding optimization; 8% for spin photonic crystal polarization modulation; 7% for photonic crystal metasurface phase modulation; 3% for adaptive thermo-optical coupling optimization due to global fusion; and 2% for environmental interference correction due to simple processing. If a sensor fault is detected, the algorithm automatically isolates the faulty module, generates a diagnostic report containing the fault type, impact range, and recovery suggestions, and transmits it to the backplane display via the internal bus.

[0117] System Application: This algorithm is applied to the dynamic resource allocation process, optimizing resource allocation in each process to ensure efficient system operation and reduce power consumption. The diagnostic report supports self-diagnosis of faults; data is transmitted to the data processing control terminal via the internal bus, optimizing signal feedback to the drive module, and adjusting the operating status of the photonic crystal substrate, drive module, and feedback module. Specific Implementation Example 3:

[0119] like Figures 1 to 5 As shown, the following is the hardware composition and description of a photonic crystal-based gradient light-emitting display screen in the light source transition region:

[0120] The photonic crystal substrate, light source module, driving module, feedback module, and data processing control terminal constitute the hardware core of the system. Manufactured using silicon-based photonic integration technology, the overall size is less than 500 square millimeters, and the total power consumption is controlled within 50 milliwatts. The display screen is divided into a core optical layer, an input terminal, a light field output layer, and a backplane layer. The hardware installation positions of each module are clearly defined to ensure efficient collaboration. The photonic crystal substrate is the optical core of the system, employing a silicon-based or polymer-based two-dimensional photonic crystal, such as polymethyl methacrylate, with a thickness of 1 to 5 micrometers. It is manufactured using silicon-based photonic integration technology, which includes substrate preparation, photolithography to define the periodic structure, chemical vapor deposition to embed optical elements, plasma etching to form the array, and chemical mechanical polishing to ensure a flatness of less than 1 nanometer.

[0121] A non-uniform periodic gradient structure is distributed on the substrate surface, with the period gradually changing from 50 nm in the central region to 200 nm at the edge. The spacing varies by approximately 10 nm per millimeter. The light transmission efficiency is modulated by the spatial distribution of the photonic bandgap. The narrow bandgap in the central region results in high transmission efficiency, while the wide bandgap in the edge region suppresses light transmission, forming an initial light intensity gradient. An array of point-defect microcavities is embedded within the substrate. Point defects are formed by removing or modifying periodic units in the periodic structure. The material is silicon or polymer, constituting a high Q-factor resonant cavity with a Q-factor ranging from 1000 to 5000. This amplifies the intensity of specific wavelengths of light through resonance, achieving localized optical field enhancement, for example, increasing the intensity of a specific wavelength of light to 2 to 5 times its original value.

[0122] The chiral structure is a periodic spiral hole array or an asymmetric hole array, made of silicon. Specifically, the structure consists of spiral holes etched in the substrate with a spiral period of 100 nanometers, a depth of 0.5 micrometers, and a diameter of 50 to 100 nanometers per hole, or an asymmetric hole array with a hole spacing variation of 10 to 50 nanometers and a hole diameter variation of 20 to 80 nanometers. It is formed by photolithography and dry etching, which supports photon spin-orbit coupling, modulates the photon spin state, and changes the polarization characteristics of the light propagation path, such as converting linear polarization into circular or elliptical polarization, thereby enhancing chromaticity and light field uniformity.

[0123] Subwavelength columnar metasurface arrays consist of columnar units made of silicon or silicon dioxide, with column heights of 10 to 50 nanometers, diameters of 50 to 100 nanometers, and column spacing of 100 nanometers. These are formed into a regular array using photolithography and plasma etching. Geometric phase modulation is used to control the direction and intensity of light propagation, creating a phase gradient greater than π / 2 for fine shaping of the optical field. The waveguide bending structure is a silicon-based bent waveguide path with a radius of 1 to 5 micrometers, a width of 100 to 200 nanometers, and a depth of 1 to 2 micrometers. The path shape is defined by photolithography and dry etching, utilizing periodic refractive index gradients to form multiple reflection paths and optimize the nonlinear optical field distribution, such as achieving optical path folding to enhance light intensity uniformity.

[0124] A transparent oxide thin-film heater array, made of indium tin oxide, is bonded to the bottom surface of the substrate. The thickness is 100 nanometers, and the resistivity is approximately 10⁻⁻⁴. 4 Ohmic centimeters are distributed in each micro-region with a spacing of 100 micrometers. Each heating unit measures 100 micrometers × 100 micrometers. Localized thermal fields are generated through resistance heating, with temperature variations ranging from 5 to 50 degrees Celsius. The refractive index of the substrate is modulated, for example, by changing the refractive index from 0.1 to 0.15, to achieve optimized thermo-optical coupling. The photonic crystal substrate is mounted on the core optical layer of the display, located at the geometric center, covering the entire display area, for example, 10 mm × 10 mm. It is fixed on the top and bottom by a 0.1 mm thick transparent glass or polymer protective layer. A point defect microcavity array and chiral structure are embedded in the middle layer of the substrate at a depth of 0.5 to 1 micrometer. A subwavelength columnar metasurface array is distributed on the top surface of the substrate at a thickness of 0.2 micrometers. A waveguide curved structure is embedded in the bottom layer of the substrate at a depth of 1 to 2 micrometers. A thin-film heater array is attached to the bottom surface of the substrate and is in direct contact with the backsheet layer to ensure efficient heat conduction. The substrate receives the light signal input from the light source, with a wavelength of 400 to 800 nanometers. The initial light intensity distribution is formed through a non-uniform periodic gradient. The local light intensity is enhanced by a microcavity array, the polarization state is controlled by a chiral structure, the phase is shaped by a metasurface, the optical path is folded by a waveguide, the refractive index is finely adjusted by a thin-film heater, and a multidimensional light field is output.

[0125] The light source module employs a broadband LED or laser light source, covering wavelengths from 400 to 800 nanometers or monochromatic tunable wavelengths, with a power of 5 to 20 milliwatts. The hardware components include a light-emitting chip, a collimating lens, and a fiber coupler. The light-emitting chip is a gallium arsenide-based LED or a semiconductor laser, approximately 0.5 mm × 0.5 mm in size, with an output optical power of 5 to 20 milliwatts. The collimating lens is made of glass, 0.5 mm in diameter, with a focal length of 1 mm, and is made of borosilicate glass, such as Edmund Optics #63-222, to ensure beam concentration. The fiber coupler is made of silicon and contains 10 to 20 fibers, 50 micrometers in diameter, with a refractive index of 1.45 to 1.5, matched to silicon waveguides, with a coupling efficiency greater than 80%, such as Corning SMF-28 fiber. The light source module is installed at the input end of the display screen, located on the left edge of the core optical layer, and fixed to a metal bracket made of aluminum alloy, measuring 2 mm × 2 mm and 0.5 mm thick. The fiber array is spaced 100 micrometers apart and connected to the substrate waveguide port. It is fixed within the input end optical coupling groove, which is 0.5 mm deep, and bonded with epoxy resin to ensure efficient injection of the light signal. The light source module emits a broadband or monochromatic light signal, which is transmitted through the fiber optic cable into the substrate waveguide, providing initial light energy. The data processing control terminal adjusts the light source intensity through a current control circuit, with a current range of 0.1 to 1 mA and a response time of less than 1 microsecond, adapting to different display requirements, such as high brightness or low power consumption scenarios.

[0126] The driving module comprises multiphysics driving elements, which control the optical properties of the photonic crystal substrate through electrophysical, mechanical, and thermophysical fields. Specifically, it includes piezoelectric actuators, transparent electrodes, lithium niobate electro-optic modulators, MEMS actuators, and a thin-film heater array, with a total power consumption of 20 to 40 milliwatts, integrated into the core optical layer and backplane layer. The piezoelectric actuators, made of lead zirconate titanate, are embedded in the middle layer of the substrate through deposition and photolithography at a depth of 0.5 to 1 micrometer, arranged in an array with a 100-micrometer spacing, aligned with the periodic structural units. Applying a voltage of 0 to 5 volts generates mechanical strain with a deformation of 1 to 10 nanometers, adjusting the substrate's periodic structure, for example, changing the period by 5 to 10 nanometers, thus controlling the light intensity gradient, with a response time of less than 50 microseconds. The transparent electrodes are indium tin oxide thin films with a resistivity of approximately 10⁻⁻⁻⁶. 4 The first type of microcavity modulator, with an ohm-cm thickness of 50 nm and a transmittance greater than 90%, is deposited by sputtering to cover the top layer of the substrate microcavity array region, achieving a coverage of greater than 90%. An electric field of 0 to 3 V per micrometer is applied to change the refractive index of the microcavity, for example, by changing the refractive index from 0.15 to 0.2, thereby controlling the resonant frequency. The Q-factor ranges from 1000 to 5000, and the response time is less than 100 nanoseconds. The second type, a lithium niobate electro-optic modulator, is a single-crystal lithium niobate thin-film device, such as an MTI CorporationLN thin film, with dimensions of 100 μm × 100 μm and a thickness of 0.3 μm. The electro-optic coefficient is approximately 30 pm / V. It is integrated into the substrate waveguide and chiral structure region through photolithography and dry etching, at a depth of 1 to 2 μm. An electric field of 0 to 3 V per micrometer is applied to adjust the refractive index, for example, by changing the refractive index from 0.1 to 0.15, thereby controlling the optical path folding path and polarization state, for example, achieving linear polarization to circular polarization conversion, with a response time of less than 500 nanoseconds. MEMS actuators are silicon-based micromechanical systems, such as the Texas Instruments DLP series micromirror actuators, measuring 50 μm × 50 μm. They include cantilever beams and electrostatic drive electrodes. The beams are 50 μm long and 0.1 μm thick, made of polycrystalline silicon, and distributed on the top layer of a metasurface array on a substrate using photolithography and sacrificial layer processes. An actuator is mounted beneath each pillar unit. A voltage of 0 to 5 volts is applied to adjust the pillar height, ranging from 10 to 50 nanometers, thus controlling the phase distribution, for example, generating a phase gradient greater than π / 2. The response time is less than 1 microsecond. The thin-film heater array is made of indium tin oxide (ITO) film with a resistivity of approximately 10⁻⁻⁻⁻⁶. 4The heating elements, each 100 nanometers thick and mounted on the bottom surface of the substrate, are located between the core optical layer and the backplane layer. Each heating unit measures 100 micrometers × 100 micrometers with a spacing of 100 micrometers. They generate a thermal field by applying a current of 0.1 to 1 milliampere, resulting in temperature variations of 5 to 50 degrees Celsius and modulating the substrate's refractive index, for example, by a variation of 0.1 to 0.15. These driving elements are powered and controlled by a driving circuit in the data processing control terminal. The piezoelectric driving circuit uses a pulse width modulation chip, such as the TIDRV2700, outputting a voltage of 0 to 5 volts; the electro-optic driving circuit uses a high-precision voltage source, such as the Keithley2400, outputting an electric field of 0 to 3 volts per micrometer; the MEMS driving circuit uses an electrostatic driving chip, such as the TIDLPC3470, outputting a voltage of 0 to 5 volts; and the thermo-optic driving circuit uses a current source, such as the ThorlabsITC4001, outputting a current of 0.1 to 1 milliampere. All of these are integrated into the backplane layer circuit board, ensuring coordinated control of multiple physical fields.

[0127] The feedback module comprises 100 to 1000 light intensity sensors, polarization sensors, phase sensors, and temperature sensors, depending on the display size, arrayed in a 100 μm × 100 μm spacing on the light field output layer. The light intensity sensor is a silicon-based photodiode, such as the Hamamatsu S1336, with a size of 50 μm × 50 μm, a sensitivity of 0.5 A / W, and a resolution of 0.1%. It is photolithographically fixed to the surface of the output layer and detects the light field intensity, for example, measuring light intensity changes in the 400 to 800 nm wavelength range. The polarization sensor is a polarization-sensitive photodetector, including a polarization beam splitter and a photodiode, such as the Thorlabs PBS101, with a size of 50 μm × 50 μm and a resolution of 1 degree. It detects the polarization state, for example, distinguishing between linear and circular polarization. The phase sensor is a silicon-based Mach-Zend interferometer, with a size of 100 μm × 100 μm and a resolution of π / 100. It measures the phase difference through interference fringes, for example, detecting changes in the phase of the optical path. The temperature sensor is a thermistor made of oxide ceramic, such as VishayNTCLE100E3, with a size of 50 μm × 50 μm and a resolution of 0.1 degrees Celsius. It detects localized temperatures, such as measuring changes in the surface temperature of a substrate. The sensor is fixed to the light field output layer on top of the core optical layer using photolithography and deposition processes, adjacent to the substrate output end, and in contact with a 0.1 mm thick transparent protective layer. It is connected to the data processing and control end via a 50 μm diameter optical fiber, such as Corning SMF-28, with a transmission rate in the microsecond range, achieving closed-loop feedback.

[0128] The data processing control unit is an integrated circuit module, comprising an embedded processor, driver circuitry, and a display unit, mounted on the backplane layer of the display screen, located below the core optical layer. The embedded processor is a field-programmable gate array (FPGA), such as the Xilinx Zynq-7000, measuring 3 mm × 3 mm, with a processing frequency of 100 MHz and power consumption of less than 5 milliwatts, responsible for algorithm execution and data processing. The driver circuitry includes a piezoelectric driver circuit using a pulse width modulation chip, such as the TIDRV2700, outputting 0 to 5 volts; an electro-optic driver circuit using a high-precision voltage source, such as the Keithley2400, outputting 0 to 3 volts per micrometer electric field; a MEMS driver circuit using an electrostatic driver chip, such as the TID LPC3470, outputting 0 to 5 volts; and a thermo-optic driver circuit using a current source, such as the Thorlabs ITC4001, outputting 0.1 to 1 milliamps of current. All circuits are integrated onto a 5 mm × 5 mm, 0.5 mm thick circuit board, bonded to the backplane layer with epoxy resin. The display unit is an organic light-emitting diode (OLED) display, such as a Samsung AMOLED, measuring 5 mm × 3 mm with a resolution of 320 × 240. It is mounted at the bottom of the backplane layer and displays light field data, polarization data, and optimization reports. The data processing control unit is connected to the drive module via an internal circuit bus, such as an I2C bus, and to the feedback module via optical fiber. It receives sensor data, generates drive signals, and consumes less than 10 milliwatts in total power. Specific Implementation Example 4:

[0130] like Figures 1 to 5 As shown below, the operating environment for this solution is described:

[0131] External environmental requirements:

[0132] The display is suitable for indoor or controlled outdoor environments with an ambient temperature range of 0 to 50 degrees Celsius and a relative humidity range of 20% to 80%, free from condensation, to avoid extreme humidity affecting the performance of the thin-film heater array or transparent electrodes. Ambient light intensity must be controlled between 100 and 1000 lux, suitable for high-resolution, flexible, or transparent display scenarios, such as indoor displays, wearable devices, or automotive screens. The system is sensitive to dust and vibration and must operate in an environment with an ISO 7 cleanliness level (less than 352,000 particles per cubic meter) and a vibration acceleration of less than 0.1g to avoid mechanical strain interfering with the accuracy of piezoelectric actuators or MEMS actuators. The display does not require external cooling equipment but must be protected from direct sunlight or high-temperature heat sources; the heat source temperature must not exceed 70 degrees Celsius to protect the silicon-based or polymer materials of the photonic crystal substrate.

[0133] System integration environment:

[0134] The display features a modular design, allowing integration into small electronic devices such as smartwatches, augmented reality glasses, or micro-projectors. The core optical layer, light field output layer, and backplane layer are bonded together with epoxy resin, resulting in an overall thickness of less than 2 mm, suitable for embedding in compact devices. The field-programmable gate array (FPGA) at the data processing control end communicates with external devices via I2C or SPI interfaces, with data transfer rates ranging from 10 to 100 megabits per second, supporting real-time control. The system supports connection to external display driver chips or microcontrollers, such as the STM32 series, with an interface voltage of 3.3 volts and communication protocols compatible with standard I2C or SPI. The operating environment requires a stable mounting platform with a fixing force of less than 1 Newton per square millimeter to avoid mechanical stress affecting the periodic structure of the photonic crystal substrate. Specific Implementation Example 5:

[0136] like Figures 1 to 5 As shown, the following is how this solution operates in a real-world scenario:

[0137] Adjustment methods and scenario descriptions:

[0138] 1. High-resolution display scenarios (such as smartphone screens):

[0139] Adjustment Method: When displaying high-resolution images (e.g., 4K resolution, 3840×2160 pixels), the data processing control unit receives light intensity sensor data and detects the light intensity gradient in the transition region. If the gradient is less than 20%, a non-uniform periodic gradient modulation process is triggered. A piezoelectric actuator applies a voltage of 0 to 5 volts, adjusting the base period from 50 nanometers to 200 nanometers to generate a light intensity gradient greater than 20%. If the local light intensity is insufficient, a microcavity array local enhancement process applies an electric field of 0 to 3 volts per micrometer through transparent electrodes, modulating the microcavity refractive index (changing from 0.15 to 0.2), with a Q factor of 1000 to 5000, enhancing the local light intensity by 2 to 5 times. The dynamic light field folding optimization process adjusts the optical path folding path through a lithium niobate electro-optic modulator, with a switching time of less than 500 nanoseconds, generating a nonlinear light field gradient to ensure a smooth transition of light intensity between pixels.

[0140] Triggering conditions: The light field data acquisition process detects light intensity fluctuations greater than 1.5%, or the time series analysis algorithm predicts that high-resolution images require fine light field control based on 30 days of historical data.

[0141] Reason for adjustment: High-resolution displays require smooth transitions in light intensity and color between pixels to avoid abrupt changes that could lead to image distortion or blurred boundaries.

[0142] Adjustment effect: Periodic gradient modulation ensures uniform light intensity distribution, microcavity enhancement improves local brightness, optical path folding optimizes nonlinear gradient, generates an ultra-smooth light field, and improves image clarity and color consistency. For example, when displaying complex graphics (such as text or photos), there is no obvious brightness jump in the transition area.

[0143] 2. Flexible display scenarios (such as wearable device screens):

[0144] Adjustment methods: In flexible displays (such as smartwatches or bendable screens), the substrate uses polymer materials (such as polymethyl methacrylate) to accommodate bending stress. The data processing control unit receives phase sensor data and detects the phase gradient. If the phase gradient is less than π / 2, the photonic crystal metasurface phase modulation process applies a voltage of 0 to 5 volts through a MEMS actuator, adjusting the metasurface pillar height by 10 to 50 nanometers to generate a phase gradient greater than π / 2. The environmental interference correction process uses data from temperature and humidity sensors (resolution 0.1 degrees Celsius, 0.2% humidity) and employs a dynamic filtering algorithm to update the interference factor weights (initial temperature 0.45, light intensity 0.35, humidity 0.2%) to correct the refractive index shift caused by bending. The adaptive thermo-optical coupling optimization process applies a current of 0.1 to 1 mA through a thin-film heater array to generate a thermal field (temperature change of 5 to 50 degrees Celsius), modulating the refractive index change to be greater than 0.1, thus optimizing the photonic bandgap.

[0145] Triggering conditions: The environmental interference correction process detects a temperature change greater than 5 degrees Celsius or a humidity change greater than 10%, or the phase sensor detects a bending that causes a phase deviation.

[0146] Reason for adjustment: When flexible displays are bent or the temperature changes, the refractive index and phase distribution of the photonic crystal substrate are easily disturbed, resulting in non-uniform light field. Dynamic adjustment is required to maintain display consistency.

[0147] Adjustment effect: Metasurface phase modulation ensures consistent light field direction, thermo-optical coupling optimizes and corrects refractive index deviation, environmental interference correction eliminates external influences, generates a smooth light field, and supports flexible screens to maintain clear display in a curved state (such as a curvature radius of 5 mm), for example, displaying dynamic images on wearable devices without distortion.

[0148] 3. Transparent display of scenes (such as augmented reality glasses):

[0149] Adjustment Method: In transparent displays (such as AR glasses), high transmittance and polarization state control must be ensured. The data processing control unit receives data from the polarization sensor and detects the polarization state. If the polarization state deviates from circular polarization, the spin photonic crystal polarization modulation process applies an electric field of 0 to 3 volts per micrometer through a lithium niobate electro-optic modulator, combined with a chiral spiral aperture (100 nm period, 0.5 μm depth), dynamically switching the polarization state from linear polarization to circular polarization. A weighted fusion algorithm integrates polarization, period, resonance, and optical path data, optimizes chromaticity distribution, and generates a driving signal to adjust the light source intensity (current 0.1 to 1 mA). The dynamic resource allocation process allocates resources according to the following proportions through a resource optimization algorithm: optical field data acquisition 35%, non-uniform periodic gradient modulation 20%, microcavity array local enhancement 15%, dynamic optical field folding optimization 10%, polarization modulation 8%, phase modulation 7%, thermo-optical coupling optimization 3%, environmental interference correction 2%, prioritizing the allocation of polarization modulation resources.

[0150] Triggering conditions: The polarization sensor detects a polarization state deviation greater than 1 degree, or the ambient light intensity changes by more than 10% (e.g., from 100 lux indoors to 1000 lux outdoors).

[0151] Reason for adjustment: Transparent displays require high light transmittance and a specific polarization state to enhance contrast and visibility. Changes in ambient light intensity may cause polarization imbalance, requiring dynamic adjustment to maintain the display effect.

[0152] Adjustment effect: The chiral structure and lithium niobate modulator optimize the polarization state, the fusion algorithm ensures color consistency, and the resource allocation prioritizes polarization control, generating a light field with high transmittance (greater than 80%) and a clear transition zone. For example, when superimposing virtual images in AR glasses, the background light and the display light are seamlessly integrated without polarization distortion.

[0153] General adjustment procedure:

[0154] In actual operation, the data processing control unit monitors light intensity, polarization, phase, and temperature in real time through the light field data acquisition process, triggering the adjustment process. A dynamic sampling algorithm optimizes the sensor sampling frequency (1 to 100 microseconds) and adjusts the data acquisition rate based on ambient light intensity (100 to 1000 lux) and temperature (0 to 50 degrees Celsius). A time series analysis algorithm analyzes 30 days of historical data, predicts light field fluctuations (triggers an early warning when the fluctuation exceeds 1.5%), and generates optimization suggestions. The adjustment signal is transmitted to the drive module via the circuit bus to adjust the period (piezoelectric actuator), resonant frequency (transparent electrode), optical path (lithium niobate modulator), phase (MEMS actuator), and refractive index (thin-film heater) of the photonic crystal substrate, achieving a gradual change in the light field. The purpose of the adjustment is to eliminate environmental interference (such as temperature, humidity, and light intensity changes) and hardware deviations (such as substrate stress and sensor drift), ensuring a smooth transition of the light field and improving display quality. Specific Implementation Example Six:

[0156] like Figures 1 to 5 As shown, the following is a supplement to the above embodiments:

[0157] Firstly, regarding the optical display output layer, a light-emitting layer is placed above the photonic crystal substrate. This light-emitting layer can be a quantum dot thin film layer or a fluorescence enhancement layer, used to amplify and convert the light field after it has been modulated by the photonic crystal, thereby forming a visual display output. This structure ensures that the optical modulation results can be transformed into a high-brightness, wide-color-gamut display effect, rather than merely remaining at the level of light field experiments.

[0158] Secondly, regarding the light source module, a hybrid driving mode of broadband LED light source and single-mode laser light source is adopted: broadband LED is used to provide substrate illumination, ensuring matching with the bandgap characteristics of the photonic crystal; single-mode laser light source is used to enhance specific wavelength channels to achieve high-contrast modulation display. To avoid the influence of laser coherent noise, a beam expander and a random phase plate are set at the output end of the laser light source, thereby reducing speckle effect and improving display uniformity.

[0159] Regarding sensor arrangement, in addition to the light intensity, polarization, phase, and temperature sensors mentioned in Example 1 arranged in a 100μm×100μm array, a humidity sensor is further integrated into the edge area of ​​the display screen for real-time detection of ambient humidity. The data is then input into the environmental interference correction process to compensate for thermal and optical modulation. The humidity sensor and temperature sensor work together to effectively avoid optical performance drift caused by environmental disturbances.

[0160] In terms of data processing and algorithm implementation, the data processing control unit is implemented using an on-chip heterogeneous integrated circuit, including an MCU control unit, an FPGA acceleration module, and a storage unit. The MCU is used to perform dynamic sampling and parameter updates, the FPGA module is used for parallel computation of optical field distribution and modulation optimization results, and the storage unit is used to store 30 days of historical operating data. The dynamic resource allocation process includes not only the allocation of computing and storage resources, but also the on-demand adjustment of the power consumption of the drive module, thereby achieving overall system energy efficiency optimization.

[0161] In terms of manufacturing process, this embodiment employs a silicon-based heterogeneous integration process to integrate a photonic crystal substrate, piezoelectric actuators, electro-optic modulators, MEMS microstructures, and thin-film heaters in multiple layers. Through layer-by-layer epitaxy and bonding techniques, different functional modules can work collaboratively on the same chip. This process solves the problem of incompatibility between multiple types of control elements, making this invention feasible for actual display manufacturing.

[0162] The following is an appendix Figure 1 To be continued Figure 4 Explanation:

[0163] Figure 1 Simulation diagrams of light field distribution for various modulation mechanisms of photonic crystal displays:

[0164] Horizontal axis (wavelength nm): Represents the optical response of the photonic crystal in the range of 400–700 nm, covering the visible light band. Vertical axis (light intensity mW / cm²): Represents the light field intensity under different modulation mechanisms.

[0165] Meaning of the curve:

[0166] The red curve, "Periodic Modulation," corresponds to the periodic structural modulation of the photonic crystal, with a spectral distribution exhibiting gentle fluctuations. The green curve, "Microcavity Resonance," produces a sharp resonance peak near 550nm, indicating strong selectivity of the cavity for specific wavelengths of light. The dark blue curve, "Polarization Modulation," corresponds to the effect of polarization angle changes on the light field distribution. The purple curve, "Phase Modulation," shows a more volatile spectral change, indicating that phase changes can significantly alter the interference effect. The sky-blue curve, "Thermo-Optical Modulation," has a relatively low overall amplitude, showing limited refractive index fine-tuning caused by temperature changes. The black curve, "Comprehensive Light Field," is the result of the superposition of multiple modulation mechanisms, with a more balanced overall distribution.

[0167] This figure illustrates the mechanism by which different control methods affect the light field. The combined light field can achieve optical enhancement at a specific wavelength while maintaining good spectral balance.

[0168] Figure 2 Simulation diagram for dynamic allocation of system resources:

[0169] Horizontal axis (time in hours): Represents system uptime (0–24 hours). Vertical axis (resource proportion): Represents the resource proportion of different control mechanisms in the entire system.

[0170] Meaning of the curve:

[0171] Red "Periodic Modulation": Has the highest proportion and exhibits periodic fluctuations. Green "Microcavity Resonance": Has a relatively stable proportion, indicating that its computation and energy consumption are controllable. Blue "Phase Modulation": Fluctuates significantly, indicating a strong dependence on real-time optical field feedback. Black dashed line "Other Modules": Represents the changes in the proportion of auxiliary functions (such as thermo-optical effects and polarization compensation).

[0172] This diagram reveals the system's resource allocation strategy at different runtime stages, and can intuitively reflect the dynamic weight of each control mechanism, providing a basis for optimizing energy consumption and computing resource allocation.

[0173] Figure 3 Simulation diagram for light intensity fluctuation monitoring and early warning:

[0174] Horizontal axis (time in hours): Represents runtime (0–25 hours). Vertical axis (normalized light intensity): Monitors relative fluctuations in light intensity with 1 as the baseline.

[0175] The blue curve, "Light Intensity Fluctuation," displays the dynamic changes in real-time light intensity within ±5%. The red dashed line, "Threshold," is set to 1.02, meaning an alert is triggered when the light intensity deviates by more than 2%. The red annotation, "Threshold 1.5%," indicates a stricter alarm mechanism to prevent display anomalies.

[0176] The diagram illustrates the system's stability and security monitoring mechanism, which can issue an early warning when light intensity fluctuations exceed a threshold, thereby ensuring the stable display effect of the photonic crystal display screen.

[0177] Figure 4 Local intensity map:

[0178] Horizontal axis (time in seconds): Represents runtime (0–0.010000 seconds). Vertical axis (normalized light intensity): Monitors relative fluctuations in light intensity with 1 as the baseline.

[0179] Color distribution (light intensity change): It shows the dynamic change of real-time light intensity in the range of -1 to 1. The color gradually changes from blue (low value -1) to yellow (high value 1), reflecting the spatial distribution change of light intensity throughout the entire operation cycle.

[0180] This figure illustrates the stability of the light intensity distribution and the monitoring mechanism of the system. It can intuitively reflect the light field fluctuation of the photonic crystal display screen in a short period of time through color changes, and help to evaluate the uniformity and dynamic response performance of the light field in the transition region.

[0181] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising a reference structure" does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0182] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A gradient light-emitting display screen with a transition region based on a photonic crystal, characterized in that, It includes a photonic crystal substrate, a light source module, a driving module, a feedback module, and a data processing control terminal; The photonic crystal substrate is a silicon-based or polymer-based two-dimensional photonic crystal, which is installed in the core optical layer of the display screen. The surface has a non-uniform periodic gradient structure with a periodic variation range of 50 to 200 nanometers. The substrate contains a microcavity array with embedded point defects, a chiral structure, a subwavelength columnar metasurface array, and a waveguide bending structure. A thin film heater array is provided below the substrate. The light source module consists of a broadband LED and a laser light source, which is installed at the input end of the display screen and coupled to the waveguide of the photonic crystal substrate via an optical fiber. The driving module includes a piezoelectric actuator, a transparent electrode, a lithium niobate electro-optic modulator, a MEMS actuator, and a thin-film heater. The piezoelectric actuator is embedded inside the photonic crystal substrate for dynamically controlling the periodic gradient. The transparent electrode covers the surface of the microcavity array for controlling the microcavity resonant frequency. The lithium niobate electro-optic modulator is integrated into the waveguide and chiral structure region for controlling the optical path folding and polarization state. The MEMS actuator is distributed on the metasurface array for controlling the phase distribution. The thin-film heater array is mounted on the bottom of the substrate for controlling the thermal field distribution. The feedback module includes a light intensity sensor, a polarization sensor, a phase sensor, and a temperature sensor, which are distributed at a spacing of 100 micrometers × 100 micrometers at the output end of the photonic crystal substrate, installed on the light field output layer of the display screen, and connected to the data processing control end via optical fiber. The data processing control terminal is an integrated circuit module installed on the back panel of the display screen. It includes a piezoelectric drive circuit, an electro-optic drive circuit, a MEMS drive circuit, and a thermo-optic drive circuit. A display screen is provided at the bottom to display light field data, polarization data, and optimization reports.

2. The gradient light-emitting display screen based on a photonic crystal in the light source transition region according to claim 1, characterized in that, The photonic crystal substrate is manufactured using silicon-based photonic integration technology. The data processing control terminal includes a control system, whose adjustment process includes non-uniform periodic gradient modulation, microcavity array local enhancement, dynamic optical field folding optimization, spin photonic crystal polarization control, photonic crystal metasurface phase control, adaptive thermo-optical coupling optimization, optical field data acquisition, environmental interference correction, and dynamic resource allocation. All processes in the control system are executed through the data processing control terminal.

3. The control system corresponding to the photonic crystal-based gradient light-emitting display screen in the light source transition region according to claim 1, characterized in that: The light field data acquisition process uses light intensity sensors and polarization sensors to collect light field intensity and polarization state data in the transition zone in real time. The light intensity sensors and polarization sensors are arranged in an array with a spacing of 100 micrometers × 100 micrometers and transmitted to the data processing control terminal through optical fiber at a microsecond frequency. A dynamic sampling algorithm is used to optimize the sampling frequency according to the ambient light intensity and temperature. The non-uniform periodic gradient modulation process interacts with the optical field data acquisition process, providing periodic modulation data to the adaptive thermo-optical coupling optimization process. The microcavity array local enhancement process interacts with the optical field data acquisition process, providing resonant data to the adaptive thermo-optical coupling optimization process. The dynamic light field folding optimization process interacts with the light field data acquisition process, providing optical path data to the adaptive thermo-optical coupling optimization process. The spin photonic crystal polarization control process interacts with the optical field data acquisition process to provide polarization data to the adaptive thermo-optical coupling optimization process. The photonic crystal metasurface phase modulation process interacts with the optical field data acquisition process, providing phase data to the adaptive thermo-optical coupling optimization process. The environmental interference correction process interacts with the optical field data acquisition process, providing correction data to the adaptive thermo-optical coupling optimization process. The adaptive thermo-optical coupling optimization process uses a weighted fusion algorithm to integrate period, resonance, optical path, polarization, phase, and correction data to optimize the optical field parameters in the transition region. The dynamic resource allocation process interacts with all other processes to optimize resource allocation.

4. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The non-uniform periodic gradient modulation process dynamically adjusts the periodic distribution of the photonic crystal through a piezoelectric actuator, with the periodic variation range being 50 to 200 nanometers, generating a transition region light field with an intensity gradient greater than 20%. The non-uniform periodic gradient modulation process generates periodic tuning parameters through analysis of 30 days of historical light field data, supports online updates to adapt to ambient light intensity and display requirements, and combines thin-film heater array to assist in periodic stability control. The periodic modulation data includes the amount of change and gradient value, and interacts with the light field data acquisition process.

5. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The microcavity array local enhancement process applies an electric field through transparent electrodes, modulates the refractive index change to be greater than 0.15, dynamically adjusts the microcavity resonant frequency, and generates local optical field enhancement with a Q factor ranging from 1000 to 5000. The microcavity array local enhancement process combines 7-day, 14-day, and 30-day optical field data analysis to dynamically optimize the microcavity resonance parameters, generating resonance data consisting of refractive index changes, resonant frequencies, light intensity values, and Q factor ranges for the adaptive thermo-optical coupling optimization process.

6. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The dynamic optical field folding optimization process adjusts the periodic refractive index gradient or waveguide bending structure within the photonic crystal using a lithium niobate electro-optic modulator, dynamically changing the optical path folding path length to generate a nonlinear optical field gradient, with a switching time of less than 500 nanoseconds. The dynamic optical field folding optimization process optimizes folding parameters by analyzing 30 days of historical optical field data and sending optical path data to 3F once per cycle, which includes path length and distribution value.

7. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The spin photonic crystal polarization modulation process uses a chiral photonic crystal structure and a lithium niobate electro-optic modulator to apply an electric field of less than 3 volts per micrometer and dynamically switch the polarization state from linear polarization to circular polarization. The polarization control process analyzes 30 days of historical polarization data, optimizes polarization state parameters, generates polarization data containing polarization type and chromaticity distribution, and transmits it to the adaptive thermo-optical coupling optimization process.

8. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The photonic crystal metasurface phase modulation process adjusts the metasurface phase distribution by using a subwavelength columnar metasurface array and a MEMS actuator, with the column height varying from 10 to 50 nanometers, generating a phase gradient greater than π / 2. The metasurface phase modulation process analyzes 30 days of historical phase data, optimizes phase distribution parameters, generates phase data containing gradient and light intensity values, and transmits it to the adaptive thermo-optical coupling optimization process.

9. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The environmental interference correction process collects environmental data through temperature sensors, light intensity sensors, and humidity sensors, and uses a dynamic filtering algorithm to update the interference factor weights. The initial weights are 0.45 for temperature, 0.35 for light intensity, and 0.2 for humidity. The dynamic filtering algorithm optimizes the weight distribution through a 30-day learning cycle, supports interference correction across environmental changes, and transmits the correction results to the adaptive thermo-optical coupling optimization process.

10. The control system corresponding to the gradient light emission display screen with a light source transition region based on a photonic crystal according to claim 3, characterized in that: The adaptive thermo-optical coupling optimization process applies a local thermal field through a thin-film heater array, modulates the refractive index change of the photonic crystal to be greater than 0.1, and optimizes the photonic bandgap distribution. The adaptive thermo-optical coupling optimization process analyzes 30 days of historical light field data to generate an optimization report that includes light intensity, colorimetry, and stability, supporting high-resolution display, flexible display, and transparent display scenarios. The data processing control terminal uses a time series analysis algorithm to analyze the light field, polarization, and power consumption data of the past 30 days, and generates a performance report that includes the system's operating status and optimization suggestions. When the light field fluctuation exceeds 1.5%, an early warning is triggered and the resource allocation ratio is adjusted. The resource dynamic allocation process receives real-time power consumption, computational latency, and data throughput data from each process. Based on 30 days of historical operating data, it uses a resource optimization algorithm to predict resource demand for the next 4 hours and dynamically adjusts the allocation ratio: 35% for the optical field data acquisition process, 20% for the non-uniform periodic gradient modulation process, and 15% for the microcavity array local enhancement process. The resource optimization algorithm supports fault self-diagnosis. When a sensor fault is detected, the faulty module is automatically isolated, and a diagnostic report containing the fault type, scope of impact, and recovery suggestions is generated and transmitted to the data processing control terminal.

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