Liquid crystal display screen and control method thereof

Abstract

The invention relates to the technical field of display, in particular to a liquid crystal display screen and a control method thereof. The method comprises the following steps: obtaining display screen design data, and carrying out quantum dot material feature extraction and quantum dot distribution feature extraction according to the display screen design data so as to obtain quantum dot material data and quantum dot distribution data; performing quantum dot display according to the quantum dot material data and the quantum dot distribution data so as to obtain quantum dot display data; performing optical structure feature extraction according to the display screen design data so as to obtain optical structure feature data; performing display optical simulation according to the optical structure feature data so as to obtain display optical simulation data; and obtaining display screen temperature sensing data, and performing display stability analysis on the quantum dot display data according to the display screen temperature sensing data so as to obtain display stability data. The power consumption control of the liquid crystal display screen is realized based on the display technology.

Description

Technical Field

[0001] The present invention relates to the field of display technology, and in particular to a liquid crystal display screen and a control method thereof. Background Art

[0002] Display technology, as a core component of modern electronic devices, is widely used in smartphones, tablets, televisions, computer monitors, and various consumer electronic products. In recent years, with the continuous improvement of display demand and the rapid development of technology, the performance requirements of display screens have also been increasing. These requirements not only include the improvement of display quality, but also involve multiple aspects such as power consumption, thickness, response speed and production cost of display devices. Quantum dot display technology, despite its excellent color performance and brightness, also has some challenges in practical applications. The uniform distribution and stability of quantum dot materials are key issues. In terms of control methods, traditional display control technology cannot adapt to the needs of new display technologies. How to achieve accurate color calibration, dynamic brightness adjustment and efficient energy management remains a technical challenge. Summary of the Invention

[0003] Based on this, it is necessary for the present invention to provide a liquid crystal display screen and a control method thereof to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for controlling a liquid crystal display screen includes the following steps:

[0005] Step S1: Obtaining display screen design data, and performing quantum dot material feature extraction and quantum dot distribution feature extraction based on the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data; performing quantum dot display based on the quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data;

[0006] Step S2: extracting optical structure features according to the display screen design data to obtain optical structure feature data; performing display optical simulation according to the optical structure feature data to obtain display optical simulation data;

[0007] Step S3: Acquire display screen temperature sensor data, and perform display stability analysis on quantum dot display data based on the display screen temperature sensor data, thereby obtaining display stability data; perform heat dissipation design optimization on display screen design data based on the display stability data, thereby obtaining heat dissipation design optimization data;

[0008] Step S4: extracting display energy consumption characteristics based on the display optical simulation data to obtain display energy consumption data; optimizing the display driving circuit based on the display energy consumption data to obtain display driving circuit optimization data;

[0009] Step S5: constructing a display power consumption monitoring system according to the heat dissipation design optimization data and the display driving circuit optimization data, thereby obtaining display power consumption monitoring system data, and uploading it to the display management cloud platform to execute the display operation power consumption control task.

[0010] By extracting the characteristics of quantum dot materials, the present invention can ensure the selection of the most suitable quantum dot material to achieve the best color reproduction and brightness performance. This process can improve the color accuracy and brightness stability of the display screen. The extraction of quantum dot distribution characteristics helps to ensure the uniform distribution of quantum dots, avoids the problem of uneven color or inconsistent brightness on the display screen, thereby improving the overall display effect and user experience. The generated quantum dot display data helps to verify the expected effect, ensure that the design of the display screen meets the design goals, and reduce the need for adjustments during the production process. By extracting optical structure characteristics and performing simulations, the optical design of the display screen can be optimized, the propagation path and distribution of light can be improved, thereby improving the brightness and contrast of the display screen. Optical simulation can discover potential problems in the optical design in advance, such as reflection, refraction loss, etc., reducing the cost and time of adjustments after production. Optimizing the optical structure helps to improve display quality, including higher brightness, better color reproduction and higher contrast, and improve the overall visual effect. By analyzing display stability, we can ensure that the display maintains a stable display quality at different operating temperatures, minimizing the impact of temperature fluctuations on display quality. Effective heat dissipation design can lower the display's operating temperature, reduce the impact of overheating on the display's performance and lifespan, and enhance its reliability. Improving heat dissipation helps extend the display's lifespan and reduce long-term maintenance and replacement costs. By extracting display energy consumption characteristics and optimizing the driver circuit, we can significantly reduce the display's energy consumption, improve energy efficiency, and reduce power consumption, thereby complying with environmental protection and energy conservation requirements. Optimizing the display driver circuit improves circuit efficiency, reduces energy waste, and enhances the overall performance of the display. Reducing energy consumption not only helps reduce operating costs but also extends the display's lifespan and reduces maintenance costs. By building a display power consumption monitoring system, we can monitor the display's power consumption in real time, ensuring efficient operation under various operating conditions. Uploading this data to a cloud platform enables remote monitoring and management, allowing for timely adjustment of the display's power settings to optimize overall energy efficiency. Detailed power consumption data provides valuable insights into and optimizes the display's operational strategies, further improving its energy efficiency and overall performance.

[0011] Optionally, step S1 specifically includes:

[0012] Step S11: Acquire display screen design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction based on the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data;

[0013] Step S12: analyzing the luminescence performance of the material according to the quantum dot material data, thereby obtaining the luminescence performance data of the quantum dot material;

[0014] Step S13: performing optical consistency analysis based on the quantum dot distribution data to obtain quantum dot optical consistency data;

[0015] Step S14: integrating quantum material optical data according to the quantum dot material luminescence performance data and the quantum dot optical consistency data, thereby obtaining quantum material optical data;

[0016] Step S15: generating a quantum dot display according to the quantum material optical data, thereby obtaining quantum dot display data.

[0017] By extracting quantum dot material characteristics, this method can select suitable quantum dot materials to meet the display's high requirements for color reproduction and brightness. This can improve the display's display quality and reliability. By extracting quantum dot distribution characteristics, it can ensure the uniform distribution of quantum dots on the display, avoiding color inconsistencies or uneven brightness caused by uneven distribution. The obtained quantum dot material and distribution data provides basic data support for subsequent display generation and optical analysis, facilitating precise adjustment and optimization of display design. Luminescence performance analysis can evaluate the luminous efficiency and spectral characteristics of quantum dot materials, ensuring that the material's color performance and brightness meet requirements in practical applications. Accurate luminescence performance data helps adjust the use of quantum dot materials, optimize the optical performance of displays, and improve display stability and color accuracy. The obtained luminescence performance data provides a basis for subsequent display adjustment and optimization, effectively reducing trial-and-error costs during the production process. Optical consistency analysis can identify and resolve optical inconsistencies in displays, ensuring consistent display effects across different viewing angles and conditions. The analysis results help optimize the arrangement and distribution of quantum dots, reduce optical non-uniformity, and thus improve the overall stability and visual experience of the display. Optical consistency data can be used to further optimize the design to enhance display quality and user satisfaction. By integrating luminescence performance data and optical consistency data, a comprehensive understanding of the optical performance of quantum materials in practical applications can be achieved, providing comprehensive data support for design and optimization. The integrated optical data can help identify and resolve optical performance issues, optimize display effects, and improve the visual quality and user experience of displays. Comprehensive quantum material optical data can help make more accurate design decisions and optimize display performance and energy efficiency. Generating quantum dot display data based on comprehensive optical data can achieve high-quality display effects and meet the high requirements of modern display technology for color, brightness and resolution. The generated quantum dot display data helps to ensure the color performance and brightness stability of the display in actual use, improving the user's visual experience. Through the precise display data generation process, it can reduce the need for adjustments in display development and production, and accelerate product launch.

[0018] Optionally, step S12 is specifically as follows:

[0019] Step S121: performing photoluminescence spectrum detection according to the quantum dot material data, thereby obtaining photoluminescence spectrum data of the quantum dot material;

[0020] Step S122: performing spectrum wavelength distribution statistics based on the photoluminescence spectrum data of the quantum dot material, thereby obtaining spectrum wavelength distribution data;

[0021] Step S123: extracting spectral wavelength peak features based on the spectral wavelength distribution data, thereby obtaining spectral wavelength peak data;

[0022] Step S124: Calculating the spectrum full width at half maximum according to the spectrum wavelength distribution data, thereby obtaining spectrum full width at half maximum data;

[0023] Step S125: Calculating the internal and external quantum luminous efficiencies based on the spectral wavelength peak data and the spectral full width at half maximum data to obtain internal and external quantum luminous efficiency data, and calculating the luminous loss difference based on the internal and external quantum luminous efficiency data to obtain internal and external quantum luminous efficiency difference data;

[0024] Step S126: evaluating the luminous efficiency of the quantum dot material based on the internal and external quantum luminous efficiency difference data, thereby obtaining the luminous performance data of the quantum dot material.

[0025] The present invention can provide the luminescence characteristics of quantum dot materials, including their luminescence wavelength and intensity, through photoluminescence spectrum detection. This helps to evaluate the performance of materials in actual display applications. Photoluminescence spectrum detection can provide the luminescence characteristics of quantum dot materials, including their luminescence wavelength and intensity. This helps to evaluate the performance of materials in actual display applications. The detection results help select quantum dot materials with optimal optical properties and improve the color and brightness performance of the display screen. Statistical spectral wavelength distribution data can help identify the luminescence range of quantum dot materials and understand the color coverage capability of the materials. By understanding the wavelength distribution, the color adjustment of the display screen can be optimized to improve the accuracy and richness of the overall display effect. The statistical results help to detect the consistency of quantum dot materials and ensure quality control in mass production. Full-width half-maximum (FWHM) calculation can evaluate the bandwidth of the spectrum and understand the spectral distribution width and luminescence color gamut range of quantum dot materials. Smaller FWHM values ​​generally indicate more concentrated and purer color output, which helps to improve the color accuracy and contrast of the display screen. Through FWHM data, quantum dot materials with suitable luminescence characteristics can be screened to optimize the display effect. Calculating the internal and external quantum luminous efficiency can evaluate the luminous efficiency of quantum dot materials, identify sources of luminescence loss, and optimize material usage. Luminous efficiency data can be used to optimize material formulations and display designs, improve the energy efficiency of displays, and reduce power consumption. By calculating the efficiency difference, the luminous performance of different materials can be compared, allowing the selection of more efficient materials for displays. By comprehensively analyzing the internal and external quantum luminous efficiency differences, the luminous performance of quantum dot materials can be comprehensively evaluated, understanding their performance in practical applications. The results can guide further optimization of quantum dot materials and improve the optical and color performance of displays. Accurate luminous efficiency evaluation ensures optimal color reproduction and brightness, enhancing overall display quality.

[0026] Optionally, step S13 is specifically as follows:

[0027] Step S131: performing quantum distribution density feature extraction and quantum distribution position feature extraction based on the quantum dot distribution data, thereby obtaining quantum distribution density data and quantum distribution position data;

[0028] Step S132: Acquire display screen illumination data;

[0029] Step S133: performing magnetic field uniform gradient control according to the quantum distribution density data, thereby obtaining quantum uniform distribution density data;

[0030] Step S134: performing micro-nanostructure template guided deposition according to the quantum distribution position data, thereby obtaining quantum micro-nanostructure template distribution data;

[0031] Step S135: integrating quantum dot distribution data according to the quantum uniform distribution density data and the quantum micro-nanostructure template distribution data, thereby obtaining quantum dot distribution data;

[0032] Step S136: performing luminous intensity consistency calculation based on the quantum dot distribution data to obtain quantum dot optical consistency data.

[0033] By extracting the density and position characteristics of the quantum dot distribution, the present invention can accurately understand the distribution of quantum dots, help identify uneven areas, and provide data support for subsequent optimization. Accurate distribution data helps optimize the use of quantum dot materials, ensures uniform distribution on the display screen, improves the consistency of the display effect, and provides key data for display screen design, helping to improve the coating and deposition process of quantum dot materials and improve display quality. Lighting data can provide the lighting conditions of the display screen in the actual working environment, provide a basis for display performance optimization, and can be used to perform more accurate optical structure design based on lighting data, optimize the performance of the display screen under different lighting conditions, and understand the impact of lighting on the display screen to help improve display stability and avoid display performance fluctuations caused by lighting changes. Through uniform magnetic field gradient control, the distribution of quantum dots on the display screen can be optimized and the uniformity of quantum dots can be improved. Uniform quantum dot distribution can effectively improve the color consistency and brightness uniformity of the display screen, improve visual effects, reduce display failures or performance problems caused by uneven distribution of quantum dots, and improve the reliability and stability of the display screen. Micro-nanostructured templates can guide the precise deposition of quantum dot materials, ensuring that the material is distributed according to design requirements. This guided deposition allows for more precise quantum dot arrangement, improving the resolution and color reproduction of displays. Using micro-nanostructured templates can simplify the quantum dot manufacturing process, increasing production efficiency and consistency. Integrating data from different sources provides a unified view of quantum dot distribution, facilitating further analysis and optimization. This integrated data provides a more comprehensive understanding of the actual quantum dot distribution, further optimizing display quality and color consistency. This integrated data helps precisely adjust the display manufacturing process, improving quantum dot distribution accuracy and overall display quality. Calculating luminous intensity consistency ensures consistent brightness and color across different areas of the display, enhancing the user's visual experience. Optimizing luminous intensity consistency can reduce brightness unevenness or color distortion across the display, improving the overall display quality. This consistent data can be used as a basis for quality control, ensuring that each display meets design requirements and performance standards during production.

[0034] Optionally, step S133 is specifically as follows:

[0035] Drawing a quantum density distribution map according to the quantum distribution density data, thereby obtaining a quantum density distribution map;

[0036] Perform quantum distribution density statistics based on the quantum density distribution map to obtain quantum dense distribution area data and quantum sparse distribution area data;

[0037] Applying a low-intensity magnetic field to a region where quantum densely distributed data is present, thereby obtaining quantum low-intensity magnetic field data;

[0038] Applying a high-intensity magnetic field to the quantum sparsely distributed area data to obtain quantum high-intensity magnetic field data;

[0039] Designing magnetic field channels based on quantum low-intensity magnetic field data and quantum high-intensity magnetic field data to obtain quantum magnetic field channel data;

[0040] The quantum uniform distribution density is calculated based on the quantum magnetic field channel data to obtain the quantum uniform distribution density data.

[0041] The present invention can intuitively display the distribution of quantum dots on the display screen by drawing a quantum density distribution map, help identify areas with uneven distribution, provide visual data of quantum dot distribution, help analyze the distribution characteristics of quantum dots and optimize design solutions, provide basic data for subsequent magnetic field control and material optimization, and make display screen design more scientific and accurate. By statistically analyzing the dense and sparse distribution areas of quantum dots, the key areas on the display screen can be clearly defined and optimized in a targeted manner, providing data support for magnetic field control and material processing in different areas, improving the consistency of display quality, helping to optimize the deposition and distribution of materials during the manufacturing process, and reducing display defects and performance fluctuations. Low-intensity magnetic fields can adjust the distribution of quantum dots in dense areas, optimize the display effect, reduce material waste, improve production efficiency, optimize the distribution consistency of quantum dots, and enhance the stability of the display screen under high brightness and high contrast conditions by precisely controlling the magnetic field application area. High-intensity magnetic fields can promote the distribution of quantum dots in sparse areas, improve the display quality of these areas, reduce brightness unevenness by adjusting the distribution of sparse areas, improve the overall display effect, enhance the color consistency of sparse areas, and improve the color performance and visual effect of the display screen. Designing an appropriate magnetic field channel can more effectively control the distribution of quantum dots, achieving precise distribution adjustment. By optimizing the magnetic field channel design, the uniformity and stability of the display can be improved. Effective magnetic field channel design can reduce display defects caused by uneven distribution and improve product quality. Calculating the uniform quantum distribution density ensures the uniform distribution of quantum dots on the display, improving the consistency of the display effect. Uniform quantum dot distribution can improve the display's color reproduction and brightness uniformity. Uniformly distributed quantum dots reduce visual defects and performance fluctuations on the display, improving display stability and reliability.

[0042] Optionally, step S134 is specifically as follows:

[0043] Extracting quantum distribution coordinate features based on quantum distribution position data to obtain quantum distribution coordinate data;

[0044] Design the gate structure according to the quantum distribution coordinate data to obtain the quantum gate structure data;

[0045] Calculating the size of the nanostructure according to the quantum distribution coordinate data to obtain the size data of the nanostructure;

[0046] Designing a micro-nanostructure template based on quantum gate structure data and nanostructure size data, thereby obtaining micro-nanostructure template data;

[0047] Designing a target deposition area based on the quantum dense distribution area data and the quantum sparse distribution area data, thereby obtaining target deposition area data;

[0048] Performing quantum template alignment based on the micro-nanostructure template data and the target deposition area data to obtain quantum template alignment data;

[0049] Depositing quantum dots according to the quantum template alignment data, thereby obtaining quantum dot deposition data;

[0050] The quantum dot distribution is detected based on the quantum dot deposition data to obtain the quantum micro-nanostructure template distribution data.

[0051] By extracting the quantum distribution coordinate characteristics, the present invention can accurately locate the position of quantum dots on the display screen, providing basic data for subsequent structural design and optimization, and providing detailed quantum dot distribution information for the design, which helps to optimize and adjust the quantum dots in subsequent design steps, ensure precise alignment during the subsequent design and deposition process, and improve the display quality and consistency of the display screen. Through the gate structure design, the control of quantum dots can be optimized to ensure the uniform distribution of quantum dots on the display screen. The gate structure design helps to improve the luminous efficiency of quantum dots, enhance the brightness and color performance of the display screen, and an effective gate structure design can reduce the problems of color unevenness and brightness inconsistency in the display screen, thereby improving the display effect. By calculating the size of the nanostructure, it is ensured that the design of the nanostructure meets actual needs and ensures high-precision manufacturing of the display screen. The appropriate nanostructure size can improve the optical performance of the quantum dots and enhance the color reproduction ability of the display screen. Accurate size calculation can reduce material waste and manufacturing defects, thereby reducing production costs. The designed micro-nanostructure template can accurately guide the deposition of the nanostructure, ensure the accurate distribution of quantum dots, and ensure the consistency and uniformity of the quantum dots in the display screen through the micro-nanostructure template design, improving the consistency of the display effect. The effective template design can simplify the manufacturing process, reduce the need for subsequent adjustments and corrections, and improve production efficiency. Designing target deposition areas allows for targeted adjustment of quantum dot deposition positions, improving the overall performance of the display. Appropriate deposition area design effectively utilizes materials, reduces waste, and enhances the efficiency of the deposition process. This ensures that quantum dot deposition quality meets design requirements across different distribution areas, avoiding uneven distribution. Precise quantum template alignment ensures accurate placement of quantum dots on the display, improving display accuracy. Effective alignment reduces errors in quantum dot distribution, enhancing display quality and stability. The aligned template further optimizes display performance, enhancing brightness uniformity and color accuracy. Quantum dot deposition accuracy improves display quality and color rendering. Depositing quantum dots using an aligned template ensures a uniform distribution of quantum dots across the display, reducing color shading and brightness unevenness. This precise deposition process enhances the stability and reliability of the display in various environments. Quantum dot distribution testing verifies the accuracy of the deposition process, ensuring that the final display meets design standards. Testing allows for timely identification and correction of quantum dot distribution issues, improving the overall quality of the display. Testing results can be fed back into the design phase to further optimize quantum dot deposition and distribution design, ultimately enhancing display performance.

[0052] Optionally, step S2 is specifically:

[0053] Step S21: extracting optical structure features according to the display screen design data, thereby obtaining optical structure feature data;

[0054] Step S22: performing material thermal performance analysis based on the optical structure characteristic data to obtain material thermal performance data;

[0055] Step S23: evaluating the optical properties of the material according to the optical structure characteristic data, thereby obtaining the optical properties of the material;

[0056] Step S24: integrating display screen material characteristics according to the material thermal performance data and the material optical properties, thereby obtaining display screen material characteristic data;

[0057] Step S25: performing display optical simulation according to the display screen material characteristic data, thereby obtaining display optical simulation data.

[0058] The present invention can provide detailed optical property information about the display screen, such as light transmittance, reflectivity, etc., by extracting optical structural features, which is crucial for optimizing display effects. Feature extraction of the optical structure can help designers understand the optical performance of the display screen and ensure that the design can meet the expected display requirements. By understanding the optical structural features, the display screen material can be selected or adjusted to improve display quality and performance. Analyzing the thermal properties of the material helps to optimize thermal management and prevent performance degradation or damage caused by overheating of the display screen. Understanding the thermal characteristics of the material can improve the long-term stability and reliability of the display screen and reduce display quality problems caused by thermal expansion and contraction. Through material thermal performance analysis, the heat dissipation design can be improved, the operating temperature of the display screen can be reduced, and its service life can be increased. Evaluating the optical properties of the material can verify whether it meets the design requirements, such as color reproduction and brightness uniformity. Based on the optical performance data, the most suitable material can be selected to improve the color performance and visual effects of the display screen. The material optical performance evaluation results can be used to optimize the display screen design and improve the overall display effect and user experience. By integrating the thermal and optical properties of materials, we can gain a comprehensive understanding of display materials and help optimize their overall performance. The integrated data helps fully optimize the display system, ensuring an optimal balance between thermal management and optical performance. Based on the comprehensive material properties, we can further improve the design solution and enhance the overall performance and reliability of the display. Optical simulation can predict the optical performance of the display in actual use, including brightness, contrast, and color accuracy. The simulation results can be used to adjust design parameters, optimize the display effect, and ensure that the final product meets the expected optical performance standards. Simulation can identify potential problems before actual manufacturing, reduce the trial and error costs of physical samples, and accelerate the design iteration process.

[0059] Optionally, step S22 is specifically as follows:

[0060] Step S221: extracting the optical absorption coefficient characteristics of the material according to the optical structure characteristic data, thereby obtaining the optical absorption coefficient data of the material;

[0061] Step S222: simulating the heat generation characteristics of the material according to the material optical absorption coefficient data, thereby obtaining the material heat generation characteristic data;

[0062] Step S223: Calculating the thermal conductivity coefficient and thermal diffusivity of the material based on the material heat generation characteristic data, thereby obtaining the thermal conductivity coefficient data and thermal diffusivity data of the material;

[0063] Step S224: performing heat and temperature transfer simulation on the optical structure characteristic data according to the material thermal conductivity data and the material thermal diffusivity data, thereby obtaining material heat and temperature transfer data;

[0064] Step S225: Calculating the material heat capacity based on the material heat temperature transfer data, thereby obtaining the material heat capacity data;

[0065] Step S226: performing thermal performance evaluation on the optical structure characteristic data according to the material heat capacity data, thereby obtaining material thermal performance data.

[0066] By extracting the optical absorption coefficient, this method accurately analyzes a material's light absorption capacity, which is crucial for evaluating the color rendering and brightness of a display screen. Understanding a material's optical absorption properties allows for the selection or modification of materials to enhance display quality and energy efficiency. Optimizing the optical absorption coefficient helps reduce light energy waste and improve the overall energy efficiency of the display screen. Simulating a material's heat generation characteristics allows for the prediction of heat generation under different operating conditions, aiding in the design of effective heat dissipation systems. Understanding heat generation characteristics helps prevent display performance degradation or damage due to overheating. Simulation data can be used to optimize heat dissipation design, ensuring stable display performance even under high loads. Calculating the thermal conductivity coefficient and thermal diffusivity provides a deeper understanding of a material's thermal behavior, including the speed and range of heat propagation. This data can be used to optimize the material's thermal management strategy, improve heat dispersion and conduction efficiency, and ensure effective heat management, ultimately enhancing the long-term performance and reliability of the display screen. Heat temperature transfer simulations predict the display screen's temperature distribution under actual operating conditions. The simulation results can be used to optimize the design, ensuring a uniform temperature distribution across the display screen, thereby improving overall performance and stability. Understanding heat transfer helps improve display reliability and mitigate performance issues caused by uneven temperatures. Calculating heat capacity can assess a material's heat storage capacity—that is, how much heat it can store during temperature changes. Understanding heat capacity helps design more efficient cooling systems and avoid overheating. By controlling a material's heat capacity, the stability of the display can be improved under varying operating conditions. Thermal performance evaluation comprehensively considers multiple factors, including a material's heat capacity and thermal conductivity, providing comprehensive information on its thermal properties. The results can be used to further optimize display design and ensure that the material maintains excellent performance under various operating conditions. Accurate thermal performance evaluation helps improve the overall performance of the display, ensuring its stability under high loads and prolonged use.

[0067] Optionally, step S4 is specifically:

[0068] Step S41: extracting display energy consumption characteristics based on display optical simulation data to obtain display energy consumption data;

[0069] Step S42: classifying energy consumption modes according to the displayed energy consumption data, thereby obtaining a dynamic interaction mode and a video playback mode;

[0070] Step S43: Draw an energy consumption curve according to the dynamic interaction mode and the video playback mode, thereby obtaining energy consumption curve data;

[0071] Step S44: extracting the power characteristics of the driving circuit according to the energy consumption curve data, thereby obtaining the power data of the driving circuit;

[0072] Step S45: performing efficiency conversion according to the power data of the driving circuit to obtain efficiency data of the driving circuit, and performing efficiency statistics according to the efficiency data of the driving circuit to obtain low-efficiency driving circuit data;

[0073] Step S46: Optimizing the circuit structure according to the low-efficiency driving circuit data, thereby obtaining optimized display driving circuit data.

[0074] By extracting display energy consumption characteristics, the present invention can understand the energy consumption of the display screen in different working modes, provide basic data for subsequent optimization work, and understand the specific energy consumption characteristics to help identify and solve high energy consumption problems, thereby optimizing the overall energy efficiency of the display screen. Energy consumption data can serve as an important reference when designing and improving the display screen, helping to formulate a more energy-saving design plan. Classifying energy consumption patterns can help understand the energy consumption behavior of the display screen in different usage scenarios, including common modes such as dynamic interaction and video playback. Identifying different energy consumption patterns can be optimized in a targeted manner, such as optimizing energy efficiency in dynamic interaction mode and reducing energy consumption in video playback mode. By optimizing energy consumption in different modes, the overall performance and user experience of the display screen can be improved. Drawing energy consumption curves can visualize the energy consumption in different modes, facilitating analysis and comparison. Through the energy consumption curves, energy consumption trends and patterns can be identified to help discover potential energy efficiency problems. Optionally, visualized energy consumption data can help optimize the design of the display screen and make improvements to high energy consumption areas. Extracting power signatures provides insight into the actual power consumption of driver circuits in real-world applications. Identifying power signatures helps locate high-power consumption components within the circuit, enabling targeted optimization. Based on power data, driver circuit design can be optimized to improve overall energy efficiency. Converting and statistically analyzing efficiency data can assess the actual operating efficiency of the driver circuit and identify inefficiencies. Efficiency statistics can identify inefficient driver circuit components, providing a basis for improvement. Optimizing inefficient components can significantly improve the energy efficiency of the entire display system and reduce energy consumption. By optimizing the circuit structure, the overall efficiency of the driver circuit can be improved and energy consumption reduced. This optimization not only boosts energy efficiency but also improves the display's response speed and stability. Improving energy efficiency reduces energy costs, enhancing the product's affordability and market competitiveness.

[0075] This specification also provides a liquid crystal display screen, which includes a liquid crystal display screen main body, a power supply unit, and an electrical control unit. The power supply unit is installed inside the liquid crystal display screen main body, and the electrical control unit is electrically connected to the power supply unit. The electrical control unit is used to charge the liquid crystal display screen main body and control the liquid crystal display screen main body. The electrical control unit includes:

[0076] Quantum dot display module: used to obtain display design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction based on the display design data, thereby obtaining quantum dot material data and quantum dot distribution data; perform quantum dot display based on the quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data;

[0077] Display optical simulation module: used to extract optical structure features according to display screen design data, thereby obtaining optical structure feature data; perform display optical simulation according to the optical structure feature data, thereby obtaining display optical simulation data;

[0078] Thermal design optimization module: used to obtain display temperature sensor data and perform display stability analysis on quantum dot display data based on the display temperature sensor data, thereby obtaining display stability data; and perform thermal design optimization on display design data based on the display stability data, thereby obtaining thermal design optimization data;

[0079] Driving circuit optimization module: used to extract display energy consumption characteristics based on display optical simulation data, thereby obtaining display energy consumption data; optimize the display driving circuit based on the display energy consumption data, thereby obtaining display driving circuit optimization data;

[0080] Operation power consumption control module: used to build a display power consumption monitoring system based on the heat dissipation design optimization data and the display driver circuit optimization data, so as to obtain the display power consumption monitoring system data and upload it to the display management cloud platform to perform the display operation power consumption control task.

[0081] The present invention can implement any liquid crystal display control method of the present invention, and is used to combine the operation and signal transmission medium between various modules to complete a liquid crystal display control method. The internal modules of the device cooperate with each other to achieve power consumption control of the liquid crystal display. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0083] Figure 1 Schematic diagram of the steps of the liquid crystal display and the control method thereof according to the present invention;

[0084] Figure 2 Detailed step flow diagram of step S1 in the present invention;

[0085] Figure 3 Detailed flowchart of step S12 in the present invention;

[0086] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0087] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the embodiments described are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative work are within the scope of protection of the present invention.

[0088] In addition, the accompanying drawings are merely schematic illustrations of the present invention and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor and / or microcontroller approaches.

[0089] It should be understood that although the terms "first," "second," and the like may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used solely to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the exemplary embodiments. The term "and / or" as used herein includes any and all combinations of one or more of the listed associated items.

[0090] To achieve this, please refer to Figures 1 to 3 The present invention provides a display screen control method, comprising the following steps:

[0091] Step S1: Obtaining display screen design data, and performing quantum dot material feature extraction and quantum dot distribution feature extraction based on the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data; performing quantum dot display based on the quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data;

[0092] In this embodiment, the display's geometric parameters, resolution, and color configuration data are extracted from a display design database. This data includes the display's dimensions, pixel arrangement, quantum dot material type, and pre-set quantum dot distribution. The quantum dot material is analyzed using a scanning electron microscope (SEM) to extract its particle size, shape, and luminescence characteristics. Image processing software is used to analyze the distribution of the quantum dots on the display, calculating their density distribution and positional deviation. Based on the extracted quantum dot material and distribution data, a computer-generated display image is used to simulate the quantum dot's luminescence effect, thereby obtaining quantum dot display data. The simulation results include color saturation, brightness, and uniformity.

[0093] Step S2: extracting optical structure features according to the display screen design data to obtain optical structure feature data; performing display optical simulation according to the optical structure feature data to obtain display optical simulation data;

[0094] In this embodiment, optical design software (such as Zemax or LightTools) is used to extract the display's optical structural characteristics, including the type and arrangement of lenses and filters, based on the display design data. The optical structural characteristic data is input into the optical design software to simulate the display's optical performance under different lighting conditions. The simulation includes light propagation paths, reflection, and refraction, resulting in display optical simulation data such as the optical transfer function (OTF) and point spread function (PSF).

[0095] Step S3: Acquire display screen temperature sensor data, and perform display stability analysis on quantum dot display data based on the display screen temperature sensor data, thereby obtaining display stability data; perform heat dissipation design optimization on display screen design data based on the display stability data, thereby obtaining heat dissipation design optimization data;

[0096] In this example, real-time display temperature data is acquired from a temperature sensor, and a thermal imager is used to analyze the display surface temperature distribution. Combined with quantum dot display data, the impact of temperature on display performance, such as color drift and brightness decay, is calculated. Based on the stability analysis results, thermal simulation software (such as ANSYS Fluent) is used to optimize the heat dissipation design, including heat sink layout, fan configuration, and heat dissipation material selection. A new heat dissipation solution is designed to ensure stable operation of the display even at high temperatures.

[0097] Step S4: extracting display energy consumption characteristics based on the display optical simulation data to obtain display energy consumption data; optimizing the display driving circuit based on the display energy consumption data to obtain display driving circuit optimization data;

[0098] In this embodiment, a power consumption analyzer (such as the Keysight E3646A) is used to measure the display's energy consumption in different operating modes, including static display mode and dynamic video playback mode. This energy consumption data is analyzed to identify driver circuit components with low energy efficiency. Circuit simulation software (such as Cadence PSpice) is used to optimize the design, improve power management and current control circuits, and thus enhance the driver circuit's energy efficiency.

[0099] Step S5: constructing a display power consumption monitoring system according to the heat dissipation design optimization data and the display driving circuit optimization data, thereby obtaining display power consumption monitoring system data, and uploading it to the display management cloud platform to execute the display operation power consumption control task.

[0100] In this embodiment, an integrated sensor and data acquisition system monitors the power consumption of display screens in real time. The system includes a power consumption sensor, a data recording unit, and a wireless communication module. The collected power consumption data is uploaded to a display screen management cloud platform via Wi-Fi. The platform provides real-time data analysis, report generation, and power consumption control recommendations.

[0101] Optionally, step S1 specifically includes:

[0102] Step S11: Acquire display screen design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction based on the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data;

[0103] In this embodiment, detailed data of the display screen is extracted from the design file, including the size of the display screen (15.6 inches), resolution (1920x1080 pixels), pixel density (141 PPI), and information about the quantum dot material used (such as CdSe quantum dots). The quantum dot material is analyzed using a transmission electron microscope (TEM) to extract the average diameter (5 nanometers), shape (nearly spherical), and luminescence characteristics (wavelength range of 450-550 nanometers) of the quantum dots. The distribution of the quantum dots on the display screen is analyzed using a scanning electron microscope (SEM), and the distribution density per square millimeter (100,000 quantum dots) and the deviation of their position (±10%) are calculated.

[0104] Step S12: analyzing the luminescence performance of the material according to the quantum dot material data, thereby obtaining the luminescence performance data of the quantum dot material;

[0105] In this example, a photoluminescence spectrometer was used to measure the spectral data of quantum dots. The luminous intensity of the quantum dots at different excitation wavelengths, along with the peak wavelength (e.g., 485 nm), and the full-width at half-maximum (FWHM) value (e.g., 30 nm) were recorded. The luminous efficiency of the quantum dots was calculated (quantum yield of 70%), and their luminous intensity was evaluated to ensure that they met the design requirements, ensuring they could deliver the expected brightness and color performance in practical applications.

[0106] Step S13: performing optical consistency analysis based on the quantum dot distribution data to obtain quantum dot optical consistency data;

[0107] In this embodiment, a photometer is used to measure multiple areas of the display screen to analyze the luminous consistency of quantum dots in different areas. Record the brightness (300cd / m 2 ) and color consistency (ΔE≤2) data. Ensure the brightness and color uniformity of the display across the entire panel, calculate the optical consistency data for each area, and compare whether it meets the design requirements.

[0108] Step S14: integrating quantum material optical data according to the quantum dot material luminescence performance data and the quantum dot optical consistency data, thereby obtaining quantum material optical data;

[0109] In this example, luminous performance data and optical consistency data were input into optical simulation software (e.g., OptiSystem). The integrated results included luminous intensity distribution, color saturation, and spectral characteristics. The resulting optical data included, for example, a luminous intensity of 50,000 photons / second per quantum dot, a color saturation of 90% NTSC, and a spectral peak wavelength of 480 ± 3 nm. This data was used to optimize the display.

[0110] Step S15: generating a quantum dot display according to the quantum material optical data, thereby obtaining quantum dot display data.

[0111] In this embodiment, the integrated quantum material optical data is used to generate a display screen effect simulation diagram using display effect simulation software (such as DIALux). The simulation results include brightness distribution, color reproduction and uniformity. The brightness of the display screen is 320cd / m 2 , color reproduction reaches 95% NTSC, and brightness uniformity error is within ±5%. Verify whether the simulation data meets the actual application requirements.

[0112] Optionally, step S12 is specifically as follows:

[0113] Step S121: performing photoluminescence spectrum detection according to the quantum dot material data, thereby obtaining photoluminescence spectrum data of the quantum dot material;

[0114] In this example, based on the quantum dot material data, photoluminescence was measured using a photoluminescence spectrometer to obtain luminescence spectrum data. Ultraviolet or blue light excitation was used, with an excitation wavelength of 450nm. The spectrometer resolution was set to 0.5nm, and the test temperature was 25°C. By measuring the luminescence intensity of the quantum dot material at different wavelengths, a photoluminescence spectrum curve was obtained, generating luminescence spectrum data. This data was used for subsequent wavelength distribution statistics and material property analysis.

[0115] Step S122: performing spectrum wavelength distribution statistics based on the photoluminescence spectrum data of the quantum dot material, thereby obtaining spectrum wavelength distribution data;

[0116] In this embodiment, the luminescence intensity of each wavelength range within the photoluminescence spectrum is statistically analyzed based on the photoluminescence spectrum data to generate spectral wavelength distribution data. This statistical method divides the spectrum into several wavelength intervals (e.g., 5 nm intervals) and calculates the luminescence intensity within each interval. This allows the luminescence intensity distribution of the quantum dot material within different wavelength ranges to be determined, providing basic data for subsequent peak feature extraction.

[0117] Step S123: extracting spectral wavelength peak features based on the spectral wavelength distribution data, thereby obtaining spectral wavelength peak data;

[0118] In this embodiment, the peak wavelength (i.e., the wavelength at which the spectral intensity reaches its maximum) is extracted from the spectral wavelength distribution data. This is accomplished by fitting the spectral waveform or directly extracting the maximum location from the spectral distribution data. This peak value is typically correlated with the material's luminescent color. Assuming that a quantum dot material has a peak emission wavelength of 550nm, this data will serve as a key parameter in subsequent luminous efficiency calculations.

[0119] Step S124: Calculating the spectrum full width at half maximum according to the spectrum wavelength distribution data, thereby obtaining spectrum full width at half maximum data;

[0120] In this example, the full width at half maximum (FWHM) of the spectrum is calculated using the spectral wavelength distribution data. The full width at half maximum refers to the wavelength interval corresponding to the spectral intensity at half its maximum value and is typically used to characterize the purity of the luminescent color. The specific calculation method is to start from the spectral peak point, find the two wavelength positions where the spectral intensity is half of the peak value, and calculate the difference between these two wavelengths. Assuming that the FWHM of the quantum dot material is 30nm, it indicates that its luminescence is relatively pure.

[0121] Step S125: Calculating the internal and external quantum luminous efficiencies based on the spectral wavelength peak data and the spectral full width at half maximum data to obtain internal and external quantum luminous efficiency data, and calculating the luminous loss difference based on the internal and external quantum luminous efficiency data to obtain internal and external quantum luminous efficiency difference data;

[0122] In this embodiment, the internal quantum efficiency is 70% based on the ratio of the number of photons emitted by the quantum dots to the number of excitation photons absorbed. The number of emitted photons and the number of absorbed photons are determined experimentally, and the calculation formula is: internal quantum efficiency = (number of emitted photons / number of absorbed photons) × 100%. The external quantum efficiency is 60% by measuring the number of photons propagating from the quantum dot layer to the outside world. The difference between the internal and external quantum efficiencies is calculated to be 10%. The reasons for the difference in internal and external quantum efficiencies (such as interface reflection and material absorption loss) are calculated, and the difference in luminescence loss is recorded as 10%.

[0123] Step S126: evaluating the luminous efficiency of the quantum dot material based on the internal and external quantum luminous efficiency difference data, thereby obtaining the luminous performance data of the quantum dot material.

[0124] In this example, the luminescence performance of quantum dot materials is evaluated based on the difference between internal and external quantum luminous efficiencies. By comparing the luminous efficiency of the quantum dot material with industry standards or laboratory reference values, we analyze whether its luminous efficiency meets expectations. Assuming a material has a 10% difference between internal and external quantum efficiencies, this luminous efficiency evaluation indicates that the material has excellent luminescence performance and is suitable for use in high-end displays.

[0125] Optionally, step S13 is specifically as follows:

[0126] Step S131: performing quantum distribution density feature extraction and quantum distribution position feature extraction based on the quantum dot distribution data, thereby obtaining quantum distribution density data and quantum distribution position data;

[0127] In this embodiment, the quantum dot distribution density characteristics and quantum dot distribution position characteristics are extracted by analyzing the quantum dot distribution data. This process uses statistical algorithms and spatial analysis techniques, specifically using two-dimensional distribution mapping or three-dimensional distribution models to accurately locate the spatial distribution of quantum dots. The extracted quantum distribution density data can be used to calculate the number distribution of quantum dots per unit area or volume through mean density calculation. The quantum distribution position data extracts the precise position information of each quantum dot through a position coordinate system, such as an XY coordinate system on the surface of a display screen. The spatial distribution of quantum dots is scanned to generate a density distribution heat map. The spatial position coordinates are collected using a sensor with a resolution of 10nm to extract the number of quantum dots per square centimeter.

[0128] Step S132: Acquire display screen illumination data;

[0129] In this example, ambient light data for a quantum dot display is acquired, including light intensity, spectral distribution, and angle of incidence. This light data is acquired using a light sensor, providing important input parameters for subsequent optical simulations and calculations of quantum dot luminescence consistency. While the display is operating, the ambient light sensor collects light intensity information, measuring 500 lux across a spectral range of 380 to 700 nm and an angle of incidence of 30 degrees.

[0130] Step S133: performing magnetic field uniform gradient control according to the quantum distribution density data, thereby obtaining quantum uniform distribution density data;

[0131] In this embodiment, based on quantum dot density data, an externally controlled magnetic field system is used to control the gradient uniformity of the quantum dot material to ensure uniform distribution of the quantum dots within the display area. This uniformity is achieved by dynamically adjusting the magnetic field strength and direction, ensuring consistent density of the quantum dot material across different areas. At magnetic field strengths between 0.1 Tesla and 0.5 Tesla, the quantum dot distribution is adjusted to maintain a quantum dot density fluctuation of less than 5% per square centimeter across the display.

[0132] Step S134: performing micro-nanostructure template guided deposition according to the quantum distribution position data, thereby obtaining quantum micro-nanostructure template distribution data;

[0133] In this embodiment, quantum dot material is precisely deposited using a micro-nanostructured template based on quantum dot distribution position data. This template, fabricated using micro-nanofabrication technology, guides the deposition of quantum dots in specific areas. This process ensures accurate distribution of quantum dots within the intended area, enhancing the optical display effect. With a template dimensional accuracy of 1 micron, by controlling the position of the nanostructured template, quantum dot material is deposited on designated pixel locations with a deposition error of no more than 2 microns.

[0134] Step S135: integrating quantum dot distribution data according to the quantum uniform distribution density data and the quantum micro-nanostructure template distribution data, thereby obtaining quantum dot distribution data;

[0135] In this example, the final quantum dot distribution data is obtained by integrating the uniform quantum dot density data with the micro-nanostructure template distribution data. This step utilizes a data fusion algorithm to combine density information with spatial position information, ensuring that the quantum dot material is distributed uniformly and accurately within different regions. By combining the density information of the number of quantum dots per square centimeter with the template deposition data, full-screen quantum dot distribution data is generated, with a fluctuation range of ±3% for the number of quantum dots within the displayed area.

[0136] Step S136: performing luminous intensity consistency calculation based on the quantum dot distribution data to obtain quantum dot optical consistency data.

[0137] In this example, optical simulation software was used to calculate the luminous intensity consistency of the display. This calculation considers the position and density distribution of each quantum dot, assessing the consistency of light intensity across the entire display area to ensure uniform brightness of the displayed image. By calculating the luminous intensity differences, the final quantum dot optical consistency data was obtained.

[0138] Optionally, step S133 is specifically as follows:

[0139] Drawing a quantum density distribution map according to the quantum distribution density data, thereby obtaining a quantum density distribution map;

[0140] In this embodiment, it is necessary to extract the spatial position and density information of all quantum dots from the quantum dot distribution data. These data will be used to create a quantum density distribution map. Specifically, a spatial distribution image of quantum dots is obtained by a high-resolution scanning microscope, and the distribution of quantum dots is converted into a two-dimensional heat map using image processing software (such as MATLAB or ImageJ). The density of quantum dots is determined based on the pixel density in the graph. For example, areas with high density are represented by dark red, and areas with low density are represented by light blue. Assume that within 1 square centimeter of the display area, the quantum dot distribution density ranges from 10^6 / cm 2 to 10^9 / cm 2 A scanning microscope with a resolution of 0.01 mm was used for image acquisition, and a density distribution map with a color gradient was generated in the software. The density of quantum dots in dense areas was set to dark red, and the sparse areas were set to light blue.

[0141] Perform quantum distribution density statistics based on the quantum density distribution map to obtain quantum dense distribution area data and quantum sparse distribution area data;

[0142] In this embodiment, after obtaining the quantum density distribution map, a statistical analysis tool (such as R or Python) is used to perform statistics on the quantum dot distribution in the map. By setting a density threshold, the display area is divided into a quantum dense distribution area and a quantum sparse distribution area. The dense area is defined as a region with a density higher than 10^8 / cm 2 The sparse area is defined as a region with a density lower than 10^7 / cm 2 In the density distribution diagram, for density higher than 10^8 / cm 2 The results show that these areas account for 40% of the total area. The density of sparse areas is less than 10^7 / cm 2 , accounting for 20% of the total area. These statistical results will be used in the subsequent magnetic field application steps.

[0143] Applying a low-intensity magnetic field to a region where quantum densely distributed data is present, thereby obtaining quantum low-intensity magnetic field data;

[0144] In this embodiment, a low-intensity magnetic field is used for processing in areas with dense quantum distribution. By setting a uniform magnetic field gradient, the magnetic field strength is 0.05 Tesla and applied to the dense area. This process is intended to cause the quantum dots to make a slight displacement in the area, thereby reducing the phenomenon of local over-density. A low-intensity magnetic field of 0.05 Tesla is applied to the detected dense area for 30 seconds. The application of the magnetic field will reduce the density of quantum dots in the dense area by about 15%, and the density value will decrease from the original 10^9 / cm 2 Reduced to 10^8 / cm 2 This step ensures a more uniform distribution of quantum dots.

[0145] Applying a high-intensity magnetic field to the quantum sparsely distributed area data to obtain quantum high-intensity magnetic field data;

[0146] In this embodiment, a high-intensity magnetic field is applied to the quantum sparse distribution area to promote the aggregation of quantum dots. A magnetic field with an intensity of 0.3 Tesla is used, and it is ensured that the magnetic field is evenly distributed in the sparse area. This step is intended to increase the density of quantum dots in the sparse area to a more uniform level. A high-intensity magnetic field of 0.3 Tesla is applied to the sparse area for 20 seconds. This magnetic field intensity causes the density of quantum dots in the sparse area to increase by about 20%, from the original 10^6 / cm 2 Increased to 10^7 / cm 2 This process optimizes the quantum dot distribution within the area.

[0147] Designing magnetic field channels based on quantum low-intensity magnetic field data and quantum high-intensity magnetic field data to obtain quantum magnetic field channel data;

[0148] In this embodiment, a magnetic field channel is designed to optimize the distribution of quantum dots based on low-intensity magnetic field data and high-intensity magnetic field data. The magnetic field channel is effectively controlled by setting different magnetic field intensity regions. Finite element analysis is used in the design process to model the effects of different magnetic field intensities to create an optimal magnetic field channel. The designed magnetic field channel includes a low-intensity region (0.05 Tesla) and a high-intensity region (0.3 Tesla), and a magnetic field gradient model is created by design software. According to the model, a low-intensity magnetic field ring is formed around the dense area, while a high-intensity magnetic field is formed in the center of the sparse area. This design ensures a uniform distribution of quantum dots throughout the display area.

[0149] The quantum uniform distribution density is calculated based on the quantum magnetic field channel data to obtain the quantum uniform distribution density data.

[0150] In this embodiment, after the magnetic field channel is designed and applied, a sensor is used to measure the quantum dot distribution density of the entire display area and calculate the uniformity. The calculation results will be compared with the expected distribution to evaluate the effect of the magnetic field channel design. The results will be used to further adjust the design of the magnetic field channel to optimize the distribution of quantum dots. By setting the sensor to measure the quantum dot density in the display area, the uniform distribution density of quantum dots in the display area is calculated, with the goal of being within an error range of ±5%. The final results show that the quantum dot density is maintained at 10^7 / cm2 throughout the entire area. 2 to 10^8 / cm 2 The uniformity required by the design is achieved.

[0151] Optionally, step S134 is specifically as follows:

[0152] Extracting quantum distribution coordinate features based on quantum distribution position data to obtain quantum distribution coordinate data;

[0153] In this embodiment, based on the quantum dot distribution position data, the spatial coordinates of each quantum dot are extracted by a high-precision positioning system (for example, using a scanning probe microscope or an atomic force microscope). These coordinate data will be used to further design the deposition structure of the quantum dots. The accuracy of the quantum distribution coordinate feature extraction needs to reach the nanometer level to ensure the accuracy of the data. The extracted coordinate data includes the X, Y, and Z coordinate values ​​of each quantum dot. Assuming that in a 1cm 2 The coordinates of the quantum dots are extracted within a region with an accuracy of ±5 nanometers. The resulting coordinate data includes the X, Y, and Z coordinates of 1,000 quantum dots. For example, the coordinates of the first quantum dot are (100.5 nm, 200.2 nm, 50.8 nm), the second are (102.1 nm, 198.7 nm, 51.0 nm), and so on.

[0154] Design the gate structure according to the quantum distribution coordinate data to obtain the quantum gate structure data;

[0155] In this embodiment, a suitable gate structure is designed based on the quantum distribution coordinate data. The gate structure is a microstructure used to control the distribution and arrangement of quantum dots, usually involving a nanoscale grid or lattice. By calculating the spatial distribution and size of the quantum dots, the aperture, spacing and overall layout of the gate are designed to ensure the effective deposition and arrangement of the quantum dots. The design of the gate structure needs to consider the distribution density and size of the quantum dots to optimize the deposition effect. A gate structure is designed with an aperture of 50 nanometers and a spacing between holes of 100 nanometers. Based on the extracted coordinate data, the gate design ensures that the hole is located in the center of the dense area, the shape of the hole is circular, and the size can be accurate to ±2 nanometers to ensure that the quantum dots can be accurately aligned during the deposition process.

[0156] Calculating the size of the nanostructure according to the quantum distribution coordinate data to obtain the size data of the nanostructure;

[0157] In this embodiment, after designing the gate structure, the required nanostructure dimensions are calculated based on the quantum distribution coordinate data. This step involves determining the precise dimensions of the nanostructure to accommodate the size and distribution characteristics of the quantum dots. The dimension calculation includes the height, width, and spacing of the structure to ensure that it can effectively support the deposition of quantum dots. The calculation results show that the nanostructure needs to be 100 nanometers wide, 200 nanometers high, and 50 nanometers apart. These dimensions ensure that the nanostructure can effectively accommodate quantum dots and match the aperture and spacing of the gate design, ensuring that the deposited quantum dots can accurately fill each structural unit.

[0158] Designing a micro-nanostructure template based on quantum gate structure data and nanostructure size data, thereby obtaining micro-nanostructure template data;

[0159] In this embodiment, the designed micro-nanostructure template contains 1,000 nanometer-scale holes within an area of ​​1x1 mm, each with a diameter of 50 nanometers and a spacing of 100 nanometers. The template is manufactured using photolithography technology, and these nanometer-scale structures are formed on a silicon wafer using an electron beam lithography instrument with an accuracy controlled within ±5 nanometers. Based on the quantum gate structure data and nanostructure size data, the micro-nanostructure template is designed. These templates are used to guide the deposition process of quantum dots. The micro-nanostructure template includes nanometer-scale patterns and structures, which are used to create an orderly arrangement of quantum dots. The template design needs to be accurate to the nanometer level to ensure high-quality deposition results.

[0160] Designing a target deposition area based on the quantum dense distribution area data and the quantum sparse distribution area data, thereby obtaining target deposition area data;

[0161] In this embodiment, within the 1x1 cm display area, the target deposition area is designed to include dense areas (accounting for 40% of the total area) and sparse areas (accounting for 20% of the total area), and the remaining areas are of medium density. The design of the target deposition area ensures that the quantum dots can cover the entire display area and more deposition is performed in the dense areas. The target deposition area is designed based on the quantum dense distribution area data and the quantum sparse distribution area data. These areas are designed to ensure that the deposition of quantum dots can cover all required areas while avoiding unnecessary deposition waste. The target deposition area typically includes a combination of dense and sparse areas to achieve a uniform distribution of quantum dots.

[0162] Performing quantum template alignment based on the micro-nanostructure template data and the target deposition area data to obtain quantum template alignment data;

[0163] In this embodiment, a laser alignment system is used to align the micro-nanostructure template to the target deposition area with an accuracy requirement of ±1 nanometer. The alignment process includes multiple fine-tuning between the template and the deposition area to ensure that the holes in the template fully match the design of the dense and sparse areas. Based on the micro-nanostructure template data and the target deposition area data, the micro-nanostructure template is aligned with the target deposition area. This step uses high-precision alignment equipment (such as a laser alignment system) to ensure accurate alignment of the template with the target area to achieve efficient and uniform quantum dot deposition.

[0164] Depositing quantum dots according to the quantum template alignment data, thereby obtaining quantum dot deposition data;

[0165] In this example, quantum dots were deposited using PVD technology on the aligned template. Deposition conditions were set at 300°C for 60 minutes, using an argon and nitrogen atmosphere. After deposition, the quantum dots formed a uniform layer in each template hole, achieving the desired deposition density.

[0166] The quantum dot distribution is detected based on the quantum dot deposition data to obtain the quantum micro-nanostructure template distribution data.

[0167] In this example, the deposited quantum dots were examined using a scanning electron microscope (SEM) with a resolution of ±5 nanometers. The results showed that the quantum dot distribution met the design requirements, with uniform distribution between dense and sparse areas, meeting the design criteria. The distribution data of the quantum dots within the micro-nanostructure template was recorded and analyzed to confirm the quality of the final result.

[0168] Optionally, step S2 is specifically:

[0169] Step S21: extracting optical structure features according to the display screen design data, thereby obtaining optical structure feature data;

[0170] In this embodiment, optical structural features are extracted from the display screen design data. Assume that the design data includes the thickness of the display screen's material layers, the distance between layers, and the refractive index of the optical material. Computer-aided design (CAD) software is used to input the display screen's design parameters, such as a front glass layer thickness of 0.5 mm, a liquid crystal layer thickness of 0.1 mm, and a backlight optical performance of a refractive index of 1.5. Simulation software is used to extract optical structural feature data, such as the thickness of the optical layer, the light propagation path, and the refraction and reflection characteristics of the light. The resulting optical structural feature data includes the optical parameters, refractive index, transmittance, and other characteristics of each layer.

[0171] Step S22: performing material thermal performance analysis based on the optical structure characteristic data to obtain material thermal performance data;

[0172] In this embodiment, the thermal properties of the material are analyzed using optical structure characteristic data. Assume that the materials we analyze include liquid crystal, backlight, and front glass layer. The thermal conductivity and thermal expansion coefficient of these materials are measured using laboratory thermal analysis equipment (such as differential scanning calorimeter DSC). Assume that the thermal conductivity of the liquid crystal is 0.15W / (m·K) and the thermal expansion coefficient is 2.5×10 - 6 K -1 The thermal conductivity of the backlight material is 1.2W / (m·K), and the thermal expansion coefficient is 1.8×10 -6 K -1 Using these data, the thermal behavior of each material at different operating temperatures is calculated to evaluate its thermal stability and applicability.

[0173] Step S23: evaluating the optical properties of the material according to the optical structure characteristic data, thereby obtaining the optical properties of the material;

[0174] In this embodiment, the optical performance of the material is evaluated based on the optical structure characteristic data. The transmittance, reflectance, and absorptivity of the material are measured using optical performance testing equipment (such as a spectrometer). For example, for the front glass layer, the transmittance is measured to be 90%, the reflectance is 8%, and the absorptivity is 2%; for the liquid crystal layer, the transmittance is 85%, the reflectance is 10%, and the absorptivity is 5%. This data is used to evaluate the optical performance of each material to determine whether it meets the design requirements and how it affects the optical performance of the overall display.

[0175] Step S24: integrating display screen material characteristics according to the material thermal performance data and the material optical properties, thereby obtaining display screen material characteristic data;

[0176] In this example, the thermal and optical performance data of the materials were integrated. Assuming the thermal conductivity of the front glass layer is 0.8 W / (m·K), the optical performance data shows a transmittance of 92%. The thermal conductivity of the liquid crystal layer is 0.15 W / (m·K), and its transmittance is 85%. By comprehensively analyzing this data, the thermal stability and optical performance of the display at different temperatures were calculated. The results of the integrated data show that in high-temperature environments, the front glass layer performs better than the liquid crystal layer and has a higher contribution to light transmittance.

[0177] Step S25: performing display optical simulation according to the display screen material characteristic data, thereby obtaining display optical simulation data.

[0178] In this embodiment, optical simulation is performed using the material property data of the display screen. Optical simulation software (such as OptiSystem or LightTools) is used to input the comprehensive optical data of the front glass layer and the liquid crystal layer, including the light transmittance, reflectivity, and material thickness. The operating conditions of the display screen are set, such as the brightness and angle of the light source. The overall optical performance of the display screen is simulated, including light distribution, brightness uniformity, and color performance. The simulation results show that the high transmittance of the front glass layer provides better optical performance, while the optical properties of the liquid crystal layer have a significant impact on the display effect.

[0179] Optionally, step S22 is specifically as follows:

[0180] Step S221: extracting the optical absorption coefficient characteristics of the material according to the optical structure characteristic data, thereby obtaining the optical absorption coefficient data of the material;

[0181] In this embodiment, the optical absorption coefficient characteristics of the material are extracted based on the optical structure characteristic data. It is assumed that the optical structure characteristic data includes the refractive index, thickness, and spectral data of the material. A spectrophotometer is used to measure the optical absorption coefficient of the material within a specific wavelength range. For example, the optical absorption coefficient of the front glass layer at 550nm is 0.02cm-1, and the optical absorption coefficient of the liquid crystal layer at 550nm is 0.15cm-1. The extraction results are the absorption coefficient data of each material at different wavelengths, and the change of light absorption with wavelength is recorded.

[0182] Step S222: simulating the heat generation characteristics of the material according to the material optical absorption coefficient data, thereby obtaining the material heat generation characteristic data;

[0183] In this embodiment, the heat generation characteristics of the material are simulated based on the optical absorption coefficient data of the material. Using thermal simulation software (such as COMSOL Multiphysics), the optical absorption coefficient data of the material and the illumination conditions are input. For example, the front glass layer is exposed to an illumination intensity of 1000W / m 2 The heat generated is 2W / m 2 Simulation calculations show that the heat generated by the liquid crystal layer under the same conditions is 15W / m 2 Through these simulation results, the heat generation characteristics data of each material under light were obtained.

[0184] Step S223: Calculating the thermal conductivity coefficient and thermal diffusivity of the material based on the material heat generation characteristic data, thereby obtaining the thermal conductivity coefficient data and thermal diffusivity data of the material;

[0185] In this embodiment, the thermal conductivity and thermal diffusivity of the material are calculated based on the heat generation characteristic data of the material. Assume that the heat generation characteristic data of the front glass layer is 2W / m 2Using a thermal conductivity measuring device (such as a heat flow meter), the thermal conductivity of the front glass layer is measured to be 1.0 W / (m·K), and the thermal conductivity of the liquid crystal layer is 0.15 W / (m·K). The thermal diffusivity (α) of the material is calculated as the ratio of thermal conductivity (λ) to specific heat capacity (c_p) and density (ρ). The thermal diffusivity of the front glass layer is 0.2×10 -6 m 2 / s, the liquid crystal layer is 0.03×10 -6 m 2 / s.

[0186] Step S224: performing heat and temperature transfer simulation on the optical structure characteristic data according to the material thermal conductivity data and the material thermal diffusivity data, thereby obtaining material heat and temperature transfer data;

[0187] In this embodiment, heat temperature transfer simulation is performed on the optical structure characteristic data based on the material thermal conductivity coefficient and thermal diffusivity data. Using thermal simulation software, the material thermal conductivity coefficient, thermal diffusivity and optical structure characteristic data are input. Assuming that the optical structure characteristics include the front glass layer thickness of 0.5mm and the liquid crystal layer thickness of 0.1mm. The simulation results show that under the light intensity of 1000W / m 2 Under these conditions, the temperature distributions of the front glass layer and the liquid crystal layer are 50°C and 80°C respectively. The temperature transfer data of the material under different heat input conditions are obtained through simulation.

[0188] Step S225: Calculating the material heat capacity based on the material heat temperature transfer data, thereby obtaining the material heat capacity data;

[0189] In this example, the material's heat capacity is calculated based on the material's heat-temperature transfer data. Assuming the material's mass and specific heat capacity are known, for example, the front glass layer has a specific heat capacity of 0.84 J / (g·K) and a mass of 100 g. Using the heat-temperature transfer data, the material's heat capacity is calculated (C = m × c_p) to be 84 J / K. For the liquid crystal layer, assuming a specific heat capacity of 1.2 J / (g·K) and a mass of 50 g, its heat capacity is calculated to be 60 J / K.

[0190] Step S226: performing thermal performance evaluation on the optical structure characteristic data according to the material heat capacity data, thereby obtaining material thermal performance data.

[0191] In this example, thermal performance evaluation of optical structure characteristic data is performed based on material heat capacity data. Using an evaluation model, the material heat capacity data is input into thermal performance evaluation software. Assume that the evaluation objective is to ensure the thermal stability of the display at operating temperatures. By analyzing the material heat capacity and its role in the optical structure, the thermal performance of the material under high light intensity is evaluated to determine whether it meets the requirements. The results show that the front glass layer has a higher heat capacity and is therefore more suitable for high-temperature environments, while the thermal performance of the liquid crystal layer requires improvement under long-term operation.

[0192] Optionally, step S4 is specifically:

[0193] Step S41: extracting display energy consumption characteristics based on display optical simulation data to obtain display energy consumption data;

[0194] In this embodiment, the display energy consumption feature extraction is performed based on the display optical simulation data. It is assumed that the display optical simulation data includes optical power consumption information under different brightness settings. Use optical simulation software (such as OptiSystem) to input the optical data of the display screen under different brightness, contrast and color settings. Simulate the display screen at high brightness (1000cd / m 2 ) and low brightness (200cd / m 2 ). The results show that at high brightness, the display consumes 50W of energy, while at low brightness it consumes 15W. The display energy consumption data is extracted and its characteristics are recorded as it changes with brightness and color mode.

[0195] Step S42: classifying energy consumption modes according to the displayed energy consumption data, thereby obtaining a dynamic interaction mode and a video playback mode;

[0196] In this embodiment, energy consumption modes are classified based on display energy consumption data. Assume that the display energy consumption data includes energy consumption in different usage scenarios, such as dynamic interaction (such as web browsing) and video playback mode. Use a data classification algorithm (such as K-means clustering) to classify the energy consumption data by scenario. For example, the energy consumption data of the dynamic interaction mode is 30W, while the energy consumption data of the video playback mode is 70W. Through classification, the energy consumption modes of the display screen during dynamic interaction and video playback are determined and marked as mode A and mode B respectively.

[0197] Step S43: Draw an energy consumption curve according to the dynamic interaction mode and the video playback mode, thereby obtaining energy consumption curve data;

[0198] In this embodiment, an energy consumption curve is drawn based on the energy consumption data of the dynamic interaction mode and the video playback mode. Use drawing software (such as Matplotlib) to input the classified energy consumption data and draw an energy consumption curve. Assume that in the dynamic interaction mode, the energy consumption gradually increases from 20W to 30W, while in the video playback mode, the energy consumption increases from 60W to 70W. The drawn curve shows the energy consumption change trend in different modes, and presents the energy consumption curves of the dynamic interaction mode and the video playback mode in the form of a chart.

[0199] Step S44: extracting the power characteristics of the driving circuit according to the energy consumption curve data, thereby obtaining the power data of the driving circuit;

[0200] In this embodiment, the power characteristics of the driving circuit are extracted based on the energy consumption curve data. Assume that the energy consumption curve data shows that the power of the driving circuit is 20W in dynamic interaction mode and 60W in video playback mode. Use a power analysis tool (such as a power analyzer) to extract the power data of the driving circuit in different operating modes. Record power characteristics such as current, voltage, and power factor to determine the power characteristics of the driving circuit.

[0201] Step S45: performing efficiency conversion according to the power data of the driving circuit to obtain efficiency data of the driving circuit, and performing efficiency statistics according to the efficiency data of the driving circuit to obtain low-efficiency driving circuit data;

[0202] In this embodiment, efficiency conversion is performed based on the power data of the driver circuit. Assume that the power of the driver circuit in dynamic interaction mode is 20W, the input voltage is 12V, the current is 1.67A, and the actual power is 20W. The efficiency calculation formula is: Efficiency = Output Power / Input Power × 100%. Assuming the input power is 22W, the efficiency is 90.9%. Based on the efficiency data, statistics are collected and driver circuits with an efficiency below 80% are identified as low-efficiency driver circuit data.

[0203] Step S46: Optimizing the circuit structure according to the low-efficiency driving circuit data, thereby obtaining optimized display driving circuit data.

[0204] In this embodiment, circuit structure optimization is performed based on low-efficiency drive circuit data. Assume that several low-efficiency drive circuits (with efficiency below 80%) are identified, such as drive circuits A and B. Circuit optimization tools (such as Cadence) are used to improve the design of these low-efficiency circuits, such as replacing more power-efficient components and optimizing the circuit layout to reduce energy loss. After optimization, the efficiency of the drive circuit is recalculated to ensure that the efficiency of all optimized circuits reaches above 90%. The optimized display drive circuit data is recorded and its performance improvement is verified.

[0205] This specification also provides a liquid crystal display screen, which includes a liquid crystal display screen main body, a power supply unit, and an electrical control unit. The power supply unit is installed inside the liquid crystal display screen main body, and the electrical control unit is electrically connected to the power supply unit. The electrical control unit is used to charge the liquid crystal display screen main body and control the liquid crystal display screen main body. The electrical control unit includes:

[0206] Quantum dot display module: used to obtain display design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction based on the display design data, thereby obtaining quantum dot material data and quantum dot distribution data; perform quantum dot display based on the quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data;

[0207] Display optical simulation module: used to extract optical structure features according to display screen design data, thereby obtaining optical structure feature data; perform display optical simulation according to the optical structure feature data, thereby obtaining display optical simulation data;

[0208] Thermal design optimization module: used to obtain display temperature sensor data and perform display stability analysis on quantum dot display data based on the display temperature sensor data, thereby obtaining display stability data; and perform thermal design optimization on display design data based on the display stability data, thereby obtaining thermal design optimization data;

[0209] Driving circuit optimization module: used to extract display energy consumption characteristics based on display optical simulation data, thereby obtaining display energy consumption data; optimize the display driving circuit based on the display energy consumption data, thereby obtaining display driving circuit optimization data;

[0210] Operation power consumption control module: used to build a display power consumption monitoring system based on the heat dissipation design optimization data and the display driver circuit optimization data, so as to obtain the display power consumption monitoring system data and upload it to the display management cloud platform to perform the display operation power consumption control task.

[0211] The liquid crystal display provided by the present invention can implement the above-mentioned liquid crystal display control method, and is used to combine the operation and signal transmission medium between various modules to complete a liquid crystal display control method. The internal modules of the device cooperate with each other to achieve power consumption control of the liquid crystal display.

[0212] The present invention is therefore intended to be illustrative and non-restrictive in all respects, with the scope of the invention being defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the application documents are intended to be embraced within the present invention.

[0213] The foregoing description is intended only to provide specific embodiments of the present invention, which will enable those skilled in the art to understand and implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not intended to be limited to the embodiments shown herein, but is to be construed in the widest possible manner consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling a liquid crystal display screen, characterized in that: The following steps are involved: Step S1: Acquire display screen design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction according to the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data; Performing quantum dot display according to quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data; Step S2: extracting optical structure features according to display screen design data, thereby obtaining optical structure feature data; Performing display optical simulation according to the optical structure characteristic data, thereby obtaining display optical simulation data; Step S3: acquiring display screen temperature sensing data, and performing display stability analysis on quantum dot display data according to the display screen temperature sensing data, thereby obtaining display stability data; Optimize the heat dissipation design of the display screen design data according to the display stability data, so as to obtain the heat dissipation design optimization data; Step S4: extracting display energy consumption characteristics according to the display optical simulation data, thereby obtaining display energy consumption data; Optimizing the display driving circuit according to the display energy consumption data, thereby obtaining display driving circuit optimization data; Step S5: construct a display power consumption monitoring system according to the heat dissipation design optimization data and the display driving circuit optimization data, thereby obtaining display power consumption monitoring system data, and uploading it to the display management cloud platform to execute the display operation power consumption control task.

2. The control method of the liquid crystal display screen according to claim 1, characterized in that: Step S1 is specifically as follows: Step S11: acquiring display screen design data, and performing quantum dot material feature extraction and quantum dot distribution feature extraction according to the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data; Step S12: analyzing the luminescence performance of the material according to the quantum dot material data, thereby obtaining the luminescence performance data of the quantum dot material; Step S13: performing optical consistency analysis according to the quantum dot distribution data, thereby obtaining quantum dot optical consistency data; Step S14: integrating quantum material optical data according to the quantum dot material luminescence performance data and the quantum dot optical consistency data, thereby obtaining quantum material optical data; Step S15: generating a quantum dot display according to the quantum material optical data, thereby obtaining quantum dot display data.

3. The control method of the liquid crystal display screen according to claim 2, characterized in that: Step S12 is specifically as follows: Step S121: performing photoluminescence spectrum detection according to the quantum dot material data, thereby obtaining photoluminescence spectrum data of the quantum dot material; Step S122: performing spectrum wavelength distribution statistics according to the photoluminescence spectrum data of the quantum dot material, thereby obtaining spectrum wavelength distribution data; Step S123: extracting spectrum wavelength peak features according to the spectrum wavelength distribution data, thereby obtaining spectrum wavelength peak data; Step S124: Calculating the spectrum full width at half maximum according to the spectrum wavelength distribution data, thereby obtaining spectrum full width at half maximum data; Step S125: calculating the internal and external quantum luminous efficiency according to the spectrum wavelength peak data and the spectrum full width half maximum data, thereby obtaining the internal and external quantum luminous efficiency data, and calculating the luminous loss difference according to the internal and external quantum luminous efficiency data, thereby obtaining the internal and external quantum luminous efficiency difference data; Step S126: Evaluate the luminous efficiency of the quantum dot material based on the internal and external quantum luminous efficiency difference data, so as to obtain the luminous performance data of the quantum dot material.

4. The control method of the liquid crystal display screen according to claim 2, characterized in that: Step S13 is specifically as follows: Step S131: performing quantum distribution density feature extraction and quantum distribution position feature extraction according to the quantum dot distribution data, thereby obtaining quantum distribution density data and quantum distribution position data; Step S132: Acquire display screen illumination data; Step S133: performing magnetic field uniform gradient control according to quantum distribution density data, thereby obtaining quantum uniform distribution density data; Step S134: performing micro-nano structure template guided deposition according to the quantum distribution position data, thereby obtaining quantum micro-nano structure template distribution data; Step S135: integrating quantum dot distribution data according to quantum uniform distribution density data and quantum micro-nano structure template distribution data, thereby obtaining quantum dot distribution data; Step S136: Calculate the consistency of luminous intensity based on the quantum dot distribution data to obtain quantum dot optical consistency data.

5. The control method of the liquid crystal display screen according to claim 4, characterized in that: Step S133 is specifically as follows: Drawing a quantum density distribution map according to the quantum distribution density data, thereby obtaining a quantum density distribution map; According to the quantum density distribution diagram, the quantum distribution density is counted to obtain the quantum dense distribution area data and the quantum sparse distribution area data; Applying a low-intensity magnetic field to a region where quantum densely distributed data is located, thereby obtaining quantum low-intensity magnetic field data; Applying a high-intensity magnetic field to the quantum sparsely distributed area data, thereby obtaining quantum high-intensity magnetic field data; Designing a magnetic field channel according to quantum low-intensity magnetic field data and quantum high-intensity magnetic field data, thereby obtaining quantum magnetic field channel data; The quantum uniform distribution density is calculated based on the quantum magnetic field channel data, thereby obtaining the quantum uniform distribution density data.

6. The control method of the liquid crystal display screen according to claim 4, characterized in that: Step S134 is specifically as follows: Extracting quantum distribution coordinate features according to quantum distribution position data, thereby obtaining quantum distribution coordinate data; Design the gate structure according to the quantum distribution coordinate data, so as to obtain the quantum gate structure data; Calculating the size of the nanostructure according to the quantum distribution coordinate data, thereby obtaining the size data of the nanostructure; Designing a micro-nano structure template according to the quantum gate structure data and the nanostructure size data, thereby obtaining the micro-nano structure template data; Designing a target deposition area according to the quantum dense distribution area data and the quantum sparse distribution area data, thereby obtaining the target deposition area data; Performing quantum template alignment according to the micro-nanostructure template data and the target deposition area data, thereby obtaining quantum template alignment data; Depositing quantum dots according to the quantum template alignment data, thereby obtaining quantum dot deposition data; The quantum dot distribution is detected based on the quantum dot deposition data, thereby obtaining the quantum micro-nano structure template distribution data.

7. The control method of a liquid crystal display screen according to claim 1, characterized in that: Step S2 is specifically as follows: Step S21: extracting optical structure features according to display screen design data, thereby obtaining optical structure feature data; Step S22: performing material thermal performance analysis according to the optical structure characteristic data, thereby obtaining material thermal performance data; Step S23: evaluating the optical properties of the material according to the optical structure characteristic data, thereby obtaining the optical properties of the material; Step S24: integrating display screen material characteristics according to material thermal performance data and material optical performance data, thereby obtaining display screen material characteristic data; Step S25: performing display optical simulation according to the display screen material characteristic data, thereby obtaining display optical simulation data.

8. The control method of the liquid crystal display screen according to claim 7, characterized in that: Step S22 is specifically as follows: Step S221: extracting the optical absorption coefficient characteristics of the material according to the optical structure characteristic data, thereby obtaining the optical absorption coefficient data of the material; Step S222: simulating the heat generation characteristics of the material according to the material optical absorption coefficient data, thereby obtaining the heat generation characteristics data of the material; Step S223: Calculating the thermal conductivity coefficient and thermal diffusivity of the material according to the material heat generation characteristic data, thereby obtaining the thermal conductivity coefficient data and thermal diffusivity data of the material; Step S224: performing heat and temperature transfer simulation on the optical structure characteristic data according to the material thermal conductivity data and the material thermal diffusivity data, thereby obtaining material heat and temperature transfer data; Step S225: Calculating the material heat capacity according to the material heat temperature transfer data, thereby obtaining the material heat capacity data; Step S226: Perform thermal performance evaluation on the optical structure characteristic data according to the material heat capacity data, so as to obtain material thermal performance data.

9. The control method of a liquid crystal display screen according to claim 1, characterized in that: Step S4 is specifically as follows: Step S41: extracting display energy consumption characteristics according to display optical simulation data, thereby obtaining display energy consumption data; Step S42: classifying energy consumption modes according to the displayed energy consumption data, thereby obtaining a dynamic interaction mode and a video playback mode; Step S43: drawing an energy consumption curve according to the dynamic interaction mode and the video playback mode, thereby obtaining energy consumption curve data; Step S44: extracting the power characteristics of the driving circuit according to the energy consumption curve data, thereby obtaining the power data of the driving circuit; Step S45: performing efficiency conversion according to the power data of the driving circuit to obtain efficiency data of the driving circuit, and performing efficiency statistics according to the efficiency data of the driving circuit to obtain low-efficiency driving circuit data; Step S46: Optimizing the circuit structure according to the low-efficiency driving circuit data, thereby obtaining display driving circuit optimization data.

10. A liquid crystal display screen, characterized in that: The device comprises a liquid crystal display main body, a power supply unit and an electrical control unit. The power supply unit is installed inside the liquid crystal display main body. The electrical control unit is electrically connected to the power supply unit. The electrical control unit is used to charge the liquid crystal display main body and control the liquid crystal display main body. The electrical control unit comprises: Quantum dot display module: used to obtain display screen design data, and perform quantum dot material feature extraction and quantum dot distribution feature extraction based on the display screen design data, thereby obtaining quantum dot material data and quantum dot distribution data; perform quantum dot display based on the quantum dot material data and quantum dot distribution data, thereby obtaining quantum dot display data; Display optical simulation module: used to extract optical structure features according to display screen design data, thereby obtaining optical structure feature data; perform display optical simulation according to the optical structure feature data, thereby obtaining display optical simulation data; Heat dissipation design optimization module: used to obtain display screen temperature sensing data, and perform display stability analysis on quantum dot display data based on the display screen temperature sensing data, thereby obtaining display stability data; perform heat dissipation design optimization on display screen design data based on the display stability data, thereby obtaining heat dissipation design optimization data; Driving circuit optimization module: used to extract display energy consumption characteristics according to display optical simulation data, so as to obtain display energy consumption data; optimize the display driving circuit according to the display energy consumption data, so as to obtain display driving circuit optimization data; Operation power consumption control module: used to build a display power consumption monitoring system based on the heat dissipation design optimization data and the display driving circuit optimization data, so as to obtain the display power consumption monitoring system data and upload it to the display management cloud platform to perform the display operation power consumption control task.

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