Heat dissipation optimization method and system for graphene semiconductors

Abstract

The present invention provides a heat dissipation optimization method and system for graphene semiconductors, which relates to the field of graphene semiconductor technology, including: based on graphene semiconductor materials, determining a honeycomb structure, the graphene semiconductor materials have a thermal radiation coefficient mark and a thermal conductivity coefficient mark; configuring multiple heat dissipation flow lines corresponding to different heat dissipation methods; configuring multiple heat dissipation distribution maps corresponding to different heat dissipation methods; analyzing the influence of the band gap on the thermal radiation characteristics, determining the first semiconductor characteristic influence index; analyzing the influence of the band gap on the thermal conductivity characteristics, determining the second semiconductor characteristic influence index; establishing a heat dissipation performance evaluation model, and combining multiple heat dissipation flow lines and multiple heat dissipation distribution maps to perform heat dissipation iterative optimization. The present invention solves the technical problem that the heat dissipation design of the prior art is difficult to flexibly adapt to the needs of different heat dissipation methods, resulting in the inability to provide stable heat dissipation performance in a variety of application scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of graphene semiconductors, and in particular to a heat dissipation optimization method and system for graphene semiconductors. Background Art

[0002] As a new type of two-dimensional material with ultra-high thermal conductivity and good thermal radiation performance, graphene is widely used in the heat dissipation management of high-performance semiconductor devices. In modern electronic devices and the semiconductor industry, with the continuous improvement of chip integration and the increase in operating frequency, the power density inside the chip has increased dramatically, resulting in significant heat accumulation problems. How to effectively manage heat to ensure device stability, performance and service life has become a key technical challenge. However, traditional heat dissipation design lacks the ability to dynamically adapt to different heat dissipation methods, such as natural convection, forced convection and liquid cooling, and cannot provide stable heat dissipation performance in a variety of application scenarios, resulting in low heat dissipation efficiency of the equipment and insufficient adaptability and reliability. Summary of the invention

[0003] The present application provides a heat dissipation optimization method and system for graphene semiconductors, aiming to solve the technical problem that the heat dissipation design of the prior art is difficult to flexibly adapt to the needs of different heat dissipation methods, resulting in the inability to provide stable heat dissipation performance in a variety of application scenarios.

[0004] The first aspect disclosed in the present application provides a heat dissipation optimization method for graphene semiconductors, the method comprising: determining a honeycomb structure based on a graphene semiconductor material, the graphene semiconductor material having a thermal radiation coefficient identifier and a thermal conductivity coefficient identifier; analyzing the heat flux distribution under different heat dissipation modes according to the honeycomb structure, and configuring a plurality of heat dissipation flow lines corresponding to different heat dissipation modes; analyzing the temperature field changes under different heat dissipation modes according to the honeycomb structure, and configuring a plurality of heat dissipation distribution maps corresponding to different heat dissipation modes; analyzing the influence of the band gap on the thermal radiation characteristics based on the plurality of heat dissipation flow lines corresponding to different heat dissipation modes and the plurality of heat dissipation distribution maps corresponding to different heat dissipation modes, and determining a first semiconductor characteristic influencing index; analyzing the influence of the band gap on the thermal conduction characteristics based on the plurality of heat dissipation flow lines corresponding to different heat dissipation modes and the plurality of heat dissipation distribution maps corresponding to different heat dissipation modes, and determining a second semiconductor characteristic influencing index; establishing a heat dissipation performance evaluation model based on the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, and performing iterative heat dissipation optimization in combination with the plurality of heat dissipation flow lines corresponding to different heat dissipation modes and the plurality of heat dissipation distribution maps corresponding to different heat dissipation modes.

[0005] The second aspect disclosed in the present application provides a heat dissipation optimization system for graphene semiconductors, the system is used for the above-mentioned heat dissipation optimization method for graphene semiconductors, and the system includes: a honeycomb structure determination module, the honeycomb structure determination module is used to determine the honeycomb structure based on the graphene semiconductor material, the graphene semiconductor material has a thermal radiation coefficient identification and a thermal conductivity coefficient identification; a heat flux distribution analysis module, the heat flux distribution analysis module is used to analyze the heat flux distribution under different heat dissipation methods according to the honeycomb structure, and configure multiple heat dissipation flow lines corresponding to different heat dissipation methods; a temperature field change analysis module, the temperature field change analysis module is used to analyze the temperature field changes under different heat dissipation methods according to the honeycomb structure, and configure multiple heat dissipation distribution maps corresponding to different heat dissipation methods; a first influencing index determination module The first influencing index determination module is used to analyze the influence of the band gap on the thermal radiation characteristics based on multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods, and determine the first semiconductor characteristic influencing index; the second influencing index determination module, the second influencing index determination module is used to analyze the influence of the band gap on the thermal conduction characteristics based on multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods, and determine the second semiconductor characteristic influencing index; the heat dissipation iterative optimization module, the heat dissipation iterative optimization module is used to establish a heat dissipation performance evaluation model according to the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, and perform heat dissipation iterative optimization in combination with the multiple heat dissipation flow lines corresponding to different heat dissipation methods and the multiple heat dissipation distribution maps corresponding to different heat dissipation methods.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] Based on graphene semiconductor materials, a honeycomb structure is determined, which provides a geometric basis for subsequent heat flux distribution and temperature field analysis. In addition, the introduction of thermal radiation coefficient and thermal conductivity coefficient identification provides key material performance data for subsequent heat dissipation optimization. Based on the heat flux distribution analysis of different heat dissipation methods, multiple heat dissipation flow lines are configured to reduce heat accumulation in hot spots and improve the heat dissipation uniformity of the entire system. Heat dissipation flow lines are customized for different heat dissipation methods, so that the heat dissipation system can adapt to a variety of working environments and heat dissipation requirements, thereby improving the versatility and flexibility of the heat dissipation solution. By analyzing the changes in temperature fields under different heat dissipation methods, the characteristics of temperature distribution during equipment operation are clarified, providing accurate basic data for optimizing the heat dissipation solution. The layout map can intuitively present the heat dissipation efficiency under different heat dissipation methods, and guide the further optimization of heat-guiding microchannels and heat dissipation flow lines; analyze the influence of band gap on thermal radiation characteristics, determine the influencing index of the first semiconductor characteristics, quantify the key parameters of thermal radiation performance, and provide basic input for the heat dissipation performance evaluation model; analyze the influence of band gap on thermal conduction characteristics, determine the influencing index of the second semiconductor characteristics, and provide the heat dissipation performance evaluation model with key data for measuring thermal conduction performance; the heat dissipation performance evaluation model integrates the dual indicators of thermal radiation characteristics and thermal conduction characteristics, and provides a full range of evaluation standards for heat dissipation solutions. Through iterative heat dissipation optimization, it ensures that the heat dissipation flow lines and distribution maps can be continuously improved in practical applications, so as to achieve the best heat dissipation effect.

[0008] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 A schematic flow chart of a heat dissipation optimization method for graphene semiconductors provided in an embodiment of the present application.

[0010] Figure 2 A schematic diagram of the structure of a heat dissipation optimization system for graphene semiconductors provided in an embodiment of the present application.

[0011] Explanation of the reference numerals: honeycomb structure determination module 10 , heat flow distribution analysis module 20 , temperature field change analysis module 30 , first influencing index determination module 40 , second influencing index determination module 50 , heat dissipation iterative optimization module 60 . DETAILED DESCRIPTION

[0012] The embodiments of the present application provide a heat dissipation optimization method and system for graphene semiconductors, thereby solving the technical problem that the heat dissipation design of the prior art is difficult to flexibly adapt to the needs of different heat dissipation methods, resulting in the inability to provide stable heat dissipation performance in a variety of application scenarios.

[0013] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced below in conjunction with the accompanying drawings of the specification. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0014] Embodiment 1, as Figure 1 As shown, an embodiment of the present application provides a heat dissipation optimization method for a graphene semiconductor, the method comprising:

[0015] A honeycomb structure is determined based on a graphene semiconductor material, wherein the graphene semiconductor material has a thermal radiation coefficient identification and a thermal conductivity coefficient identification.

[0016] Identify graphene semiconductor materials. Graphene is a two-dimensional material formed by a single layer of carbon atoms arranged in a honeycomb shape. It has excellent thermal conductivity and electronic properties. Its thermal conductivity coefficient is very high and can effectively conduct heat. Analyze graphene semiconductor materials and identify their thermal radiation coefficient and thermal conductivity coefficient. The thermal radiation coefficient is a measure of the radiation capacity per unit area of ​​a material, and the thermal conductivity coefficient is the thermal conductivity of a material under a unit temperature difference. These two parameters are used to evaluate and optimize the heat dissipation performance of graphene. Determine the honeycomb structure based on graphene semiconductor materials. This structure is inspired by the nest structure of bees in nature. It has been widely studied and applied for its advantages in mechanical stability and material efficiency. The honeycomb structure can effectively improve the heat dissipation efficiency by increasing the heat dissipation surface area and optimizing the heat flow path.

[0017] According to the honeycomb structure, the heat flow distribution under different heat dissipation modes is analyzed, and a plurality of heat dissipation flow lines corresponding to the different heat dissipation modes are configured.

[0018] Numerical simulation tools are used to simulate the heat flow of honeycomb graphene structures under different heat dissipation conditions, including natural convection, forced convection, radiation heat dissipation, etc. The simulation tools generate a visual image of heat flow to determine how heat propagates from the heat source through the honeycomb structure, analyze the distribution of heat flux density and temperature in the honeycomb structure, identify heat accumulation areas and possible cold spots, and design heat dissipation flow lines based on the heat flow distribution results, that is, determine the optimal path for heat from the source to the heat dissipation medium (such as air or coolant). These paths need to ensure that heat energy is effectively and evenly removed from the surface of the semiconductor chip. For different heat dissipation methods, specific flow lines are designed. For example, in the scenario of forced heat dissipation using fans, the flow lines will consider the air flow direction and speed; when using a liquid cooling system, the flow rate, path and cooling efficiency of the coolant are considered. According to the simulation results and experimental data, the heat dissipation flow lines are iteratively adjusted to optimize the heat flow path to reduce thermal resistance and improve heat dissipation efficiency, and finally obtain multiple heat dissipation flow lines corresponding to different heat dissipation methods.

[0019] According to the honeycomb structure, the temperature field changes under different heat dissipation modes are analyzed, and a plurality of heat dissipation distribution maps corresponding to the different heat dissipation modes are configured.

[0020] Thermal analysis and finite element analysis software are used to simulate the temperature field of the honeycomb graphene structure under different heat dissipation conditions. The simulation includes but is not limited to natural convection, forced convection, liquid cooling and radiation cooling, and changes in parameters such as ambient temperature, heat input and flow rate of the cooling medium. It is determined how these variables affect the temperature distribution. Based on the simulation results, temperature distribution maps are generated. These maps show the temperature gradients of various parts in the honeycomb structure, highlighting hot spots and areas with better cooling effects. A corresponding heat dissipation distribution map is configured for each heat dissipation method, and multiple heat dissipation distribution maps corresponding to different heat dissipation methods are determined.

[0021] Based on multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods, the influence of the band gap on the thermal radiation characteristics is analyzed, and the first semiconductor characteristic influencing index is determined.

[0022] Analyze how the band gap width affects the thermal radiation characteristics of graphene. The band gap is the energy difference between the conduction band and the valence band in the band structure of semiconductor materials. It determines the electronic and optical properties of the material, including the thermal radiation ability. For example, use a computational model to simulate the effect of band gap changes on thermal radiation efficiency, and analyze the regulatory effect of band gap changes on thermal radiation characteristics under different heat dissipation conditions. Integrate the band gap analysis results with the heat dissipation flow lines and heat dissipation distribution map data corresponding to various heat dissipation methods, analyze how the band gap affects the thermal radiation performance of graphene semiconductors under different heat dissipation flow configurations, and define quantitative indicators to measure the effect of the band gap on thermal radiation characteristics. These indicators include thermal radiation efficiency, peak position of the thermal radiation spectrum, peak width, and the relationship with specific heat dissipation flow lines and temperature distribution, so as to determine the first semiconductor characteristic influencing index, which is used to compare the performance under different materials, structures and heat dissipation configurations.

[0023] Based on multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods, the influence of the band gap on the thermal conductivity characteristics is analyzed, and the influencing index of the second semiconductor characteristics is determined.

[0024] Analyze how the band gap width affects the thermal conductivity characteristics of graphene. The band gap usually affects the mobility of electrons, which is closely related to the thermal conductivity of the material. A smaller band gap can promote easier excitation of electrons, which may enhance the thermoelectric effect and improve thermal conduction. Use simulation tools, such as quantum mechanics calculation software or molecular dynamics simulation, to predict the thermal conductivity characteristics of graphene under different band gap configurations. Analyze how the change in the material band gap affects the thermal conduction path and efficiency under different heat dissipation configurations. Integrate the analysis of the impact of the band gap on the thermal conductivity characteristics with the data of the heat dissipation flow line and the heat dissipation distribution map, aiming to evaluate and optimize the specific impact of the band gap on thermal conduction under a specific heat dissipation method. Define quantitative indicators to measure the impact of the band gap on the thermal conduction characteristics, such as thermal conductivity, thermal diffusivity or thermal impedance, so as to determine the second semiconductor characteristic influencing indicator, which should reflect the thermal management ability of the material under different heat dissipation conditions.

[0025] According to the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, a heat dissipation performance evaluation model is established, and heat dissipation iterative optimization is performed in combination with multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods.

[0026] The parameters of the heat dissipation performance evaluation model are defined, including thermal conductivity, thermal radiation efficiency, heat flux density, temperature gradient, etc. These parameters are provided by the first and second semiconductor characteristic influencing indicators. The model is constructed using appropriate physical and thermodynamic equations, which can describe the heat transfer and thermal radiation processes under different heat dissipation methods.

[0027] The data of heat dissipation flow lines and heat dissipation distribution maps corresponding to different heat dissipation methods are input into the heat dissipation performance evaluation model, and the model is used to perform multiple rounds of iterative optimization of the heat dissipation system. Each round of optimization adjusts the heat dissipation flow lines and heat dissipation distribution configuration based on the thermal performance indicators output by the model. The main goal of the optimization is to reduce the highest temperature point, reduce temperature non-uniformity, enhance the effectiveness of heat flow, and ensure that the thermal management system can maintain high efficiency under all operating conditions. Use simulation or experimental methods to test the heat dissipation solution after each iteration, record and analyze key performance indicators such as temperature and heat flow, and feed the test results back to the evaluation model. Adjust and refine the heat dissipation solution based on actual performance, and select the final heat dissipation solution based on factors such as heat dissipation performance, cost-benefit analysis, system complexity and maintainability to complete the iterative optimization of heat dissipation.

[0028] Through the above-mentioned iterative heat dissipation optimization process, it can be ensured that the heat dissipation system of the graphene semiconductor material is not only optimal in theory, but also can work effectively in practical applications, thereby improving the performance and reliability of semiconductor equipment.

[0029] Furthermore, according to the honeycomb structure, the heat flow distribution under different heat dissipation modes is analyzed, and a plurality of heat dissipation flow lines corresponding to the different heat dissipation modes are configured. The method includes:

[0030] Based on the thermal radiation coefficient identifier, combined with the heat flux distribution under different heat dissipation methods, a first heat guiding microchannel is configured; based on the thermal conductivity coefficient identifier, combined with the heat flux distribution under different heat dissipation methods, a second heat guiding microchannel is configured; with the honeycomb structure as the starting point constraint condition of the multiple heat dissipation flow lines, with the first heat guiding microchannel and the second heat guiding microchannel as the transfer constraint conditions of the multiple heat dissipation flow lines, multiple heat dissipation flow lines corresponding to different heat dissipation methods are configured.

[0031] The thermal radiation coefficient reflects the amount of heat energy that can be radiated per unit area of ​​the material per unit time. It evaluates the impact of the thermal radiation coefficient on the heat dissipation performance, especially under different environmental and operating conditions. It uses computational fluid dynamics tools to simulate the heat flux distribution under different heat dissipation methods, such as natural convection, forced convection, and radiation heat dissipation, to determine the areas where heat radiation is most concentrated. These areas usually require more effective heat guidance strategies. The first heat guidance microchannel is designed and configured in the heat radiation concentrated area to optimize the radiation transmission and dispersion of heat.

[0032] The thermal conductivity coefficient symbol reflects the thermal conductivity of the material under a unit temperature difference. It evaluates the impact of the thermal conductivity coefficient on the overall heat dissipation performance and determines the heat conduction paths that require special attention. Fluid dynamics tools are continued to be used for simulation, especially for heat dissipation methods dominated by heat conduction, such as direct contact with metal heat sinks, to determine the paths where heat conduction is most frequent. These paths are the key areas for configuring the second microchannel. The second heat-guiding microchannel is designed and configured on the heat conduction path to enhance the thermal conductivity of the material.

[0033] Analyze the characteristics of the honeycomb structure, including its geometric shape, material properties and thermal characteristics, take the honeycomb structure as the starting point constraint of the heat dissipation flow line, and consider its specific location in the device and the concentrated area of ​​heat generation. Take the first heat guiding microchannel and the second heat guiding microchannel as the transfer constraint of the heat dissipation flow line, that is, use the first heat guiding microchannel to optimize the thermal radiation characteristics to ensure that the thermal radiation from the heat source to the heat dissipation interface can be efficiently transferred, and use the second heat guiding microchannel to optimize the heat conduction path to ensure that the heat energy is efficiently transferred through heat conduction, especially in areas with greater heat dissipation requirements.

[0034] According to the thermal management characteristics of the first and second microchannels, multiple heat dissipation flow lines are designed. These lines should be arranged reasonably to cover the entire honeycomb structure to ensure that the heat can be evenly dissipated. The configuration of the flow lines is adjusted for different heat dissipation methods. For example, when using liquid cooling, a tighter microchannel network needs to be configured to ensure that the coolant can flow efficiently and take away the heat. Based on the configuration results, multiple heat dissipation flow lines corresponding to different heat dissipation methods are obtained.

[0035] Furthermore, based on the thermal radiation coefficient identifier and in combination with the heat flux distribution under different heat dissipation modes, a first heat guiding microchannel is configured, and the method further includes:

[0036] By presetting the heat dissipation scenario, multiple heat flux density partitions are added, wherein each heat flux density partition has at least one heat concentration point; based on the first heat guiding microchannel, the coverage is calculated in combination with the multiple heat flux density partitions; based on the coverage, a first heat flux compensation mechanism is established, and the first heat flux compensation mechanism is used to perform heat dissipation iterative constraints on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

[0037] Define preset heat dissipation scenarios based on the operating conditions and environment of the equipment, such as high-load operation, ambient temperature changes, different operating modes, etc. Use thermal simulation software to simulate the thermal behavior of the equipment under these preset heat dissipation scenarios. According to the simulation results, determine the areas with high heat flux density. These areas generate more heat when the equipment is running and require special attention. Calibrate multiple heat flux density partitions in the heat dissipation model, and each partition contains at least one heat concentration point, that is, the area with the highest heat flux.

[0038] Analyze the design of the first heat-guiding microchannels, determine the specific position and layout of these microchannels in the heat dissipation model, and calculate the coverage by combining multiple heat flux density partitions. The coverage is the ratio of the heat flux density partition area covered by the microchannel to the total heat flux density partition area. High coverage means that the microchannel can effectively manage the heat flow of most heat concentration points.

[0039] The heat flux compensation mechanism is defined according to the coverage, where areas with high coverage require less heat flux compensation, while areas with low coverage require more heat flux compensation. The heat flux that needs to be compensated is determined by analysis, including the direction, size and distribution of the compensated heat flux. The compensation goal is to improve the coverage and ensure that the key heat flux density partitions are effectively covered by the microchannels. The first heat flux compensation mechanism is established based on the analysis results, including density compensation, geometric compensation, layout compensation, etc. Based on the first heat flux compensation mechanism, the constraints for the heat dissipation iteration process are set. These constraints are intended to adjust the heat dissipation flow lines to compensate for those areas with insufficient heat coverage.

[0040] By establishing and implementing the first heat flow compensation mechanism, effective management of heat in the device can be ensured, especially in areas where heat is prone to accumulation and difficult to dissipate. This approach helps to improve the reliability and efficiency of the device and ensure that optimal performance can be maintained under various operating conditions.

[0041] Furthermore, the method further comprises:

[0042] By presetting a heat dissipation scenario, a plurality of thermal sensitivity partitions are identified, wherein each thermal sensitivity partition has at least one heat damage concentration point; based on the first heat guiding microchannel, the overlap is calculated in combination with the plurality of thermal sensitivity partitions; based on the overlap, a second heat flow compensation mechanism is established, and the second heat flow compensation mechanism is used to perform heat dissipation iterative constraints on a plurality of heat dissipation flow lines corresponding to different heat dissipation methods.

[0043] According to preset heat dissipation scenarios, such as high-load operation, ambient temperature changes, different operating modes, etc., thermal simulation tools are used to simulate thermal behavior in heat dissipation scenarios. Based on the simulation results, areas that are highly sensitive to temperature changes and may cause functional degradation or damage due to overheating are identified. These heat-sensitive areas are calibrated in the heat dissipation model, and each heat-sensitive area contains at least one thermal damage concentration point, which are the locations where thermal failure is most likely to occur.

[0044] The overlap degree indicates the ratio of the effective area covered by the first heat-guiding microchannel within the thermal sensitivity partition. It is used to measure the degree of protection of the thermally sensitive area by the microchannel design. Specifically, it is the ratio of the thermally sensitive partition area covered by the microchannel to the total area of ​​the thermally sensitive partition. The overlap degree ranges from 0 to 1. The larger the value, the more comprehensive the protection of the thermally sensitive partition by the microchannel.

[0045] The compensation mechanism is defined according to the overlap. The compensation goal is to increase the coverage of the microchannels on the thermally sensitive partitions, especially to protect the thermal damage concentration points. For the thermally sensitive areas with insufficient overlap, heat dissipation compensation is performed by adjusting the microchannel layout, density or design parameters. Based on the analysis results, a second heat flow compensation mechanism is established, including density compensation, geometric compensation, etc. Based on the second heat flow compensation mechanism, the constraints for the heat dissipation iteration process are set to adjust the heat dissipation flow lines to compensate for the areas with insufficient overlap.

[0046] Furthermore, in the preset heat dissipation scenario, multiple temperature radiation gradient buffer areas are added according to the multiple heat flux density partitions and the multiple thermal sensitivity partitions;

[0047] Based on the first heat flow compensation mechanism and the second heat flow compensation mechanism, and in combination with the plurality of temperature radiation gradient buffer regions, a reserved heat dissipation flow line of the first heat guiding microchannel is determined.

[0048] Combined with multiple heat flux density partitions and multiple thermal sensitivity partitions, thermal simulation tools are used to identify the temperature gradient change areas between these partitions. These gradient areas are usually the key points of heat transfer transition. Buffer areas are added in areas with large temperature gradient transitions to smooth heat flow transfer and avoid excessive thermal stress or excessive localized heat accumulation. These buffer areas effectively reduce the probability of hot spots by diffusing heat flow or reducing heat flow concentration, thereby protecting heat-sensitive areas.

[0049] Through the first heat flow compensation mechanism, high coverage areas are given priority and heat dissipation flow lines are reserved in these areas to ensure that the heat flow can be conducted quickly and effectively; through the second heat flow compensation mechanism, more heat dissipation flow lines are reserved in heat-sensitive areas to reduce the risk of possible thermal damage. Combined with the layout of the buffer area, the reserved heat dissipation flow lines are optimized so that they can effectively use these buffer areas to diffuse heat. By combining the heat dissipation flow lines designed in the buffer area, the concentration of heat flow in the transition area is reduced, and the heat transfer process is smoothed.

[0050] Furthermore, based on the thermal conductivity index and in combination with the heat flux distribution under different heat dissipation modes, a second heat guiding microchannel is configured, and the method further includes:

[0051] In the preset heat dissipation scenario, a third heat flow compensation mechanism and a fourth heat flow compensation mechanism are established according to the second heat conducting microchannel; based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, combined with multiple temperature conduction gradient buffer areas, the reserved heat dissipation flow line of the second heat conducting microchannel is determined.

[0052] Similar to the first heat flow compensation mechanism, in the preset heat dissipation scenario, the characteristics of the heat flow dense area are analyzed, the heat concentration point is identified, and the heat flux density distribution map is drawn using the thermal simulation tool to determine the key areas that need to be compensated. According to the coverage of the second heat guiding microchannel and the heat flux density distribution, a third heat flow compensation mechanism is established to reduce local heat accumulation. Similar to the second heat flow compensation mechanism, in the preset heat dissipation scenario, the areas that are sensitive to temperature changes and susceptible to thermal damage are analyzed, and the thermal damage concentration point is determined. According to the overlap between the second heat guiding microchannel and the thermal damage concentration point, a fourth heat flow compensation mechanism is established to enhance the protection of heat-sensitive components.

[0053] Based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, higher density and wider heat dissipation flow lines are set in heat flow intensive areas and heat sensitive areas to quickly guide heat to the cooling areas. Combined with the temperature conduction gradient buffer area, the reserved heat dissipation flow lines are optimized so that they can effectively utilize these buffer areas to diffuse heat.

[0054] Furthermore, based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, in combination with a plurality of temperature conduction gradient buffer regions, a reserved heat dissipation flow line of the second heat guiding microchannel is determined, and the method includes:

[0055] A scaling factor is configured according to the reserved heat dissipation flow lines of the first heat guiding microchannel and the reserved heat dissipation flow lines of the second heat guiding microchannel; based on the scaling factor, heat dissipation iterative optimization is performed in combination with multiple heat dissipation flow lines corresponding to different heat dissipation methods, and a heat dissipation performance evaluation result is obtained through a heat dissipation performance evaluation model; through the heat dissipation performance evaluation result and in combination with the scaling factor, heat dissipation iterative back-tracing configuration is performed on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

[0056] The scaling factor is an adjustment parameter used to control the length, width or density of the reserved heat dissipation flow lines of the first and second heat guiding microchannels, thereby optimizing the heat conduction and heat radiation performance. The range of the scaling factor is determined according to the thermal management requirements and physical limits of the equipment. Specifically, the first heat guiding microchannel is mainly responsible for radiative heat dissipation, and its design has a greater impact on the thermal radiation efficiency. The scaling factor is used to adjust the geometric characteristics of the microchannel (such as width, surface area) to optimize the thermal radiation effect; the second heat guiding microchannel is responsible for heat conduction and is suitable for heat flux-intensive areas and temperature gradient areas. The scaling factor is used to optimize the layout density, thickness and thermal contact area of ​​the microchannel to improve the conduction efficiency. The thermal simulation tool is used to analyze the thermal distribution characteristics of the reserved heat dissipation flow lines of the first and second heat guiding microchannels in different scenarios, and determine the areas that need to be optimized. For heat flux-intensive areas or temperature-sensitive areas, a larger scaling factor is configured to increase the density or width of the heat dissipation flow line. For areas with low heat flux or temperature insensitive areas, a smaller scaling factor is configured to reduce the redundant design of the heat dissipation channel.

[0057] Based on the scaling factor, multiple heat dissipation flow lines corresponding to different heat dissipation methods are optimized. For example, for natural convection, the surface area and radiation performance of the heat dissipation flow lines are optimized to ensure that heat can be naturally dissipated through convection and radiation; for forced convection, the layout of the microchannels is adjusted to match the airflow path, reduce airflow resistance and improve heat dissipation efficiency; for liquid cooling, the thickness of the microchannels and the number of flow channels are increased to improve the liquid cooling effect while ensuring the rationality of the flow resistance.

[0058] According to the initial configuration of the scaling factor, combined with different heat dissipation methods, simulation tools are used to perform thermal behavior analysis and record heat dissipation performance parameters. By analyzing the initial simulation results, performance bottlenecks such as hot spots and paths with high thermal resistance are identified. For hot spots, the scaling factor is increased, such as increasing the width or density of the microchannel to optimize the heat dissipation flow line; for areas with poor heat flow conduction, the direction or layout of the microchannel is adjusted to reduce thermal resistance.

[0059] Multiple rounds of iterations are performed. In each round of iteration, the scaling factor and heat dissipation flow line design are adjusted according to the results of the previous round of simulation to continuously optimize the heat dissipation performance. For the heat dissipation performance evaluation model, the scaling factor, the heat dissipation flow line layout of different heat dissipation methods, the heat flux density and the temperature distribution diagram are input to output the heat dissipation performance evaluation results.

[0060] Analyze the hot spots in the heat dissipation performance evaluation results and identify possible causes of the hot spots, such as insufficient microchannel layout density and unreasonable flow line design. For areas with poor performance in the evaluation results, retroactively adjust the scaling factor, such as increasing the scaling factor of the hot spot area to improve the heat transfer capacity; reduce the scaling factor of the redundant area to optimize the design resources.

[0061] According to the scaling factor adjustment results, the direction and density of the heat dissipation flow line are readjusted to cover the hot spot area more efficiently until the termination condition of the iterative backtracking is reached, such as the heat dissipation performance index reaches the design target. According to the iterative results, the final heat dissipation solution is determined, including the optimized heat dissipation flow line design and scaling factor distribution.

[0062] In summary, the heat dissipation optimization method for graphene semiconductors provided in the embodiments of the present application has the following technical effects:

[0063] Based on graphene semiconductor materials, a honeycomb structure is determined, which provides a geometric basis for subsequent heat flux distribution and temperature field analysis. In addition, the introduction of thermal radiation coefficient and thermal conductivity coefficient identification provides key material performance data for subsequent heat dissipation optimization. Based on the heat flux distribution analysis of different heat dissipation methods, multiple heat dissipation flow lines are configured to reduce heat accumulation in hot spots and improve the heat dissipation uniformity of the entire system. Heat dissipation flow lines are customized for different heat dissipation methods, so that the heat dissipation system can adapt to a variety of working environments and heat dissipation requirements, thereby improving the versatility and flexibility of the heat dissipation solution. By analyzing the changes in temperature fields under different heat dissipation methods, the characteristics of temperature distribution during equipment operation are clarified, providing accurate basic data for optimizing the heat dissipation solution. The layout map can intuitively present the heat dissipation efficiency under different heat dissipation methods, and guide the further optimization of heat-guiding microchannels and heat dissipation flow lines; analyze the influence of band gap on thermal radiation characteristics, determine the influencing index of the first semiconductor characteristics, quantify the key parameters of thermal radiation performance, and provide basic input for the heat dissipation performance evaluation model; analyze the influence of band gap on thermal conduction characteristics, determine the influencing index of the second semiconductor characteristics, and provide the heat dissipation performance evaluation model with key data for measuring thermal conduction performance; the heat dissipation performance evaluation model integrates the dual indicators of thermal radiation characteristics and thermal conduction characteristics, and provides a full range of evaluation standards for heat dissipation solutions. Through iterative heat dissipation optimization, it ensures that the heat dissipation flow lines and distribution maps can be continuously improved in practical applications, so as to achieve the best heat dissipation effect.

[0064] Embodiment 2, based on the same inventive concept as the heat dissipation optimization method for graphene semiconductor in the above embodiment, Figure 2 As shown, an embodiment of the present application provides a heat dissipation optimization system for a graphene semiconductor, the system comprising:

[0065] A honeycomb structure determination module 10, the honeycomb structure determination module 10 is used to determine the honeycomb structure based on the graphene semiconductor material, the graphene semiconductor material has a thermal radiation coefficient mark and a thermal conductivity coefficient mark; a heat flux distribution analysis module 20, the heat flux distribution analysis module 20 is used to analyze the heat flux distribution under different heat dissipation methods according to the honeycomb structure, and configure a plurality of heat dissipation flow lines corresponding to different heat dissipation methods; a temperature field change analysis module 30, the temperature field change analysis module 30 is used to analyze the temperature field changes under different heat dissipation methods according to the honeycomb structure, and configure a plurality of heat dissipation distribution maps corresponding to different heat dissipation methods; a first influencing index determination module 40, the first influencing index determination module 40 is used to determine the heat flux distribution under different heat dissipation methods according to the multiple heat dissipation methods corresponding ... The invention discloses a heat dissipation iterative optimization module 60, wherein the heat dissipation iterative optimization module 60 is used to establish a heat dissipation performance evaluation model according to the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, and to perform heat dissipation iterative optimization in combination with the multiple heat dissipation flow lines corresponding to different heat dissipation methods and the multiple heat dissipation distribution maps corresponding to different heat dissipation methods.

[0066] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0067] Based on the thermal radiation coefficient identifier, combined with the heat flux distribution under different heat dissipation methods, a first heat guiding microchannel is configured; based on the thermal conductivity coefficient identifier, combined with the heat flux distribution under different heat dissipation methods, a second heat guiding microchannel is configured; with the honeycomb structure as the starting point constraint condition of the multiple heat dissipation flow lines, with the first heat guiding microchannel and the second heat guiding microchannel as the transfer constraint conditions of the multiple heat dissipation flow lines, multiple heat dissipation flow lines corresponding to different heat dissipation methods are configured.

[0068] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0069] By presetting the heat dissipation scenario, multiple heat flux density partitions are added, wherein each heat flux density partition has at least one heat concentration point; based on the first heat guiding microchannel, the coverage is calculated in combination with the multiple heat flux density partitions; based on the coverage, a first heat flux compensation mechanism is established, and the first heat flux compensation mechanism is used to perform heat dissipation iterative constraints on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

[0070] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0071] By presetting a heat dissipation scenario, a plurality of thermal sensitivity partitions are identified, wherein each thermal sensitivity partition has at least one heat damage concentration point; based on the first heat guiding microchannel, the overlap is calculated in combination with the plurality of thermal sensitivity partitions; based on the overlap, a second heat flow compensation mechanism is established, and the second heat flow compensation mechanism is used to perform heat dissipation iterative constraints on a plurality of heat dissipation flow lines corresponding to different heat dissipation methods.

[0072] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0073] In the preset heat dissipation scenario, multiple temperature radiation gradient buffer areas are added according to the multiple heat flux density partitions and the multiple thermal sensitivity partitions; based on the first heat flux compensation mechanism and the second heat flux compensation mechanism, combined with the multiple temperature radiation gradient buffer areas, the reserved heat dissipation flow line of the first heat guiding microchannel is determined.

[0074] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0075] In the preset heat dissipation scenario, a third heat flow compensation mechanism and a fourth heat flow compensation mechanism are established according to the second heat conducting microchannel; based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, combined with multiple temperature conduction gradient buffer areas, the reserved heat dissipation flow line of the second heat conducting microchannel is determined.

[0076] Furthermore, the heat flow distribution analysis module 20 also includes the following operation steps:

[0077] A scaling factor is configured according to the reserved heat dissipation flow lines of the first heat guiding microchannel and the reserved heat dissipation flow lines of the second heat guiding microchannel; based on the scaling factor, heat dissipation iterative optimization is performed in combination with multiple heat dissipation flow lines corresponding to different heat dissipation methods, and a heat dissipation performance evaluation result is obtained through a heat dissipation performance evaluation model; through the heat dissipation performance evaluation result and in combination with the scaling factor, heat dissipation iterative back-tracing configuration is performed on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

[0078] Through the above-mentioned detailed description of the heat dissipation optimization method for graphene semiconductors in this specification, those skilled in the art can clearly understand the heat dissipation optimization system for graphene semiconductors in this embodiment. Since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description.

[0079] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be 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 application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A heat dissipation optimization method for graphene semiconductors, characterized in that: The method comprises: Based on the graphene semiconductor material, a honeycomb structure is determined, wherein the graphene semiconductor material has a thermal radiation coefficient mark and a thermal conductivity coefficient mark; According to the honeycomb structure, the heat flow distribution under different heat dissipation modes is analyzed, and a plurality of heat dissipation flow lines corresponding to the different heat dissipation modes are configured; According to the honeycomb structure, the temperature field changes under different heat dissipation modes are analyzed, and a plurality of heat dissipation distribution maps corresponding to the different heat dissipation modes are configured; Based on a plurality of heat dissipation flow lines corresponding to different heat dissipation methods and a plurality of heat dissipation distribution maps corresponding to different heat dissipation methods, the influence of the band gap on the thermal radiation characteristics is analyzed to determine the first semiconductor characteristic influence index; Based on multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods, the influence of the band gap on the thermal conductivity characteristics is analyzed to determine the influencing index of the second semiconductor characteristics; A heat dissipation performance evaluation model is established according to the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, and heat dissipation iterative optimization is performed in combination with a plurality of heat dissipation flow lines corresponding to different heat dissipation methods and a plurality of heat dissipation distribution maps corresponding to different heat dissipation methods; According to the honeycomb structure, the heat flow distribution under different heat dissipation modes is analyzed, and a plurality of heat dissipation flow lines corresponding to the different heat dissipation modes are configured. The method includes: Based on the thermal radiation coefficient identifier and in combination with the heat flux distribution under different heat dissipation modes, a first heat guiding microchannel is configured; Based on the thermal conductivity index and in combination with the heat flux distribution under different heat dissipation modes, a second heat guiding microchannel is configured; The honeycomb structure is used as the starting point constraint condition of the multiple heat dissipation flow lines, the first heat guiding microchannel and the second heat guiding microchannel are used as the transfer constraint conditions of the multiple heat dissipation flow lines, and multiple heat dissipation flow lines corresponding to different heat dissipation methods are configured.

2. The heat dissipation optimization method for graphene semiconductors according to claim 1, characterized in that: Based on the thermal radiation coefficient identifier and in combination with the heat flux distribution under different heat dissipation modes, a first heat guiding microchannel is configured, and the method further includes: By presetting the heat dissipation scenario, multiple heat flux density zones are added, wherein each heat flux density zone has at least one heat concentration point; Calculating coverage based on the first heat guiding microchannel in combination with the plurality of heat flux density partitions; Based on the coverage, a first heat flow compensation mechanism is established, and the first heat flow compensation mechanism is used to perform heat dissipation iteration constraints on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

3. The heat dissipation optimization method for graphene semiconductors according to claim 2, characterized in that: The method further comprises: By presetting the heat dissipation scenario, a plurality of thermal sensitivity zones are identified, wherein each thermal sensitivity zone has at least one thermal damage concentration point; Calculating an overlap based on the first heat guiding microchannel and in combination with the plurality of thermal sensitivity zones; Based on the overlap, a second heat flow compensation mechanism is established, and the second heat flow compensation mechanism is used to perform heat dissipation iteration constraints on a plurality of heat dissipation flow lines corresponding to different heat dissipation modes.

4. The heat dissipation optimization method for graphene semiconductors according to claim 3, characterized in that: In the preset heat dissipation scenario, multiple temperature radiation gradient buffer areas are added according to the multiple heat flux density partitions and the multiple thermal sensitivity partitions; Based on the first heat flow compensation mechanism and the second heat flow compensation mechanism, and in combination with the plurality of temperature radiation gradient buffer regions, a reserved heat dissipation flow line of the first heat guiding microchannel is determined.

5. The heat dissipation optimization method for graphene semiconductors according to claim 4, characterized in that: Based on the thermal conductivity index and in combination with the heat flux distribution under different heat dissipation modes, a second heat guiding microchannel is configured, and the method further includes: In the preset heat dissipation scenario, a third heat flow compensation mechanism and a fourth heat flow compensation mechanism are established according to the second heat guiding microchannel; Based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, in combination with a plurality of temperature conduction gradient buffer regions, a reserved heat dissipation flow line of the second heat guiding microchannel is determined.

6. The heat dissipation optimization method for graphene semiconductors according to claim 5, characterized in that: Based on the third heat flow compensation mechanism and the fourth heat flow compensation mechanism, in combination with a plurality of temperature conduction gradient buffer regions, a reserved heat dissipation flow line of the second heat guiding microchannel is determined, the method comprising: configuring a scaling factor according to a reserved heat dissipation flow line of the first heat guiding microchannel and a reserved heat dissipation flow line of the second heat guiding microchannel; Based on the scaling factor, heat dissipation iterative optimization is performed in combination with a plurality of heat dissipation flow lines corresponding to different heat dissipation methods, and a heat dissipation performance evaluation result is obtained through a heat dissipation performance evaluation model; Through the heat dissipation performance evaluation result and in combination with the scaling factor, heat dissipation iterative backtracking configuration is performed on multiple heat dissipation flow lines corresponding to different heat dissipation methods.

7. A heat dissipation optimization system for graphene semiconductors, characterized in that: For implementing the heat dissipation optimization method for graphene semiconductors according to any one of claims 1 to 6, the system comprises: A honeycomb structure determination module, the honeycomb structure determination module is used to determine the honeycomb structure based on the graphene semiconductor material, the graphene semiconductor material has a thermal radiation coefficient mark and a thermal conductivity coefficient mark; A heat flow distribution analysis module, which is used to analyze the heat flow distribution under different heat dissipation modes according to the honeycomb structure and configure a plurality of heat dissipation flow lines corresponding to the different heat dissipation modes; A temperature field change analysis module, which is used to analyze the temperature field changes under different heat dissipation modes according to the honeycomb structure, and configure a plurality of heat dissipation distribution maps corresponding to different heat dissipation modes; A first influencing index determination module, the first influencing index determination module is used to analyze the influence of the band gap on the thermal radiation characteristics based on a plurality of heat dissipation flow lines corresponding to different heat dissipation methods and a plurality of heat dissipation distribution maps corresponding to different heat dissipation methods, and determine the first semiconductor characteristic influencing index; A second influencing index determination module, the second influencing index determination module is used to analyze the influence of the band gap on the thermal conductivity characteristics based on a plurality of heat dissipation flow lines corresponding to different heat dissipation methods and a plurality of heat dissipation distribution maps corresponding to different heat dissipation methods, and determine the second semiconductor characteristic influencing index; The heat dissipation iteration optimization module is used to establish a heat dissipation performance evaluation model according to the first semiconductor characteristic influencing index and the second semiconductor characteristic influencing index, and to perform heat dissipation iterative optimization in combination with multiple heat dissipation flow lines corresponding to different heat dissipation methods and multiple heat dissipation distribution maps corresponding to different heat dissipation methods.

Images