Diamond array type micropore heat dissipation substrate adaptive to multi-granularity fluorescent powder and design method of diamond array type micropore heat dissipation substrate

Abstract

The invention discloses a diamond array type microporous heat dissipation substrate adaptive to multi-granularity fluorescent powder and a design method of the diamond array type microporous heat dissipation substrate. According to the invention, the diamond array micropore design is adaptive to fluorescent powder with different particle sizes, the maximum luminous efficiency is realized through optimization under specific incident power, and the method is a multi-dimensional, multi-physical field and refined coupling optimization process. The ultra-high thermal conductivity of diamond is used as a framework, and the aperture, depth, shape, connecting rib width, array mode and even inner wall surface of a micropore are precisely designed and optimized in a regional, self-adaptive and nanoscale manner, so that fluorescent powder of each particle size can be ensured to be in a'exclusive 'micropore environment; and optimal thermal management and light extraction conditions are obtained, so that the maximum light energy is released under the given excitation power.

Description

Technical Field

[0001] The present invention belongs to the field of heat dissipation technology, and in particular to a diamond array microporous heat dissipation substrate adapted for multi-granularity phosphors and a design method thereof. Background Art

[0002] Laser-excited phosphors (LAPs), a new generation of high-brightness solid-state light sources, hold great potential in applications such as automotive headlights and projection systems. However, high-power blue laser light incident on the phosphor generates significant heat. If heat dissipation is poorly managed, the phosphor's temperature rise can lead to a decrease in luminous efficiency (thermal quenching), brightness saturation, and even material degradation (Li Qian, Liu Yingying, Wang Yangang, et al. A wavelength conversion device: CN 110737085 A[P]. 2020.01.31). Therefore, effective thermal management structures are crucial for maintaining the phosphor's high quantum efficiency and stable luminescence. Conventional LED phosphor packages currently experience "efficiency droop" under high drive conditions, making them unable to withstand the high power density of laser light sources. To address these issues, researchers have developed various high-thermal-conductivity substrates and heat-dissipating structures to improve the heat dissipation performance of phosphor light converters (e.g., Yu, Z.; Zhao, J.; Yang, Z.; Mou, Y.; Zhang, H.; Xu, R.; Wang, Q.; Zeng, L.; Lei, L.; Lin, S.; Li, H.; Peng, Y.; Chen, D.; Chen, M. A Novel PiGF@DiamondColor Converter with a Record Thermal Conductivity for Laser-DrivenProjection Display. Advanced Materials 2024, 2406147.). For example, in remote phosphor light sources, the introduction of high-thermal-conductivity substrates, such as copper- and ceramic-based heat-dissipating substrates, can significantly reduce the phosphor's operating temperature and delay the luminescence saturation point. This article will introduce existing heat-dissipation enhancement technologies and propose an innovative diamond substrate micropore array structure to further improve the phosphor's luminous efficiency.

[0003] Single-crystal sapphire, ceramic, and metal substrates: Traditional LED packaging often uses substrate materials such as sapphire, aluminum nitride (AlN), aluminum, and copper, which combine certain thermal conductivity and optical properties. For example, sapphire has high reflectivity and high-temperature resistance, but its thermal conductivity is only approximately 30 W / (m·K). In contrast, AlN ceramic, aluminum, or copper substrates have higher thermal conductivity (tens to hundreds of W / (m·K)), which can partially alleviate heat accumulation in the phosphor. These substrates are relatively low-cost, but due to their limited thermal conductivity, they cannot fully meet the heat dissipation requirements of ultra-high-power laser lighting.

[0004] Diamond substrate: Artificially grown single crystal diamond is considered an ideal heat dissipation substrate due to its extremely high thermal conductivity (>2000 W / (m·K)) and high transparency in visible light. Recently, a design has used diamond as a phosphor film (PiGF) substrate and combined it with different groove structures to achieve excellent results. Guo et al. reported that the La3Si6N11:Ce phosphor glass film was sintered on a transparent diamond sheet (PiGF@diamond). The equivalent thermal conductivity of the composite material reached ≈599 W / (m·K), which is about 60 times that of traditional PiGF@sapphire (Guo, H.; Ding, X.; Li, J.; Yan, C.; Liu, X.; Li, Z. Opto-Thermal Enhancement of Phosphor-In-Glass Utilizing Nano Boron-Coated CopperMicropillar Substrate. IEEE Trans. Electron Devices 2024, 71 (12), 7621–7627.). Thanks to this exceptional heat dissipation performance, the converter maintains luminous saturation even at laser power densities as high as 40.24 W / mm², achieving a maximum luminous flux of 5602 lumens while suppressing the phosphor temperature rise to less than 130°C. This achievement demonstrates that a diamond substrate can significantly improve the saturation threshold and brightness level of phosphors.

[0005] While research into using diamond materials for phosphor light sources has made progress, current efforts focus on attaching a thin diamond film to the substrate surface to accelerate heat diffusion. For example, a patent filed by Shenzhen Lightpeak Technology involves depositing a transparent diamond film on the substrate or phosphor layer, acting as a heat diffusion layer to rapidly dissipate heat from the phosphor and reduce thermal saturation. This structure has been shown to prevent the loss of luminous efficiency caused by overheating and degradation of the phosphor layer. However, in these solutions, the diamond primarily serves as a planar heat dissipation layer, without any specific design considerations for the substrate surface topography. As power levels continue to increase, further exploring the potential of diamond for heat dissipation while maintaining optimal optical light extraction efficiency has become a new research and development direction.

[0006] Microstructure heat dissipation enhancement design: In addition to the material itself, it is also crucial for heat dissipation and light extraction. Some studies have made three-dimensional structures on high thermal conductivity substrates to expand the heat dissipation area, improve the heat flow path and optical path. For example, Ding et al. designed a three-dimensional copper micro-column array substrate, embedding the phosphor glass between the copper micro-columns to form a "metal-micro-column-glass" composite structure. The copper micro-columns significantly enhance internal heat transfer as micro-heat channels, and avoid light absorption by copper by coating an insulating boron nitride (BN) thin layer. Experiments show that compared with pure flat phosphor glass, the micro-column substrate reduces the converter temperature by about 21.9°C (at 8.48 W laser input), increases the phosphor saturation threshold by 68.5%, and increases the luminous efficiency by about 20.3%, and the maximum luminous flux by 68.5%. As can be seen, the introduction of three-dimensional structures such as micro-columns / micro-holes can simultaneously consider heat dissipation and optical performance, greatly improving the stability and brightness of high-power laser phosphor light sources.

[0007] Another related idea is to optimize the microstructure of the phosphor film and substrate interface. For example, some studies have adopted a "double-sided heat dissipation" sandwich structure: the phosphor glass film is sandwiched between sapphire with micro-tapered "moth eye" structure and high thermal conductivity ceramic to form a microstructure interface (Mou, Y.; Peng, Y.; Wang, X.; Liu, J.; Zhao, J.; Hao, Z.; Yu, Z.; Wang, Q.; Xu, J. Unique Sandwich and Microstructure Design of Phosphor-in-Glass Film for High Brightness Laser-Driven White Lighting. Journal of the European Ceramic Society 2024, 44 (4), 2408-2417.). This core-microstructure interface design not only improves light transmission and extraction (micro-tapered structure can reduce total reflection loss), but also allows the phosphor film to dissipate heat to both the top and bottom sides. Experiments obtained white light output of 5197 lm under 30 W / mm² laser excitation, with lower operating temperature and higher saturation threshold, significantly improving over traditional single-layer structures.

[0008] In summary, high thermal conductivity materials + heat dissipation microstructure is an effective way to improve the performance of laser phosphor light sources. Diamond, as the material with the most outstanding thermal conductivity, is expected to further break through the brightness limit if combined with a clever microstructure design. SUMMARY

[0009] The purpose of the present invention is to solve the problems of limited light output efficiency of phosphors when high laser power and high energy density act together (the excitation light is uneven and needs to be concentrated at a reflective angle); the problem of reduced luminous efficiency of phosphors due to poor heat dissipation of ordinary high-conductivity material substrates with planar structures (thermal quenching, light flux saturation, thermal aging, sintering and photobleaching, etc.); and the problem of multi-scale optical scattering regulation and light output stability (the functional mapping relationship between phosphor particle size and micropore diameter, depth, bottom structure and porosity of the diamond base material). It is proposed to prepare a periodic micropore array structure on a diamond substrate to simultaneously achieve efficient heat dissipation and high light output.

[0010] The technical solution for achieving the purpose of the present invention is: on the one hand, a diamond array microporous heat dissipation substrate adapted to multi-particle size phosphor bodies is provided, wherein the substrate comprises diamond, and the diamond is provided with array micropores, and the array micropores can adapt to the multi-particle size phosphor bodies. At the same time, when the volume of the diamond is constant, the phosphor can achieve the maximum heat transfer coefficient and the maximum luminous power.

[0011] In another aspect, a method for designing a diamond array microporous heat dissipation substrate is provided, the method comprising the following steps:

[0012] Step 1: Under the condition of a given total diamond volume, the decision variables in the design process are selected, including phosphor parameters, array micropore process parameters, and phosphor and micropore adaptation parameters;

[0013] Step 2: Select a certain type of phosphor and obtain its parameters. At the same time, customize a series of array micropore process parameter solutions and calculate the phosphor and micropore adaptation parameters.

[0014] Step 3, calculating the adaptation index between the phosphor parameters in step 2 and each array micropore process parameter solution and the phosphor and micropore adaptation parameters;

[0015] Step 4: screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution that is adapted to the phosphor parameters in step 2;

[0016] Step 5: Calculate the maximum luminous power of each array-type micropore process parameter solution screened in step 4, and take the array-type micropore process parameter solution with the maximum luminous power as the maximum value as the optimal array-type micropore process parameter solution.

[0017] Furthermore, in step 1, the phosphor parameters include particle size d p The micropore process parameters include pore shape S, pore diameter d, pore depth h, rib width w and array mode A, and the phosphor and micropore adaptation parameters include porosity Φ.

[0018] Furthermore, the calculation formula of the porosity Φ is:

[0019] ; Where, is the cross-sectional area of ​​the micropore, are the length and width of the rectangular unit respectively, and the rectangular unit is a single rectangular unit in the rectangular array that evenly divides the diamond surface. is the hole shape coefficient.

[0020] Furthermore, the hole shape S includes rectangle, hexagon and circle; when the hole shape S is a rectangle, the hole shape coefficient ; When the hole shape S is hexagonal, the hole shape coefficient ; When the hole shape S is circular, the hole shape coefficient .

[0021] Furthermore, the array mode A includes a rectangular array and a honeycomb array;

[0022] For rectangular arrays, the following conditions must be met:

[0023]

[0024] Where n is the number of holes punched along the sides of the rectangle, is the equivalent diameter of the diamond surface in the direction of the rectangular edge, and d is the equivalent diameter of the micropore;

[0025] For cellular arrays, the following conditions should be met:

[0026]

[0027] Where, is the number of stacked layers of micropores.

[0028] Furthermore, the calculation formula of the adaptation index in step 3 is:

[0029]

[0030] Where, represents the fitness index, are all weight coefficients and their sum is 1, is the geometric packing adaptation function, is the heat diffusion adaptation function, is the light excitation volume adaptation function, which can be expressed as:

[0031]

[0032]

[0033]

[0034] Where, is the characteristic length of the hole cross section, λ is the optimal matching ratio, and α is the adjustable matching bandwidth; It is the sum of the resistance values ​​after considering the thermal resistance of the diamond body, the thermal resistance of the phosphor body and the contact thermal resistance of the interface between the two. is the reference thermal resistance; is the laser penetration depth.

[0035] Furthermore, the step 4 of screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution that is adapted to the phosphor parameters in step 2 specifically includes:

[0036] Step 4-1, arranging the process parameter solutions of each arrayed micropore in descending order according to the adaptation index value;

[0037] Step 4-2, selecting an array micropore process parameter solution with a fitness index value greater than a preset first threshold;

[0038] Step 4-3, for the array micropore process parameter solution obtained in step 4-2, scan the values ​​of all decision variables in the definition domain, and eliminate the array micropore process parameter solution that does not conform to the actual situation or the change in the evaluation index is less than the preset second threshold; the evaluation index includes the heat transfer coefficient after the mixture of diamond and phosphor, that is, the equivalent heat transfer coefficient.

[0039] Furthermore, the method further comprises:

[0040] Step 6: Calculate the equivalent heat transfer coefficient of the optimal array micropore process parameter solution and output it to an external terminal.

[0041] Furthermore, the method further comprises:

[0042] Step 7, repeating steps 2 to 5 several times to obtain multiple sets of design solutions, each set of design solutions including decision variables, fitness indexes, and optimal array micropore process parameter solutions;

[0043] Step 8: Based on multiple sets of design schemes, use machine learning algorithms to perform iterative optimization until the optimization conditions are met and output the final array micropore process parameter scheme.

[0044] Compared with the prior art, the present invention has the following significant advantages:

[0045] (1) The diamond array micropore design of the present invention is adapted to phosphors of different particle sizes and achieves maximum luminous efficiency at a specific incident power through optimization. It is a multi-dimensional, multi-physics, and finely coupled optimization process. It utilizes the ultra-high thermal conductivity of diamond as a skeleton and performs regional, adaptive, and nano-scale precision design and optimization of the micropore diameter, depth, shape, rib width, array pattern, and even the inner wall surface of the pore to ensure that each phosphor particle size can obtain the best thermal management and light extraction conditions in its "exclusive" micropore environment, thereby releasing the maximum light energy at a given excitation power.

[0046] (2) The existing technology uses diamond only as a planar heat diffusion layer. Although it can reduce the temperature rise of the phosphor to a certain extent, its heat conduction path is limited to a two-dimensional surface, making it difficult to cope with local heat accumulation under high laser power density. The present invention prepares a periodic micropore array on the diamond substrate to construct a three-dimensional heat dissipation channel, so that the heat generated by the phosphor can be more efficiently diffused to the substrate and the external environment, greatly reducing the equivalent thermal resistance and significantly improving the heat dissipation capacity, thereby delaying the thermal quenching phenomenon and maintaining high light flux output.

[0047] (3) Existing technologies usually use uniform particle size phosphors or single pore size designs, resulting in loose filling, high thermal resistance, and low light scattering efficiency. This invention proposes for the first time a quantitative adaptation method for multi-particle size phosphors and pore structure parameters. By optimizing the pore size, pore depth, porosity, and array method, phosphors of different particle sizes can be partitioned and multi-scale matched in the same substrate, ensuring the close packing and uniform distribution of particles. This not only improves the heat conduction path, but also enhances the photon excitation and escape efficiency, thereby achieving higher luminous efficiency and lower temperature rise under the action of high-power lasers.

[0048] (4) Existing technologies mostly improve heat dissipation or optical performance, lacking systematic optimization that takes both into account. The present invention establishes a complete multi-objective optimization design process, combining algorithm optimization with multi-physics field coupling simulation, while simultaneously weighing the equivalent thermal resistance and light output power to obtain the optimal design parameter combination; and combined with low-damage drilling, phosphor embedding and other process flows, the optimization results are made engineering feasible. As a result, the present invention achieves an improvement in optical light extraction efficiency while maintaining ultra-high heat dissipation performance, and has significant overall performance advantages.

[0049] The present invention is further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 Schematic diagram of the overall structural parameter control of the diamond substrate.

[0051] Figure 2This is a flow chart of the design method of the diamond array microporous heat dissipation substrate of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0053] It should be noted that if the embodiments of the present invention involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0054] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but this must be based on the fact that ordinary technicians in this field can implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0055] In one embodiment, a diamond array microporous heat dissipation substrate adapted to multi-size phosphor bodies is provided, wherein the substrate comprises diamonds, and the diamonds are provided with array micropores, and the array micropores can adapt to the multi-size phosphor bodies. At the same time, when the volume of the diamond is constant, the phosphor can achieve a maximum heat transfer coefficient and a maximum luminous power.

[0056] Here, "adaptation" does not mean fixing an aperture to accommodate phosphors of all particle sizes, but refers to regional, multi-scale aperture design, which is the most direct and efficient method to adapt to multi-particle phosphors. On the same diamond substrate, the substrate can be divided into several functional areas. The design logic is to coordinate different apertures to fill phosphors of different particle sizes according to the heat load distribution or desired luminescence characteristics of different areas. For example, in the central area with the highest laser power density, it may be necessary to fill large-particle phosphors with excellent thermal conductivity and relatively small stacking thermal resistance, and fill them with small apertures at the same time; but in the peripheral area, a small amount of small-particle phosphors should be added while using large-particle phosphors and filled with relatively large apertures.

[0057] In one embodiment, combined Figure 2, a design method of a diamond array type micro-hole heat dissipation substrate adapted to multi-granularity fluorescent powder is provided, the method comprising the following steps:

[0058] Step 1, under the condition of a given total diamond volume, selecting decision variables in the design process, including fluorescent powder parameters, array type micro-hole process parameters and fluorescent powder and micro-hole adaptation parameters;

[0059] Step 2, selecting a certain type of fluorescent powder and obtaining its parameters; at the same time, customizing a series of array type micro-hole process parameter schemes and calculating fluorescent powder and micro-hole adaptation parameters;

[0060] Step 3, calculating the adaptation index between the fluorescent powder parameters and each array type micro-hole process parameter scheme and the fluorescent powder and micro-hole adaptation parameters in step 2;

[0061] Step 4, screening the array type micro-hole process parameter schemes based on the adaptation index to obtain the array type micro-hole process parameter scheme adapted to the fluorescent powder parameters in step 2;

[0062] Step 5, calculating the maximum luminous power of each array type micro-hole process parameter scheme screened in step 4, and taking the array type micro-hole process parameter scheme with the maximum luminous power as the maximum value as the optimal array type micro-hole process parameter scheme.

[0063] Further, in one of the embodiments, in step 1, in combination with Figure 1 , the fluorescent powder parameters include particle size d p distribution, the micro-hole process parameters include hole shape S, hole diameter d, hole depth h, web width w and array type A, and the fluorescent powder and micro-hole adaptation parameters include porosity Φ.

[0064] Here, the decision variables are as shown in Table 1.

[0065] Table 1 Explanation of decision variables

[0066] parameter Physical meaning Modeling method Hole shape (S) Control the arrangement density and connectivity of the thermal conduction channels, and control the porosity Direct: circle, square, hexagon Aperture () Determine the phosphor particle size adaptability and porosity Designed to match particle size distribution Hole depth () <![CDATA[决定荧光粉堆积程度 ϕ packing 、 Equivalent thermal resistance R eq 、 Volume fraction ϕ fill and the number of phosphor stacking layers N layers ]]> Through hole / blind via; considering thermal resistance model Porosity () Trade-off between thermal conductivity skeleton retention and filling volume Explicit formula derivation + FEA assistance Width of connecting bar () Control hole spacing to influence thermal network integrity Implicit in the function of arrangement+ Array method () Determine the number of holes per unit area and the shape of the heat conduction path Matrix / Cellular Array <![CDATA[粒径 d p Distribution]]> Filling and stacking strategies under multiple particle size distributions Required distribution matching strategy (large particle / small particle classification)

[0067] Preferably, in some embodiments, the calculation formula of the porosity Φ is:

[0068]

[0069] In the formula, is the cross-sectional area of the micro-hole, are the length and width of the rectangular unit, respectively, the rectangular unit being a single rectangular unit in the rectangular array uniformly divided on the diamond surface, is the hole shape coefficient.

[0070] Here, in particular, if the rectangular unit is square, The calculation formula of porosity Φ is:

[0071]

[0072] Here, the hole shape S includes a rectangle, a hexagon, and a circle; when the hole shape S is a rectangle, the hole shape coefficient is ; when the hole shape S is a hexagon, the hole shape coefficient is ; and when the hole shape S is a circle, the hole shape coefficient is .

[0073] Preferably, in some embodiments, the array mode A includes a rectangular array and a honeycomb array.

[0074] For the rectangular array, the following should be satisfied:

[0075]

[0076] to achieve reasonable spatial geometric feature arrangement.

[0077] In the formula, n is the number of holes along the rectangular edge direction, is the equivalent diameter of the diamond surface in the rectangular edge direction, and d is the equivalent diameter of the micro-hole.

[0078] For the honeycomb array, the following should be satisfied:

[0079]

[0080] to achieve geometric continuity in space.

[0081] In the formula, is the number of stacked layers of micro-holes, which is usually an odd number.

[0082] Further, in one of the embodiments, the calculation formula of the fitting index in step 3 is:

[0083]

[0084] In the formula, represents the fitting index, are weight coefficients and sum to 1, is a geometric packing fitting function, is a thermal diffusion fitting function (the design goal is that the smaller the thermal resistance, the better), is a light excitation volume fitting function (it is hoped that the filling volume V phos of the fluorescent powder is located as much as possible within the laser penetration depth h excite ).

[0085] Here, the weight coefficients are defined according to the actual application (heat dominated / light dominated). Preferably, the weight ω1=ω2=0.4, ω3=0.2 is set. If the heat problem is serious, ω2 can be increased.

[0086] Here, the adaptation index comprehensively reflects the matching effect of the following three mechanisms: geometric matching: whether the particle size is suitable for filling the hole and whether it forms a dense packing; thermal adaptation: whether the structure provides a good heat diffusion channel and low thermal resistance; optical adaptation: whether the hole structure can provide sufficient excitation light excitation volume and avoid thermal quenching.

[0087] Here, preferably, the adaptation function of each sub-item is represented as follows:

[0088]

[0089]

[0090]

[0091] In the formula, is the characteristic length of the hole cross section, and the optimal ratio is usually d p ∈[0.4, 0.6] interval, λ is the optimal matching ratio (usually 0.5), and α is the adjustment matching bandwidth (usually 20-40); is the sum of the resistances of the diamond body thermal resistance, the fluorescent powder thermal resistance, and the contact thermal resistance of the combined surface, is the reference thermal resistance; is the laser penetration depth. It should be noted that when all decision variables are a fixed value, R total is the equivalent thermal resistance R eq The calculation method is based on the Maxwell-Eucken mixing calculation formula or the multi-layer material finite element calculation model.

[0092] Here, the geometric packing adaptation function is not limited to the above Gaussian type, but can also be other types of distribution, such as inverse parabolic function, inverse Lorentz function, piecewise function and triangular function, etc.

[0093] Here, the light excitation volume adaptation function shows that when the hole is too deep, i.e. h excite , the excess volume of fluorescent powder cannot be effectively excited, causing material waste, and the porosity Φ directly reflects the upper limit of the filling volume.

[0094] Further, in one embodiment, the step 4 of screening the array type micro-pore process parameter scheme based on the adaptation index to obtain the array type micro-pore process parameter scheme adapted to the fluorescent powder parameters in step 2, specifically includes:

[0095] Step 4-1, arranging the process parameter solutions of each arrayed micropore in descending order according to the adaptation index value;

[0096] Step 4-2, selecting an array micropore process parameter solution with a fitness index value greater than a preset first threshold;

[0097] Step 4-3, for the array micropore process parameter solution obtained in step 4-2, scan the values ​​of all decision variables in the definition domain, and eliminate the array micropore process parameter solution that does not conform to the actual situation or the change in the evaluation index is less than the preset second threshold; the evaluation index includes the heat transfer coefficient after the mixture of diamond and phosphor, that is, the equivalent heat transfer coefficient.

[0098] Furthermore, in one embodiment, the method further comprises:

[0099] Step 6: Calculate the equivalent heat transfer coefficient of the optimal array micropore process parameter solution and output it to an external terminal.

[0100] Furthermore, in one embodiment, the method further comprises:

[0101] Step 7, repeating steps 2 to 5 several times to obtain multiple sets of design solutions, each set of design solutions including decision variables, fitness indexes, and optimal array micropore process parameter solutions;

[0102] Step 8: Based on multiple sets of design schemes, use machine learning algorithms to perform iterative optimization until the optimization conditions are met and output the final array micropore process parameter scheme.

[0103] Here, the machine learning algorithm adopts but is not limited to neural network (NN), Gaussian process regression (GPR) or support vector regression (SVR), NSGA-II or NSGA-III, etc.

[0104] Here, the specific process of step 8 is as follows:

[0105] (1) Initialize the population and treat each set of design solutions as an individual.

[0106] (2) Evaluate each individual and calculate the total equivalent thermal resistance R under the current type of phosphor and diamond drilling parameters (array micropore process parameters) through phosphor filling rate calculation, thermal conduction simulation model and optical simulation model. eq (equivalent heat transfer coefficient) and .

[0107] (3) Non-dominated sorting, according to R eq and Sort the population and find non-dominated solutions (i.e., part of the Pareto optimal solution set).

[0108] (4) Calculate the crowding distance and evaluate the distribution uniformity of non-dominated solutions on the Pareto front.

[0109] (5) Selection, crossover, and mutation: Based on sorting and crowding distance, select better individuals for genetic operations to generate the next generation population.

[0110] (6) Iteration: Repeat (2) to (5) until the optimization condition is met.

[0111] In addition, during the evaluation phase, a surrogate model built with machine learning can be used to replace time-consuming physical field simulations. A small number of representative points in the design space are selected for high-precision physical simulations (such as FEA / DEM). Machine learning methods such as neural networks (NN), Gaussian process regression (GPR), or support vector regression (SVR) are used to learn the relationship between decision variables and R. eq and Finally, to accelerate optimization, in most iterations of the optimizer, a trained proxy model is used for fast performance prediction, and real physical simulation is only called in critical areas or areas with high uncertainty.

[0112] The design concept flow of the present invention is described in detail below.

[0113] Assume that the diamond volume V 总 Fixed (e.g. 1×10 -6 m³), h=100 μm, A=V / h, light source incident power P0=10W, ambient temperature T amb =300 K, maximum light temperature T max =373 K, thermal conductivity of diamond k diamond =2000 W / m·K, thermal conductivity of phosphor k phosphor =5 W / m·K, thermal attenuation constant T0=50 K, and the “[]” symbol is used to indicate the property setting of a parameter for ease of programming.

[0114] Step 1: Input parameter definition and constraint settings

[0115] a) Variables:

[0116] Shape: ['circle', 'square', 'hexagon'];

[0117] Array mode: ['square', 'hex'];

[0118] Aperture d: continuous variable, range [3 mean(d p ), 50 μm].

[0119] Hole spacing a: continuous, [d+1 μm, 100 μm] (ensure w=ad≥1 μm strength limit).

[0120] Depth: ['through' (depth=h), 'blind' (depth=0.5-0.9h)].

[0121] Particle size d p : Distribution type (e.g. μ=2 μm, σ=1 μm for normal distribution), or fixed value.

[0122] b) Constraints:

[0123] Process: d ≥ 1 μm (limited by processing technology); Φ eff <0.8 (limited by structural stability).

[0124] Performance: T <T max ;f fill >0.8 (limited by fill threshold).

[0125] Quantitative matching initial value: d≥3d p (Assuming minimum stacking); a ≥ d + w min .

[0126] Sample input: d p ~N(2,1), shape=circle, array=square.

[0127] Input logic: Use a dictionary to store variable space, gridded discretization or continuous optimization preparation. The constraint process should first screen the space to avoid invalid calculations.

[0128] Step 2: Build a physical model

[0129] a) Construct a geometric mapping about Φ: parameters (S, S', A, d, a) → porosity.

[0130] Calculation formula: circle-square: πd² / (4a²); hex-hex: (3 / 4)d² / a², etc.

[0131] Coefficient derivation: A hole / A cell ; Method: Standard geometric area → density division.

[0132] b) Particle filling model (d) p -d function matching, i.e. f fill ): Construct Gaussian function + Monte Carlo method.

[0133] f fill (d p, d) =exp[-(d p / d-0.25)^2 / (2*0.5^2)](If r opt =0.25, so d opt =4d p ).

[0134] d p Distribution: f fill _avg=(1 / N)Σf fill (d p(i) , d), set N = 1000 and perform Monte Carlo sampling to simulate particles entering the hole. If random_pos <d-d p(i) It is considered successful.

[0135] Impact analysis: When d=4d p When f fill ≈1,Φ eff Get the maximum value; when d<2d p When f fill <0.5, indicating that the air gap increases and R thermal ≈1 / k air , k eff Reduce by 50%; when d>10d p When f fill Approaching 1 but with a longer thermal path, k eff Indirectly reduce, so k can be done eff Correction, i.e. k eff =1 / (1+(d / a)^2).

[0136] The derivation logic of the filling model: The Gaussian equation is derived from the energy barrier probability, while Monte Carlo increases the randomness of particle distribution and ensures quantitative accuracy (such as variance < 5%).

[0137] c) Thermal conductivity model (k eff ):Φ eff =Φ aera *f fill *(depth / h).

[0138] Bruggeman:Φ eff (k phosphor -k eff ) / (k phosphor +2k eff )+(1-Φ eff )(k diamond -k eff ) / (k diamond +2k eff )=0.

[0139] Equation solving: numerical root finding (e.g. scipy.root_scalar); blind hole correction equation: k eff =k eff +(1-depth / h)*k diamond (including the bottom path addition). For example, when Φ eff =0.5, k eff ≈521.7W / m·K.

[0140] d) Luminous model (P out ):T=T amb +P0*h / (k eff *V 总 / h);η=exp[-(TT amb ) / T0];P out =Φ eff *V 总 *η*scale (scale is the excitation power factor, normalized = 1).

[0141] Influencing factors: High Φ eff Value means V 总 Small, while k eff decreases, the temperature rises, and η decreases, so many aspects need to be considered during the matching process.

[0142] Design logic: Model hierarchical progression, i.e. geometry → microscopic filling → macroscopic performance, each with a closed-form / numerical solution for easy quantitative mapping.

[0143] Step 3: Simulation and calculation chain

[0144] For each parameter combination, the calculation chain is: Monte Carlo filling → porosity Φ → equivalent thermal conductivity k eff →Temperature T→Luminous power P out .

[0145] For example, when d p =18 μm, and adopts hexagonal-hybrid array, d graded range is 36-72 μm, Cr3C2 coating, gradient through hole (depth changes from 100 μm to 60 μm, average depth 80 μm), Φ area After optimization, Φ area ≈0.75 (hexagonal-hybrid packing, the coating enhances the effective area by about 10%); f fill ≈0.92 (based on Gaussian model, average d≈3d p , r opt =0.25, σ=0.5, hierarchical adaptation multiple d p distribution, using Monte Carlo simulation to get the mean value, where N = 1000); Φeff =Φ area ×f fill ×(depth avg / h)≈0.75×0.92×0.8≈0.55; k eff ≈340 W / m·K (calculated by Bruggeman model, coating correction does not exceed 20%); T≈300+10×(1-0.5) / (340×0.01 / 10 -4 )≈300+0.00015 K (from this we can see that ΔT is extremely small, and the impact may be more significant under actual high power density); P out ∝0.55×exp[-(T-300) / 50]≈0.55 (normalized, the maximum error is about 22%, minimizing thermal quenching). It should be noted that the calculation of this chain process requires ensuring stable tracking.

[0146] Step 4: Multi-objective optimization

[0147] a) Related algorithm: NSGA-II (genetic algorithm, pop=50, gen=20), goal: maximum k eff and maximum P out , variable vector [d,a,depth,shape_idx,array_idx]. The penalty function is: if T>T max or f fill <0.8, obj=-inf. Use the deap library or scipy.optimize to achieve a Pareto frontier (e.g., 100 solution sets).

[0148] b) Quantitative matching output: Frontier points such as (d=4d p , a=1.25d, hex array)→Φ eff =0.5, k eff =520,P out =0.5.

[0149] c) Design Logic: NSGA-II processes non-convex spaces and generates matching "spectra"; it is more efficient than grid search (accelerated by proxy models such as Gaussian Process).

[0150] Step 5: Output and Sensitivity Analysis

[0151] a) Output: best matching table, Pareto chart (e.g. k eff -P out curve), parameter relationships (such as d opt =4d p ±σ), etc.

[0152] b) Parameter sensitivity: perform numerical differentiation, such as ∂P out / ∂d≈(P out (d+Δ)-P out (d)) / Δ; For example, when d is highly sensitive, its value increases by 10%, P out Increased to 15%.

[0153] c) Results display: For example, the optimal match in the ideal case: shape S = hexagon, array A = hex, d = 8 μm (4d p ), a=10 μm, through hole, k eff =550, P out =0.727.

[0154] d) Core logic: Analysis guides iteration (for example, when ∂ / ∂d p When high, prioritize homogenization d p ).

[0155] In one embodiment, a design system for a diamond array microporous heat dissipation substrate adapted for multi-size phosphors is provided. The system includes the following steps performed in sequence:

[0156] The first module is used to select the decision variables in the design process, including phosphor parameters, array micropore process parameters, and phosphor and micropore adaptation parameters, given the total diamond volume.

[0157] The second module is used to select a certain type of phosphor and obtain its parameters; at the same time, customize a series of array micropore process parameter solutions and calculate the phosphor and micropore adaptation parameters;

[0158] The third module is used to calculate the adaptation index between the phosphor parameters output by the second module and each array micropore process parameter solution and the phosphor and micropore adaptation parameters;

[0159] The fourth module is configured to implement: screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution adapted to the phosphor parameters in the second module;

[0160] The fifth module is used to realize: calculating the maximum luminous power of each array micropore process parameter scheme screened by the fourth module, and taking the array micropore process parameter scheme with the maximum luminous power as the maximum value as the optimal array micropore process parameter scheme.

[0161] Regarding the specific limitations of the design system for a diamond array microporous heat dissipation substrate adapted for multi-particle phosphor bodies, please refer to the limitations of the design method for a diamond array microporous heat dissipation substrate adapted for multi-particle phosphor bodies described above, and will not be repeated here. Each module in the above-mentioned design system for a diamond array microporous heat dissipation substrate can be implemented in whole or in part through software, hardware, and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0162] In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following is achieved:

[0163] Step 1: Under the condition of a given total diamond volume, the decision variables in the design process are selected, including phosphor parameters, array micropore process parameters, and phosphor and micropore adaptation parameters;

[0164] Step 2: Select a certain type of phosphor and obtain its parameters. At the same time, customize a series of array micropore process parameter solutions and calculate the phosphor and micropore adaptation parameters.

[0165] Step 3, calculating the adaptation index between the phosphor parameters in step 2 and each array micropore process parameter solution and the phosphor and micropore adaptation parameters;

[0166] Step 4: screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution that is adapted to the phosphor parameters in step 2;

[0167] Step 5: Calculate the maximum luminous power of each array-type micropore process parameter solution screened in step 4, and take the array-type micropore process parameter solution with the maximum luminous power as the maximum value as the optimal array-type micropore process parameter solution.

[0168] The specific limitations of each step can be found in the above-mentioned limitations on the design method of a diamond array microporous heat dissipation substrate adapted for multi-size phosphors, which will not be repeated here.

[0169] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the computer program implements:

[0170] Step 1: Under the condition of a given total diamond volume, the decision variables in the design process are selected, including phosphor parameters, array micropore process parameters, and phosphor and micropore adaptation parameters;

[0171] Step 2, select a certain type of phosphor and obtain its parameters; at the same time, custom build a series of array type micro-hole process parameter schemes, and calculate the phosphor and micro-hole adaptation parameters;

[0172] Step 3, calculate the adaptation index between the phosphor parameters in step 2 and each array type micro-hole process parameter scheme, and the adaptation index between the phosphor and micro-hole adaptation parameters;

[0173] Step 4, screen the array type micro-hole process parameter scheme based on the adaptation index to obtain the array type micro-hole process parameter scheme adapted to the phosphor parameters in step 2;

[0174] Step 5, calculate the maximum luminous power of each array type micro-hole process parameter scheme screened in step 4, and take the array type micro-hole process parameter scheme with the maximum luminous power as the optimal array type micro-hole process parameter scheme.

[0175] For the specific definition of each step, please refer to the definition of the design method of the diamond array type micro-hole heat dissipation substrate adapted to the multi-granularity phosphor body in the above, which will not be repeated here.

[0176] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A diamond array microporous heat dissipation substrate adapted for multi-size phosphors, characterized in that: The substrate comprises diamond, and the diamond is provided with arrayed micropores, and the arrayed micropores can adapt to multi-size phosphors. At the same time, when the volume of the diamond is constant, the phosphor can achieve a maximum heat transfer coefficient and a maximum luminous power.

2. The design method of the diamond array microporous heat dissipation substrate according to claim 1 is characterized in that: The method comprises the following steps: Step 1: Under the condition of a given total diamond volume, the decision variables in the design process are selected, including phosphor parameters, array micropore process parameters, and phosphor and micropore adaptation parameters; Step 2: Select a certain type of phosphor and obtain its parameters. At the same time, customize a series of array micropore process parameter solutions and calculate the phosphor and micropore adaptation parameters. Step 3, calculating the adaptation index between the phosphor parameters in step 2 and each array micropore process parameter solution and the phosphor and micropore adaptation parameters; Step 4: screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution that is adapted to the phosphor parameters in step 2; Step 5: Calculate the maximum luminous power of each array-type micropore process parameter solution screened in step 4, and take the array-type micropore process parameter solution with the maximum luminous power as the maximum value as the optimal array-type micropore process parameter solution.

3. The design method according to claim 2, characterized in that: In step 1, the phosphor parameters include particle size d p The micropore process parameters include pore shape S, pore diameter d, pore depth h, rib width w and array mode A, and the phosphor and micropore adaptation parameters include porosity Φ.

4. The design method according to claim 3, characterized in that: The calculation formula of the porosity Φ is: ； Where, is the cross-sectional area of ​​the micropore, are the length and width of the rectangular unit respectively, and the rectangular unit is a single rectangular unit in the rectangular array that evenly divides the diamond surface. is the hole shape coefficient.

5. The design method according to claim 4, characterized in that: The hole shape S includes rectangle, hexagon and circle; when the hole shape S is rectangle, the hole shape coefficient ; When the hole shape S is hexagonal, the hole shape coefficient ; When the hole shape S is circular, the hole shape coefficient .

6. The design method according to claim 4, characterized in that: The array type A includes a rectangular array and a honeycomb array; For rectangular arrays, the following conditions must be met: ； Where n is the number of holes punched along the sides of the rectangle, is the equivalent diameter of the diamond surface in the direction of the rectangular edge, and d is the equivalent diameter of the micropore; For cellular arrays, the following conditions should be met: ； Where, is the number of stacked layers of micropores.

7. The design method according to claim 2, characterized in that: The calculation formula for the adaptation index in step 3 is: ； Where, represents the fitness index, are all weight coefficients and their sum is 1, is the geometric packing adaptation function, is the heat diffusion adaptation function, is the light excitation volume adaptation function, which can be expressed as: ； ； ； Where, is the characteristic length of the hole cross section, λ is the optimal matching ratio, and α is the adjustable matching bandwidth; It is the sum of the resistance values ​​after considering the thermal resistance of the diamond body, the thermal resistance of the phosphor body and the contact thermal resistance of the interface between the two. is the reference thermal resistance; is the laser penetration depth.

8. The design method according to claim 2, characterized in that: Step 4, screening the array micropore process parameter solution based on the adaptation index to obtain the array micropore process parameter solution that is adapted to the phosphor parameters in step 2, specifically includes: Step 4-1, arranging the process parameter solutions of each arrayed micropore in descending order according to the adaptation index value; Step 4-2, selecting an array micropore process parameter solution with a fitness index value greater than a preset first threshold; Step 4-3, for the array micropore process parameter solution obtained in step 4-2, scan the values ​​of all decision variables in the definition domain, and eliminate the array micropore process parameter solution that does not conform to the actual situation or the change in the evaluation index is less than the preset second threshold; the evaluation index includes the heat transfer coefficient after the mixture of diamond and phosphor, that is, the equivalent heat transfer coefficient.

9. The design method according to claim 8, characterized in that: The method further comprises: Step 6: Calculate the equivalent heat transfer coefficient of the optimal array micropore process parameter solution and output it to an external terminal.

10. The design method according to claim 9, characterized in that: The method further comprises: Step 7, repeating steps 2 to 5 several times to obtain multiple sets of design solutions, each set of design solutions including decision variables, fitness indexes, and optimal array micropore process parameter solutions; Step 8: Based on multiple sets of design schemes, use machine learning algorithms to perform iterative optimization until the optimization conditions are met and output the final array micropore process parameter scheme.

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