A method for active design of metal surface micro-nano structure based on thermodynamic principle

Abstract

The application discloses a kind of metal surface micro-nano structure active design method based on thermodynamic principle.It is carried out according to the following steps: step S1: obtaining the surface topography parameters of target metal sample;Step S2: parameterization characterization is carried out to the surface topography based on the theory of general shape, and the general shape dimension and scale coefficient are extracted;Step S3: the general shape dimension and scale coefficient are used as geometric boundary conditions, and the high-temperature mechanical property parameters of the target metal material are combined to establish a thermal coupling simulation model.The present application takes the minimum potential energy principle and the minimum entropy generation principle as the design criterion, and takes the regulation of contact pressure distribution, the optimization of heat flow path and the control of oxide layer adhesion behavior as the three core objectives.Through the active design of three types of candidate micro-nano structures, the quantitative design criteria between the structure geometric parameters and the multi-field coupling response are established, and the design paradigm change from experience trial and error to physical driving is realized.

Description

Technical Field

[0001] This invention relates to the field of laser micro / nano fabrication and surface engineering technology, and in particular to an active design method for metal surface micro / nano structures based on thermodynamic principles. Background Technology

[0002] Metal interfaces are the core components for load transfer and energy exchange in mechanical systems. Under complex service conditions such as high temperature, heavy load, and alternating load, frictional wear and fatigue damage at the interface are key bottlenecks restricting the reliability and service life of mechanical systems. Especially in ultra-high temperature environments of 600~1000℃, the three damage forms of thermal fatigue, high temperature oxidation, and wear are coupled and intensified, making the interface failure mechanism more complex and further increasing the technical difficulty of surface performance control.

[0003] Fabricating micro / nanostructures on metal surfaces is a crucial technique for controlling interfacial tribological properties and enhancing interfacial damage resistance. Femtosecond laser processing, with its ultrashort pulse width and extremely high peak power density, enables precise machining at sub-micron to nanoscale dimensions with minimal heat-affected zones, making it the mainstream technology for fabricating surface micro / nanostructures. Existing technologies include various femtosecond laser-based methods for fabricating surface micro / nanostructures. These include directly forming micro / nanostructures on metal surfaces through focused ablation of femtosecond laser pulses, fabricating oxide-based interfacial expanded micro / nanostructures, constructing pit arrays with specific aspect ratios using layered dynamic focusing processes, and building nucleation gradient multi-element structure spliced ​​surfaces using direct writing techniques. These technologies can optimize specific properties of metal surfaces to a certain extent.

[0004] However, research has found that existing technologies still have the following shortcomings:

[0005] 1. Micro- and nanostructure design lacks a physical principle-driven approach. Existing design methods mostly adopt an empirical cycle of fabrication, characterization, and trial and error. The core geometric parameters of micro- and nanostructures, such as the diameter, depth, spacing, and area coverage of micro-pits, are mainly determined by repeated trials and empirical adjustments in process experiments. A systematic design criterion based on fundamental thermodynamic principles has not been established. Designers cannot predict the optimal parameter combination under specific operating conditions, resulting in high trial and error costs and low efficiency in the R&D process.

[0006] 2. Lack of quantitative correlation between structural geometric parameters and multi-field coupling response. Existing micro-nano structure designs are mostly aimed at single functional objectives, such as light trapping and heating, heat transfer enhancement, and anti-reflection and anti-transmission. A quantitative mapping relationship between structural geometric parameters and multi-field coupling response of interface temperature field and stress field has not yet been established. It is impossible to derive the target structural parameters in reverse from the actual mechanical and thermal requirements of service conditions, resulting in insufficient predictability and transferability of design results.

[0007] 3. Lack of a systematic design framework for ultra-high temperature multi-damage coupling scenarios. Existing technologies are mostly designed for medium and low temperature operating conditions at room temperature or not exceeding 400℃, focusing on the performance requirements of a single physical field. They do not cover the ultra-high temperature service range of 600~1000℃, and cannot achieve synergistic control of thermal fatigue, oxidation and wear damage, making it difficult to meet the damage resistance design requirements of key friction pairs under extreme high temperature environments. Summary of the Invention

[0008] The purpose of this invention is to provide an active design method for metal surface micro / nanostructures based on thermodynamic principles. This invention uses the principles of minimum potential energy and minimum entropy generation as design criteria, and focuses on three core objectives: controlling contact pressure distribution, optimizing heat flow paths, and controlling oxide layer adhesion behavior. By actively designing three types of candidate micro / nanostructures, it establishes quantitative design criteria between structural geometric parameters and multi-field coupling responses, achieving a paradigm shift from empirical trial and error to a physics-driven design approach.

[0009] The technical solution of this invention: an active design method for metal surface micro / nano structures based on thermodynamic principles, comprising the following steps:

[0010] Step S1: Obtain the surface morphology parameters of the target metal sample;

[0011] Step S2: Based on generic theory, the surface morphology is parametrically characterized, and the generic dimension and scale coefficient are extracted;

[0012] Step S3: Using the generic dimension and scale coefficient as geometric boundary conditions, and combining them with the high-temperature mechanical property parameters of the target metallic material, establish a thermo-mechanical coupling simulation model;

[0013] Step S4: Based on the principle of minimum potential energy and the principle of minimum entropy generation, set optimization objectives including uniform contact pressure distribution, optimal heat flow path and maximum oxide layer adhesion stability.

[0014] Step S5: Based on the optimization objective of step S4, design candidate micro-nano structures including micro-pit arrays, trench networks, and gradient meshes, and define the geometric parameters of each type of structure;

[0015] Step S6: Based on the thermo-mechanical coupling simulation model, the geometric parameters of the candidate micro-nano structures are simulated and screened using the orthogonal experimental design method. The optimal parameter combination is obtained by minimizing the interface peak stress, minimizing the heat flux density gradient, and maximizing the oxide layer interface peeling energy as screening criteria.

[0016] Step S7: Establish a quantitative mapping relationship between the geometric parameters of micro / nano structures and the multi-field coupling response based on the optimal parameter combination, and form design criteria;

[0017] Step S8: Based on the design criteria, and combined with the temperature and load conditions of the target service conditions, output the optimal micro / nano structure type and geometric parameter combination.

[0018] In the above-mentioned active design method for metal surface micro / nano structures based on thermodynamic principles, step S2 uses an improved adaptive box counting algorithm to extract the generic dimension, and the value range of the generic dimension is greater than 2.0 and less than 3.0.

[0019] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the thermo-mechanical coupling simulation model is a fully thermo-mechanically coupled three-dimensional contact pair model, incorporating both convective and radiative heat transfer conditions into the thermal boundary.

[0020] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the uniformization of contact pressure distribution is achieved by inducing local plastic deformation through micro / nano structures, dissipating mechanical energy, and reducing the peak contact pressure; the optimization of heat flow path is achieved by constructing low thermal resistance channels through micro / nano structures, guiding the orderly transfer of heat flow, and reducing the interface temperature gradient; and the maximization of oxide layer adhesion stability is achieved by regulating the stress state at the interface between the oxide layer and the substrate through micro / nano structures, thereby improving the oxide layer interface peeling energy.

[0021] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the micro-pit array is an array of pits, whose geometric parameters include the pit diameter, pit depth, depth-to-diameter ratio, area coverage, and arrangement method. The arrangement method includes square arrangement and hexagonal arrangement.

[0022] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the trench network is a network of trenches, and its geometric parameters include trench width, trench depth, trench spacing and trench direction, with the trench direction perpendicular to the main heat flow direction.

[0023] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the gradient grid is a multi-scale grid structure, whose geometric parameters include the side length and height of the first-level grid, the side length and height of the second-level grid, the side length and height of the third-level grid, and the area coverage.

[0024] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the simulation screening in step S6 is performed using finite element software, and the material constitutive model is selected using J2 flow theory combined with isotropic hardening law.

[0025] In the aforementioned active design method for metal surface micro / nano structures based on thermodynamic principles, the simulation screening in step S6 uses an L9 or L16 orthogonal array to conduct independent parameter screening and range analysis for the three types of candidate micro / nano structures.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This invention introduces the principle of minimum potential energy and the principle of minimum entropy generation into the field of metal surface micro-nano structure design for the first time. With the two thermodynamic principles as the core design criteria, it transforms contact pressure regulation, heat flow path optimization, and oxide layer adhesion control into quantifiable design goals, so that the entire design process has a clear thermodynamic and physical basis, reduces the number of trial and error in process experiments, and improves design efficiency and the scientific nature of the design scheme.

[0028] 2. This invention conducts systematic thermo-mechanical coupling simulation screening through orthogonal experimental design, quantitatively analyzes the influence of various geometric parameters on interface performance, establishes a quantitative mapping relationship between key geometric parameters of micro-nano structures and core response indicators such as interface peak stress, maximum temperature gradient, and oxide layer interface peeling energy, and forms standardized parametric design criteria, making the design results predictable and repeatable, and allowing for direct derivation of suitable structural parameter schemes based on service conditions.

[0029] 3. This invention addresses different damage mechanisms in different working conditions, such as abrasive wear-dominated areas, oxidation wear coupling areas, adhesion and spalling synergistic areas, heat flow concentration areas, and thermal stress concentration areas. It designs three types of micro / nano structures with clearly defined functions: micro-pit arrays, trench networks, and gradient meshes. The geometric parameters and physical functions of each type of structure correspond one-to-one, achieving a systematic match between damage mechanisms, structural types, and geometric parameters. This invention can specifically address various interface damage problems under ultra-high temperatures. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of the process of the present invention;

[0031] Figure 2 This is a schematic diagram of the micro-pit array structure of the present invention;

[0032] Figure 3 This is a schematic diagram of the trench network structure of the present invention;

[0033] Figure 4 This is a schematic diagram of the gradient grid structure of the present invention. Detailed Implementation

[0034] The present invention will be further described below with reference to the accompanying drawings and embodiments, but this should not be construed as limiting the present invention.

[0035] Example 1: An active design method for micro / nano structures on metal surfaces based on thermodynamic principles. The target service condition in this example is an oxidation-wear coupling zone with a normal load of 50N and a temperature of 750℃. (See attached diagram.) Figure 1 As shown, proceed with the following steps:

[0036] Step S1: Polish the target metal (using Inconel 718 nickel-based high-temperature alloy) sample to a mirror finish (roughness ≤ 0.05 μm), and use a white light interferometer to measure the sample surface to obtain surface morphology parameters such as the arithmetic mean deviation of the profile Ra and the maximum height of the profile Rz.

[0037] Step S2: Input the surface morphology parameters into the generic theoretical characterization model, and extract the generic dimension D = 2.35 and the scale coefficient using the improved adaptive box counting algorithm. The specific calculation process of the improved adaptive box counting algorithm is as follows:

[0038] Step S2.1: Multi-scale box coverage calculation. Select a set of box side lengths δ that vary in a geometric progression, and cover the three-dimensional surface topography to be measured respectively. Calculate the total number of boxes N(δ) required to completely cover the surface topography under each set of box side lengths; convert all scale points into double logarithmic coordinate data points (lnδ, lnN).

[0039] Step S2.2: Adaptive piecewise linear fitting. Divide all double logarithmic data points into transition segments. Optimal self-similar segment truncated segment There are three segments in total. The least squares method is used to perform linear fitting on each of the three segments. The optimal segmentation point is determined through a traversal optimization process, minimizing the sum of the fitting deviations for the three segments. At this point, the middle segment... This is the scale-free region with the best surface self-similarity.

[0040] Step S2.3: Solving for characteristic parameters. The fitted line of the interval is solved, and the absolute value of the slope of the line is the generic dimension D; the scaling factor G is derived from the intercept of the fitted line. The minimum box side length corresponding to the interval is the lower limit of the self-similarity metric scale δmin.

[0041] Step S2.4: Precision Verification. Verification The goodness of fit of the intervals is used to ensure that the correlation coefficient of the linear fit meets the accuracy requirements. The final output is a generic dimension D=2.35 and a scaling factor. .

[0042] Step S3: Convert the generic dimension and scale coefficient into surface roughness power spectral density, and construct a rough surface geometric profile with fractal characteristics using ABAQUS's random surface generation tool or a user subroutine (such as UMESHMOTION) as the geometric input for contact simulation; as shown in Table 1 below.

[0043]

[0044] Table 1. High-Temperature Mechanical Properties Data of Inconel 718

[0045] Based on the high-temperature mechanical properties of Inconel 718 nickel-based superalloy at 750℃ (elastic modulus E=178GPa, Poisson's ratio ν=0.290, coefficient of thermal expansion...), (Yield strength 750-830MPa, creep characteristics), establish a fully thermo-coupled three-dimensional spherical-plane contact pair model; specific settings are as follows:

[0046] Analysis type: Full thermo-mechanical coupling analysis is adopted, and the asymmetric solver is enabled to adapt to highly nonlinear contact problems, so as to achieve strong bidirectional coupling between the temperature field and the stress field, and simultaneously calculate the influence of frictional heat generation on the stress field and the reaction of temperature changes on material properties and contact state.

[0047] Elements and Mesh: The workpiece uses a C3D8RT three-dimensional eight-node hexahedral linear reduced integral thermo-coupled element, with each node containing 3 displacement degrees of freedom and 1 temperature degree of freedom; the dual part is silicon nitride. Because the high-temperature stiffness is much higher than that of the matrix and the deformation is negligible, it is set as an analytical rigid body and no element division is required. The mesh adopts a partitioned non-uniform strategy: a circular region with a radius of 1.5 times the contact half-width centered at the initial contact point is the contact refinement zone, with the element size controlled at 5-10μm to ensure the accuracy of the calculation of contact pressure and temperature gradient; the transition zone is located outside the refinement zone, with the element size gradient ratio not exceeding 1.5; the element size of the non-contact zone far from the contact is 50-100μm; the overall number of elements is controlled at 80,000-150,000, with additional local refinement at geometric features such as the edges of micro-pits and the corners of pit bottoms;

[0048] Displacement boundary conditions: A fully fixed displacement constraint (Ux=Uy=Uz=0) is applied to the bottom surface of the workpiece to simulate the constrained state of the sample installed in the fixture; there is no additional displacement constraint on the outer surface of the workpiece, allowing free thermal expansion; the dual sphere retains only the vertical Z-direction translational degree of freedom, and constrains the other 5 degrees of freedom to simulate the vertical loading state of the indenter.

[0049] Thermal boundary conditions: The initial temperature field of the model is uniformly set to 750℃ to simulate the steady-state initial state after preheating in the sample furnace; pressure-dependent contact heat conduction is defined between contact pairs to reflect the regulatory effect of contact pressure on interfacial thermal resistance; convective heat transfer boundaries are applied to all outer surfaces of the workpiece, and the convective heat transfer coefficient is taken as... Simultaneously apply a radiative heat transfer boundary with a surface emissivity of 0.5-0.7 to match the surface characteristics of the oxidized nickel-based alloy; set the model symmetry plane as an adiabatic boundary.

[0050] Load application method: The normal load adopts a linear ramp method, starting from zero at the beginning of the analysis step and increasing to the target value of 50N. After reaching the target value, it remains constant to avoid stress waves and numerical oscillations caused by instantaneous loading. The load is applied to the reference point of the dual sphere, and a concentrated force is applied along the Z direction of the contact normal. The thermal load is provided only through the frictional heat generated by the contact surface and boundary convection and radiation, without any additional volume heat source.

[0051] Analysis Steps and Time Control: Three analysis steps are set: initial step, transient loading analysis step, and quasi-static load holding analysis step. The transient loading step lasts 0.1-1.0 s, simulating the transient response during load application and initial contact. The quasi-static load holding step lasts 10-50 s, simulating the thermal equilibrium process after contact stabilization. Automatic time increment is enabled, and the initial increment step is set to... s, the minimum increment step is set to The maximum increment step is set to 0.1s; the maximum allowable temperature change per step is controlled within 5-10℃ to ensure the convergence accuracy of the material's nonlinear constitutive model; geometric nonlinearity and automatic stabilization settings are enabled, and the damping coefficient is set to... This suppresses numerical oscillations caused by abrupt changes in contact states.

[0052] Contact and Material Constitutive Model: A surface-to-surface contact pair is defined, with the upper surface of the workpiece as the target surface and the surface of the dual sphere as the contact surface. Normal behavior adopts "Hard" contact, allowing separation after contact. Tangential behavior uses a temperature-dependent Coulomb friction model, with a friction coefficient of 0.35-0.45 at 750℃. The workpiece material constitutive model employs J2 flow theory combined with isotropic hardening, using the Mises criterion for yielding, and employing a temperature-dependent piecewise linear plasticity hardening law. High-temperature creep effect uses a time-hardening power-law creep model, with parameters calibrated based on 750℃ creep test data from Inconel 718.

[0053] Step S4: Based on the principle of minimum potential energy (the real displacement field minimizes the total potential energy functional, the criterion is...) The principle of minimum entropy generation (linear non-equilibrium steady state minimizes the total entropy generation rate, the criterion is...) and The following three optimization objectives are set:

[0054] Objective T1: To achieve uniform contact pressure distribution by inducing local plastic deformation through micro-nano structures, dissipating mechanical energy, and reducing peak contact pressure.

[0055] Objective T2: Optimize the heat flow path by constructing low thermal resistance channels through micro-nano structures to guide the orderly transfer of heat flow and reduce the interface temperature gradient;

[0056] Objective T3: Maximize oxide layer adhesion stability by regulating the stress state at the oxide layer / substrate interface through micro / nano structures to improve oxide layer interface exfoliation energy.

[0057] Step S5: Based on the optimization objective of step S4, design candidate micro-nano structures including micro-pit arrays, trench networks, and gradient meshes, and define the geometric parameters of each type of structure;

[0058] As attached Figure 2 As shown, for the coupled oxidation and wear conditions, a micro-pit array is selected as the candidate structure, where all micro-pits are evenly distributed at equal intervals, and the coordinate axis unit is micrometer; the micro-pit array is an array of micrometer-level pits, and its geometric parameters are defined as follows: micro-pit diameter d = 20-70μm (step size 10μm), micro-pit depth h, depth-to-diameter ratio h / d = 0.1-0.7 (step size 0.1), area coverage φ = 10%-40% (step size 5%), and arrangement method (square arrangement, hexagonal close arrangement).

[0059] Step S6: Based on the aforementioned thermo-coupling simulation model, the geometric parameters of the micro-pit array are simulated and screened using an orthogonal experimental design method. The optimal parameter combination is obtained by minimizing the interface peak stress, minimizing the heat flux density gradient, and maximizing the oxide layer interface peeling energy, based on the screening criteria. Based on the above thermo-coupling simulation model, the following parameters are selected: The orthogonal array sets four levels for each of the four factors: micro-pit diameter, aspect ratio, area coverage, and arrangement, as shown in Table 2 below.

[0060]

[0061] Table 2

[0062] A total of 16 simulation experiments were conducted, and the results are shown in Table 3 below.

[0063] Table 3

[0064] Among them, the structure-free control group =468MPa =42.5℃ / mm, =6.8J / m².

[0065] Using the minimization of peak interfacial stress, the minimization of heat flux density gradient, and the maximization of oxide layer interfacial exfoliation energy as screening criteria, range analysis was performed on the simulation results to clarify the order of influence of each parameter on the response index. The optimal parameter range for multi-objective comprehensive optimization was preliminarily selected. The analysis results for minimizing peak interfacial stress, minimizing heat flux density gradient, and maximizing oxide layer interfacial exfoliation energy are shown in Tables 4-6 below.

[0066]

[0067] Table 4 Peak Stress Range analysis

[0068] The order of importance of factors in the table above is: d > h / d > arrangement > φ. Optimal level combination: d = 50μm, h / d = 0.45, φ = 30%, hexagonal close-packed.

[0069]

[0070] Table 5 Temperature gradient Range analysis

[0071] The order of importance of factors in the table above is: d > h / d > φ > arrangement. The optimal level combination is: d = 50μm, h / d = 0.45, φ = 30%, with a slightly better hexagonal close-packed arrangement.

[0072]

[0073] Table 6 Interface stripping energy Range analysis

[0074] The order of importance of factors in the table above is: arrangement > h / d > d > φ. The optimal level combination is: d = 50 μm, h / d = 0.45, φ = 30%, hexagonal close-packed.

[0075] Select 3-5 optimal parameter combinations from the candidate parameters.

[0076] Step S7: Based on the optimal parameter combination fitting, establish a quantitative functional relationship between the micro-pit diameter, depth-to-diameter ratio, area coverage and the interface peak stress, maximum temperature gradient and interface peeling energy, form a parameterized design criterion for the micro-pit array in the oxidation wear coupling zone, and realize the reverse derivation of structural parameters according to the response target;

[0077] Step S8: Based on the design criteria and considering the temperature and load conditions of the target service conditions, output the optimal micro / nano structure type and geometric parameter combination, resulting in the final preferred scheme: a hexagonal densely packed micro-pit array with a pit diameter d = 50 μm, a pit depth h = 22.5 μm (depth-to-diameter ratio 0.45), and an area coverage φ = 30%. Verify the optimal scheme through simulation; the results are shown in Table 7.

[0078]

[0079] Table 7

[0080] Compared with the control group with an unstructured smooth surface, this scheme significantly improved the peak interfacial stress by 24.8%, the interfacial temperature gradient by 29.9%, and the oxide layer interfacial exfoliation efficiency by 98.5%, achieving significant improvements in all three optimization objectives.

[0081] Example 2: An active design method for metal surface micro / nano structures based on thermodynamic principles. The target service condition in this example is a heat flux density region with an interface temperature gradient > 30℃ / mm. The method is carried out according to the following steps:

[0082] Step S1: Polish the Inconel 718 nickel-based superalloy sample to a mirror finish (roughness ≤ 0.05 μm), and use a white light interferometer to measure the sample surface to obtain surface morphology parameters such as the arithmetic mean deviation of the profile Ra and the maximum profile height Rz.

[0083] Step S2: Input the surface morphology parameters into the generic theory characterization model, and extract the generic dimension D = 2.32 and the scale coefficient G = using the improved adaptive box counting algorithm, similar to Example 1. .

[0084] Step S3: Input the generic dimension and scale coefficient as geometric boundary conditions into the ABAQUS finite element software, and combine the high-temperature mechanical properties of Inconel 718 nickel-based superalloy material in the heat flux dense region of the interface temperature gradient > 30℃ / mm to establish a fully thermo-mechanically coupled three-dimensional spherical-plane contact pair model. The specific configuration standard is the same as in Example 1.

[0085] Step S4: Based on the principle of minimum potential energy and the principle of minimum entropy generation, set the following three optimization objectives.

[0086] Objective T1: To achieve uniform contact pressure distribution by inducing local plastic deformation through micro-nano structures, dissipating mechanical energy, and reducing peak contact pressure.

[0087] Objective T2: Optimize the heat flow path by constructing low thermal resistance channels through micro-nano structures to guide the orderly transfer of heat flow and reduce the interface temperature gradient;

[0088] Objective T3: Maximize oxide layer adhesion stability by regulating the stress state at the oxide layer / substrate interface through micro / nano structures to improve oxide layer interface exfoliation energy.

[0089] Step S5: Based on the optimization objective of step S4, design candidate micro-nano structures including micro-pit arrays, trench networks, and gradient meshes, and define the geometric parameters of each type of structure;

[0090] As attached Figure 3 As shown, a trench network structure is designed and optimized for heat flow dense areas with an interface temperature gradient > 30℃ / mm. All trenches have equal widths and are evenly distributed with equal spacing. The coordinate axis unit is micrometer. The trench network consists of micrometer-level trenches distributed in a network shape. Its geometric parameters include: trench width w, trench depth h, trench spacing s, and trench direction. The trench direction is based on the main heat flow direction and is set with multiple horizontal groups from 0° to 90°.

[0091] Step S6: Based on the aforementioned thermo-coupling simulation model, the geometric parameters of the trench network are simulated and screened using an orthogonal experimental design method. The optimal parameter combination is obtained by minimizing the interface peak stress, minimizing the heat flux density gradient, and maximizing the oxide layer interface peeling energy, using L16(4) as the screening criteria. 4 An orthogonal array is used, with four levels for each of the four factors: trench width, trench depth, trench spacing, and trench direction, as shown in Table 8 below.

[0092]

[0093] Table 8

[0094] Sixteen simulation experiments were conducted, and the results are shown in Table 9 below.

[0095]

[0096] Table 9

[0097] Among them, the structure-free control group =505MPa, =48.5℃ / mm, =6.2J / m².

[0098] Using the minimization of peak interfacial stress, the minimization of heat flux density gradient, and the maximization of oxide layer interface peeling energy as screening criteria, range analysis was performed on the simulation results to clarify the order of influence of each parameter on the response index. The optimal parameter range for multi-objective comprehensive optimization was preliminarily selected. The analysis results for minimizing peak interfacial stress, minimizing heat flux density gradient, and maximizing oxide layer interface peeling energy are shown in Tables 10-12 below.

[0099]

[0100] Table 10 Peak Stress Range analysis

[0101] The order of importance of factors in the table above is: θ > w > h > s. Optimal: w = 35 μm, h = 20 μm, s = 90 μm, θ = 90° (perpendicular to the main heat flow direction);

[0102]

[0103] Table 11 Temperature gradient Range analysis

[0104] The order of importance of factors in the table above is: θ > w > h > s. Optimal: w = 35 μm, h = 20 μm, s = 90 μm, θ = 90°.

[0105]

[0106] Table 12 Interface stripping energy Range analysis

[0107] The order of importance of factors in the table above is: θ > w > h > s. Optimal: w = 35 μm, h = 20 μm, s = 90 μm, θ = 90°.

[0108] Select 3-5 optimal parameter combinations from the candidate parameters.

[0109] Step S7: Establish a quantitative mapping relationship between trench width, depth, spacing, direction and interface temperature gradient, peak stress and interface peeling energy, and form a design criterion for trench network in heat flow dense area.

[0110] Step S8: Based on the design criteria and considering the temperature and load conditions of the target service conditions, output the optimal micro / nano structure type and geometric parameter combination, and output the final preferred scheme: the trench direction is perpendicular to the main heat flow direction, the trench width w = 35 μm, the trench depth h = 20 μm, and the trench spacing s = 90 μm. Verify the comprehensive optimal scheme through simulation, and the results are shown in Table 13.

[0111]

[0112] Table 13

[0113] The direction of the groove (θ) is the primary factor affecting the three optimization objectives. Grooves perpendicular to the main heat flow direction can effectively cut off the heat flow concentration path and reduce thermal stress concentration.

[0114] Example 3: An active design method for metal surface micro / nano structures based on thermodynamic principles. The target service condition in this example is a region of adhesion and peeling synergy at 900℃ and a normal load of 80N. The method is carried out according to the following steps:

[0115] Step S1: Polish the Inconel 718 nickel-based superalloy sample to a mirror finish (roughness ≤ 0.05 μm), and use a white light interferometer to measure the sample surface to obtain surface morphology parameters such as the arithmetic mean deviation of the profile Ra and the maximum profile height Rz.

[0116] Step S2: Input the surface morphology parameters into the generic theory characterization model, and extract the generic dimension D = 2.38 and the scale coefficient G = using the improved adaptive box counting algorithm, similar to Example 1. .

[0117] Step S3: Input the generic dimension and scale coefficient as geometric boundary conditions into the ABAQUS finite element software, and combine them with the high-temperature mechanical properties of Inconel 718 nickel-based superalloy material at 900℃ (elastic modulus E=169GPa, Poisson's ratio ν=0.334, coefficient of thermal expansion). (Yield strength 340-420MPa, creep characteristics), establish a fully thermo-coupled three-dimensional spherical-plane contact pair model, with specific configuration standards the same as in Example 1.

[0118] Step S4: Based on the principle of minimum potential energy and the principle of minimum entropy generation, set the following three optimization objectives.

[0119] Objective T1: To achieve uniform contact pressure distribution by inducing local plastic deformation through micro-nano structures, dissipating mechanical energy, and reducing peak contact pressure.

[0120] Objective T2: Optimize the heat flow path by constructing low thermal resistance channels through micro-nano structures to guide the orderly transfer of heat flow and reduce the interface temperature gradient;

[0121] Objective T3: Maximize oxide layer adhesion stability by regulating the stress state at the oxide layer / substrate interface through micro / nano structures to improve oxide layer interface exfoliation energy.

[0122] Step S5: Based on the optimization objective of step S4, design candidate micro-nano structures including micro-pit arrays, trench networks, and gradient meshes, and define the geometric parameters of each type of structure;

[0123] As attached Figure 4 As shown, for the high-temperature adhesion and peeling condition, a gradient mesh is selected as the candidate structure, where h is the height of the mesh, and the mesh is arranged with different height gradients. ; l represents the length of the grid, which is arranged with different length gradients. The coordinate axes are all in micrometers; the gradient grid is a multi-level scale grid structure, and its geometric parameters are defined as follows: the side length and height of the first-level (bottom layer) grid, the side length and height of the second-level (middle layer) grid, the side length and height of the third-level (top layer) grid, and the area coverage.

[0124] Step S6: Based on the aforementioned thermo-coupling simulation model, the geometric parameters of the gradient mesh are simulated and screened using an orthogonal experimental design method. The optimal parameter combination is obtained by using the minimization of interface peak stress, the minimization of heat flux density gradient, and the maximization of oxide layer interface peeling energy as screening criteria. The orthogonal array has four levels for each of the four factors: first-level grid side length, second-level to first-level scale ratio, third-level to first-level scale ratio, and area coverage, as shown in Table 14 below.

[0125]

[0126] Table 14

[0127] Sixteen simulation experiments were conducted, and the results are shown in Table 15 below.

[0128]

[0129] Table 15

[0130] Among them, the structure-free control group =452MPa =48.0℃ / mm, =5.2J / m².

[0131] Using the minimization of peak interfacial stress, the minimization of heat flux density gradient, and the maximization of oxide layer interfacial exfoliation energy as screening criteria, range analysis was performed on the simulation results to clarify the order of influence of each parameter on the response index. The optimal parameter range for multi-objective comprehensive optimization was preliminarily selected. The analysis results for minimizing peak interfacial stress, minimizing heat flux density gradient, and maximizing oxide layer interfacial exfoliation energy are shown in Tables 16-18 below.

[0132]

[0133] Table 16 Peak Stress Range analysis

[0134]

[0135]

[0136] Table 17 Temperature Gradient Range analysis

[0137]

[0138]

[0139] Table 18 Interface stripping energy Range analysis

[0140]

[0141] Select 3-5 optimal parameter combinations from the candidate parameters.

[0142] Step S7: Establish a quantitative mapping relationship between multi-level scale ratio, coverage and interface stress, temperature gradient and oxide layer peeling energy, and form a gradient grid design criterion for high-temperature adhesion peeling zone.

[0143] Step S8: Based on the design criteria and considering the temperature and load conditions of the target service conditions, output the optimal micro / nano structure type and geometric parameter combination, resulting in the final preferred scheme: a three-level gradient mesh, with the first-level (bottom layer) mesh having an edge length of 290 μm and a height of 12 μm, the second-level (middle layer) mesh having an edge length of 145 μm and a height of 7 μm, and the third-level (top layer) mesh having an edge length of 58 μm and a height of 3 μm, with an area coverage of φ=40%. Verify the optimal scheme through simulation, and the results are shown in Table 19.

[0144]

[0145] Table 19

[0146] Compared with the unstructured control group, this scheme reduces the peak interfacial stress by 26.5%, the maximum interfacial temperature gradient by 33.3%, and the oxide layer interfacial peeling energy by 115.4%, exhibiting the best overall performance under ultra-high temperature and high load conditions.

[0147] The above embodiments 1-3 are further converted into process parameters executable by a femtosecond laser processing device; the laser processing parameter conversion is based on the typical femtosecond laser system parameters in Table 20 below.

[0148]

[0149] Table 20

[0150] The typical processing parameters of Inconel 718 in the calibration experiment are: pulse energy 200μJ, repetition frequency 100kHz, scan speed 100mm / s, scan radius 200μm. In the single-pulse calibration experiment, the power is reduced from 20W to 6.5W (step size 1.5W), repetition frequency 25kHz, scan speed 2500mm / s, and spot diameter 39.5μm.

[0151] For the micro-pit array in Example 1, fixed-point pulse ablation (i.e., the laser beam is fixed at a certain point and ablated with a set number of pulses, then moves to the next position after completion) is used instead of continuous scanning. The key processing parameters are converted as follows:

[0152] 1. Micro-pit diameter d and defocusing amount Δz

[0153] The diameter of the micro-pit is primarily controlled by the defocusing amount. For a typical focused spot diameter d0≈40μm and a target diameter d=50μm, the required positive defocusing amount is approximately:

[0154] ;

[0155] When the beam focusing half-angle θ≈8∘ (corresponding to numerical aperture NA≈0.14), Δz≈(50−40) / (2×0.14)≈36μm. That is, a defocusing amount of about 30-50μm can obtain a micro-pit with a diameter of 40-55μm.

[0156] 2. Micro-crater depth h, single-pulse energy Ep, and pulse number N

[0157] The depth of the microcrater is determined by both the single-pulse energy and the number of pulses. The single-pulse ablation depth of the Inconel 718 is logarithmically related to the flux. To achieve a depth of h = 22.5 μm:

[0158] The single-pulse energy is set to 120-180μJ (corresponding to an average power of 12-18W).

[0159] Each micro-pit has 80-150 pulses.

[0160] Within this parameter range, the ablation depth per pulse is approximately 0.15-0.28 μm, and a depth of 20-25 μm can be achieved by accumulating 80-150 pulses.

[0161] 3. Arrangement method and scanning path

[0162] The relationship between the center-to-center distance l of adjacent hexagonal closely packed micropits and the diameter d and coverage φ is as follows:

[0163] ;

[0164] When d=50μm and φ=30%, l≈87μm. The laser beam is sequentially positioned to the center of each micro-pit using a galvanometer scanning system, with an adjacent positioning distance of 87μm.

[0165] Recommended fabrication parameters for micro-pit arrays are shown in Table 21 below.

[0166]

[0167] Table 21

[0168] The groove network in Example 2 is processed using a continuous scanning method, with the laser beam moving continuously along a preset path. The key processing parameters are converted as follows:

[0169] 1. Groove width w, defocusing amount Δz, and scanning interval

[0170] The trench width is mainly controlled by the defocus amount. When the target width w=35μm, the defocus amount is about 10-30μm (slightly less than the defocus amount required for the micro-pit, because the trench is continuously scanned and the actual ablation width is slightly larger than the static spot).

[0171] 2. Trench depth h, scanning speed v, and repetition frequency

[0172] The trench depth is determined by both the pulse overlap rate and the single-pulse energy. To achieve a depth of h=20μm: single pulse energy 100-150μJ; repetition frequency 100kHz; scan speed 50-80mm / s.

[0173] 3. Trench spacing s and scanning path planning

[0174] The groove spacing s = 90 μm is directly set by the spacing between adjacent paths during galvanometer scanning.

[0175] 4. Groove direction θ and scanning path direction

[0176] The direction of the groove is achieved by the geometric orientation of the scanning path, where θ=90∘ indicates that the direction of the groove extension is perpendicular to the direction of the main heat flow.

[0177] Recommended processing parameters for trench networks are shown in Table 22 below.

[0178]

[0179] Table 22

[0180] For the gradient mesh in Example 3, a layer-by-layer scanning strategy is adopted, processing it sequentially from large to small at three different scales. The key processing parameters are transformed as follows:

[0181] 1. Grid side length Li and scan path planning at each level

[0182] The side lengths of each grid level are directly set by the path geometry of the galvanometer scan. The first-level grid (290×290μm squares), the second-level grid (145×145μm), and the third-level grid (58×58μm) are achieved by controlling the scanning path through numerical control programming.

[0183] 2. Grid height (Hi) at each level, in relation to scanning speed and number of scans

[0184] Height control at each level is achieved by adjusting the scanning speed and the number of repeated scans, as shown in Table 23 below.

[0185]

[0186] Table 23

[0187] 3. Control of coverage rate φ=40% and the ratio of mesh width to mesh side length

[0188] Grid area coverage φ and rib width The relationship between the grid side length L and the grid side length L is:

[0189] ;

[0190] When φ=40% and L=290μm ≈67μm. Rib width is controlled by defocusing amount, which is set to 40-60μm in this case.

[0191] Recommended processing parameters for gradient meshes are shown in Table 24 below.

[0192]

[0193] Table 24

[0194] In summary, the active design method for metal surface micro / nanostructures based on thermodynamic principles proposed in this invention has been validated through system simulations under three typical operating conditions. This demonstrates that the method can accurately output suitable micro / nanostructure parameter schemes for service scenarios dominated by different damage mechanisms, effectively improving the overall damage resistance of metal interface joints in ultra-high temperature environments of 600-1000℃. Compared to the traditional empirical design model of fabrication, characterization, and trial and error, this invention uses the principles of minimum potential energy and minimum entropy generation as underlying physical drivers. Relying on generic morphology characterization methods and a fully thermo-mechanical coupling simulation system, it establishes quantitative design criteria for the geometric parameters of micro / nanostructures and the multi-field coupling response of the interface, achieving the physicalization, quantification, and predictability of the design process, significantly reducing the R&D cycle and experimental trial and error costs. The three functionally differentiated micro / nanostructure partitioning adaptation schemes can cover various ultra-high temperature damage scenarios such as abrasive wear, oxidative wear, heat flux concentration, and adhesive peeling, forming a complete systematic design framework. This method is widely applicable to various high-temperature alloy materials and can provide reliable surface performance optimization solutions for key friction pairs in high-end equipment such as special robot joints and hot-end components of aero engines. It has important engineering application value for improving the service reliability and service life of mechanical systems under extreme working conditions.

Claims

1. An active design method for micro / nano structures on metal surfaces based on thermodynamic principles, characterized in that: Follow these steps: Step S1: Obtain the surface morphology parameters of the target metal sample; Step S2: Based on generic theory, the surface morphology is parametrically characterized, and the generic dimension and scale coefficient are extracted; Step S3: Using the generic dimension and scale coefficient as geometric boundary conditions, and combining them with the high-temperature mechanical property parameters of the target metallic material, a thermo-mechanical coupling simulation model is established; Step S4: Based on the principle of minimum potential energy and the principle of minimum entropy generation, set optimization objectives including uniform contact pressure distribution, optimal heat flow path and maximum oxide layer adhesion stability. Step S5: Based on the optimization objective of step S4, design candidate micro-nano structures including micro-pit arrays, trench networks, and gradient meshes, and define the geometric parameters of each type of structure; Step S6: Based on the thermo-mechanical coupling simulation model, the geometric parameters of the candidate micro-nano structures are simulated and screened using the orthogonal experimental design method. The optimal parameter combination is obtained by minimizing the interface peak stress, minimizing the heat flux density gradient, and maximizing the oxide layer interface peeling energy as screening criteria. Step S7: Establish a quantitative mapping relationship between the geometric parameters of micro / nano structures and the multi-field coupling response based on the optimal parameter combination, and form design criteria; Step S8: Based on the design criteria, and combined with the temperature and load conditions of the target service conditions, output the optimal micro / nano structure type and geometric parameter combination.

2. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: In step S2, an improved adaptive box counting algorithm is used to extract the generic dimension, and the value of the generic dimension is greater than 2.0 and less than 3.

0.

3. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: The thermo-coupling simulation model is a fully thermo-coupling three-dimensional contact pair model, with the thermal boundary incorporating both convective and radiative heat transfer conditions.

4. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: The uniformity of contact pressure distribution is achieved by inducing local plastic deformation through micro-nano structures, dissipating mechanical energy, and reducing the peak contact pressure. The optimization of the heat flow path is achieved by constructing low thermal resistance channels through micro-nano structures, guiding the orderly transfer of heat flow, and reducing the interface temperature gradient. The maximization of oxide layer adhesion stability is achieved by regulating the stress state of the oxide layer and substrate interface through micro-nano structures, thereby improving the oxide layer interface peeling energy.

5. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: The micro-pit array is an array of pits, and its geometric parameters include the micro-pit diameter, micro-pit depth, depth-to-diameter ratio, area coverage, and arrangement. The arrangement includes square arrangement and hexagonal arrangement.

6. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: The trench network is a network of trenches, and its geometric parameters include trench width, trench depth, trench spacing and trench direction, with the trench direction perpendicular to the main heat flow direction.

7. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: The gradient grid is a multi-scale grid structure, and its geometric parameters include the side length and height of the first-level grid, the side length and height of the second-level grid, the side length and height of the third-level grid, and the area coverage.

8. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 1, characterized in that: In step S6, the simulation screening is performed using finite element software, and the material constitutive model is selected from the J2 flow theory combined with the isotropic hardening rule.

9. The active design method for metal surface micro / nano structures based on thermodynamic principles according to claim 8, characterized in that: In step S6, the simulation screening uses an L9 or L16 orthogonal array to conduct independent parameter screening and range analysis for the three types of candidate micro-nano structures.

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