Method for designing medium / high-entropy carbide in ultrahigh-temperature ceramic for hot-end component through multi-index screening

Abstract

The invention discloses a method for designing medium / high-entropy carbide in ultrahigh-temperature ceramic for a multi-index screening hot-end component, and belongs to the field of ultrahigh-temperature ceramic materials. The method is based on first principle high-throughput calculation and comprises the following steps: firstly, constructing a unary carbide model, performing disordered doping by adopting mcsqs codes in an ATAT toolkit to establish a quasi-random structure model, and then obtaining an elastic constant through a structural relaxation and energy-strain method; further, multi-dimensional performance indexes such as mechanical stability, Young modulus, hardness and fracture toughness of the material are calculated and evaluated, and finally candidate components with excellent comprehensive performance are quickly locked through a multi-stage collaborative screening process. According to the method, material preliminary screening is converted into efficient virtual calculation from traditional time-consuming experiment'trial and error ', the research and development cost is remarkably reduced, the research and development period is remarkably shortened, and reliable prediction and guidance are provided for high-performance ceramic material design facing the extreme environment.

Description

Technical Field

[0001] This invention relates to a multi-index screening method for designing medium / high entropy carbides in ultra-high temperature ceramics for hot-end components, belonging to the field of ultra-high temperature ceramic materials. Background Technology

[0002] Hot-end components of equipment such as aero-engines are subjected to extreme high temperatures, high-speed exhaust erosion, and severe thermal shock during long-term service, placing near-limit demands on the high-temperature strength, toughness, and stability of materials. Traditional ceramic materials struggle to achieve these properties simultaneously, while high-entropy carbides, with their "cocktail" effect, are considered a highly promising solution. However, the vast compositional design space of high-entropy ceramics presents significant challenges to screening through traditional trial-and-error experiments: single synthesis and performance testing cycles are lengthy and costly, and experimental methods struggle to systematically traverse and evaluate tens of thousands of candidate components, severely restricting the efficiency of new material design and development. Therefore, a high-throughput computational method is urgently needed to rapidly and cost-effectively predict and screen high-performance candidate materials from a massive pool of compositions, guiding experiments and reducing R&D costs and timelines. Summary of the Invention

[0003] In view of the above-mentioned prior art, the present invention discloses a high-entropy carbide design method based on first-principles high-throughput computing and multi-index collaborative screening, so as to solve the problems of long experimental development cycle, high cost and difficulty in systematic screening of high-entropy carbides due to their huge composition space in the prior art.

[0004] To achieve the above objectives, the technical solution adopted by this invention is: to provide a design method for screening high-entropy carbides in ultra-high temperature ceramics for hot-end components, which includes the following steps:

[0005] S1: Construct a monolithic carbide crystal structure model;

[0006] S2: Determine the target element system and composition range;

[0007] S3: Based on the element system and composition range determined in step S2, the mcsqs code in Alloy Theoretic AutomatedToolkit is used to randomly dop the cation sites of the unary carbide crystal structure model constructed in step S1 to obtain a medium / high entropy carbide quasi-random structure model.

[0008] S4: Import the medium / high entropy carbide quasi-random structure model constructed in step S3 into the same folder, perform structural relaxation on the medium entropy carbide model, and obtain the medium entropy carbide model with the lowest energy.

[0009] S5: Based on the crystal structure symmetry of the research object, apply a small strain to the equilibrium lattice structure according to the energy change of the optimized medium / high entropy carbide quasi-random structure model in step S4 to obtain the energy-strain relationship;

[0010] S6: Based on the energy-strain relationship obtained in step S5, the elastic stiffness constant C of the medium / high entropy carbides is obtained by fitting the second derivative of energy with respect to strain. ij ;

[0011] S7: Determine the mechanical stability of medium / high entropy carbides based on the elastic stiffness coefficient calculated in step S6;

[0012] S8: Based on the elastic stiffness coefficients obtained in step S6, use the VRH criterion to calculate the Young's modulus E, shear modulus G, bulk modulus B, Poisson's ratio v, and Pugh ratio B / G of medium / high entropy carbides.

[0013] S9: Calculate the Vickers hardness H of medium / high entropy carbides based on the shear modulus G and bulk modulus B from step S8. V In step S8, the fracture toughness K of high-entropy carbides is calculated using Young's modulus E and Poisson's ratio v. IC ;

[0014] S10: Mechanical stability, Young's modulus E, Poisson's ratio v, and Vickers hardness H obtained from steps S7, S8, S9, and S10. V Fracture toughness K IC High-throughput screening of medium / high entropy carbides

[0015] Based on the above technical solution, the present invention can be further improved as follows.

[0016] Furthermore, in step 1, the selected elements are added sequentially to construct binary, ternary, and even pentagonal system models, thereby clearly tracking the incremental contribution and evolution of each element's introduction to performance.

[0017] Furthermore, the elements in step 2 include at least five of the following: Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, and W.

[0018] Furthermore, the structural relaxation parameters in step 4 include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, the total energy convergence criterion is 10⁻⁵ eV, the stress convergence criterion is 0.015 eV / Å, and the maximum number of ion steps is 300 steps.

[0019] The beneficial effects of this invention are as follows: Based on a monolithic carbide crystal structure model and element types, this invention uses the mcsqs code in the Alloy Theoretic Automated Toolkit to perform disordered doping on the monolithic carbide crystal structure model, obtaining a medium / high entropy quasi-random structure model; then, the medium / high entropy quasi-random structure model is structurally optimized to obtain the medium / high entropy quasi-random structure model with the lowest energy; small strains are applied to the medium / high entropy quasi-random structure model with the lowest energy to obtain elastic constants; based on the elastic constants, the mechanical stability, Young's modulus E, Poisson's ratio v, and Vickers hardness H of the medium / high entropy carbide are calculated. V and fracture toughness K IC By employing multi-dimensional performance indicators, a multi-level screening process is used to quickly identify candidate components with excellent overall performance. This method transforms the initial screening of materials from time-consuming and costly experimental "trial and error" into efficient virtual computation, significantly shortening the R&D cycle and reducing experimental costs. The multi-level collaborative screening system established in this invention, from stability criteria (Born criterion) to macroscopic performance indicators (modulus, hardness, toughness), ensures the mechanical and structural feasibility of recommended components and improves the success rate of experimental verification. Simultaneously, the progressive design strategy adopted, moving from univariate to multivariate elements, clearly reveals the incremental contributions of different elements, providing direct guidance for rational component design targeting specific performance needs, and forming a complete design closed loop from computational prediction to experimental targeted synthesis. Attached Figure Description

[0020] Figure 1 This is a flowchart of high-throughput design for medium / high entropy carbide ceramics;

[0021] Figure 2 This is a flowchart for high-throughput screening of medium / high entropy carbides. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer and to enable those skilled in the art to implement it based on the description, the invention is further described below with reference to examples. It should be understood that the following description is not intended to limit the scope of the invention, but is exemplary. Furthermore, in the following description, technical descriptions disclosed in the art are omitted to avoid unnecessarily obscuring the concept of the invention.

[0023] Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0024] Specific implementation method one: as follows Figure 1 and Figure 2As shown, a multi-index screening design method for high-entropy alloys to meet the performance requirements of high-temperature bearings, and a design method for high-entropy carbides in ultra-high temperature ceramics for hot-end components, the specific steps of which include:

[0025] S1: Construct crystal structure models of unary to pentagonal carbides;

[0026] S2: Determine the target element system and composition range;

[0027] S3: Based on the element system and composition range determined in step S2, the cation sites of the binary to pentagonal carbide crystal structure model constructed in step S1 are randomly doped using the mcsqs code in Alloy Theoretic AutomatedToolkit to obtain a medium / high entropy quasi-random structure model of carbide.

[0028] S4: Import the medium / high entropy carbide quasi-random structure models constructed in step S3 into the same folder. Perform structural relaxation on the medium entropy carbide model to obtain the medium entropy carbide model with the lowest energy. The structural relaxation parameters include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, and the total energy convergence criterion is 10. -5 eV, stress convergence criterion is 0.015 eV / Å, maximum ion steps are 300 steps;

[0029] S5: Based on the crystal structure symmetry of the research object, apply a small strain to the equilibrium lattice structure of the optimized medium / high entropy carbide quasi-random structure in step S4 according to the energy change to obtain the energy-strain relationship;

[0030] S6: Based on the energy-strain relationship obtained in step S5, the elastic stiffness constant C of the medium / high entropy carbides is obtained by fitting the second derivative of energy with respect to strain. ij ;

[0031] S7: Based on the elastic stiffness coefficient calculated in step S6, determine the mechanical stability of medium / high entropy carbides using formula (1);

[0032] , , , (1),

[0033] In formula (1), C 11 C 12 C 44 Both represent elastic stiffness constants;

[0034] S8: Based on the elastic stiffness coefficient obtained in step S6, the Young's modulus E, shear modulus G, bulk modulus B, Poisson's ratio v and Pugh ratio B / G of medium / high entropy carbides are calculated using the VRH criterion according to formulas (2)~(7).

[0035] (2),

[0036] (3),

[0037] (4),

[0038] (5),

[0039] (6),

[0040] (7),

[0041] In formulas (2) to (7), C 11 C 12 C 44 Both represent the elastic stiffness constant, G V G R Indicates shear modulus;

[0042] S9: Based on the shear modulus G and bulk modulus B in step S8, calculate the Vickers hardness H of the medium / high entropy carbide according to formula (8). V Based on Young's modulus E and Poisson's ratio v in step S8, the fracture toughness K of medium / high entropy carbides is calculated according to formula (9). IC ;

[0043] (8),

[0044] (9),

[0045] Where k is B / G and V0 is the volume;

[0046] S10: Mechanical stability, Young's modulus E, Poisson's ratio v, and Vickers hardness H obtained from steps S7, S8, S9, and S10. V Fracture toughness K IC High-throughput screening of medium / high entropy carbides.

[0047] The elements include at least five of Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, and W. The high-throughput calculation method for the mechanical properties of medium / high entropy carbides of this invention can calculate the mechanical properties of multiple different medium / high entropy carbides at once.

[0048] Example 1

[0049] S1: Construct crystal structure models of unary to pentagonal carbides with a crystal system of Fm3m;

[0050] S2: Select five elements Ti, Zr, Hf, Nb, and Ta, and arrange and combine the elements;

[0051] S3: Use the mcsqs code in the Alloy Theoretic Automated Toolkit to randomly dop the cation sites of the binary to pentagonal carbide crystal structure models constructed in step S1 to obtain all medium / high entropy carbide quasi-random structure models.

[0052] S4: Import the medium / high entropy carbide quasi-random structure models constructed in step S3 into the same folder. Perform structural relaxation on the medium entropy carbide model to obtain the medium entropy carbide model with the lowest energy. The structural relaxation parameters include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, and the k-point adopts the Monkhorst-Pack scheme and is set to...

[0053] The total energy convergence criterion is 10 for 8×8×8. -5 eV, stress convergence criterion is 0.015 eV / Å, maximum ion steps are 300 steps;

[0054] S5: Based on the crystal structure symmetry of the research object, a small strain is applied to the equilibrium lattice structure of the optimized medium / high entropy carbide quasi-random structure in step S4 according to the energy change, obtaining the energy-strain relationship. The structure optimization parameters include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, and the total energy convergence criterion is 10. -5 eV, stress convergence criterion is 0.015 eV / Å, maximum ion steps are 300 steps;

[0055] S6: Based on the energy-strain relationship obtained in step S5, the elastic stiffness constant C of the medium / high entropy carbides is obtained by fitting the second derivative of energy with respect to strain. ij ;

[0056] S7: Based on the mechanical and thermophysical properties of medium / high entropy carbides, five high-performance medium-entropy carbides were finally screened from all medium / high entropy carbides, as shown in Table 1.

[0057] Table 1 Screening results of Example 1

[0058] Medium and high entropy carbides Young's modulus E (GPa) <![CDATA[Vickers hardness H V (GPa)]]> <![CDATA[Fracture toughness K IC (MPa·m 1 / 2 )]]> Pugh compared to B / G Poisson's ratio v TiTaC 510.01 27.52 5.47 1.412 0.21 HfTaC 515.69 27.57 5.40 1.397 0.21 TiNbTaC 507.92 27.02 5.46 1.43 0.22 TiZrNbTaC 491.26 28.01 5.25 1.37 0.21 TiZrHfNbTaC 482.41 28.43 5.14 1.35 0.20

[0059] Example 2

[0060] S1: Construct crystal structure models of unary to pentagonal carbides with a crystal system of Fm3m;

[0061] S2: Select five elements Ti, Zr, Hf, W, and Ta, and arrange and combine the elements;

[0062] S3: Use the mcsqs code in the Alloy Theoretic Automated Toolkit to randomly dop the cation sites of the binary to pentagonal carbide crystal structure models constructed in step S1 to obtain all medium / high entropy carbide quasi-random structure models.

[0063] S4: Import the medium / high entropy carbide quasi-random structure models constructed in step S3 into the same folder. Perform structural relaxation on the medium entropy carbide model to obtain the medium entropy carbide model with the lowest energy. The structural relaxation parameters include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, and the total energy convergence criterion is 10. -5 eV, stress convergence criterion is 0.015 eV / Å, maximum ion steps are 300 steps;

[0064] S5: Based on the crystal structure symmetry of the research object, a small strain is applied to the equilibrium lattice structure of the optimized medium / high entropy carbide quasi-random structure in step S4 according to the energy change, obtaining the energy-strain relationship. The structure optimization parameters include: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, and the total energy convergence criterion is 10. -5 eV, stress convergence criterion is 0.015 eV / Å, maximum ion steps are 300 steps;

[0065] S6: Based on the energy-strain relationship obtained in step S5, the elastic stiffness constant C of the medium / high entropy carbides is obtained by fitting the second derivative of energy with respect to strain. ij ;

[0066] S7: Based on the mechanical and thermophysical properties of medium / high entropy carbides, six high-performance medium-entropy carbides were finally screened from all medium / high entropy carbides, as shown in Table 2.

[0067] Table 2 Screening Results of Example 2

[0068] Medium and high entropy carbides Young's modulus E (GPa) <![CDATA[Vickers hardness H V (GPa)]]> <![CDATA[Fracture toughness K IC (MPa·m 1 / 2 )]]> Pugh compared to B / G Poisson's ratio v WTaC 559.43 26.54 6.16 1.55 0.23 TiTaC 510.01 27.52 5.47 1.41 0.21 HfTaC 515.69 27.57 5.40 1.40 0.21 WTiTaC 530.31 26.59 5.73 1.47 0.22 WTiHfTaC 506.94 26.33 5.48 1.45 0.22 WTiZrHfTaC 500.73 26.54 5.17 1.44 0.22

Claims

1. A multi-index screening method for designing ultra-high temperature ceramic medium / high entropy carbides for hot-end components, characterized in that, Includes the following steps: S1: Construct a monolithic carbide crystal structure model; S2: Determine the target element system and composition range; S3: Based on the element system and composition range determined in step S2, the mcsqs code in Alloy Theoretic AutomatedToolkit is used to perform disordered cation site doping on the unary carbide crystal structure model constructed in step S1 to obtain a medium / high entropy carbide quasi-random structure model. S4: Perform structural relaxation on the quasi-stochastic structure model constructed in step S3 to obtain a stable structure model with the lowest energy. S5: Apply a set of small strains that conform to crystal symmetry to the stable structural model obtained in step S4, and perform structural optimization on each strain configuration to obtain the corresponding total energy of the system and establish the energy-strain relationship; S6: Based on the energy-strain relationship obtained in step S5, the elastic stiffness constant C of the material is calculated by fitting the second derivative of energy with respect to strain. ij ; S7: The elastic stiffness constant C calculated based on step S6 ij To determine the mechanical stability of a material; S8: Elastic stiffness constant C calculated based on step S6 ij The Voigt-Reuss-Hill approximation was used to calculate the Young's modulus E, shear modulus G, bulk modulus B, Poisson's ratio ν, and Pugh ratio B / G of the material. S9: Calculate the Vickers hardness H of the material based on the shear modulus G and bulk modulus B obtained in step S8. V ; The fracture toughness K of the material is calculated based on the Young's modulus E and Poisson's ratio ν obtained in step S8. IC ; S10: Mechanical stability, Young's modulus E, and Vickers hardness H obtained from steps S7, S8, and S9. V and fracture toughness K IC Set performance thresholds to perform multi-index collaborative screening and output the preferred components that meet all preset conditions.

2. The design method for ultra-high temperature ceramic medium / high entropy carbides for hot-end components using multi-index screening according to claim 1, characterized in that, In step S2, the target element system includes at least five transition metal elements selected from Ti, V, Cr, Zr, Nb, Mo, Hf, Ta, and W.

3. The design method for ultra-high temperature ceramic medium / high entropy carbides for hot-end components using multi-index screening according to claim 1, characterized in that, In step S4, structural relaxation is performed using first-principles calculations with the following parameters: the functional is selected as the PBE form in GGA, the optimization algorithm is selected as BFGS, the pseudopotential is selected as PAW, the cutoff energy is set to 550 eV, the k-point adopts the Monkhorst-Pack scheme and is set to 8×8×8, the total energy convergence criterion is 10⁻⁵ eV, the stress convergence criterion is 0.015 eV / Å, and the maximum number of ion steps is 300 steps.

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