Hydrogen embrittlement resistant structure, design method, system, and aluminum alloy

Abstract

The application provides an anti-hydrogen embrittlement structure, a design method, a system and an aluminum alloy. The method comprises the following steps: based on a constructed high-precision multi-scale calculation method, connecting a first principle calculation model and a molecular dynamics calculation model, intelligently recommending a potential hydrogen trapping precipitation phase in the aluminum alloy, clearly defining a thermodynamic formation interval of the new structure in the aluminum alloy intragranular dispersion distribution, quickly determining an optimal heat treatment process of the hydrogen trapping structure, completing the doping of specified elements into the specific structure, realizing the strong capture of hydrogen atoms in the aluminum alloy grain, and avoiding the hydrogen embrittlement of the aluminum alloy under the corrosion environment caused by hydrogen aggregation. The design model greatly improves the screening efficiency of the aluminum alloy anti-hydrogen embrittlement structure under the severe corrosion environment, greatly shortens the establishment time of the optimal heat treatment scheme of the anti-hydrogen embrittlement structure aluminum alloy, and provides an efficient method for the design and preparation of the anti-hydrogen embrittlement aluminum alloy.

Description

Technical Field

[0001] This invention relates to the fields of multi-scale intelligent computing, intelligent model application, and alloy preparation. Specifically, it relates to an aluminum alloy hydrogen embrittlement-resistant structure established by multi-scale corrosion integrated calculation, an intelligent design method and system for the structure, and an aluminum alloy containing the hydrogen embrittlement-resistant structure, which can design and optimize the steady-state and metastable precipitates with nanoscale dispersed distribution within the grains. Background Technology

[0002] With the continuous development of aerospace, high-speed rail, and lightweight automobiles, aluminum alloys are being used more and more widely in these industries. However, during the service life of these materials, the damage caused by hydrogen to high-strength structural materials is becoming increasingly significant. Furthermore, facing the urgent demands for the development of new and clean energy, especially the development of fuel cell vehicles, the hydrogen energy industry, as a crucial link in the new energy industry, has developed rapidly. The supply and transportation of hydrogen also urgently require the development of highly corrosion-resistant and hydrogen-embrittlement-resistant materials.

[0003] For aluminum alloys, the locations of hydrogen atoms can be categorized into three types: lattice, dislocations, and vacancy defects. Among these, grain boundaries have the weakest hydrogen-capturing ability and the lowest binding energy. Processing and heat treatment directly affect dislocation density; high dislocation density is conducive to hydrogen atom capture. Vacancy defects or precipitates, which possess the strongest hydrogen-capturing ability (high hydrogen capture energy), are most complex to form due to the influence of alloying elements, processing techniques, and heat treatment processes. Therefore, in designing high-resistance to hydrogen embrittlement aluminum alloys, the most crucial aspect is designing and preparing vacancy defects and precipitates with high binding energy within the aluminum alloy.

[0004] Discovering and preparing precipitate structures with high hydrogen capture energy is the most challenging aspect of hydrogen embrittlement resistance design. Common alloying elements in aluminum alloys include Mg, Zn, Cu, Mn, Si, and Li, while trace elements include Sc, Fe, Cr, Zr, Ti, La, Ce, and Y. There are an infinite number of possible precipitate combinations among these elements, such as AlFe3, AlCr2, Al4Cu9, AlCu, Al2Cu, Al3Mg2, Al4Mn, Al3Ti, Al3Zr, Al3Sc, MgZn2, Mg3Zn3Al2, Al6CuMg4, Al7Cu2Fe, and Mn3Fe3SiAl. 12Numerous precipitated phases exist in aluminum alloys, including Mg2Si, VAl3, LaAl, AlFeMnSi, AlZnCuMg, LaAl2, and CeAl2. Different elemental ratios and space group structures also exist among the same alloying elements. Experiments have shown that the Al3Zr and Al2CuMg phases in aluminum alloys possess high hydrogen-capturing capabilities, while the precipitated strengthening phase η-MgZn2 in traditional 7xxx series aluminum alloys does not capture hydrogen atoms. High-strength 7xxx series aluminum alloys are commonly used in high-load-bearing components such as aircraft wing frames and high-speed rail sleeper beams. The diffusion and accumulation of hydrogen atoms within these alloys makes them prone to stress corrosion cracking and other failures, jeopardizing the service safety of engineering components.

[0005] Traditional hydrogen embrittlement resistant structural design involves orthogonal experiments with predetermined alloying elements, combining multiple compositions and conducting experimental verification. The design inspiration often stems from the experiential judgment of on-site personnel, frequently requiring multiple production batches for trial and error, resulting in wasted time and costs. Furthermore, the experimental efficiency of orthogonal experimental methods is only high for a small number of alloying elements; it is extremely inefficient for complex alloy compositions (number > 5). Given the complex elemental composition and heat treatment processes in aluminum alloys, rapidly screening for and successfully preparing high hydrogen-capturing structures will help reduce the accumulation of hydrogen atoms, thereby improving the hydrogen embrittlement resistance of aluminum alloys. Ultimately, this achieves the goal of rapidly designing hydrogen embrittlement resistant aluminum alloys, significantly shortening the production cycle and reducing trial and error costs. Summary of the Invention

[0006] The main problem addressed by this invention is the high cost and low efficiency of traditional alloy hydrogen embrittlement resistance structure design. Some structures, after screening, are metastable, making it impossible to provide a clear heat treatment process for achieving these structures. The main objective is to propose an intelligent design scheme for aluminum alloy hydrogen embrittlement resistance structures based on multi-scale corrosion integration. By selecting basic elements, an intelligent model recommends potential precipitate phase structures, and high-throughput first-principles calculations are performed. Data is processed and interatomic potential functions are constructed, enabling molecular dynamics structural transformation simulations and rapid customization of heat treatment processes.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for designing a hydrogen embrittlement-resistant structure, the method comprising: S1. Select basic alloying elements and determine various precipitates and intermediate metastable transition phases; S2. Based on multi-scale corrosion integrated calculation, the equivalent atomic positions of the various precipitated phases and intermediate metastable transition phases are determined, and a doping model is constructed to perform Gibbs free energy calculation based on first principles. S3. Determine the precipitated phase structure with optimal hydrogen capture performance based on the parameters of the precipitated phase; the parameters of the precipitated phase include the structure formation energy, hydrogen capture energy, and the probability of the structure's existence. S4. For the optimal precipitate structure, the structural parameters are calculated using first-principles calculations. Then, machine learning is used to construct the interatomic potential function corresponding to the optimal precipitate structure based on the structural parameters. The structural parameters include the energy, force, and stress of each precipitate structure. S5. Based on the optimal hydrogen capture model and interatomic potential function, molecular dynamics simulations of precipitation phase transitions at different temperatures were conducted, and the optimal heat treatment process parameters for the optimal precipitation phase structure were determined.

[0008] Preferably, in step S1, the specific method for determining multiple precipitated phases is as follows: Based on database retrieval, only relevant structures containing selected alloying elements are identified, forming a set of precipitates Φ. The selection method for the set of precipitates Φ is as follows:

[0009] in, , , Represents alloying elements. i , j , k Represents the number of atoms of each element. E f The formation energy of the precipitated phase structure is represented. Represents a doping model based on the original structure. Indicates the average formation energy of the structure; When the formation energy of the precipitated phase is less than 80% of the overall distribution, the precipitated phase is doped to construct the corresponding transition phase.

[0010] Preferably, the doping sites in the structure of the transition phase are determined based on an equivalent site feature matrix M; the equivalent site feature matrix is:

[0011]

[0012]

[0013]

[0014]

[0015]

[0016] Where T, R, and A represent the atom type matrix, distance matrix, and angle matrix from the nearest neighbor to the 12th nearest neighbor atom, respectively. r i(k) , θ i(k)The terms represent the interatomic distance and x-axis angle between atom i and atom k, respectively. Atom k is the nearest neighbor to the 12th nearest neighbor of atom i.

[0017] Preferably, in step S2, the equivalent atomic positions are determined as follows: S21. Calculate the maximum permissible radius. R H :

[0018] Where x represents the gap position coordinate, p i The three-dimensional atomic coordinates representing the interstitial position and its nearest neighbor atoms. r max This represents the maximum atomic radius among the nearest neighbor atoms; S22, when R H When the radius threshold is greater than or equal to the radius threshold, the corresponding position is determined as the equivalent atomic position.

[0019] Preferably, in step S3, the optimal precipitated phase structure is determined as follows: The formation energy of precipitated phase structure was calculated based on the doping model. E f and hydrogen capture energy µ H ; Based on formation energy E f and hydrogen capture energy µ H The computational structure has the possibility P; The structure with the smallest P value is selected as the optimal precipitate structure.

[0020] Preferably, forming energy E f and hydrogen capture energy µ H The calculation method is as follows:

[0021]

[0022] in, E The total energy obtained from first-principles calculations for the precipitated phase. The energy of a single atom that makes up the precipitated phase. n This represents the total number of atoms in the system. and The energy of the precipitated phase is calculated using first principles for both hydrogen-containing and non-hydrogen-containing phases.

[0023] Preferably, the probability P of the structure's existence is calculated as follows: .

[0024] Preferably, in step S4, the interatomic potential function is constructed as follows: S41. Construct the overall expression for the interatomic potential function based on the structural parameters of the optimal precipitated phase structure:

[0025] In the formula, F is a set of multiple basis vectors containing angular features A and distance features R, and n represents the total number of atoms in the system. This represents the number of atoms in the i-th atom; S42. Calculate and determine the equivalent position feature matrix M; S43. Adjust the weights of the structural parameters in the model, calculate the repeatability of the configuration, and determine the configuration with the highest repeatability as the final interatomic potential function.

[0026] Preferably, the repeatability is represented by the feature matrix K:

[0027] in, N It is the total number of atoms. V It represents the structural volume, and T represents the element type. S M is the spatial matrix, M is the equivalent characteristic matrix of each atom in the configuration, and f represents the characteristic matrix function.

[0028] Preferably, in step S5, the precipitation phase transition simulation refers to a Monte Carlo simulation based on molecular dynamics, during which the concentration of locally segregated ions and the radial distribution function are calculated. g (r) is used to determine whether the precipitated phase has been formed by segregation from the matrix; The concentration of locally segregated ions is calculated as follows:

[0029] in, Here, ρ is the local volume, ρ is the elemental density, and r is the stage radius. It is the ratio of the total number of elements N in the system to the total volume V.

[0030] Preferably, the radial distribution function g The calculation method for (r) is as follows:

[0031] Where α is the type of the central atom element, β is the type of the nearest neighbor atom element, r is the atomic distance, and t is the simulation time. Let r represent the smoothing function, σ represent the smoothing width, and r represent the smoothing width. ij This represents the distance between atoms i and j. It is the set of α-type atoms in the enriched region at time t. This represents the total number of α atoms within the local range. This represents the number density of β atoms within the local range, where the local range refers to the range within the radius of the central atom r.

[0032] Secondly, the present invention provides a hydrogen embrittlement resistant structural design system for performing the hydrogen embrittlement resistant structural design method described above, the system comprising: The recommendation module identifies various precipitates and intermediate metastable transition phases based on the selected basic alloying elements. The equivalent atomic position calculation module establishes the equivalent atomic positions of the various precipitated phases and intermediate metastable transition phases based on multi-scale corrosion integrated calculation, constructs a doping model, and performs Gibbs free energy calculation based on first principles. The precipitate screening module determines the precipitate structure with optimal hydrogen capture performance based on the parameters of the precipitate; the parameters of the precipitate include the structure formation energy, hydrogen capture energy, and the probability of the structure's existence. The potential function calculation module calculates the structural parameters of the optimal precipitate structure using first-principles calculations, and then uses machine learning to construct the interatomic potential function corresponding to the optimal precipitate structure based on the structural parameters; the structural parameters include the energy, force, and stress of each precipitate structure; The heat treatment process estimation module, based on the optimal hydrogen capture model and interatomic potential function, conducts molecular dynamics phase transformation simulations at different temperatures and determines the optimal heat treatment process parameters for the optimal precipitated phase structure.

[0033] Preferably, the system may also include a database that stores at least structural data of possible precipitates.

[0034] Thirdly, the present invention also provides a hydrogen embrittlement resistant structure, characterized in that the hydrogen embrittlement resistant structure is designed by the hydrogen embrittlement resistant structure design method described above; The hydrogen embrittlement resistant structure is formed inside the alloy and is a stable or metastable structure with a strong hydrogen capture capability. Its size is 50-180 nm and contains the specific element Cu.

[0035] Fourthly, the present invention also provides an aluminum alloy, wherein the composition of the aluminum alloy, by weight percentage, is: Cu 0.5-2.0 wt.%, Sc 0.05-0.5 wt.%, with the balance being Al and unavoidable impurities; The aluminum alloy possesses the hydrogen embrittlement resistant structure described above.

[0036] Preferably, the ratio of Cu to Sc is less than 2.5.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows: This scheme utilizes multi-scale corrosion integrated calculations to determine the structures of all and potential hydrogen-capturing precipitates within the alloy system. It rapidly constructs high-throughput computational models and equivalent hydrogen-doping models, clarifying the structural type and dispersed distribution of these hydrogen-capturing structures in the aluminum alloy, and quickly establishing heat treatment processes. For the thermodynamic state of transition phases (metastable intermediate phases) that are difficult to define in traditional designs, excessive solution treatment or aging treatment can cause the intragranular precipitates to transform into stable structures, ultimately losing their hydrogen-capturing effect on the aluminum alloy. This scheme implements the calculated alloy heat treatment process, which can optimize the fabrication of novel intragranular dispersed nanoscale precipitates (including metastable structures), thereby achieving strong hydrogen atom capture in the aluminum alloy. This scheme can significantly improve the efficiency of hydrogen embrittlement resistance design, significantly optimize the hydrogen embrittlement resistance of aluminum alloys, and ultimately control and prepare high-strength aluminum alloys with excellent ductility under corrosive environments, providing a new solution for the preparation of corrosion-resistant high-strength aluminum alloys. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the hydrogen embrittlement resistant structural design method of the present invention; Figure 2 This embodiment of the invention describes the potential precipitated phase structure generated by the system based on the determined elements Al / Sc / Cu. Figure 3 This refers to the Cu content threshold value for metastable precipitates determined based on the formation energy in this embodiment of the invention. Figure 4 The dispersed precipitate and its elemental distribution in Embodiment 3 of the present invention; Figure 5 The release rates of hydrogen atoms captured by the alloy matrix at different temperatures after cathode hydrogen charging in Example 3 and Comparative Example 1 of the present invention; Figure 6 This is a comparison of the hydrogen embrittlement sensitivity of Examples 2, 3, and 4, Comparative Example 1 and Comparative Example 2 of the present invention under a simulated seawater 3.5 wt.% NaCl coupled cathode hydrogen-filled environment; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0040] The technical solutions described below in conjunction with the embodiments will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] This invention aims to provide a design scheme for an aluminum alloy structure resistant to hydrogen embrittlement. Based on fundamentally established alloying elements (e.g., Al, Sc, and Cu), and potential alloy structures recommended by a design model, first-principles calculations are used to determine the hydrogen capture energy at different hydrogen atom positions, thus identifying the optimal hydrogen-capturing precipitate structure. Based on molecular dynamics simulations, the heat treatment process is optimized to achieve a corrosion-resistant aluminum alloy with a nanoscale metastable precipitate dispersed within the grains. Under simulated harsh marine corrosion conditions (3.5 wt.% NaCl solution), the elongation after fracture of the aluminum alloy after cathodic hydrogen charging reaches 20%-25%.

[0042] The implementation of this solution will be described in detail below with reference to specific embodiments.

[0043] Example 1 In one embodiment, the present invention provides a method for designing a structure resistant to hydrogen embrittlement. A hydrogen embrittlement structure refers to a dispersed precipitate phase that can be formed within an alloy through a specific heat treatment process, exhibiting a certain degree of structural stability and strong hydrogen atom trapping capability.

[0044] The model constructed in this scheme is based on multi-scale corrosion integrated calculation. The model calculation relies on the first-principles method at the nanoscale for autonomous steady-state analysis of precipitate structure and analysis of hydrogen atom trapping ability.

[0045] The multi-scale corrosion integrated calculation in this embodiment involves automatic diffusion and transformation simulation of precipitated phase structure at the micron scale, including the elemental composition distribution and size of the precipitated phase. The simulation temperature range is 90℃-600℃, thereby directly determining the heat treatment process.

[0046] This embodiment takes the hydrogen embrittlement resistance design problem of aluminum alloys as an example, combined with... Figure 1 As shown, the method of this scheme mainly includes the following key steps: S1. Select the basic alloying elements in the aluminum alloy, and the system will automatically recommend multiple potential precipitates and their intermediate metastable transition phase models. Furthermore, the preferred method for autonomously recommending precipitates is to retrieve relevant structures from a local database, and these structures should contain only the selected alloying elements. , , It does not contain other alloying elements; the specific number of alloying elements selected can be arbitrarily set. In this embodiment, three alloying elements are selected as an example for explanation. In this embodiment, the recommended number of hydrogen capture sites is 1-16. The formula for the set of precipitated phases Φ is as follows:

[0047] In the above formula, , , Represents alloying elements. i , j , k Represents the number of atoms of each element. E f The formation energy of the precipitated phase structure is represented. Represents a doping model based on the original structure. This represents the average formation energy of the structure. When the formation energy of the precipitated phase is lower than 80% of the overall distribution, the model will be automatically considered for doping to construct an intermediate transition phase, thereby expanding the structure set and discovering strong hydrogen-capturing structures that have not been found in conventional experiments.

[0048] In this embodiment, the selection of doping sites in the intermediate metastable transition phase model structure, such as the transition phase and intermediate phase, considers the equivalent position feature matrix M calculated from the type and position information of atoms and their nearest neighbors in the precipitated phase structure. The position information includes distance and angular orientation. The calculation formula for matrix M is as follows:

[0049]

[0050]

[0051]

[0052]

[0053]

[0054] The above formula takes into account the atom type matrix T, the distance matrix R, and the interatomic spacing from the nearest neighbor atom to the 12th nearest neighbor atom. r i(k) Angle matrix A and x-axis angle terms θ i(k) The three together constitute iThe environmental feature encoding of atoms, also known as the environmental feature encoding of defective atoms. In this embodiment, the nearest neighbor range is preferably considered up to the 12th nearest neighbor. However, those skilled in the art should know that the selection of the nearest neighbor range can be more than the 12th nearest neighbor. Expanding the screening of the nearest neighbor range does not affect the execution, implementation and effect of the present invention, and should also be considered as falling within the protection scope of the present invention.

[0055] S2. Based on the equivalent atomic positions rapidly established by multi-scale corrosion integrated calculation, the various precipitated phases and intermediate metastable transition phase models described in step S1 are used to construct defect and surface / interface hydrogen atom doping models, and Gibbs free energy calculations are performed based on first principles, such as calculating formation energy and hydrogen capture energy. In this step, the hydrogen atom doping atoms take into account the characteristic matrix M, tetrahedral (octahedral) interstitial spaces, and the number of hydrogen atoms. In this embodiment, the equivalent position structure of the defects is determined based on the characteristic matrix M to determine whether they are similar. If they are similar, they are discarded to reduce the amount of calculation. The doping index considers the maximum allowable radius. R H The equivalent atomic positions of the doped atoms (i.e., the doping model obtained after doping) are expressed as follows:

[0056]

[0057] In the formula, x is the coordinate of the gap position, p i The three-dimensional atomic coordinates representing the interstitial position and its nearest neighbor atoms. r max It is the maximum atomic radius among the nearest neighbor atoms.

[0058] That is, when When the corresponding position is determined, it is identified as the equivalent atomic position. In this embodiment, 0.65 represents the radius threshold. As those skilled in the art know, this radius threshold can be set based on specific simulation calculation needs, such as 0.62, 0.63, 0.67, etc. Therefore, 0.65 in this embodiment should not be interpreted as a limitation on the scope of protection of this application.

[0059] S3. Determine the precipitate structure with optimal hydrogen capture performance based on parameters such as the formation energy and hydrogen capture energy of the precipitate phase; Formation energy in this step E f Hydrogen capture energy The probability P of the structure's existence is calculated using the following formulas:

[0060]

[0061] In the formula, E The total energy obtained from first-principles calculations for the precipitated phase. The energy of a single atom that makes up the precipitated phase. n This represents the total number of atoms in the system. and The energy of the precipitated phase is calculated using first principles for both hydrogen-containing and non-hydrogen-containing phases.

[0062] First-principles calculations were performed to determine the Gibbs free energy distribution of hydrogen atoms in various vacancy defects within the structure, including the structure formation energy E. f and hydrogen capture energy Its advantageous hydrogen capture energy distribution range is: The hydrogen capture energy ranges from 20 eV / H to 0 eV / H, with lower values ​​being more favorable for hydrogen capture. The structure with the lowest value is considered the optimal precipitating phase structure for hydrogen capture. However, considering only the hydrogen capture energy might prevent the structure from precipitating from the matrix. Therefore, this embodiment considers both the structure formation energy (selectivity coefficient 0~1) and the hydrogen capture energy (selectivity coefficient 1~0), with the sum of the two selection coefficients being 1. Combining these two factors forms the structure existence probability P:

[0063] The selection coefficient is preferably chosen to be within the above range in order to avoid situations where the hydrogen capture capacity is weak or the structure cannot be formed.

[0064] In this embodiment, the structure with the smallest P value is selected as the optimal precipitation phase structure, which is also the optimal hydrogen capture model.

[0065] S4. The system calculates the structural parameters such as energy, force, and stress of each precipitated phase structure using first-principles calculations, and uses these structural parameters and machine learning methods such as active learning to construct the interatomic potential function corresponding to the optimal precipitated phase structure. In this step, the interatomic potential function constructed based on active learning refers to the energy-position function describing atoms under complex environmental conditions. In this embodiment, the overall expression of the interatomic potential function is as follows:

[0066] In the formula, F is a set of multiple basis vectors containing angular features A and distance features R, and n represents the total number of atoms in the system. This represents the number of atoms in the i-th atom.

[0067] In this embodiment, the specific construction of the interatomic potential function can be carried out using various active learning and other machine learning models in the field, which will not be elaborated here.

[0068] Preferably, in the training process of inter-atomic potential functions, the key to efficiently training inter-atomic potential functions is to encompass the most atomic environmental parameter information based on the minimum configuration sample size. Obtaining multiple atomic position, energy, and force information through high-throughput computation, while providing numerous repetitive information between samples, reduces machine learning training efficiency and wastes computational resources. In this embodiment, the optimization method is to simplify the structure by constructing an equivalent position feature matrix M, and utilize the model repetition feature matrix K. By adjusting matrix M, the atomic position, energy, and force information are adjusted, and configurations with high repetition are selected, thereby shuffling the model order, reducing erroneous models, and improving model training efficiency. Its model repetition (independent) feature matrix... K The expression is as follows:

[0069] in N V is the total number of atoms, V is the structural volume, and T is the element type. S M is the spatial matrix, M is the equivalent positional characteristic matrix of each atom in the configuration, and f represents the characteristic matrix function.

[0070] Establishing a high-precision interatomic potential function requires adjusting information such as force weights (ranging from 0 to 0.1), energy weights (ranging from 0 to 1), stress weights (ranging from 0 to 0.005), and model equivalence, in order to obtain a high-precision interatomic potential function.

[0071] S5. Based on the optimal hydrogen capture model obtained in step S3 and the interatomic potential function obtained in step S4, conduct molecular dynamics phase transition simulations at different temperatures, and directly determine the optimal heat treatment process parameters for achieving the high hydrogen capture phase structure (i.e., the selected optimal phase structure) using a computer intelligent system.

[0072] In this embodiment, the precipitation phase transformation simulation refers to a Monte Carlo simulation based on molecular dynamics. The system constructs the parent material (elements) according to the basic alloy system. ), and randomly doped with different amounts of alloying elements ( and (etc.), the maximum model size distribution in a single direction is 10 to 500 nanometers, the Monte Carlo chemical potential of the involved elements can be obtained from step S2, the exchange frequency is one exchange every 1000 to 10000 steps, and the number of atoms exchanged each time is set to 10% to 50% of the total number of atoms. Its simulation temperature range is 90 degrees Celsius to 600 degrees Celsius.

[0073] In the molecular dynamics simulation, the concentration of locally segregated ions will be calculated. ρ and radial distribution function g(r) Two key indicators are used to determine whether the precipitated phase has been formed by segregation from the matrix; secondly, it is determined which structure the structural phase formed at different temperatures is the one identified in step S1, and whether it is the most favorable structure against hydrogen embrittlement, thus obtaining the temperature corresponding to the most favorable structure against hydrogen embrittlement. In this embodiment, the g(r) value of the hydrogen-capturing structure is compared in real time. The more hydrogen-capturing structures are generated, the better the corresponding process (including the corresponding temperature, etc.). The calculation of the g(r) value will be introduced later.

[0074] The concentration of locally segregated ions ρ Using a specific alloy atom as the core, cutoff radius r The maximum model size, with a numerical range of 10% to 50%, is calculated as follows:

[0075]

[0076]

[0077] Local segregation ion concentration ρ Much higher than average concentration At that temperature, it is determined that the alloy has gradually begun to form a precipitated phase. Based on the optimal hydrogen-trapping structure g(r) calculated in S3, the real-time calculated concentration of segregated ions ρ is much higher than the average concentration. area g (r), thereby collaboratively determining whether the optimal hydrogen-capturing structure designed in S3 has been generated, and clarifying when the optimal hydrogen-capturing structure in step S3 appeared.

[0078] Furthermore, in this embodiment, to improve the recognition sensitivity of target data, the radial distribution function g(r) index is calculated as follows: enriched regions are screened based on the local segregated ion concentration, and then the element-resolved RDF is calculated only within these regions, thereby setting the calculation method for g(r). This method can effectively avoid the dilution of local precipitated phase structure characteristics by global averaging, and improve the recognition sensitivity of segregated clusters, precipitated phase initiation, and hydrogen-capturing structure formation. Simultaneously, the formula introduces the time variable t, which can be used to track the evolution process of local enriched structures in real time.

[0079] Among the improvements g (r) is calculated as follows:

[0080] Where α represents the type of the central atom element, β represents the type of the nearest neighbor atom element, r represents the atomic distance, and t represents the simulation time. Let r represent the smoothing function, σ represent the smoothing width, and r represent the smoothing width. ij This represents the distance between atoms i and j. This represents the set of α-type atoms in the enriched region at simulation time t. This represents the total number of α atoms within the local range. This represents the number density of β atoms within the local range, where the local range refers to the range within the radius of the central atom r.

[0081] Example 2 In this embodiment, the actual application process of this solution is illustrated using Al, Sc, and Cu elements as examples.

[0082] Based on the determined elements Al, Sc, and Cu, the model recommends the following precipitate structures, including but not limited to: Al3Cu, Al2Cu, AlCu, AlCu2, AlCu3, Al4Cu9, Al3Cu2, Al3Sc, Al2Sc, AlSc, AlSc2, AlSc3, and AlSc4. E f >0 is excluded), AlCu2Sc, Al2CuSc, AlCuSc, and their formation energies are -0.103 eV / atom, -0.165 eV / atom, -0.242 eV / atom, -0.202 eV / atom, -0.233 eV / atom, -0.195 eV / atom, -0.479 eV / atom, -0.531 eV / atom, -0.466 eV / atom, -0.366 eV / atom, -0.289 eV / atom, 0.505 eV / atom, -0.429 eV / atom, -0.401 eV / atom, and -0.434 eV / atom, respectively.

[0083] Since the formation energy of the Al3Sc precipitate structure is lower than 80% of the total formation energy, configuration set condition 2 is triggered, thus enabling the model to construct doped atoms. The equivalent position matrix of Al atoms in the Al3Sc configuration is calculated as follows:

[0084]

[0085]

[0086]

[0087] Therefore, it can be known that the Al atom position is a position with a different characteristic matrix M from other positions, and thus it was discovered as an independent site that can be doped with hydrogen atoms. First-principles calculations were performed in high throughput to obtain parameters such as formation energy and hydrogen capture energy.

[0088] For the equivalent positional feature M of the tetrahedral interstitial sites in Al3Sc tet As shown in the following formula,

[0089] Based on the formation energy and hydrogen capture energy, and through systematic selection, the selection coefficients show that the formation energy ranges from 0.2 to 0.8, while the hydrogen capture energy ranges from 0.8 to 0.2. The combined coefficients thus determine the optimal hydrogen embrittlement resistant structure type and forming possibility of the aluminum alloy under this condition.

[0090] Calculated ScAl2Cu -OCT ScAl2Cu -TET2 ,ScAl 3-Al ,ScAl 3-Sc ,ScAl 3-BRG ,ScAl 3-OCT2 ,ScAl 3-TET2 ,ScAlCu 2-Cu ,ScAlCu 2-Sc ,ScAlCu 2-BRG ,ScAlCu 2-BRG2 ,ScAlCu 2-OCT1 ,ScAlCu 2-TET ,ScAlCu 2-TET2 ,ScCu 3-Cu ,ScCu 3-Sc ,ScCu 3-BRG ,ScCu 3-OCT2 ,ScCu 3-TET The hydrogen capture energies are respectively 0.8059eV / H, -0.2858 eV / H, 0.3036 eV / H, 0.7021 eV / H, 0.0334 eV / H, 0.2435 eV / H, 0.0279 eV / H, -0.7348 eV / H, 0.4132 eV / H, -0.5430 eV / H, -0.8434 eV / H, -0.5731 eV / H, -0.8482 eV / H, -0.8435 eV / H, -1.0191 eV / H, 0.7930 eV / H, -4.2721 eV / H, 0.0585 eV / H, -3.0190 eV / H. Therefore, it can be observed that the overall hydrogen-capturing ability of the precipitated phase structure increases with the increase of Cu element. However, when considering the formation energy, it is found that the formation energy of Cu3Sc is much lower than that of AlCu2Sc, indicating a weak probability of this phase precipitating within the matrix. Setting the selection coefficients to 0.8 and 0.2 respectively, the probability P of its existence is calculated as follows:

[0091]

[0092] Therefore, it is generally determined that the AlCu2Sc structure has superior formation ability and hydrogen capture ability. Figure 2 The system autonomously defines the potential hydrogen-capturing precipitation phase structures in some aluminum alloys, including Al3Cu, Al2Cu, AlCu2, AlCu3, Al4Cu9, Al3Cu2, Al3Sc, Al2Sc, AlSc, AlSc2, AlSc3, AlSc4, AlCu2Sc, Al2CuSc, and AlCuSc, with AlCuSc being the preferred structure.

[0093] Subsequently, indices such as interatomic interaction forces, structural energy, and stress are extracted, and interatomic potential functions for molecular dynamics simulations are autonomously constructed through training. The energy accuracy includes, but is not limited to, any one or any two of the following: 1 meV / atom, 2 meV / atom, 3 meV / atom, 4 meV / atom, 5 meV / atom, 6 meV / atom, 7 meV / atom, 8 meV / atom, 9 meV / atom, 10 meV / atom. The first-principles calculation energy thresholds for the supplementary configuration include, but are not limited to, any one or any two of the following: 2000 eV, 3000 eV, 4000 eV, 5000 eV, 6000 eV, 7000 eV, 8000 eV. To ensure computational efficiency, the molecular dynamics heat treatment simulation configuration size parameters include, but are not limited to, any one or any two of the following: 10 nm, 15 nm, 20 nm, 25 nm, 40 nm, and 80 nm; the simulation diffusion exchange parameters may include, but are not limited to, 50, 100, 150, and 200; and the simulation heat treatment temperature may include, but is not limited to, 90℃, 100℃, 110℃, 120℃, 130℃, 150℃, 180℃, 200℃, 400℃, 410℃, 420℃, 430℃, 450℃, 460℃, 470℃, 480℃, 490℃, 500℃, 510℃, 520℃, 530℃, 540℃, 550℃, and 600℃.

[0094] During the simulation, the local ion concentration of solute atoms Sc within the stage distances around each element in real time can include, but is not limited to, 0.2 nm, 0.3 nm, 0.5 nm, 1 nm, 1.2 nm, 1.5 nm, 1.8 nm, 2 nm, 2.5 nm, 3 nm, 3.5 nm, 4 nm, 4.5 nm, and 5 nm. As the simulation progressed, the proportion of precipitated phases increased to 0.192, 0.252, 0.27, 0.281, 0.348, 0.301, 0.221, 0.333, 0.311, 0.253, 0.382, 0.237, 0.235, 0.259, 0.352, 0.275, 0.312, 0.359, 0.333, 0.484, 0.375, 0.324, 0.344, 0.452, 0.29, 0.273, and 0.433. 0.419, 0.357, 0.429, 0.483, 0.333, 0.4, 0.379, 0.259, 0.323, 0.273, 0.407, 0.333, 0.304, 0.4, 0.529, 0.467, 0.75, 0.533, 0.533, 0.5, 0.583, 0.385, 0.615, 0.538, 0.545, 0.667, 0.556, 0.875, 0.75, 0.714, 0.857.

[0095] Monitoring the structure of high-density regions during molecular dynamics simulations g (r) value, and compare it with the AlCu2Sc structure g Comparing the g(r) values, the AlCu2Sc structure shows peak values ​​of 60.9598 (Cu-Al) and 30.4799 (Cu-Cu) at 2.74 Å, and peak values ​​of 46.0749 (Cu-Cu) and 23.0375 (Al-Al) at 3.86 Å. At this point, by comparing the g(r) values ​​in the high-ρ precipitate region, we can determine whether the peak values ​​of the structures correspond to each other, thus assessing whether the hydrogen capture capacity of the precipitate phase meets the design requirements.

[0096] In summary, the actual calculation process in this embodiment is as follows: Three basic elements, Al, Cu, and Sc, were selected, and intelligent recommendations were made for basic precipitated phase structures including Al3Cu, Al2Cu, AlCu, AlCu2, AlCu3, Al4Cu9, Al3Cu2, Al3Sc, Al2Sc, AlSc, AlSc2, AlSc3, AlSc4, AlCu2Sc, Al2CuSc, and AlCuSc. Subsequently, the hydrogen capture energy and formation energy were calculated, determining that the hydrogen capture energy of AlCu2Sc is -0.5675 eV / H, and the formation energy is 0.363 eV / atom. The overall probability of existence, P, is -0.414, making it the optimal hydrogen capture structure. A molecular dynamics potential function was constructed, with an energy error of only 7 meV / atom. Based on this function, a molecular dynamics Monte Carlo simulation was performed, clarifying the heat treatment process as solution treatment at 470℃ for 4 h followed by aging treatment at 120℃ for 6 h.

[0097] Example 3 Example 3 is identical to Example 2 in terms of elements, optimal precipitated phase, and interatomic potential function. The difference lies in that the system recommends the optimal heat treatment process, i.e.: Solution treatment at 500℃ for 4 h followed by aging treatment at 120℃ for 6 h.

[0098] Figure 4 The microstructure of Example 3 is shown; it can be seen that the present invention achieves the diffuse distribution of spherical metastable nanoscale precipitates inside the aluminum alloy grains, with a size distribution range of 50-180 nm; Sc atoms are aggregated, and Cu is also present in this region.

[0099] Example 4 In molecular dynamics simulations, the temperature and calculation time can be freely set. Molecular dynamics simulations can be performed at different temperatures and times, and the g(r) values ​​can be compared in real time. The more optimal precipitated phase structures generated, the better the corresponding process can be determined.

[0100] This embodiment 4 is identical to embodiment 3 in terms of elements, optimal precipitated phase, and interatomic potential function. The difference lies in the set temperature and calculation time. The recommended heat treatment process after calculation is as follows: Solution treatment at 530℃ for 4 h followed by aging treatment at 120℃ for 6 h.

[0101] Comparative Example 1 Comparative Example 1 and Example 2 are completely identical in terms of elements, optimal precipitated phase, and interatomic potential function, the difference being that no aging heat treatment was performed.

[0102] Comparative Example 2 Comparative Example 2 presents the slow strain rate tensile test data and hydrogen embrittlement susceptibility of 7N01 aluminum alloy under hydrogen charging in a 3.5 wt.% NaCl corrosive environment, which are currently widely reported. The difference is that this alloy contains 4.38 wt.% Zn and 1.114 wt.% Mg.

[0103] Figure 3 The mechanical tensile properties of Examples 2, 3, 4 and Comparative Example 1 under slow strain rate mechanical tensile properties in simulated seawater with a coupled cathode of 3.5 wt.% NaCl are compared. It can be seen that under the specified Cu / Sc elemental ratio, the heat treatment process determined by multi-scale corrosion integrated calculation results in a significant improvement in strength and plasticity of Examples 2, 3, and 4 compared to Comparative Example 1. Even under severe corrosion and hydrogen charging conditions, the elongation of the samples of the present invention reaches 20%-25%.

[0104] Figure 5 For Example 3 and Comparative Example 1, in a 3.5 wt.% NaCl environment, at 1 mA / cm 2 The hydrogen atom release rate after charging with hydrogen at a current density for 24 hours shows that Example 3 has a large number of vacancy defects, and these sites have a very strong hydrogen-capturing ability. When Example 3 is heated to above 400°C, the strongly captured hydrogen atoms begin to be released in large quantities, which proves the high hydrogen capture efficiency of the metastable precipitated phase structure designed in this invention, as well as the scale of hydrogen capture after its dispersion distribution.

[0105] Figure 6 The results show the hydrogen embrittlement susceptibility of Examples 2, 3, 4, Comparative Example 1, and Comparative Example 2. It can be seen that the hydrogen embrittlement susceptibility of Comparative Example 1, without the application of a multi-scale corrosion integrated calculation design heat treatment process, reached 0.70. However, the hydrogen embrittlement susceptibility of Examples 2, 3, and 4, after employing a specific heat treatment process, decreased significantly, specifically 0.34 for Example 2, 0.15 for Example 3, and 0.36 for Example 4. Comparative Example 2 is a 7N01 aluminum alloy used in high-speed rail trains, whose hydrogen embrittlement susceptibility under cathodic hydrogen charging conditions is 0.43, significantly higher than that of the aluminum alloy of this invention. The hydrogen embrittlement susceptibility of Example 3 prepared by this invention decreased by 78.6%.

[0106] In summary, the hydrogen embrittlement resistant design model of this invention can significantly improve the hydrogen embrittlement resistance of aluminum alloys, quickly realize the designed metastable hydrogen capture structure, and achieve good plasticity and low hydrogen embrittlement sensitivity under harsh corrosive environments.

[0107] Example 5 In yet another embodiment, the solution of the present invention can also be implemented by a hydrogen embrittlement resistant structural design system. This system is capable of performing the hydrogen embrittlement resistant structural design method as described in Embodiment 1, and includes: The recommendation module identifies various precipitates and intermediate metastable transition phases based on the selected basic alloying elements. The equivalent atomic position calculation module establishes the equivalent atomic positions of the various precipitated phases and intermediate metastable transition phases based on multi-scale corrosion integrated calculation, constructs a doping model, and performs Gibbs free energy calculation based on first principles. The precipitate screening module determines the precipitate structure with optimal hydrogen capture performance based on the parameters of the precipitate; the parameters of the precipitate include the structure formation energy, hydrogen capture energy, and the probability of the structure's existence. The potential function calculation module calculates the structural parameters of the optimal precipitate structure using first-principles calculations, and then uses machine learning to construct the interatomic potential function corresponding to the optimal precipitate structure based on the structural parameters; the structural parameters include the energy, force, and stress of each precipitate structure; The heat treatment process estimation module, based on the optimal hydrogen capture model and interatomic potential function, conducts molecular dynamics phase transformation simulations at different temperatures and determines the optimal heat treatment process parameters for the optimal precipitated phase structure.

[0108] Preferably, the system may also include a database that stores at least structural data of possible precipitates.

[0109] Furthermore, the present invention can also be implemented by an electronic device or a computer-readable storage medium, which, when running, or when being read and executed by a computer device, can execute instructions therein to implement the hydrogen embrittlement resistant structural design method as described in Example 1.

[0110] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the contents of the present invention under the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.

Claims

1. A method for designing a structure resistant to hydrogen embrittlement, characterized in that, The method includes: S1. Select basic alloying elements and determine various precipitates and intermediate metastable transition phases; S2. Based on multi-scale corrosion integrated calculation, the equivalent atomic positions of the various precipitated phases and intermediate metastable transition phases are determined, and a doping model is constructed to perform Gibbs free energy calculation based on first principles. S3. Determine the precipitated phase structure with optimal hydrogen capture performance based on the parameters of the precipitated phase; the parameters of the precipitated phase include the structure formation energy, hydrogen capture energy, and the probability of the structure's existence. S4. For the optimal precipitate structure, the structural parameters are calculated using first-principles calculations. Then, machine learning is used to construct the interatomic potential function corresponding to the optimal precipitate structure based on the structural parameters. The structural parameters include the energy, force, and stress of each precipitate structure. S5. Based on the optimal hydrogen capture model and interatomic potential function, molecular dynamics simulations of precipitation phase transitions at different temperatures were conducted, and the optimal heat treatment process parameters for the optimal precipitation phase structure were determined.

2. The method according to claim 1, characterized in that, In S1, the specific method for determining multiple precipitated phases is as follows: Based on database retrieval, only relevant structures containing selected alloying elements are identified, forming a set of precipitates Φ. The selection method for the set of precipitates Φ is as follows: in, , , Represents alloying elements. i , j , k Represents the number of atoms of each element. E f The formation energy of the precipitated phase structure is represented. Represents a doping model based on the original structure. Indicates the average formation energy of the structure; When the formation energy of the precipitated phase is less than 80% of the overall distribution, the precipitated phase is doped to construct the corresponding transition phase.

3. The method according to claim 2, characterized in that, The doping sites in the structure of the transition phase are determined based on the equivalent site feature matrix M; the equivalent site feature matrix is: Where T, R, and A represent the atom type matrix, distance matrix, and angle matrix from the nearest neighbor to the 12th nearest neighbor atom, respectively. r i(k) , θ i(k) The terms represent the interatomic distance and x-axis angle between atom i and atom k, respectively. Atom k is the nearest neighbor to the 12th nearest neighbor of atom i.

4. The method according to claim 1, characterized in that, In S2, the equivalent atom positions are determined as follows: S21. Calculate the maximum permissible radius. R H : Where x represents the gap position coordinate, p i The three-dimensional atomic coordinates representing the interstitial position and its nearest neighbor atoms. r max This represents the maximum atomic radius among the nearest neighbor atoms; S22, when R H When the radius threshold is greater than or equal to the radius threshold, the corresponding position is determined as the equivalent atomic position.

5. The method according to claim 1, characterized in that, In S3, the optimal precipitated phase structure is determined as follows: The formation energy of precipitated phase structure was calculated based on the doping model. E f and hydrogen capture energy µ H ; Based on formation energy E f and hydrogen capture energy µ H The computational structure has the possibility P; The structure with the smallest P value is selected as the optimal precipitate structure.

6. The method according to claim 1, characterized in that, In S4, the interatomic potential function is constructed as follows: S41. Construct the overall expression for the interatomic potential function based on the structural parameters of the optimal precipitated phase structure: In the formula, F is a set of multiple basis vectors containing angular features A and distance features R, and n represents the total number of atoms in the system. This represents the number of atoms in the i-th atom; S42. Calculate and determine the equivalent position feature matrix M; S43. Adjust the weights of the structural parameters in the model, calculate the repeatability of the configuration, and determine the configuration with the highest repeatability as the final interatomic potential function.

7. The method according to claim 1, characterized in that, In S5, the precipitation phase transition simulation refers to a Monte Carlo simulation based on molecular dynamics, during which the concentration of locally segregated ions and the radial distribution function are calculated. g (r) is used to determine whether the precipitated phase has been formed by segregation from the matrix; The concentration of locally segregated ions is calculated as follows: in, Here, ρ is the local volume, ρ is the elemental density, and r is the stage radius. It is the ratio of the total number of elements N in the system to the total volume V; radial distribution function g The calculation method for (r) is as follows: Where α represents the type of the central atom element, β represents the type of the nearest neighbor atom element, r represents the atomic distance, and t represents the simulation time. Let r represent the smoothing function, σ represent the smoothing width, and r represent the smoothing width. ij This represents the distance between atoms i and j. This represents the set of α-type atoms in the enriched region at simulation time t. This represents the total number of α atoms within the local range. This represents the number density of β atoms within the local range, where the local range refers to the range within the radius of the central atom r.

8. A hydrogen embrittlement resistant structural design system, characterized in that, The system is used to perform the hydrogen embrittlement resistant structural design method as described in any one of claims 1-7, the system comprising: The recommendation module identifies various precipitates and intermediate metastable transition phases based on the selected basic alloying elements. The equivalent atomic position calculation module establishes the equivalent atomic positions of the various precipitated phases and intermediate metastable transition phases based on multi-scale corrosion integrated calculation, constructs a doping model, and performs Gibbs free energy calculation based on first principles. The precipitate screening module determines the precipitate structure with optimal hydrogen capture performance based on the parameters of the precipitate; the parameters of the precipitate include the structure formation energy, hydrogen capture energy, and the probability of the structure's existence. The potential function calculation module calculates the structural parameters of the optimal precipitate structure using first-principles calculations, and then uses machine learning to construct the interatomic potential function corresponding to the optimal precipitate structure based on the structural parameters; the structural parameters include the energy, force, and stress of each precipitate structure; The heat treatment process estimation module, based on the optimal hydrogen capture model and interatomic potential function, conducts molecular dynamics phase transformation simulations at different temperatures and determines the optimal heat treatment process parameters for the optimal precipitated phase structure.

9. A hydrogen embrittlement resistant structure, characterized in that, The hydrogen embrittlement resistant structure is designed by any of the methods described in claims 1-7; The hydrogen embrittlement resistant structure is formed inside the alloy and is a stable or metastable structure with a strong hydrogen capture capability. Its size is 50-180 nm and contains the specific element Cu.

10. An aluminum alloy, characterized in that, The aluminum alloy has the following composition by weight percentage: Cu 0.5-2.0 wt.%, Sc 0.05-0.5 wt.%, with the balance being Al and unavoidable impurities; The aluminum alloy has the hydrogen embrittlement resistant structure as described in claim 9.

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