A method, system, device and storage medium for calculating metal hardness

Abstract

The present invention discloses a method, system, device and storage medium for calculating metal hardness, comprising constructing an initial defect target model, optimizing the initial defect target model according to a preset initial dislocation value and a measured dislocation density to obtain a first target model, calculating an ion injection speed according to the mass of ions to be injected and a preset injection energy, and constructing a second target model according to the ion injection speed and the first target model; calculating the hardness of a metal material after ion injection from a microscopic perspective, finally applying pressure to the second target model through a preset pressure head, and calculating a first actual injection depth during the injection process and a first Z-direction load component of the preset pressure head; and calculating the hardness of the metal to be simulated after ion injection according to the first actual injection depth and the first Z-direction load component, thereby improving the optimization efficiency of process parameters, reducing the complexity of operation, and achieving the purpose of predicting the influence of ion injection on the hardness of parts.

Description

Technical Field

[0001] The present invention relates to the technical field related to calculation of metal hardness, and in particular to a calculation method, system, device and storage medium for metal hardness. Background Art

[0002] As one of the important properties of materials, the improvement of hardness will significantly enhance the strength of materials, improve the wear resistance of parts, and increase fatigue life. The ion implantation process uses high-energy ions to bombard the surface of parts. Through solid solution strengthening, amorphous strengthening and dispersion strengthening mechanisms, it can improve the surface properties of parts. It is widely used due to its low processing temperature and small impact on the surface accuracy of parts.

[0003] At present, the hardness of the sample before and after ion implantation is mainly measured by microhardness tester or nanoindenter to measure the strengthening effect of ion implantation. However, this method is cumbersome and has a long research cycle, and is not conducive to observing the influence of ion implantation process parameters on hardness and the strengthening mechanism. Summary of the invention

[0004] The present invention aims to at least solve the technical problems existing in the prior art. To this end, the present invention proposes a calculation method, system, device and storage medium for metal hardness, which can predict the influence of ion implantation on the hardness of parts, improve the optimization efficiency of process parameters and reduce the complexity of operation.

[0005] A first aspect of the present invention provides a method for calculating metal hardness, comprising the following steps:

[0006] Obtaining the measured dislocation density of the metal to be simulated;

[0007] Constructing an initial defect target model, optimizing the initial defect target model according to a preset initial dislocation value and the measured dislocation density, to obtain a first target model;

[0008] Calculating an ion implantation speed according to the mass of the ions to be implanted and a preset implantation energy, and constructing a second target model according to the ion implantation speed and the first target model;

[0009] Applying pressure to the second target model by a preset pressure head, and calculating a first actual penetration depth and a first Z-direction load component of the preset pressure head during the pressure application process;

[0010] The hardness of the metal to be simulated after ion implantation is calculated according to the first actual indentation depth and the first Z-direction load component.

[0011] The control method according to the embodiment of the present invention has at least the following beneficial effects:

[0012] The method first constructs an initial defect target model, optimizes the initial defect target model according to a preset initial dislocation value and a measured dislocation density, obtains a first target model, calculates an ion injection speed according to the mass of the ions to be injected and the preset injection energy, and constructs a second target model according to the ion injection speed and the first target model; calculates the hardness of the metal material after ion injection from a microscopic perspective, and finally applies pressure to the second target model through a preset pressure head, and calculates a first actual injection depth during the injection process and a first Z-direction load component of the preset pressure head; calculates the hardness of the metal to be simulated after ion injection according to the first actual injection depth and the first Z-direction load component, thereby improving the optimization efficiency of process parameters, reducing the complexity of operation, and achieving the purpose of predicting the influence of ion injection on the hardness of parts.

[0013] According to some embodiments of the present invention, the method for calculating the metal hardness further includes:

[0014] Applying pressure to the first target model by a preset pressure head, and calculating a second actual penetration depth and a second Z-direction load component of the preset pressure head during the pressure application process;

[0015] The hardness of the metal to be simulated before ion implantation is calculated according to the second actual indentation depth and the second Z-direction load component.

[0016] According to some embodiments of the present invention, the step of optimizing the initial defect target model according to the preset initial dislocation value and the measured dislocation density to obtain the first target model includes:

[0017] According to the preset initial dislocation value, the initial defect target model is optimized by using the Minimize command of Lammps software and the NVT or NPT ensemble to obtain a first defect target model with minimized system potential energy;

[0018] Calculating the dislocation density of the first target plate of the first defective target model by Ovito software;

[0019] Calculating a dislocation density deviation value according to the dislocation density of the first target plate and the measured dislocation density;

[0020] Optimizing the preset initial dislocation value according to the dislocation density deviation value to obtain a first dislocation value;

[0021] The initial defect target model is reversely optimized according to the first dislocation value to obtain the optimized initial defect target model, and the optimized initial defect target model is used as the first target model.

[0022] According to some embodiments of the present invention, the step of calculating the ion implantation rate according to the mass of the ions to be implanted and the preset implantation energy, and constructing the second target model according to the ion implantation rate and the first target model includes:

[0023] Dividing the first target model from bottom to top into a boundary layer, a constant temperature layer and a Newtonian layer according to a preset lattice constant;

[0024] The ion implantation rate is calculated according to the mass of the ions to be implanted and the preset implantation energy using the following formula:

[0025]

[0026] Wherein, v is the ion injection velocity, m is the mass of the ions to be injected, and E is the preset injection energy;

[0027] The ions to be implanted are implanted into the Newtonian layer of the first target model according to the ion implantation speed to obtain the second target model.

[0028] According to some embodiments of the present invention, applying pressure to the second target model by a preset pressure head, and calculating a first actual penetration depth during the pressure application process and a first Z-direction load component of the preset pressure head, comprises:

[0029] Applying pressure to the second target model by a preset pressure head at a preset speed;

[0030] Acquire the three-dimensional coordinates of each ion during the pressure application process, and calculate the first Z-direction load component of the preset pressure head during the pressure application process according to the three-dimensional coordinates of each ion and the preset force constant;

[0031] Obtaining the Z coordinate of the preset pressure head when pressure is to be applied;

[0032] The Z coordinate of the ion from the center of the pressure head is calculated using the following formula according to the Z coordinate of the preset pressure head when pressure is applied:

[0033] Z=R s -0.4t

[0034] Where Z is the Z coordinate of the ion from the center of the pressure head, R s is the Z coordinate of the preset pressure head when pressure is applied, and t is the loading time;

[0035] Screening all ions whose Z coordinates from the center of the indenter are greater than R+a / 2 to obtain screened ions, wherein R is the indenter radius and a is a preset lattice constant;

[0036] Finding the minimum z coordinate of the screened ions;

[0037] The difference between the Z coordinate of the preset pressure head when pressure is to be applied and the minimum Z coordinate of the screened ions is calculated to obtain the first actual penetration depth.

[0038] According to some embodiments of the present invention, calculating the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component includes:

[0039] Obtaining the residual depth value of the metal to be simulated after unloading;

[0040] According to the first Z-direction load component and the first actual penetration depth, the following formula is used to perform data fitting to obtain a first fitting parameter and a second fitting parameter:

[0041] P=P0(hh f ) m

[0042] Where P is the first Z-axis load component, h is the first actual penetration depth, and h f is the residual depth value after unloading, P0 is the first fitting parameter, and m is the second fitting parameter;

[0043] The hardness of the metal to be simulated after ion implantation is calculated using the following formula according to the first fitting parameter and the second fitting parameter:

[0044] S=dP / dh

[0045] h c =h max -εP max / S

[0046]

[0047]

[0048] Where S is the unloading stiffness, h c is the contact depth, ε is the preset indenter shape coefficient value, h max is the maximum value of the first actual pressing depth, P max is the maximum value of the first Z-direction load component, A c is the hardness parameter value, R is the radius of the preset indenter, and H is the hardness of the metal to be simulated after ion implantation.

[0049] According to some embodiments of the present invention, obtaining the measured dislocation density of the metal to be simulated includes:

[0050] The measured dislocation density is obtained by measuring the dislocation density at a preset depth of the metal to be simulated by a backscattered electron diffraction method or a transmission electron microscope test method.

[0051] A second aspect of the present invention provides a system for calculating metal hardness, the system comprising:

[0052] A data acquisition module, used to obtain the measured dislocation density of the metal to be simulated;

[0053] A first target model building module is used to build an initial defect target model, optimize the initial defect target model according to a preset initial dislocation value and the measured dislocation density, and obtain a first target model;

[0054] A second target model building module, used for calculating the ion injection speed according to the mass of the ions to be injected and the preset injection energy, and building a second target model according to the ion injection speed and the first target model;

[0055] A pressing depth and load component calculation module, used to apply pressure to the second target model through a preset pressing head, and calculate a first actual pressing depth during the pressing process and a first Z-direction load component of the preset pressing head;

[0056] A hardness calculation module is used to calculate the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component.

[0057] The system constructs an initial defect target model, optimizes the initial defect target model according to a preset initial dislocation value and a measured dislocation density, obtains a first target model, calculates the ion injection speed according to the mass of the ions to be injected and the preset injection energy, and constructs a second target model according to the ion injection speed and the first target model; calculates the hardness of the metal material after ion injection from a microscopic perspective, and finally applies pressure to the second target model through a preset pressure head, and calculates a first actual injection depth during the injection process and a first Z-direction load component of the preset pressure head; calculates the hardness of the metal to be simulated after ion injection according to the first actual injection depth and the first Z-direction load component, thereby improving the optimization efficiency of process parameters, reducing the complexity of operations, and achieving the purpose of predicting the influence of ion injection on the hardness of parts.

[0058] According to a third aspect of the present invention, there is provided an electronic device for calculating metal hardness, comprising at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions executable by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute the above-mentioned method for calculating metal hardness.

[0059] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned method for calculating metal hardness.

[0060] It should be noted that the beneficial effects between the second to fourth aspects of the present invention and the prior art are the same as the beneficial effects between the above-mentioned metal hardness calculation system and the prior art, and will not be described in detail here.

[0061] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0063] Figure 1 is a flow chart of a method for calculating metal hardness according to an embodiment of the present invention;

[0064] Figure 2 It is a schematic diagram of target plate size and layering of a method for calculating metal hardness provided by an embodiment of the present invention;

[0065] Figure 3 is a schematic diagram of initial defect distribution of a method for calculating metal hardness provided by an embodiment of the present invention;

[0066] Figure 4 It is a schematic diagram of the relationship between the actual indentation depth and the loading time of a method for calculating the metal hardness provided by an embodiment of the present invention;

[0067] Figure 5 It is a schematic diagram of the relationship between load and penetration depth in a method for calculating metal hardness provided by an embodiment of the present invention;

[0068] Figure 6 The figure is a schematic diagram of the structure of a metal hardness calculation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0070] In the description of the present invention, if there is a description of first, second, etc., it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0071] In the description of the present invention, it should be understood that descriptions involving orientation, such as orientation or positional relationship indicated as up, down, etc., are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0072] In the description of the present invention, it should be noted that, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific content of the technical solution.

[0073] As one of the important properties of materials, the improvement of hardness will significantly enhance the strength of materials, improve the wear resistance of parts, and increase fatigue life. The ion implantation process uses high-energy ions to bombard the surface of parts. Through solid solution strengthening, amorphous strengthening and dispersion strengthening mechanisms, it can improve the surface properties of parts. It is widely used due to its low processing temperature and small impact on the surface accuracy of parts.

[0074] At present, the hardness of the sample before and after ion implantation is mainly measured by microhardness tester or nanoindenter to measure the strengthening effect of ion implantation. However, this method is cumbersome and has a long research cycle, and is not conducive to observing the influence of ion implantation process parameters on hardness and the strengthening mechanism.

[0075] In order to solve the above technical defects, refer to Figure 1 The present invention provides a method for calculating metal hardness, comprising:

[0076] Step S101, obtaining the measured dislocation density of the metal to be simulated;

[0077] Step S102, constructing an initial defect target model, optimizing the initial defect target model according to a preset initial dislocation value and a measured dislocation density, and obtaining a first target model;

[0078] Step S103, calculating the ion implantation speed according to the mass of the ions to be implanted and the preset implantation energy, and constructing the second target model according to the ion implantation speed and the first target model;

[0079] Step S104, applying pressure to the second target model by a preset pressure head, and calculating a first actual penetration depth and a first Z-direction load component of the preset pressure head during the pressure application process;

[0080] Step S105 : calculating the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component.

[0081] The method constructs an initial defect target model, optimizes the initial defect target model according to a preset initial dislocation value and a measured dislocation density, obtains a first target model, calculates an ion injection speed according to the mass of the ions to be injected and the preset injection energy, and constructs a second target model according to the ion injection speed and the first target model; calculates the hardness of the metal material after ion injection from a microscopic perspective, and finally applies pressure to the second target model through a preset pressure head, and calculates a first actual injection depth during the injection process and a first Z-direction load component of the preset pressure head; calculates the hardness of the metal to be simulated after ion injection according to the first actual injection depth and the first Z-direction load component, thereby improving the optimization efficiency of process parameters, reducing the complexity of operations, and achieving the purpose of predicting the influence of ion injection on the hardness of parts.

[0082] In some embodiments, the method for calculating the metal hardness further includes:

[0083] Step S201, applying pressure to the first target model by a preset pressure head, and calculating a second actual penetration depth and a second Z-direction load component of the preset pressure head during the pressure application process;

[0084] Step S202: Calculate the hardness of the metal to be simulated before ion implantation according to the second actual indentation depth and the second Z-direction load component.

[0085] This embodiment applies pressure to the first target model through a preset pressure head, thereby realizing the hardness calculation of the metal material before ion implantation from a microscopic perspective.

[0086] In some embodiments, optimizing the initial defect target model according to the preset initial dislocation value and the measured dislocation density to obtain the first target model includes:

[0087] Step S301, optimizing the initial defect target model by using the Minimize command of Lammps software and the NVT or NPT ensemble according to the preset initial dislocation value, to obtain the first defect target model with minimized system potential energy;

[0088] Step S302, calculating the dislocation density of the first target plate of the first defective target model by using Ovito software;

[0089] Step S303, calculating the dislocation density deviation value according to the dislocation density of the first target plate and the measured dislocation density;

[0090] Step S304, optimizing the preset initial dislocation value according to the dislocation density deviation value to obtain the first dislocation value;

[0091] Step S305 , reversely optimize the initial defect target model according to the first mismatch value to obtain an optimized initial defect target model, and use the optimized initial defect target model as the first target model.

[0092] This embodiment optimizes the initial defect target model through the Minimize command of Lammps software and the NVT or NPT ensemble, and optimizes the initial defect target model to obtain an optimized initial defect target model, thereby achieving accurate construction of the model before ion implantation and providing a more accurate data basis for subsequent hardness calculations.

[0093] In some embodiments, the ion implantation speed is calculated according to the mass of the ions to be implanted and the preset implantation energy, and the second target model is constructed according to the ion implantation speed and the first target model, including:

[0094] Step S401, dividing the first target model from bottom to top into a boundary layer, a constant temperature layer and a Newtonian layer according to a preset lattice constant;

[0095] Step S402: Calculate the ion implantation rate according to the mass of the ions to be implanted and the preset implantation energy using the following formula:

[0096]

[0097] Wherein, v is the ion injection velocity, m is the mass of the ions to be injected, and E is the preset injection energy;

[0098] Step S403 , injecting the ions to be injected into the Newtonian layer of the first target model according to the ion injection speed to obtain the second target model.

[0099] In this embodiment, the first target model is divided into a boundary layer, a constant temperature layer and a Newtonian layer from bottom to top according to a preset lattice constant, and the ions to be injected are injected into the Newtonian layer of the first target model according to the ion injection speed to obtain the second target model, thereby realizing the accurate construction of the model after ion injection and providing a more accurate data basis for the subsequent hardness calculation after ion injection.

[0100] In some embodiments, applying pressure to the second target model by a preset pressure head, and calculating a first actual penetration depth and a first Z-direction load component of the preset pressure head during the pressure application process, include:

[0101] Step S501, applying pressure to the second target model by a preset pressure head at a preset speed;

[0102] Step S502, obtaining the three-dimensional coordinates of each ion during the pressure application process, and calculating the first Z-direction load component of the preset pressure head during the pressure application process according to the three-dimensional coordinates of each ion and the preset force constant;

[0103] Step S503, obtaining the Z coordinate of the preset pressure head when pressure is to be applied;

[0104] Step S504, according to the preset Z coordinate of the pressure head when pressure is to be applied, the Z coordinate of the ion from the center of the pressure head is calculated using the following formula:

[0105] Z=R s -0.4t

[0106] Where Z is the Z coordinate of the ion from the center of the pressure head, R s is the Z coordinate of the preset pressure head when pressure is applied, and t is the loading time;

[0107] Step S505, screening all ions whose Z coordinates from the center of the indenter are greater than R+a / 2 to obtain screened ions, where R is the indenter radius and a is a preset lattice constant;

[0108] Step S506, finding the minimum z coordinate of the screened ions;

[0109] Step S507 : Calculate the difference between the Z coordinate of the preset pressure head when pressure is applied and the minimum z coordinate of the screened ions to obtain a first actual penetration depth.

[0110] This embodiment applies pressure to the second target model at a preset speed through a preset pressure head, and calculates the first actual penetration depth and the first Z-direction load component of the preset pressure head during the pressure application process, thereby realizing the calculation of the hardness of the part due to ion implantation.

[0111] In some embodiments, calculating the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component includes:

[0112] Step S601, obtaining the residual depth value of the metal to be simulated after unloading;

[0113] Step S602: According to the first Z-direction load component and the first actual indentation depth, data fitting is performed using the following formula to obtain a first fitting parameter and a second fitting parameter:

[0114] P=P0(hh f ) m

[0115] Where P is the first Z-axis load component, h is the first actual penetration depth, and h f is the residual depth value after unloading, P0 is the first fitting parameter, and m is the second fitting parameter;

[0116] Step S603: Calculate the hardness of the metal to be simulated after ion implantation using the following formula according to the first fitting parameter and the second fitting parameter:

[0117] S=dP / dh

[0118] h c =h max -εP max / S

[0119]

[0120]

[0121] Where S is the unloading stiffness, h c is the contact depth, ε is the preset indenter shape coefficient value, h max is the maximum value of the first actual pressing depth, P max is the maximum value of the first Z-direction load component, A c is the hardness parameter value, R is the radius of the preset indenter, and H is the hardness of the metal to be simulated after ion implantation.

[0122] This embodiment calculates the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component, and then compares the hardness change of the material before and after the ion implantation to explore the strengthening mechanism of the ion implantation process.

[0123] In some embodiments, obtaining the measured dislocation density of the metal to be simulated includes:

[0124] Step S701 : measuring the dislocation density at a preset depth of the metal to be simulated by a backscattered electron diffraction method or a transmission electron microscope test method to obtain a measured dislocation density.

[0125] This embodiment measures the dislocation density at a preset depth of the metal to be simulated by a backscattered electron diffraction method or a transmission electron microscopy test method, which provides an accurate reference for the subsequent construction of the first target model.

[0126] Specifically, refer to Figure 2 , wherein, in order to facilitate understanding by those skilled in the art, a set of optimal embodiments are provided below:

[0127] 1. Data acquisition:

[0128] Carry out backscattered electron diffraction technology or transmission electron microscopy experiments to measure the surface dislocation density of the target parts.

[0129] Specifically, since the ion implantation process mainly acts on the surface of the material, the backscattered electron diffraction technique or transmission electron microscopy test should be used to measure the dislocation density from the surface to a depth of 1 mm for the target part. In this case, taking 9310 gear steel as an example, the dislocation density of the part surface measured by the backscattered electron diffraction technique is 4 to 6×10 15 / m 2 .

[0130] 2. Construct the first target model:

[0131] Reference Figure 2 You can use atomsk software or other suitable software to write a program to build a target plate with initial defects. First, generate a perfect single crystal target body as required. In this case, according to the surface state of 9310 steel, the target plate lattice structure is determined to be body-centered cubic, and the lattice constant is The target size is set to

[0132] Afterwards, dislocations or dislocation loops are introduced into the perfect single crystal, and an lmp type file suitable for Lammps software is output. The lmp type file is read using the read_data command of the Lammps software, and energy minimization and relaxation calculations are performed on the model to obtain the first target model.

[0133] When performing energy minimization and relaxation calculations, the time step can be set to 0.001ps, and the Velocity-Verlet integration algorithm is used. To reduce the scale effect, the x and y directions of the target are set to periodic boundary conditions, the positive z direction is a free boundary condition, and the negative z direction is a fixed boundary condition. The atomic interaction potential can be selected. For example, the eam / fs potential function that is more suitable for metal-metal interactions is used between iron atoms, the lj potential function is used between chromium ions, and the Tersoff / ZBL potential function is used between chromium ions and iron atoms.

[0134] Specifically, because the software introduces dislocations or dislocation loops in the target by deleting or adding atoms, some atoms may be too close or unbalanced, causing the model to crash during calculation. The Minimize command of Lammps software can minimize the potential energy of the system and avoid extreme situations between atoms.

[0135] During the relaxation stage, the model calculation temperature can be set to room temperature 293K, and the NVT or NPT ensemble can be used in the calculation. Finally, the dislocation line is stabilized in a reasonable state consistent with the actual situation, and the model reaches a dynamic equilibrium process with relatively stable total energy.

[0136] Reference Figure 3 Finally, after the calculation is completed, a restart type file containing target plate information, interaction potential, boundary conditions, time step, etc. is output. The target plate contained in the file is the target plate with initial defects that has been constructed. The dislocation density of the target plate at this time can be calculated using Ovito software. If there is a deviation from the measured result range, the number of introduced dislocations or dislocation loops needs to be appropriately reduced or increased, and this step needs to be repeated. In this case, the final dislocation density of the target plate is 5.7×10 15 / m 2 .

[0137] 3. Construct the second target model:

[0138] The restart type file of the first target model is read by the read_restart command of Lammps software. This file already contains target plate information, interaction potential, boundary conditions, time step and other information, so there is no need to reset it.

[0139] The target is set as a boundary layer, a constant temperature layer and a Newton layer from bottom to top. The boundary layer is set to completely fix the atoms to prevent the target from moving during ion implantation. A thermostat is used in the constant temperature layer so that the model can dissipate heat reasonably. The thermostat can be a Berendsen thermostat or other suitable thermostat. The Newton layer conforms to Newton's law and uses the NVE ensemble. This area is the area where the injected atoms interact with the target atoms.

[0140] In this embodiment, the ions are set at a distance from the upper surface of the sample. The model injects one ion every 20 ps, ​​which allows the system to relax fully after each ion impact. The injection ion speed is determined according to the following relationship:

[0141]

[0142] Where, E is the implantation energy, in J; m is the mass of the implanted ions, in kg. For example, in this embodiment, E = 1 keV = 1.602 × 10 -16 J, ion is chromium ion, its mass

[0143] After the calculation is completed, the second target model is obtained, and a restart type file containing target plate information, interaction potential, boundary conditions, time step and other information is output again.

[0144] 4. Calculate the first actual indentation depth and the first Z-direction load component of the preset indenter:

[0145] For the models before and after ion implantation calculations, a molecular dynamics model of nanoindentation was constructed and simulation calculations were carried out.

[0146] For the first target model before ion implantation: read the restart result file of the first target model. This file contains some target plate information, interaction potential, boundary conditions, time step and other information, and sets the target from bottom to top as boundary layer, isothermal layer and Newton layer respectively, and the setting method is the same as the second target model.

[0147] For the second target model after ion implantation: read the restart result file of the second target model in step 1. The file contains information such as target plate information, interaction potential, boundary conditions, time step, etc.

[0148] The radius is A spherical indenter is used. The non-atomic rigid sphere that comes with LAMMPS is used as the indenter, which repels all atoms it contacts. The interaction potential is:

[0149] F(r)=-k(rR) 2

[0150] Where r is the distance from the atom to the center of the indenter, and R is the radius of the indenter, which is k is the specified force constant, set

[0151] To prevent the indenter from being too close to the atoms on the target surface at the initial moment of nanoindentation calculation, which would lead to errors in the calculation of interaction forces, the indenter is set to be The uniform loading starts at the point where the pressure head is loaded. The z coordinate of the center of the pressure head at the initial moment is marked as R s At this time R s is the sum of the target plate surface height and the indenter radius, plus Right now The center of the indenter is consistent with the center of the target in the horizontal direction, that is, the x and y coordinates are Loading and unloading speed is The maximum indentation depth is

[0152] This step stores data every 1ps, i.e., 1000 steps, and stores the three-dimensional coordinates (x′ i ,y′ i ,z′ i ) is recorded in the dump file, where i represents the atomic number and the force vector acting on the target plate is stored, where the z-direction load is P.

[0153] The actual penetration depth of the indenter during the nanoindentation process is extracted from the stored dump file.

[0154] Specifically, the average z-coordinate of the atoms on the target surface before the nanoindentation begins is taken as the starting point, and this value is recorded as h s , the pressing depth is

[0155] Screening distance from the center of the pressure head (71.575, 71.575, R s -0.4t) is less than R+a / 2, where R sis the z coordinate of the center of the indenter at the initial moment, t is the loading time, R is the radius of the indenter, and a is the lattice constant. Find the atom with the smallest z coordinate among the selected atoms, and record its z coordinate as h t The actual penetration depth of the indenter is h = h s -h t , where h s The height at which the indenter starts to be inserted.

[0156] Reference Figure 4 , perform this step for each dump file to obtain the actual penetration depth at the corresponding moment, so as to understand the change of the actual penetration depth over time.

[0157] 5. Calculate hardness:

[0158] Reference Figure 5 , the Oliver-Pharr method is used to calculate the target hardness. First, the unloading section is fitted:

[0159] P=P0(hh f ) m

[0160] Where P is the first Z-axis load component, h is the first actual penetration depth, and h f is the residual depth value after unloading, P0 is the first fitting parameter, and m is the second fitting parameter;

[0161] The hardness of the metal to be simulated after ion implantation is calculated using the following formula according to the first fitting parameter and the second fitting parameter:

[0162] S=dP / dh

[0163] h c =h max -εP max / S

[0164]

[0165]

[0166] Where S is the unloading stiffness, h c is the contact depth, ε is the preset indenter shape coefficient value, h max is the maximum value of the first actual pressing depth, P max is the maximum value of the first Z-direction load component, A c is the hardness parameter value, R is the radius of the preset indenter, and H is the hardness of the metal to be simulated after ion implantation.

[0167] The hardness of the target plate before ion implantation calculated in this embodiment is 17.2 GPa, and the hardness of the target plate after ion implantation is 18.5 GPa, which is consistent with the experimental results.

[0168] In addition, refer to Figure 6 One embodiment of the present invention provides a metal hardness calculation system, including a data acquisition module 1100, a first target model construction module 1200, a second target model construction module 1300, an indentation depth and load component calculation module 1400 and a hardness calculation module 1500, wherein:

[0169] The data acquisition module 1100 is used to obtain the measured dislocation density of the metal to be simulated;

[0170] The first target model building module 1200 is used to build an initial defect target model, optimize the initial defect target model according to a preset initial dislocation value and a measured dislocation density, and obtain a first target model;

[0171] The second target model building module 1300 is used to calculate the ion implantation speed according to the mass of the ions to be implanted and the preset implantation energy, and to build the second target model according to the ion implantation speed and the first target model;

[0172] The indentation depth and load component calculation module 1400 is used to apply pressure to the second target model through a preset indenter, and calculate a first actual indentation depth and a first Z-direction load component of the preset indenter during the pressure application process;

[0173] The hardness calculation module 1500 is used to calculate the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component.

[0174] The system constructs an initial defect target model, optimizes the initial defect target model according to a preset initial dislocation value and a measured dislocation density, obtains a first target model, calculates the ion injection speed according to the mass of the ions to be injected and the preset injection energy, and constructs a second target model according to the ion injection speed and the first target model; calculates the hardness of the metal material after ion injection from a microscopic perspective, and finally applies pressure to the second target model through a preset pressure head, and calculates a first actual injection depth during the injection process and a first Z-direction load component of the preset pressure head; calculates the hardness of the metal to be simulated after ion injection according to the first actual injection depth and the first Z-direction load component, thereby improving the optimization efficiency of process parameters, reducing the complexity of operations, and achieving the purpose of predicting the influence of ion injection on the hardness of parts.

[0175] It should be noted that the present system embodiment and the above-mentioned system embodiment are based on the same inventive concept, so the relevant contents of the above-mentioned method embodiment are also applicable to the present system embodiment and will not be repeated here.

[0176] The present application also provides an electronic device for calculating metal hardness, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for calculating metal hardness as described above is implemented.

[0177] The processor and the memory may be connected via a bus or other means.

[0178] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0179] The non-transient software program and instructions required to implement the metal hardness calculation method of the above embodiment are stored in the memory. When executed by the processor, the metal hardness calculation method of the above embodiment is executed, for example, the above described Figure 1 The method comprises steps S101 to S105.

[0180] The present application also provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute: the metal hardness calculation method as described above.

[0181] The computer-readable storage medium stores computer-executable instructions, which are executed by a processor or a controller, for example, by a processor in the above electronic device embodiment, so that the above processor can execute the metal hardness calculation method in the above embodiment, for example, execute the above described Figure 1 The method comprises steps S101 to S105.

[0182] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program units or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media generally contain computer readable instructions, data structures, program elements, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0183] The embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge scope of ordinary technicians in the relevant technical field without departing from the purpose of the present invention.

Claims

1. A method for calculating metal hardness, characterized in that: The calculation method of the metal hardness includes: Obtaining the measured dislocation density of the metal to be simulated; Constructing an initial defect target model, optimizing the initial defect target model according to a preset initial dislocation value and the measured dislocation density, to obtain a first target model; The ion implantation speed is calculated according to the mass of the ions to be implanted and the preset implantation energy, and the second target model is constructed according to the ion implantation speed and the first target model, specifically: Dividing the first target model from bottom to top into a boundary layer, a constant temperature layer and a Newtonian layer according to a preset lattice constant; The ion implantation rate is calculated according to the mass of the ions to be implanted and the preset implantation energy using the following formula: Wherein, v is the ion injection velocity, m is the mass of the ions to be injected, and E is the preset injection energy; Injecting the ions to be injected into the Newtonian layer of the first target model according to the ion injection speed to obtain the second target model; The second target model is pressed by a preset pressure head, and a first actual pressing depth during the pressing process and a first Z-direction load component of the preset pressure head are calculated, specifically: Applying pressure to the second target model by a preset pressure head at a preset speed; Acquire the three-dimensional coordinates of each ion during the pressure application process, and calculate the first Z-direction load component of the preset pressure head during the pressure application process according to the three-dimensional coordinates of each ion and the preset force constant; Obtaining the Z coordinate of the preset pressure head when pressure is to be applied; The Z coordinate of the ion from the center of the pressure head is calculated using the following formula according to the Z coordinate of the preset pressure head when pressure is applied: Z=R s -0.4t Where Z is the Z coordinate of the ion from the center of the pressure head, R s is the Z coordinate of the preset pressure head when pressure is applied, and t is the loading time; Screening all ions whose Z coordinates from the center of the indenter are greater than R+a / 2 to obtain screened ions, wherein R is the indenter radius and a is a preset lattice constant; Finding the minimum z coordinate of the screened ions; Calculating the difference between the Z coordinate of the preset pressure head when the pressure is to be applied and the minimum z coordinate of the screened ions to obtain the first actual penetration depth; The hardness of the metal to be simulated after ion implantation is calculated according to the first actual indentation depth and the first Z-direction load component, specifically: Obtaining the residual depth value of the metal to be simulated after unloading; According to the first Z-direction load component and the first actual penetration depth, the following formula is used to perform data fitting to obtain a first fitting parameter and a second fitting parameter: P=P0(h-h f ) m Where P is the first Z-axis load component, h is the first actual penetration depth, and h f is the residual depth value after unloading, P0 is the first fitting parameter, and m is the second fitting parameter; The hardness of the metal to be simulated after ion implantation is calculated using the following formula according to the first fitting parameter and the second fitting parameter: S=dP / dh h c =h max -εP max / S Where S is the unloading stiffness, h c is the contact depth, ε is the preset indenter shape coefficient value, h max is the maximum value of the first actual pressing depth, P max is the maximum value of the first Z-direction load component, A c is the hardness parameter value, R is the radius of the preset indenter, and H is the hardness of the metal to be simulated after ion implantation.

2. A method for calculating metal hardness according to claim 1, characterized in that: The calculation method of the metal hardness also includes: Applying pressure to the first target model by a preset pressure head, and calculating a second actual penetration depth and a second Z-direction load component of the preset pressure head during the pressure application process; The hardness of the metal to be simulated before ion implantation is calculated according to the second actual indentation depth and the second Z-direction load component.

3. The method for calculating metal hardness according to claim 1, characterized in that: The step of optimizing the initial defect target model according to the preset initial dislocation value and the measured dislocation density to obtain a first target model includes: According to the preset initial dislocation value, the initial defect target model is optimized by using the Minimize command of Lammps software and the NVT or NPT ensemble to obtain a first defect target model with minimized system potential energy; Calculating the dislocation density of the first target plate of the first defective target model by Ovito software; Calculating a dislocation density deviation value according to the dislocation density of the first target plate and the measured dislocation density; Optimizing the preset initial dislocation value according to the dislocation density deviation value to obtain a first dislocation value; The initial defect target model is reversely optimized according to the first dislocation value to obtain the optimized initial defect target model, and the optimized initial defect target model is used as the first target model.

4. The method for calculating metal hardness according to claim 1, characterized in that: The step of obtaining the measured dislocation density of the metal to be simulated comprises: The measured dislocation density is obtained by measuring the dislocation density at a preset depth of the metal to be simulated by a backscattered electron diffraction method or a transmission electron microscope test method.

5. A metal hardness calculation system, characterized in that: The metal hardness calculation system comprises: A data acquisition module, used to obtain the measured dislocation density of the metal to be simulated; A first target model building module is used to build an initial defect target model, optimize the initial defect target model according to a preset initial dislocation value and the measured dislocation density, and obtain a first target model; The second target model building module is used to calculate the ion injection speed according to the mass of the ions to be injected and the preset injection energy, and to build the second target model according to the ion injection speed and the first target model, specifically: Dividing the first target model from bottom to top into a boundary layer, a constant temperature layer and a Newtonian layer according to a preset lattice constant; The ion implantation rate is calculated according to the mass of the ions to be implanted and the preset implantation energy using the following formula: Wherein, v is the ion injection velocity, m is the mass of the ions to be injected, and E is the preset injection energy; Injecting the ions to be injected into the Newtonian layer of the first target model according to the ion injection speed to obtain the second target model; The indentation depth and load component calculation module is used to apply pressure to the second target model through a preset indenter, and calculate the first actual indentation depth during the pressure application process and the first Z-direction load component of the preset indenter, specifically: Applying pressure to the second target model by a preset pressure head at a preset speed; Acquire the three-dimensional coordinates of each ion during the pressure application process, and calculate the first Z-direction load component of the preset pressure head during the pressure application process according to the three-dimensional coordinates of each ion and the preset force constant; Obtaining the Z coordinate of the preset pressure head when pressure is to be applied; The Z coordinate of the ion from the center of the pressure head is calculated using the following formula according to the Z coordinate of the preset pressure head when pressure is applied: Z=R s -0.4t Where Z is the Z coordinate of the ion from the center of the pressure head, R s is the Z coordinate of the preset pressure head when pressure is applied, and t is the loading time; Screening all ions whose Z coordinates from the center of the indenter are greater than R+a / 2 to obtain screened ions, wherein R is the indenter radius and a is a preset lattice constant; Finding the minimum z coordinate of the screened ions; Calculating the difference between the Z coordinate of the preset pressure head when the pressure is to be applied and the minimum z coordinate of the screened ions to obtain the first actual penetration depth; A hardness calculation module is used to calculate the hardness of the metal to be simulated after ion implantation according to the first actual indentation depth and the first Z-direction load component, specifically: Obtaining the residual depth value of the metal to be simulated after unloading; According to the first Z-direction load component and the first actual penetration depth, the following formula is used to perform data fitting to obtain a first fitting parameter and a second fitting parameter: P=P0(h-h f ) m Where P is the first Z-axis load component, h is the first actual penetration depth, and h f is the residual depth value after unloading, P0 is the first fitting parameter, and m is the second fitting parameter; The hardness of the metal to be simulated after ion implantation is calculated using the following formula according to the first fitting parameter and the second fitting parameter: S=dP / dh h c =h max -εP max / S Where S is the unloading stiffness, h c is the contact depth, ε is the preset indenter shape coefficient value, h max is the maximum value of the first actual pressing depth, P max is the maximum value of the first Z-direction load component, A c is the hardness parameter value, R is the radius of the preset indenter, and H is the hardness of the metal to be simulated after ion implantation.

6. A device for calculating metal hardness, characterized in that: It includes at least one control processor and a memory for communicating with the at least one control processor; the memory stores instructions that can be executed by the at least one control processor, and the instructions are executed by the at least one control processor so that the at least one control processor can execute a metal hardness calculation method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method for calculating metal hardness as claimed in any one of claims 1 to 4.

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