18 results about "Interaction potential" patented technology

The invention provides a metal matrix composite microstructure strengthening simulation method and system, and relates to the technical field of composite mechanical property simulation, and the method comprises the following steps: establishing a polycrystalline aluminum matrix atomic model and a spherical silicon nitride particle strengthening phase atomic model unit; embedding the spherical silicon nitride particles into the polycrystalline aluminum matrix according to the target embedding position coordinates, and integrating to generate an atomic scale structure model; according to the method, an embedded atom potential function is adopted to describe interaction among atoms in a polycrystalline aluminum matrix, a Tersoft potential function is adopted to describe covalent bond interaction among atoms in spherical silicon nitride particles, and a Lennard-Jones potential function is adopted to describe interaction among heteroatoms at a Si3N4 / Al interface; based on the interaction potential between atoms, molecular dynamics simulation is adopted for conducting uniaxial stretching simulation on the atomic scale structure model, mechanical property parameters of the particle reinforced metal matrix composite are obtained through calculation, and a visualization method is combined for analyzing the microcosmic strengthening mechanism of the particle reinforced metal matrix composite.

The invention belongs to the field of automatic driving, and discloses a vehicle trajectory prediction method and system based on an interaction potential field and a graph convolutional network, and the method comprises the steps: obtaining time sequence features based on the historical trajectory data of a vehicle, representing the interaction influence relation between vehicles through the interaction potential field, and extracting the longitudinal and transverse interaction features of the vehicle through combining with the graph convolutional network; and splicing the time sequence features, the vehicle inherent features and the interaction features to form time sequence interaction fusion features, inputting the time sequence interaction fusion features to a decoder model, and finally outputting a high-precision vehicle prediction trajectory. According to the method, the vehicle time sequence features are extracted, the vehicle interaction feature extraction model is constructed by using the interaction potential field and the graph convolutional network, the complex interaction relationship between vehicles is effectively captured, the problem that an existing method neglects external factors and environment vehicle interaction is solved, directivity influence is introduced through the interaction potential field, and the vehicle interaction effect is improved. And the vehicle motion state is integrated, so that the trajectory prediction accuracy is remarkably improved, and the method is suitable for high-precision trajectory prediction requirements in complex traffic scenes.

The application relates to a method for regulating the thermal conductivity of a nanometer semiconductor interface in contact and non-contact states, which comprises the following steps: (1) establishing a molecular dynamics thermal transport model composed of a hot region A and a cold region B; (2) performing molecular dynamics simulation and data processing: comparing the interface thermal conductivities under different twist angles in the contact state and the non-contact state to determine the dependence of the interface thermal conductivity on the twist angle; in the contact state, comparing the overlapping areas of the phonon state density at the contact interface under different twist angles to determine the influence of the overlapping area of the phonon state density on the thermal transport of different interface twist angles; in the non-contact state, comparing the force constants of the interface interaction potential and the LJ potential under different twist angles to determine the influence of the force constant on the thermal transport of different interface twist angles. The application realizes effective regulation of the ITC by regulating the twist angle, the normal load and the potential well depth, and provides an important basis for the thermal management of nanometer devices.

The present invention discloses a method, system, device and medium for reconstructing an atomic interaction potential function, including: obtaining the potential function to be reconstructed; constructing an atomic interaction model, and calculating the first force and potential energy results of the potential function to be reconstructed and the second force and potential energy results of the ZBL potential function through the atomic interaction model; smoothly connecting the potential function to be reconstructed and the ZBL potential function to obtain a transition potential function and the third force and potential energy results of the transition potential function; constructing a table potential function, and reconstructing the potential function to be reconstructed, the ZBL potential function and the transition potential function and the corresponding first force and potential energy results, second force and potential energy results and third force and potential energy results according to the table potential function to obtain a reconstructed potential function. The present invention reconstructs based on the existing potential function that can accurately describe the properties of substances, so that it can be used for short-range interactions caused by high-energy atomic collisions.

The invention relates to the technical field of numerical simulation and ultra-precision machining, and particularly discloses a laser-assisted cutting tool wear simulation test method and device, and the method comprises the following steps: S1, building a tool material model through an LAMMPS language; s2, setting system boundary conditions, ensuring unification of physical quantity units and the boundary conditions, and ensuring simulation accuracy and comparability; s2, establishing an ionic group model right above the tool material model established in S1, setting an interaction potential function between atoms, and ensuring that a simulation result accords with an actual physical process; s3, layering the initial model set in the S1, setting an integral time step length and total relaxation time, and enabling the relaxation system model to reach a stable state through a conjugate gradient method and an isothermal isometric system; and S4, setting an incident angle and a speed of the ionic group, outputting an atomic parameter, a thermodynamic parameter and a visual image in the process of bombarding the tool material by the ionic group, and carrying out subsequent analysis and result verification.

The present invention discloses a method and system for correcting the machine learning interatomic interaction potential. The method proposed in the present invention uses molecular dynamics simulation to calculate the free energy of each phase of the material, and uses the equality of the two-phase free energy involved in the phase boundary in the experimentally measured phase diagram as the correction basis to correct the training data set required for the machine learning interatomic interaction potential. The machine learning interatomic interaction potential is then trained using the corrected training data set, thereby obtaining a more accurate and reliable machine learning interatomic interaction potential, providing more accurate and reliable data support and technical support for the simulation calculation of material properties.

The present application relates to a kind of dislocation-mediated diamond ductile-brittle transition simulation method under hydrostatic pressure, comprising the following steps: constructing the potential function model of dislocation-mediated diamond under hydrostatic pressure;Randomly generate potential function undetermined coefficient, obtain the material parameters of diamond to be tested, with the material parameters of diamond to be tested as target, undetermined coefficient of potential function is optimized and solved by genetic algorithm, obtain multiple potential functions to be tested;From multiple potential functions to be tested, according to the parameter variation result of shear loading force under hydrostatic pressure strain condition of multiple diamond configurations, filter out the potential function that meets the material parameters of diamond to be tested;According to the potential function that meets the material parameters of diamond to be tested, the interaction between diamond atoms is calculated, and the ductile-brittle transition of dislocation-mediated diamond under hydrostatic pressure is simulated by interaction potential parameter.Compared with prior art, the present application can effectively analyze diamond dislocation slip mechanism, with the advantages of high calculation accuracy, good simulation performance and the like.

The application discloses a kind of nanoparticle aggregation settlement performance parameter processing method, applied to water environment science and technology field.The application includes the following steps: obtaining the particle size of the nanoparticle of the sample to be tested, Zeta potential and electrophoretic mobility under different test liquid conditions;In MATLAB computing environment, the thickness of humic acid adsorption layer on the surface of the nanoparticle of the sample to be tested is solved by numerical inversion fitting algorithm;The thickness of humic acid adsorption layer, the particle size and Zeta potential of the nanoparticle are used as input parameters, and the van der waals attractive interaction potential, electrostatic double layer repulsive interaction potential, steric interaction potential and total potential energy are calculated based on XDLVO theory.The application improves the efficiency, accuracy and repeatability of parameter solving and energy calculation, and provides reliable data and calculation basis for the analysis of nanoparticle aggregation settlement mechanism and the prediction of stability under complex water quality conditions.

The invention relates to the technical field of numerical simulation and ultra-precision machining, and particularly discloses a simulation test method and device for wear of a black metal cutting cutter, and the method comprises the following steps: S1, building a model: compiling a three-dimensional geometric model of a black metal and diamond cutter action system through an LAMMPS language; s2, determining a simulation dimension as three dimensions, setting a unit, defining an atom type and a lattice structure, performing regional division on the black metal model and the diamond cutter model, setting a Newton layer, a constant-temperature layer and a fixed layer respectively, and setting an interaction potential function between atoms to describe interaction between the atoms, so as to ensure that a simulation result accords with an actual physical process; setting an integral time step length and total relaxation time, relaxation the system model through a conjugate gradient method and an isothermal isovolumetric method to enable the system model to reach a stable state, and setting a motion track of the black metal friction cutter; and S3, the change trend of the lattice structure of the tool material in the friction process and the non-crystallization phenomenon are obtained, and the tool abrasion condition is analyzed.

The application discloses a force field development method for hydrogen adsorption of metal organic framework (MOF) containing unsaturated metal sites, which firstly carries out calculation simulation of hydrogen adsorption isotherm of Cu-BTC (metal-organic framework material), and focuses on development of the force field. By constructing an accurate molecular model and corresponding force field parameters, hydrogen adsorption behavior of Cu-BTC under different pressure conditions is successfully simulated. In the calculation research, the DFT and molecular simulation combination method is adopted to develop the force field, and the interaction potential between hydrogen molecules and the pore surface of Cu-BTC is corrected in combination with experimental data. The results show that the developed force field can accurately predict the hydrogen adsorption isotherm in Cu-BTC, and has good consistency with the experimental results, thereby providing a theoretical basis for further development of MOF materials for hydrogen storage.

This application discloses a method and system for predicting the migration of rare earth elements. This application can acquire bio-disturbance information and physicochemical state information corresponding to a target region. Based on the bio-disturbance information, interface interaction analysis is performed on the surface property characteristics of natural colloids in the physicochemical state information to obtain and calculate the interaction potential energy based on the effective surface potential of the natural colloids under biological mediation, thus obtaining the dynamic migration information corresponding to the target colloidal carrier. According to a preset porous media evolution relationship, physical conservation analysis is performed on the hydrodynamic characteristics in the dynamic migration information and physicochemical state information to obtain and, based on the physical constraint characteristic information corresponding to the target region, the network parameters of the initial prediction network are updated through a preset joint loss function to perform spatiotemporal evolution prediction processing for rare earth elements in the target region. Therefore, this application improves the accuracy of spatiotemporal evolution prediction of rare earth elements and the reliability of engineering applications.

The present invention discloses an atomic-level simulation method for direct bonding of rough surfaces of nano-twinned copper. The interatomic interaction potential function in molecular dynamics is determined by first principles, and a polycrystalline nano-twinned copper supercell model is constructed based on experimental parameters to generate a rough surface with fractal characteristics. Molecular dynamics simulation is used to simulate the bonding and annealing processes to obtain a polycrystalline nano-twinned copper model after bonding, and the performance of the interconnection structure is calculated based on this. The result feedback is used to optimize the material and process parameters of copper-copper direct bonding. The present invention establishes an atomic-level polycrystalline nano-twinned copper model through simulation, derives the optimal performance parameter combination of the interconnection structure, reduces the trial and error cost in testing and production, improves the interface quality of copper-copper direct bonding, and provides guidance for the design and process optimization of high-density packaging.

The invention relates to a deep learning potential function-based hafnium-based oxide solid solution dielectric property calculation method and system, and the method comprises the steps: S1, building a hafnium-based oxide solid solution model with HfO2 as a parent phase structure, and building an initial data set through first principle molecular dynamics simulation; s2, training an inter-atomic interaction potential function by using a deep neural network; s3, performing large-scale molecular dynamics simulation based on the potential function, screening candidate configurations, constructing an incremental data set, and iteratively optimizing the potential function; s4, verifying the precision of the potential function optimized in the step S3 by the system, comparing and predicting the equilibrium state physical property of the material, and ensuring the accuracy of the potential function model; and S5, performing deep potential energy molecular dynamics simulation based on the potential function optimized in S3, and researching the phase stability and dielectric property of the system. Compared with the prior art, the device structure of the dynamic random access memory is combined, and a prospective solution is provided for improving the capacitor performance of the dynamic random access memory.

The application provides a long-range many-body effect and short-range angle-dependent interaction potential model and a construction method, and belongs to the field of material simulation, and specifically comprises the following steps: firstly, fitting various potential functions, fitting target data is obtained from external input or through first-principle calculation, and the fitting target data is used as a fitting target set; fitting each potential function, preparing a predictive property calculation structure according to the fitting target set, and calculating a corresponding predictive property; the calculation result of the predictive property is consistent with each fitting target; then, using the least square method as a cost function, evaluating the potential function by calculating the energy value of each correlation model and the square sum of the deviation of each fitting target, and setting a weight factor for each fitting target; finally, setting an optimization algorithm, taking the calculation result of the potential function as a fitting target, and adopting step-by-step fitting to construct a long-range many-body effect and short-range angle-dependent interaction potential hybrid model; and the application effectively guarantees the hcp phase stability of high c / a ratio hcp metals.

The application relates to the technical fields of numerical simulation and ultra-precision machining, and particularly discloses a simulation test method and device for laser-assisted cutting tool wear, which comprises the following steps: S1: a tool material model is established through LAMMPS language; S2: system boundary conditions are set to ensure that physical quantity units and boundary conditions are unified, simulation accuracy and comparability are ensured; an ion group model is established directly above the tool material model established in S1, an interaction potential function between atoms is set, and it is ensured that simulation results are in line with actual physical processes; S3: the initial model set in S1 is layered, an integral time step and total relaxation time are set, a conjugate gradient method and an isothermal isochoric system relaxation system model are used, and the system model is made to reach a stable state; S4: the incident angle and speed of the ion group are set, atomic parameters, thermodynamic parameters and visualized images in the process that the ion group bombards the tool material are output, and subsequent analysis and result verification are carried out.

The invention discloses a method for calculating interaction between particles, hardware, a medium and a product, and the method comprises the steps: obtaining and taking a reference subunit as a sphere center and a preset truncation radius as a radius, and constructing a hemisphere model; a to-be-screened unit is determined according to the hemisphere model, and to-be-screened particle information of all to-be-screened particles in the space to which the to-be-screened particles belong is obtained and sent to a calculation component of the reference subunit; calculating the interaction force and the interaction potential energy between each reference particle and each to-be-screened particle according to the to-be-screened particle information and the reference particle information by a calculating part of the reference subunit, and accumulating and updating the reference particle information; each interaction force is sent back to the calculation component of the corresponding to-be-screened unit according to the offset address; the calculation component of each to-be-screened unit subtracts each interaction force from the to-be-screened particle information; and returning to execute the operation of acquiring the reference subunit until all the subunits are acquired as the reference subunits, thereby ensuring that the interaction does not have repeated calculation, and improving the calculation efficiency.

The invention discloses a method for constructing an inter-atomic interaction potential function of a multi-element doped silicon carbide reinforced aluminum matrix composite, and relates to a method for constructing an inter-atomic interaction potential function of a composite material. The inter-atomic interaction potential function of the multi-element doped SiC / Al composite material is constructed according to DPGEN software, the method is suitable for describing the deformation behavior of the silicon carbide reinforced aluminum matrix composite material formed by combining five elements of C, Si, Al, Cu and Mg, the problems of high cost and high time consumption of a first principle calculation method are solved, a feasible method is provided for metal matrix composite material potential function training, and the method is suitable for popularization and application. The method is suitable for constructing an inter-atomic potential function for metal matrix composite materials with different matrixes and different reinforcement bodies, and can describe the dynamic deformation and damage evolution process of the atomic scale after a system is subjected to an external load from the atomic scale, including behaviors such as dislocation initiation and movement, grain boundary slippage, crack propagation and interface failure. And a theoretical basis is provided for damage mechanism research and molecular dynamics simulation of the metal-based composite material.

The invention relates to a reaction force field construction method, system and equipment for molecular dynamics simulation, belongs to the technical field of computational chemistry and material simulation, and solves the problems that in the prior art, a reaction force field construction method is insufficient in physical precision when describing short-range strong repulsion among atoms; and the efficiency is low when parameterization is carried out on a high-precision physical model. Comprising the steps of obtaining a first principle potential energy data set in a preset atom short distance range based on a target multi-body atom group; wherein elements in the first principle potential energy data set are distance vectors and multi-body interaction potential energy corresponding to the distance vectors; training a selected machine learning model on the basis of the first principle potential energy data set to obtain a potential energy agent model, and then obtaining an optimal short-range potential function by adopting Bayesian optimization on the basis of a selected potential function; and based on the optimal short-range potential function and the potential function of the reference reaction force field, a mixed potential function of the target multi-body atomic group is obtained, and construction of the reaction force field is completed.