24 results about "Molecular simulation" patented technology

The present invention efficiently calculates molecular energy corresponding to a plurality of interatomic distances.　An information processing device (10) estimates, for interatomic distances (14a, 14b, 14c), estimated execution times (15a, 15b, 15c) and estimated repetition counts (16a, 16b, 16c) of an algorithm that calculates molecular energies using quantum circuit data, on the basis of molecular information (13). The information processing device (10) determines repetition counts (18a, 18b, 18c) for the interatomic distances (14a, 14b, 14c) on the basis of a restriction time (17), the estimated execution times (15a, 15b, 15c), and the estimated repetition counts (16a, 16b, 16c). The information processing device (10) calculates, by executing the algorithm, molecular energies (19a, 19b, 19c) for the interatomic distances (14a, 14b, 14c) on the basis of the repetition counts (18a, 18b, 18c).

This invention relates to a method for constructing a machine learning potential energy model based on hierarchical active learning, comprising the following steps: constructing a database of background solvent molecules and lithium salt molecules; initializing a machine learning potential energy model committee; outer active learning automatically exploring the chemical species composition space of the electrolyte, generating electrolyte formulations and initial structures; determining whether a structure needs to be included in the labeling range based on uncertainty calculations; automatically constructing a liquid phase environment based on classical force field simulation methods; performing high-precision simulations based on first-principles calculations and labeling the energy and force values ​​of the structures; inner active learning driving the machine learning potential energy model to explore the configuration space and label the energy and force values ​​of structures with high uncertainty; obtaining a first-principles structure database of the real liquid phase environment through several iterations; and training to obtain the final high-performance machine learning potential energy model. This invention systematically and comprehensively samples the chemical species composition space of the electrolyte and the molecular simulation configuration space based on hierarchical active learning, thereby ensuring the predictive performance and simulation accuracy of the machine learning potential model on unknown and complex electrolyte systems.

The application discloses a rubber-cement composite material surface modifier optimization method based on molecular simulation, which comprises the following steps: based on molecular dynamics simulation, a full-atom numerical model for characterizing the physicochemical properties of cement matrix, rubber and modifier material is constructed by using Materials Studio software; based on the full-atom numerical model, the Gibbs free energy of the material system is calculated by using a quantum mechanics method to predict whether chemical reaction or physical adsorption behavior occurs between the selected modifier and the two types of materials of rubber and cement, and finally a rubber-cement-based composite material system model before and after the treatment of the modifier is constructed; the free volume fraction and atomic concentration of the composite material system model before and after the modification are analyzed on a microscale to quantitatively evaluate the effect of the modifier on the material performance, and then the optimal surface modifier is determined. The application can construct a numerical model accurately reflecting the material properties and analyze and optimize the material surface / interface modifier.

The application discloses a method and device for determining gas storage efficiency of a hydrate promoter, the method comprising: constructing a gas-liquid two-phase molecular simulation system, the molecular simulation system comprising a filled gas box and a water solution box spliced in sequence along a set direction; inputting a plurality of test parameter groups into the gas-liquid two-phase molecular simulation system to form parameter regulation under a multivariate grid simulation framework, and realizing simulation of hydrate nucleation or growth of a gas; obtaining trajectory data of molecular dynamics simulation in the process of simulation of hydrate nucleation or growth of the gas, the trajectory data comprising the number of newly formed hydrate cages, the mass of the gas, the promoter and water in the hydrate within a set sampling time; and calculating the gas storage efficiency of the hydrate under the action of the promoter according to the trajectory data of the molecular dynamics simulation and a pre-constructed gas storage efficiency mathematical model. Based on the calculation result of the gas storage efficiency of the hydrate, the reliability of the promoter screening can be improved, and the screening process of the promoter can be accelerated.

The present application belongs to the field of computational chemistry and molecular simulation technology, and relates to a kind of aromatic eutectic solvent multiscale molecular simulation screening method and system based on multi-objective collaborative scoring model.Establish target molecule model library and eutectic solvent candidate component library;Quantum chemistry calculation is carried out on target molecules and eutectic solvent candidate system, and quantum chemistry descriptors are extracted;Molecular dynamics simulation system is constructed, and molecular dynamics descriptors such as aromatic space enrichment coefficient Kπ, glycosidic bond interaction index Ggly and lignin bond type affinity index Lβ are extracted;Multi-scale feature vectors are obtained by normalization processing, input into multi-objective collaborative scoring model, calculate and extract score SE, grading score SF, and judge and output active ingredient extraction priority, lignocellulose grading priority or segmented collaborative processing mode.The present application is suitable for eutectic solvent calculation screening and application mode discrimination when there is a target conflict between plant aromatic active ingredient extraction and lignocellulose grading treatment.

The application discloses a construction system of a hydrate promoter gas-liquid two-phase molecular simulation system, which comprises a structure generation unit, a partition construction unit and a gas-liquid splicing unit.

This application discloses a method and apparatus for predicting the electrical risk of oil-paper insulated equipment. The method includes: acquiring multiple oil and gas sample data with labels and confidence levels from the oil-paper insulated equipment at different time windows; generating a molecular model formulation of the mixture; constructing a molecular simulation mixture model of the mixture formulation at the current temperature; and performing geometric optimization, model annealing, and ensemble balancing to obtain a steady-state model. The method then calculates the total dipole moment of the molecular dynamics system of the steady-state model and the dielectric loss factor, using the planned quantitative value of the dielectric loss factor to assess the degree of electrical risk of the oil-paper insulated equipment. Therefore, this method provides a mechanistic and quantitative mapping from monitoring data to electrical risk, accurately calculates real-time dielectric parameters, considers individual equipment differences, quantifies risk values, and classifies them, improving the accuracy of early degradation identification and thus enhancing the accuracy of electrical risk monitoring for oil-paper insulated equipment.

This application discloses an analytical method for electrolyte systems based on low-scaling Monte Carlo simulations of electrostatic interactions, relating to the field of molecular simulation technology. The method includes: constructing an initial model of the target system and configuring simulation parameters; initializing local electric displacement auxiliary field variables; using these variables to describe the local electric displacement state of the target system; randomly selecting and updating an object; the updated object being the particle configuration and / or the local electric displacement auxiliary field variables; determining the equivalent local electric field strength at the target spatial location after updating the object; updating the local dielectric constant at the target spatial location based on the equivalent local electric field strength; and after updating the local dielectric constant, determining the various electrostatic interaction energies in the target system and evaluating the total electrostatic energy. This method can accurately describe the complex electrostatic interactions between components caused by local electric fields, high charge density, and the dielectric response properties of the components while ensuring computational efficiency.

The application discloses a kind of electrochemical reaction driven proton conduction simulation method, it relates to molecular simulation technical field.The application includes: constructing PEM solution structure model and bipolar plate structure model;PEM solution structure model, bipolar plate structure model is sequentially arranged along the height direction of simulation box, and BPP / / PEM sandwich structure model is obtained;Annihilation region and generation region are set in the region of proton exchange membrane close to cathode and anode respectively;Delete proton in annihilation region and randomly generate equivalent proton in generation region, to simulate the charge transfer process of bipolar plate structure model and external circuit;The occurrence number of proton hopping molecular simulation process and the distribution state of proton in system are counted, and the conduction performance of proton under different conduction paths is evaluated based on the statistical result.The application not only reproduces the proton conduction phenomenon, but also reveals the internal correlation between transmission characteristics and structural characteristics from nanometer level.

This invention discloses a method for obtaining interface thickness parameters based on a microscopic all-atom composite model, belonging to the field of molecular simulation. First, using MS software, a periodic model of polymer A and polymer B with local energy minimization is constructed. After combining the two, geometric optimization and kinetic equilibrium optimization are performed to obtain a globally energy-minimized all-atom composite model. Finally, using secondary programming techniques in the Perl script module of MS software, the atomic concentration distribution data points of the all-atom composite model are calculated, the atomic concentration distribution curve is plotted, and smoothing is performed. A criterion for determining the presence of interface thickness in the all-atom composite model is set to determine whether interface thickness exists. A formula for calculating the interface thickness of the all-atom composite model is defined to calculate the interface thickness of the all-atom composite model with interface thickness, thereby quickly, efficiently, accurately, and quantitatively calculating the interface layer thickness of the polymer composite material. Furthermore, this invention also has the advantages of convenient operation.

The application relates to a method for constructing a quantitative structure-activity relationship of a dendrimer molecular structure and salt tolerance and application. According to the quantitative structure-activity relationship, the salt tolerance of an oil field chemical polymer can be obtained according to the molecular structure of the dendrimer, without needing to pass through traditional experiments or complicated molecular simulation dynamics calculation. Meanwhile, the quantitative structure-activity relationship can be used to quickly screen the dendrimer with good salt tolerance, and has a good reference significance for the rapid design and research and development of the salt-resistant polymer for drilling fluid and even oil field chemicals.

The application discloses a method for screening and extracting DES of tea saponin based on molecular simulation and machine learning, and relates to the technical field of tea saponin extraction, which comprises the following steps: constructing a molecular model of tea saponin, cellulose, a hydrogen bond donor, a hydrogen bond acceptor and a DES and optimizing the molecular model to obtain a molecular polarity index; generating a topological structure, obtaining a trajectory and energy through MD simulation, and calculating E(TeaS-DES), E(TeaS-Cells) and SI; determining an extraction rate, combining the molecular polarity index, SI and process parameters to construct a data set, training a machine learning model, predicting the extraction rate and locking the optimal DES and process. The application can directly guide the screening of DES by using simulation energy and structure descriptors, reduces the number of experiments and shortens the research and development cycle.

This invention discloses an estrogen receptor target identification and toxicity prediction system and its operation method based on graph neural networks and molecular simulation technology. The system converts compound structures into molecular graphs, constructs atomic node features and chemical bond edge features / types, inputs these into a graph neural network for characterization learning, and outputs the binding probabilities of estrogen receptor subtypes such as ESR1, ESR2, and GPER1, as well as predicted toxicity endpoints such as logAC50 / AC50. Based on the predicted target, the system automatically selects the receptor structure and adaptively generates docking box parameters. It then calls AutoDock Vina to complete molecular docking to obtain binding energies and optimal conformations. The system also displays the three-dimensional complex, interaction statistics, public database annotation information, and toxicological explanations based on a large language model in an interactive interface. This system achieves a high-throughput, interpretable, integrated "prediction-docking-annotation" analysis workflow for ER targets.

This invention discloses a method, apparatus, device, and storage medium for determining shale relaxation time, comprising: simulating a pre-defined molecular simulation model in a pre-set experimental simulation environment to obtain the inter-pair distance and inter-pair angle of hydrogen proton pairs in the molecular simulation model; obtaining the residual dipole coupling relaxation time based on the inter-pair distance and inter-pair angle; and obtaining the transverse relaxation time based on the residual dipole coupling relaxation time and the theoretical relaxation time. The shale relaxation time determination method, apparatus, device, and storage medium disclosed in this application solve the problem of uncertainty or significant mismatch between the pore size distribution derived from the transverse relaxation time based on NMR theory and the actual pore size distribution. This allows for a more accurate reflection of the actual pore size distribution through the calculation of the residual dipole coupling relaxation time under nano-constraint effects, thereby ensuring the accuracy of shale oil reservoir evaluation.

The present invention efficiently calculates molecular energy corresponding to a plurality of interatomic distances.　An information processing device (10) estimates, for interatomic distances (16a, 16b, 16c, 16d), execution times (17a, 17b, 17c, 17d) of algorithm (13) for calculating molecular energy using quantum circuit data. The information processing device (10) determines an interatomic distance group (16) on the basis of a limit time (17) and the execution times (17a, 17b, 17c, 17d). The information processing device (10) calculates molecular energies (18c, 18d) by executing the algorithm (13) on the interatomic distances (16c, 16d) included in the interatomic distance group (16). The information processing device (10) outputs: the molecular energies (18c, 18d); and molecular energies (18a, 18b) that correspond to the interatomic distances (16a, 16b) not included in the interatomic distance group (16) and that are calculated by algorithm (14).

The application adopts a method for identifying a thermal response characteristic temperature zone of heavy oil aggregation structure based on molecular simulation, identifies the thermal response characteristic temperature zone of heavy oil aggregation structure by processing trajectory data, and belongs to the technical field of computational material science, molecular simulation and heavy oil flowability evaluation. The method comprises the following steps: obtaining component composition and experimental characterization parameters of a heavy oil sample, constructing a representative SARA four-component heavy oil molecular model; setting different temperature conditions and performing molecular dynamics simulation; calculating the viscosity, diffusion coefficient, solvent accessible surface area, pi-pi stacking aggregate size, aggregate cohesive energy and interaction energy between the aggregate and surrounding molecules of the heavy oil from the simulation trajectory; and determining the thermal response characteristic temperature zone of the heavy oil aggregation structure according to the progressive response relationship between the above indexes. The application can quantitatively identify the thermal response transition characteristics of the heavy oil aggregation structure from the molecular scale, and provide a molecular scale basis for temperature window division and subsequent flowability regulation in the process of multi-element thermal combination flooding.

The application provides a molecular simulation method for the mechanism of drilling fluid treating agent / solvent, comprising the following steps: constructing a drilling fluid treating agent / solvent binary system model; determining force field parameters and simulation parameters of the drilling fluid treating agent and the solvent molecules; sequentially performing dynamic equilibrium of the drilling fluid treating agent / solvent binary system under NVT ensemble and NPT ensemble according to the force field parameters and the simulation parameters; after the drilling fluid treating agent / solvent binary system reaches the specified temperature and pressure parameters, performing molecular dynamics simulation on the drilling fluid treating agent / solvent binary system under NPT ensemble, taking the last trajectory file to calculate dynamic parameters, and completing the micro evaluation of the drilling fluid treating agent binary system. The application can characterize the law of the interaction between the water-based drilling fluid treating agent and water molecules under high temperature and high pressure conditions from the atomic scale, and can in-situ characterize the micro dynamics of the treating agent molecules under high temperature environment, thereby reducing the experimental cost.

This invention discloses a method for calculating the interfacial tension of oil and water within nanopores, belonging to the field of molecular simulation and interface physics. The method includes: constructing an oil-water two-phase model in a silica nanochannel; applying equal and opposite external forces to the oil and water phases to perform all-atom molecular dynamics simulation; after the simulation, identifying interface atoms using a sliding window method based on atomic trajectory data, and combining quadratic curve fitting and effective frame screening to reconstruct the geometry of the oil-water interface with high precision; finally, calculating the interfacial tension according to the mechanical equilibrium formula, where θ is determined by the tangent of the fitted curve at the nearest neighbor of the wall. This invention avoids the low resolution problem of traditional density profiling methods at the nanoscale, significantly improving the accuracy of interface positioning and the reliability of tension calculation, and is suitable for quantitative research on nano-percolation behavior in unconventional oil and gas resources.