201 results about "Molecular model" patented technology

The invention discloses a drug target interaction prediction method based on a protein sequence. The method comprises the following steps: constructing a drug target database; constructing a target feature extractor based on a pre-trained protein language model; constructing a drug feature extractor based on a pre-trained molecular model; constructing a feature learning method by adopting a self-attention mechanism, constructing a drug target interaction learning method by adopting a cross attention mechanism, constructing a predictor in combination with a linear layer, and constructing a prediction drug target interaction model; training and optimizing parameters of the drug target interaction prediction model to obtain an optimized drug target prediction model; inputting a drug target into the optimized prediction model, outputting a prediction result, and finally marking potential active sites and important amino acid residues of the drug and the target through attention score visualization. According to the method, the precision of predicting the interaction between the drug and the target spot based on the protein sequence is improved, and the interpretability of the deep learning model is realized.

The invention relates to the technical field of carbon dioxide sequestration and shale gas development, and particularly discloses a shale micro-nano pore multiphase multicomponent competitive adsorption data determination method and device, and the method comprises the steps: obtaining a shale core sample of a target area, and determining the type and relative content change characteristics of surface functional groups of the shale core sample; key structures and force field parameters of shale clay minerals in a target block are collected, and a shale clay mineral molecular model is established; establishing a plurality of fluid molecular models; establishing slit models, and establishing a multiphase fluid system model between the slit models to obtain a stable configuration; applying an external electric field to the stable configuration, and performing molecular dynamics calculation to obtain molecular trajectory coordinates and dynamics information of the multi-phase multi-component fluid; and calculating competitive adsorption data of the shale micro-nano pore multi-phase multi-component fluid under the action of the electric field. According to the scheme, the occurrence state and the competitive adsorption behavior of the shale micro-nano pore multi-phase multi-component fluid under the action of the electric field can be disclosed from the molecular scale.

The present invention discloses a method for predicting electrolyte performance, comprising: constructing a molecular model of each component according to the formula of the electrolyte to be tested; determining a matching force field form; constructing an electrolyte model to be tested; performing molecular dynamics simulation on the electrolyte model to be tested, setting the simulated temperature to gradually decrease from room temperature to obtain a simulated electrolyte system to be tested; determining the probability of occurrence of each solvation configuration of each component in the simulated electrolyte system to be tested in the overall configuration of all components; determining the desolvation energy barrier of each solvation configuration according to first principles; determining the average desolvation energy barrier corresponding to the simulated electrolyte system to be tested according to each desolvation energy barrier of each solvation configuration and the probability of occurrence of each solvation configuration in the overall configuration; determining the low-temperature performance of the electrolyte to be tested according to the average desolvation energy barrier. The above method predicts low-temperature performance more accurately. Also disclosed is an electrolyte performance prediction device, an electronic device, and a storage medium.

The invention relates to the technical field of quality analysis of plastic packaging materials, and particularly discloses a quality analysis method of a plastic packaging product, which comprises the following steps of: acquiring chemical composition information of a target material by adopting Fourier transform infrared spectroscopy and thermogravimetric analysis, and constructing an atomic-scale three-dimensional molecular model on the basis of polymer types and auxiliary ratio; auxiliary agent diffusion behaviors are simulated and tracked through molecular dynamics, and key transmission parameters are obtained; importing the parameters into a finite element model, establishing a multi-physics field coupling migration simulation model, and simulating the migration trends of the assistants under different environmental conditions; establishing a quantitative correlation model to predict the long-term stability of the material by combining accelerated aging experiment data; according to the method, the prediction precision of the service life and the function stability of the plastic packaging material is improved, the research and development cost is reduced, and the product quality consistency and the market competitiveness are improved.

The invention belongs to the technical field of oil displacement of oil fields, and particularly relates to a molecular dynamics simulation method for substitution and adsorption characteristics of an oil-water interface. The simulation method is provided through substitution and adsorption of water-soluble chemical agent molecules to oil-phase active molecules on an oil-water interface, after a water-soluble chemical agent molecular model is added to a first target cubic box, molecular dynamic equilibrium simulation is carried out on a system, and the water-soluble chemical agent molecular model is obtained. Hydrophobic groups in the water-soluble chemical agent molecular model are inserted into an oil molecule cubic box due to hydrophobicity, and hydrophilic groups are substituted and adsorbed with water molecules at an oil-water interface. Molecular dynamics simulation is carried out on the water-soluble chemical agent by adjusting the type and concentration of the water-soluble chemical agent and factors such as temperature and pressure of a simulation environment, so that the competition efficiency of the water-soluble chemical agent is improved; by analyzing the interaction between the water-soluble chemical agent and the oil-phase active component and the water, the action strength between the water-soluble chemical agent and the oil-phase active component and the water is evaluated on the microscopic level, and the action mechanism of the substitution adsorption behavior is revealed.

The invention discloses a high-flux molecular modeling method of an asphalt binder. The method comprises the following steps: creating an asphalt binder component molecular library; according to given modeling requirements, component molecules of the asphalt binder component molecule library are randomly extracted, and an asphalt binder model is generated through modeling; on the basis of topological information of an asphalt binder model, according to a molecular simulation CVFF empirical force field, determining bonding categories of component atoms of the asphalt binder so as to determine atomic simulation force field parameters; and finally, outputting a data file of the asphalt binder model according to a set format requirement. According to the method, the initial model construction of the asphalt binder model and the automatic generation of the atomic scale simulation file are realized, the workload of manual modeling is reduced, the modeling requirement can be automatically processed, the asphalt binder molecular model can be automatically generated, and the model creation speed is improved.

The invention relates to the field of federated learning and molecular discovery, in particular to a multi-party cooperation federated learning model method for molecular discovery. The invention discloses a multi-party cooperation federation learning model method for molecular discovery. A heterogeneous difference privacy technology is introduced into each local client, and it is ensured that molecular local model parameters are protected in the training process. Next, the protected local model parameter information is uploaded to a central server, projection transformation and weighted averaging are carried out through a Lanczos algorithm, and finally new global model parameters are generated and released to a client for multiple times of communication updating training; according to the method, the privacy protection problem of different molecular data sources is effectively solved by utilizing heterogeneous differential privacy, so that the privacy of the molecular data is guaranteed; and meanwhile, a Lanczos algorithm is adopted to carry out projection transformation to optimize a molecular model fusion mode in a multi-party cooperation process, new global model parameters are generated, and the prediction accuracy of the molecular model can be improved.

The invention discloses a biomass pyrolytic reaction network prediction method based on a graph theory and quantum chemistry, which comprises the following steps: analyzing the molecular structure of a biomass initial reactant, abstracting the molecular structure into a directed graph molecular model, marking a potential conversion path after molecular mechanics optimization, generating a unique identifier by using an atom numbering rule and a Hash algorithm, and predicting the biomass pyrolytic reaction network. Functional groups are extracted and packaged into sub-graph modules, chemical bond parameters are obtained in combination with quantum chemistry calculation and are converted into fracture probabilities, basic reaction building blocks are predefined to traverse and mark breakable bonds, fragments are recombined and then de-weighted through Hash, and then reaction activation energy weights are given to side chemical bond fracture reactions; an energy optimal path is screened by means of a priority queue search algorithm, accurate analysis of a chemical bond fracture path and intermediate product conversion in the biomass pyrolysis reaction network is finally achieved, reaction path and product distribution are efficiently predicted, and the calculation efficiency and precision of a complex system are balanced.

The invention relates to a method for constructing polyurethane molecular models with different crosslinking uniformity degrees, and belongs to the technical field of molecular dynamics simulation. According to the method, an initial amorphous structure is constructed through Packmol and Lammpps software, dynamic relaxation is carried out, a Python script is combined to simulate cross-linking reactions of isocyanate and polyol in different space lattices, the cross-linking cutoff distance and a reaction area are controlled, and regulation and control of the local cross-linking degree are achieved. According to the method, the average crosslinking degree and the crosslinking distribution uniformity coefficient can be calculated, the spatial non-uniformity of a crosslinking network can be quantitatively described, the method is suitable for researching the influence of factors such as high temperature, nano filler introduction or non-uniform mixing of a reaction system and the like on the structural performance of polyurethane, and the technical blank in the aspect of non-uniform crosslinking model construction is filled.

The invention discloses an input-output method and system realized based on a calculation engine in the coal chemical industry, and relates to the technical field of coal chemical industry, and the method comprises the steps: building a molecular model based on a reaction network of a coal molecular structure, and updating the parameters of the molecular model in real time through extended Kalman filtering; constructing a data fusion layer through a hybrid modeling technology, and constructing a coal chemical industry residual learning architecture by using a mechanism model and a neural network series structure; evaluating a data-driven model prediction confidence interval according to a Monte Carlo method; a digital twin verification platform is constructed based on hardware-in-the-loop test, and a data-driven adaptive iteration mechanism is constructed through an online and offline collaborative updating mechanism. The method has the beneficial effects that the medium component fluctuation is accurately captured, the output accuracy is improved, reliable evaluation dependence is provided, and the real-time response force and long-term stability of the system in a complex environment are improved.

The invention discloses a molecular dynamics simulation method for CO2-ion oil displacement, and belongs to the technical field of CO2 oil displacement. The method comprises the steps that an oil molecule model, a water molecule model, a CO2 molecule model, a CaCl2 molecule model and a graphene plate model corresponding to target oil reservoir characteristics are established; carrying out geometric structure optimization on each model; the optimized molecular model is assembled into a 'CO2-CaCl2-H2O' ternary displacement system, and molecular dynamics simulation is executed; during simulation, an NVT ensemble is selected, periodic boundary conditions are applied, a COMPASS II force field is adopted, atomic potential parameters are configured, and after operation energy is minimized and temperature is initialized, displacement process simulation is executed; and quantitatively evaluating the oil displacement effect of the displacement medium of the 'CO2-CaCl2-H2O' ternary system on the basis of the trajectory file output by simulation. According to the method, the behavior of molecules under the synergistic effect of multiple displacement media can be better explained, the oil displacement micromechanism under the synergistic effect of the multiple displacement media is embodied, and the method has important significance for optimizing the compact oil reservoir development effect and improving the recovery efficiency.

The invention provides a method for predicting a polyimide stress threshold. The method comprises the following steps: 1) constructing a polyimide full-atom molecular model by adopting molecular simulation software; 2) performing mechanical tensile simulation on the molecular model to calculate a stress-strain curve; 3) calculating a creep curve of the molecular model under different constant stresses according to a stress-strain curve calculation result, and determining a mechanical failure interval according to the creep curve; and 4) selecting different stress values in a mechanical failure interval by using a dichotomy to carry out creep curve iteration, and finally determining a stress threshold. The method provided by the invention not only can efficiently predict the stress thresholds of the polyimides with different structures, but also can simulate and analyze the creep behavior of the polyimides in the tensile stress process, and provides a theoretical basis for guiding the structural design and mechanical property optimization of polyimide materials.

The invention provides a molecular simulation method and device for interaction behaviors of vulcanized rubber powder and asphalt, and relates to the technical field of molecular simulation, and the method comprises the following steps: respectively constructing a rubber powder molecular model and an asphalt molecular model through molecular simulation software; establishing a rubber powder modified asphalt system model according to the rubber powder molecular model and the asphalt molecular model; distributing molecular force fields to the rubber powder molecular model, the asphalt molecular model and the rubber powder modified asphalt system model; performing energy minimization processing and relaxation operation on the rubber powder modified asphalt system model, and calculating thermodynamic parameters and particle motion trails of the rubber powder modified asphalt system model; and evaluating the interaction effect of the vulcanized rubber powder and the asphalt according to the thermodynamic parameters and the particle motion trail of the rubber powder modified asphalt system model. According to the molecular simulation method, the interaction between the vulcanized rubber powder and the asphalt is systematically explained from the molecular level.

The invention relates to the technical field of building construction, and provides a high polymer grouting material-concrete interface molecular model construction method which comprises the following steps: constructing an initial PU model, and performing molecular dynamics simulation and full-atom simulation on the model; performing energy minimization and dynamic balance K by adopting an NVT and NPT ensemble; performing crosslinking simulation on the PU model, performing multiple crosslinking cycles at 300K by modifying chemical bonds and adjusting crosslinking degree, and loosening to a stable state under NPT ensemble; constructing a calcium silicate hydrate model, and performing molecular dynamics simulation by using a CSH-FF force field; and combining the PU model with the calcium silicate hydrate model, and performing energy minimization and dynamic balance to complete model construction. Through a molecular dynamics simulation method, the limitation of a traditional experimental technology is broken through, and scientific theoretical support and practical guidance are provided for design of a high polymer grouting material and enhancement of a concrete structure.

The invention relates to the field of oil reservoir exploration and development, and discloses a heavy oil micromechanism characterization method and device, a storage medium and a processor, and the method comprises the following steps: determining the molecular composition of a heavy oil sample and the content of each molecule; classifying the molecules based on the features of the molecules to obtain a classification result, and selecting at least one target molecule from each category of the classification result; establishing a heavy oil system molecular model based on a heavy oil simulation system composed of the target molecules; based on the thickened oil system molecular model and a pre-established mineral pore molecular model, establishing a thickened oil system flow model; and determining the thickened oil micromechanism according to the simulation result of the thickened oil system flow model. Based on the scheme of the application, the similarity degree of properties between the thick oil simulation system and the real thick oil system can be improved, so that the accuracy of the subsequent micro simulation result of the thick oil can be improved, and the accuracy of the obtained thick oil micro mechanism can be improved.

The invention relates to the technical field of nanofluid enhanced heat transfer simulation, in particular to a molecular dynamics-based mixed nanofluid heat transfer characteristic analysis method, which comprises the following steps of: constructing a molecular model comprising copper, graphene nanoparticles and an ionic liquid / water mixed base solution, and calculating the heat transfer characteristic of the mixed nanofluid through a distribution potential function and a periodic boundary condition; and performing energy minimization and molecular dynamic relaxation to achieve thermodynamic equilibrium. A steady-state temperature gradient is established based on the unbalanced molecular dynamics principle, and the thermal conductivity is calculated according to the Fourier law. Microcosmic parameters such as a radial distribution function, mean square displacement and the number of hydrogen bonds are synchronously analyzed, and a coupling mechanism of interaction and heat transfer performance of the nano-particle-base fluid interface is disclosed. According to the method, the heat transfer characteristic of the mixed nanofluid can be clarified on the molecular scale, and an efficient and reliable analysis means is provided for nanofluid screening and design in application of a solar heat collector, a heat management system and the like.

To provide a method enabling creation of a polymer material model having a crosslinked structure close to reality.SOLUTION: A method for creating a polymer material model is provided. The creation method includes: a first step S1 of inputting, to a computer, a pre-crosslinking coarse grained molecular model in which a structural unit of a molecular chain before crosslinking is substituted with coarse grained particles; a second step S2 of analyzing the molecular chain after crosslinking; a third step S3 of inputting, to the computer, a chemical structure of the structural unit after crosslinking on the basis of a result of the analysis; a fourth step S4 of inputting, to the computer, a post-crosslinking structural unit model in which the chemical structure of the structural unit after crosslinking is modeled as an entire atomic model or a united atom model; a fifth step S5 of the computer calculating structural relaxation based on a molecular dynamics method for the pre-crosslinking coarse grained molecular model; and a sixth step S6 of the computer allocating a post-crosslinking structural unit model to the coarse grained particles of the pre-crosslinking coarse grained molecular model after the structural relaxation, to create a post-crosslinking molecular model in which the molecular chain after crosslinking is modeled as the entire atomic model or the united atom model.SELECTED DRAWING: Figure 3

The invention discloses a prediction method, and particularly relates to a protein DNA binding tendency prediction method based on a multi-modal biomolecular model, which comprises the following steps: S1, inputting a protein sequence; s2, predicting a three-dimensional structure; s3, secondary structure calculation is carried out; s4, calculating the accessibility of the solvent; s5, performing protein function annotation; s6, generating feature representation; step S7, sample representation; s8, obtaining a training set; s9, generating all protein residue samples; step S10, constructing a protein map; step S11, building a graph neural network; step S12, adjusting through a convolutional layer; step S13, training and storing the model; and step S14, outputting a PWM matrix. The invention relates to a protein DNA binding tendency prediction method based on a multi-modal biomolecular model, which can reduce the calculation cost of the existing protein DNA binding tendency prediction method and improve the recognition accuracy.

The invention discloses a molecular simulation-based method for estimating CO2 / CH4 adsorption capacity in a shale reservoir, which comprises the following steps of: firstly, selecting different mineral components from the shale reservoir, and determining reservoir temperature and pressure corresponding to each mineral component; the method comprises the following steps: constructing molecular models of different mineral components in a shale reservoir and a to-be-detected gas molecular model by using molecular simulation software, and carrying out geometric optimization; setting temperature and pressure conditions conforming to the actual reservoir in the simulation environment, and introducing gas molecules to perform molecular dynamics simulation so as to research the competitive adsorption behavior and obtain adsorption quantity data; based on simulation data, an adsorption capacity calculation expression comprehensively considering the coupling influence of multiple factors such as temperature and pressure is established, and the actual shale reservoir gas adsorption capacity is rapidly and accurately estimated. Through molecular simulation, the limitation that a traditional experiment is long in period, high in cost and difficult to separate multi-factor influences is overcome, and an efficient and reliable theoretical tool is provided for shale gas reserve prediction and carbon dioxide geological storage benefit evaluation.

The invention provides a coal surface wettability prediction method based on a molecular dynamics simulation technology, and the method comprises the steps: constructing a coal macromolecular model, carrying out geometric structure optimization and annealing dynamics simulation, carrying out the section processing of the model, introducing a vacuum layer, and constructing a coal surface model with a preset density; performing isothermal adsorption simulation on the coal surface model, constructing a water ball model with a preset diameter, placing the water ball model on the coal surface after gas adsorption to form a coal-gas-water three-phase composite model, performing geometric structure optimization treatment on the coal-gas-water three-phase composite model, and selecting the model with the lowest energy after optimization; performing NVT ensemble molecular dynamics simulation on the coal-gas-water three-phase composite model to obtain a movement track of a water ball on the coal surface after the system is balanced; and selecting the last frame of balanced snapshot from the motion trail for analysis, selecting the vicinity of the contact point of the water polo and the base in the snapshot, making a tangent line along the contour of the water polo, and measuring the included angle between the tangent line and the base line.

A method and system for component deconvolution through a hybrid model based on methylation information is disclosed. The hybrid model may be trained in a manner independent of marked or known component contributions. The system generates a methylation feature for each training sample of a plurality of training samples. The methylation signature may be based on counts or percentages of methylation variation (s) expressed in methylation sequence reads of the training sample at each of the plurality of genomic regions. The system may train the hybrid model using maximum likelihood estimates to deconvolve component contributions. The hybrid model may include a group sub-model and a deconvolution sub-model. The compositional molecular model predicts compositional likelihood based on methylation characteristics. The deconvolution sub-model predicts component contributions based on component possibilities.

The invention discloses a foamed rubber asphalt formula determination method. The method comprises the following steps: S1, constructing a molecular model of a foamed rubber asphalt composite system; s2, performing molecular dynamics simulation on the molecular model to obtain a balanced stable structure configuration; s3, based on the stable structure configuration, under the conditions of different rubber mixing amounts, foaming medium mixing amounts and temperatures, calculating the shear modulus, interface adhesion work and fracture energy of the foam rubber asphalt system; and S4, performing multi-objective optimization by taking the shear modulus, the interface adhesion work and the fracture energy as performance indexes, and determining a combination of the temperature, the foaming medium mixing amount and the rubber mixing amount of the optimal formula of the foamed rubber asphalt. According to the method, the combination of the foaming temperature, the foaming medium mixing amount and the rubber mixing amount is determined through molecular modeling and a multi-objective optimization algorithm, and performance prediction and parameter optimization of the foamed rubber asphalt are achieved.

The invention discloses a method for analyzing the dynamic evolution process of a methane leakage nano-channel in cold spring hydrate, and belongs to the field of natural gas hydrate science and engineering. The method comprises the following steps: constructing a hydrate molecular model and selecting a methane and water molecule force field; a hydrate block and a middle gas channel are arranged in the simulation box, and the gas channel is filled with a methane and water mixture to construct an initial simulation system; performing molecular dynamics simulation on the system under the conditions of energy minimization, pre-balance and different pressures and methane accelerations, and remodeling a gas channel dynamic evolution process in a hydrate growth process; carrying out analysis and three-dimensional rendering on the simulated track, and drawing a three-dimensional morphology graph of the gas channel changing along with time; quantitatively extracting surface area data of the gas channel, and calculating key kinetic parameters, including attenuation rate and half-life period, of the evolution process of the gas channel. According to the invention, the quantitative characterization of the dynamic evolution process of the methane leakage nano-channel in the cold spring environment is systematically realized on the molecular scale for the first time, and the contraction closing behavior of the gas channel under the condition of no methane leakage and the dynamic maintaining or adjusting process of the gas channel under the condition of continuous seepage can be accurately simulated and distinguished; the limitation of a traditional static pore model is overcome, and key basic parameters and method support are provided for revealing the interaction mechanism of methane migration and hydrate growth and constructing a cross-scale seepage model.

The invention provides a micro-scale steady-state meniscus model construction method and device, equipment and a medium, and belongs to the field of micro-scale in-pore flow simulation calculation. According to the method, a micro-scale pore meniscus molecular model containing an upper flat plate, a lower flat plate and a left fixed flat plate is constructed, and liquid is filled in the micro-scale pore meniscus molecular model; the method comprises the following steps: performing energy minimization to obtain a liquid static structure, moving a flat plate to obtain a steady-state structure, performing stress analysis on the steady-state meniscus structure, and counting horizontal tangential force borne by the flat plate under the unit length of a liquid-solid interface within preset time. By constructing the micro-scale pore meniscus molecular model, fluid dynamic behaviors of a three-phase contact line area under the micro-scale can be simulated, data which is difficult to obtain in experiments such as a three-phase interface liquid molecule migration mechanism and the like can be obtained, and the problem that a current experimental method is difficult to reveal a micro-nano liquid-solid interface flow mechanism is solved.

The invention 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.The method comprises the steps that tea saponin, cellulose, a hydrogen bond donor, a hydrogen bond receptor and a DES molecular model are constructed and optimized, and a molecular polarity index is obtained; the method comprises the following steps: generating a topology, obtaining a trajectory and energy through MD simulation, and calculating E (TeaS-DES), E (TeaS-Cell) and SI; and measuring the extraction rate, combining the molecular polarity index, SI, process parameters and the like to construct a data set to train a machine learning model, predicting the extraction rate, and locking the optimal DES and process. According to the method, DES screening can be directly guided through simulated energy and structure descriptors, the number of experiments is reduced, and the research and development period is shortened.

The invention discloses a VR-based protein sequence multi-user collaborative design method and system, a client and a storage medium, and the method comprises the steps: obtaining and analyzing a protein structure file of a protein sequence, and obtaining protein structure data; performing editing operation on chemical bonds and atoms of the protein sequence according to the protein structure data, and performing optimization adjustment by using a molecular model minimization algorithm; converting the amino acid structure data and the protein structure data into a directed graph by adopting a breadth-first search algorithm, and identifying and connecting amino groups and carboxyl groups based on the directed graph; and performing modeling and rendering according to the target protein structure file, generating a target three-dimensional model, and presenting the target three-dimensional model in user interfaces of all users. According to the method, protein sequence design, molecular modeling, optimization calculation and virtual reality interaction are integrated, multi-user collaborative design and remote interaction functions are supported, and the interaction efficiency and intuition of protein sequence design and connection are remarkably improved.

The application discloses a screening method of a phosphogypsum flotation collector, and comprises the following steps: providing a molecular structure of the collector, and obtaining the composition of impurities in the phosphogypsum; constructing a molecular model of the collector and a unit cell model of the impurities respectively, and performing geometric optimization to obtain an optimized collector molecular model and an optimized impurity unit cell model; constructing a unit cell box of the impurities; constructing an adsorption model between the collector and the impurities based on the optimized collector molecular model and the unit cell box of the impurities; performing molecular dynamics simulation calculation on the adsorption model to obtain the adsorption energy between the collector and the impurities; and sorting the adsorption energy according to the size to screen out the collector with better collection effect. The application reveals the adsorption mechanism of the collector and the phosphogypsum impurities from the molecular and atomic scales, can more quickly select the optimal collector compounding scheme based on different regional phosphogypsum impurity phases, and provides theoretical support for phosphogypsum impurity removal.

The invention discloses a quantum chemical screening method for extracting arbutin, and relates to the technical field of natural product extraction, and the quantum chemical screening method comprises the following steps: constructing an arbutin single-molecule model and a hydrogen bond donor and hydrogen bond receptor single-molecule model by using GaussView software, firstly performing conformation search through MOPAC and molplus programs to obtain a most stable molecular structure, and then extracting the arbutin from the molecular structure; carrying out geometric optimization and single-point energy calculation by utilizing Gaussian; the optimized hydrogen bond donor and hydrogen bond acceptor establish random clusters according to different molar ratios, the random clusters with target molecules are established, a cluster model with an optimal structure is selected for geometric optimization and single-point energy calculation, meanwhile, the binding energy between the eutectic solvent and arbutin is calculated, and IGMH analysis, ESP analysis and AIM analysis are carried out. The invention provides a universal method for green and efficient extraction of active ingredients of natural products.

The invention provides a method for predicting the load performance of a corrosion inhibitor on a covalent organic framework material. The method is applied to the field of material simulation and design. The method comprises the following steps: determining the length of a target monomer connecting chain in various covalent organic framework material structures in a chain length increasing manner, and constructing covalent organic framework material unit cell models of various corresponding different topological structures based on the length of the target monomer connecting chain; performing structure optimization on the covalent organic framework material unit cell model and the molecular models of the various corrosion inhibitors to obtain an optimized covalent organic framework material unit cell model and an optimized molecular model; determining adsorption energy, electronic structure change and electronic interaction of molecular models of different optimized corrosion inhibitors on each optimized covalent organic framework material unit cell model; based on adsorption energy, electron structure change and electron interaction, the load performance of different corrosion inhibitors on the covalent organic framework material is predicted.

The present disclosure relates to the technical field of nanoparticle material simulation, and particularly relates to a method and device for generating active nanoparticles and an electronic device. The method comprises: generating a base of active nanoparticles according to a third quantity and first configuration parameters; generating a modification structure containing a second quantity of molecular structures according to the second quantity; performing a preset operation on the modification structure to obtain a processed modification structure; connecting a connection site in the processed modification structure with a modification site of the base of the active nanoparticles to obtain a molecular model of the active nanoparticles; determining a charge carried by each atom in the molecular model based on force field parameters of a chemical environment corresponding to the molecular model; and performing relaxation processing on the molecular model based on atomic coordinates of each atom in the molecular model, the charge carried by each atom, and the force field parameters to obtain the active nanoparticles.