24 results about "Molecular model" patented technology

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 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.

This invention discloses a method for constructing a macromolecular model of Hami oil-rich coal and its application. The molecular formula and functional group characteristics of the coal sample are determined through elemental analysis and infrared spectroscopy. A planar structural model is constructed using the Wiser model framework, and a stable configuration is obtained after geometric optimization. Finally, a pyrolysis reaction model containing multiple molecules is constructed through stacking. Targeting the high-oxygen and high-cycloalkane structural characteristics of Hami oil-rich coal, a C1... 128 H 82 NO 16 and C 111 H 88 NO 28 Two precise models were used, and the accuracy of the calculated infrared spectra was verified by comparing them with experimental spectra. ReaxFF molecular dynamics simulations were performed using this model, revealing the influence of different heating rates and pyrolysis temperatures on product distribution. The optimal simulation temperature and critical values ​​for pyrolysis rate control were determined, and the difference in ethylene formation pathways between alkyl-rich coal and ether-rich coal was analyzed. This invention fills the gap in precise models for Hami oil-rich coal, providing key theoretical basis and parameter guidance for optimizing pyrolysis processes, achieving targeted regulation, and improving energy efficiency.

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.

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.

The application relates to a method for evaluating adsorption of organic matters on silicon dioxide based on molecular dynamics simulation, which comprises the following steps: constructing a hydroxylated silicon dioxide surface model; wherein the density of silanol on the hydroxylated silicon dioxide surface is 0-9.4 OH / nm 2 ; constructing an organic matter molecular model and inserting the organic matter molecular model into the hydroxylated silicon dioxide surface model to obtain an organic matter / silicon dioxide model; performing molecular dynamics simulation on the organic matter / silicon dioxide model; and evaluating the obtained simulation result. The application directly reveals the interaction between different organic matter molecules and different hydroxylated silicon dioxide surfaces at an atomic scale, evaluates the interfacial activity of the formed silicon dioxide surfaces with different hydroxylization degrees and different ionization degrees, and can provide important theoretical guidance for improving the crude oil recovery rate, mineral flotation efficiency, solid surface self-cleaning and other fields.

The application belongs to the technical field of analytical testing and substance component detection, and specifically discloses a novel compound identification method based on atlas analysis of a combined instrument, which comprises the following steps: synchronously aligning the chromatographic retention time, ion drift time, mass-to-charge ratio and ion abundance of a sample to be detected to extract a four-dimensional characteristic peak group; based on an addition rule, gathering ion clusters to confirm a single isotopic mass; calculating a mass offset and matching a conversion reaction dictionary to anchor a candidate metabolite; comparing secondary mass spectrum fragments and mapping to a parent fragmentation path to generate a two-dimensional plane structure; based on this, enumerating isomers, constructing a three-dimensional rigid body molecular model and deducing a theoretical collision cross section area; finally, comparing the actually measured and theoretical collision cross section areas, combining the polarity difference of the retention time mapping to perform orthogonal constraint verification, and outputting the target three-dimensional structure of the metabolite. The application realizes the reliability of compound confirmation in a complex sample.

The application relates to a nanometric cutting molecular model construction method and device and computer equipment. The method comprises the following steps: acquiring a nanometric cutting transmission electron microscope image; determining a real object area and a background area of the nanometric cutting transmission electron microscope image, and dividing the real object area into a workpiece area and a tool area; creating a target topography template according to the nanometric cutting transmission electron microscope image; determining actual physical sizes of the workpiece area, the tool area and the whole nanometric cutting transmission electron microscope image according to an internal scale of the nanometric cutting transmission electron microscope image; and constructing a nanometric cutting molecular model according to crystallographic parameters of a target workpiece and crystallographic parameters of a target tool based on the actual physical sizes of the workpiece area, the tool area and the whole nanometric cutting transmission electron microscope image, the first topography template and the second topography template. The above scheme can construct a nanometric cutting molecular model with accurate sizes and standard crystal orientations.

An estimation system comprises at least one processor. The at least one processor acquires a target molecule model representing a conformation of a target molecule, generates a molecule-of-interest model representing a conformation of a molecule of interest, the molecule of interest being a molecule capable of binding to the target molecule, calculates energy of interaction between the molecule of interest and the target molecule as intermolecular interaction energy based on a positional relationship between the target molecule model and the molecule-of-interest model, calculates energy of interaction in the molecule of interest as intramolecular interaction energy, and estimates a conformation of the molecule of interest based on the intermolecular interaction energy and the intramolecular interaction energy.

The application discloses a first-principle-based conductive polyaniline doped acid screening method and device and a storage medium, and belongs to the field of electrical properties of conductive materials. The method first constructs finite molecular models and periodic molecular models of different types of doped protonic acids of aniline tetramer, performs geometric optimization on the finite molecular models, and calculates electrostatic potential, frontier molecular orbit and energy gap; then, K-point convergence test is carried out on the periodic molecular models; the periodic molecular models with the optimal K-point grid density are subjected to geometric optimization and calculation of state density; the electronic structures and conductive properties of the finite molecular models and the periodic molecular models of different types of doped protonic acids are compared and analyzed, and the conductive polyaniline doped acid with high conductivity is screened. The method can explain the phenomenon of the significant improvement of the conductivity of the doped-state polyaniline from a deeper level, thereby accurately guiding the screening and reverse design of new materials.

This makes it possible to predict the behavior of oxygen molecules within the pores of a carbon support. [Solution] The analysis method comprises a modeling step, a setting step, a simulation step, and a calculation step. In the modeling step, the carbon support of the hydrogen fuel cell is modeled as a cylindrical carbon nanotube model. In the setting step, the number of water molecule models, oxygen molecule models, and nitrogen molecule models to be placed within the carbon nanotube model is set. In the simulation step, a simulation is performed on the diffusion of water molecule models, oxygen molecule models, and nitrogen molecule models within the carbon nanotube model. In the calculation step, the diffusion coefficient of the oxygen molecule model is calculated based on the simulation results.

The invention relates to the technical field of coal bed gas exploration, in particular to a visualization method for simulating micro occurrence and flowing of deep coal rock gas. According to the visualization method for simulating the microscopic occurrence and flowing of the deep coal rock gas, in-situ pressure, temperature and crustal stress parameters of a preset burial depth are estimated, and simulation boundary conditions including the in-situ pressure, temperature and crustal stress parameters are loaded into a molecular model, so that a simulation boundary consistent with an actual deep environment is directly established, and the real deep coal rock gas microcosmic occurrence and flowing are simulated. And the technical bottleneck that in-situ complex conditions cannot be reproduced in a laboratory is solved, so that a simulation result is closer to engineering practice, and the accuracy and reliability of a visual result are ensured. According to the visualization method, calculation of free-state methane is introduced in a targeted mode, so that the method is more adaptive to the characteristic that the proportion of the free-state methane in the deep coal and rock gas is high, and it is guaranteed that the visualization method can more accurately simulate the actual situation of the deep coal and rock gas.

A method and system for quantitatively evaluating kerogen swelling oil in shale is provided. The method includes: establishing different types of kerogen molecular models, and loading each of the kerogen molecular models into a graphene slit-type pore composed of a lamellar structure; performing energy minimization (EM), relaxation and annealing to obtain a kerogen slit-type pore; loading a shale oil molecule into the kerogen slit-type pore to obtain an initial model of swelling and adsorption of shale oil in kerogen; assigning a value to a force field of the shale oil molecule and the kerogen molecule in the swelling and adsorption model to obtain a density of the kerogen and the shale oil; plotting a density curve of the kerogen and the shale oil; calculating kerogen swelling oil mass; determining per-unit kerogen swelling oil mass; and determining the kerogen swelling oil mass in different evolution stages.

The application provides a molecular framework structure construction method and device based on machine learning reasoning, relates to the technical field of molecular construction, and comprises the following steps: modeling a to-be-connected molecule and a new molecule to obtain a first molecule definition model and a second molecule definition model; constructing a first 3D molecule model of the to-be-connected molecule and a second 3D molecule model of the new molecule according to the first molecule definition model and the second molecule definition model; extracting a connectable point with the same coordinate as a connected point and connecting the connected point to obtain an initial molecular structure according to the first 3D molecule model and the second 3D molecule model; deducing based on the initial molecular structure by using inheritance and transformation rules to obtain a deduction result; constructing a training data set according to the deduction result, so that a molecular connection model is trained; and inputting a to-be-spliced graph structure and a quantity into the molecular connection model to obtain a target molecular structure, so that the molecular framework structure construction of splicing periodic structures with high efficiency and high accuracy is realized.

The application provides a chemical grammar-based cross-modal three-dimensional molecular geometry generation method. The method comprises: obtaining a chemical grammar representation of a target molecule; inputting the chemical grammar representation into a frozen-parameter one-dimensional molecular base model to obtain a one-dimensional semantic hidden state; using a learnable query vector and a trainable projector to extract key chemical knowledge from the hidden state and map it to a three-dimensional geometry space to obtain three-dimensional conditional features; and finally inputting the three-dimensional conditional features into a three-dimensional diffusion model to generate three-dimensional geometry coordinates of the target molecule. The application bridges one-dimensional chemical grammar and three-dimensional geometry structure through a unified framework, significantly improves the geometry fidelity, chemical effectiveness and structure stability of the generated molecules by using cross-modal knowledge transfer without retraining the one-dimensional molecular model, and solves the problem that the prior art is difficult to balance syntax rules and geometry structure.

The application discloses a CO2-ion water flooding molecular dynamics simulation method and belongs to the technical field of CO2 oil displacement. The method comprises the following steps: establishing oil molecule models, water molecule models, CO2 molecule models, CaCl2 molecule models and graphene plate models corresponding to the characteristics of a target oil reservoir; optimizing the geometric structures of the models; assembling the optimized molecular models into a CO2-CaCl2-H2O ternary displacement system and performing molecular dynamics simulation; selecting an NVT ensemble during simulation, applying a periodic boundary condition, adopting a COMPASS II force field and configuring atomic potential parameters, running energy minimization and temperature initialization, and then performing displacement process simulation; quantitatively evaluating the oil displacement effect of the displacement medium of the CO2-CaCl2-H2O ternary system based on a trajectory file output by simulation; and the application can better explain the behavior of molecules under the synergistic action of multiple displacement media, reflect the oil displacement microscopic mechanism under the synergistic action of multiple displacement media, and has important significance for optimizing the development effect of tight oil reservoirs and improving the recovery rate.

The application relates to an epoxy asphalt compatibility quantitative analysis and formula optimization method based on interface trajectory identification. A composite system molecular model containing an epoxy system crosslinking network and asphalt four-component molecules is constructed, molecular dynamics trajectory characteristics of molecules in an interface region are obtained, and single-molecule trajectories are automatically classified based on a machine learning algorithm, so that identification of an epoxy phase, an asphalt phase and an interface mixed state is realized. On this basis, the proportion of mixed state molecules, the cross-phase diffusion depth and the trajectory distribution characteristics are extracted, and a compatibility index I is constructed, which is used for quantitatively evaluating the compatibility level under different formulas. The method introduces a "default preferred threshold + reference system adaptive calibration" strategy, so as to ensure the robustness and migration of trajectory classification under different temperatures, formulas and simulation conditions.

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.

This application provides a method and system for simulating the molecular dynamics of anhydride-cured epoxy resin, comprising: constructing a monomer molecular model; constructing an amorphous structure model based on the monomer molecular model, wherein the monomers include epoxy resin and anhydride curing agent monomer molecules; generating force field parameters of the monomer molecules using an open-source program and labeling C and O atoms in the monomer molecules; setting up a dynamic simulation ensemble to perform molecular dynamics simulation, and obtaining a three-dimensional crosslinked network structure by performing a crosslinking reaction based on an automatic reaction site identification algorithm; optimizing the three-dimensional crosslinked network structure and performing dynamic simulation to calculate the macroscopic properties of the anhydride-cured epoxy resin molecules. This application makes the crosslinking reaction process of anhydride-cured epoxy resin closer to the real reaction process. Through molecular dynamics simulation, a series of crosslinked structures with different degrees of crosslinking can be obtained to explore the structural and performance differences of different degrees of crosslinking during the crosslinking reaction process, providing theoretical guidance for the development of high-performance epoxy resin systems.

The application discloses an optimization design method and preparation method of organic-inorganic double modified flame-retardant high-toughness epoxy resin and application thereof in structural engineering. In view of the problems of large test amount and poor reliability of a traditional test method, the application adopts a method combining molecular dynamics simulation, data enhancement and meta-heuristic algorithm optimization machine learning, establishes a biological base hyperbranched polymer and aluminum tailing double modified epoxy resin molecular model, performs glass transition and tensile behavior simulation after NVT / NPT balance and crosslinking modeling, performs data enhancement by using a nearest neighbor interpolation method, optimizes an XGBoost model by using a particle swarm algorithm improved by using an S-shaped weight function to perform performance prediction, and determines an optimal ratio (bisphenol A: phenolic amine: biological base hyperbranched polymer: aluminum tailing = 0.53:0.37:0.07:0.03) by combining SHAP explainability analysis and a quaternary phase diagram. The prepared epoxy resin has significantly improved flame-retardant performance and toughness, and can be used for wet connection in a negative bending moment area of a concrete simply supported to continuous beam, thereby prolonging the service life of the structure.

The application relates to the technical field of coalbed methane exploration, in particular to a coal rock molecular model construction method considering physicochemical properties and fluid occurrence behavior. In the coal rock molecular model construction method, first, an initial model is constructed by using the measured data of the physicochemical properties of a coal rock sample, then the initial model is simulated for methane occurrence behavior to obtain simulation parameter values; then, an experiment on the coal rock sample is carried out for methane occurrence behavior to obtain experimental parameter values; then, the initial model is optimized according to the experimental parameter values; the optimized model is repeatedly simulated for methane occurrence behavior and optimized, the optimization iteration of the model is realized, the model after the optimization iteration meets the set requirements; finally, the model after the optimization iteration is compared and verified with the actual parameters of the coal rock sample, when the total matching degree of the model reaches the set requirements, the final qualified model is obtained, so that the model can be closer to the actual state of the real coal rock.

The application discloses an evaluation method and device for asphaltene adsorption interface stability. The method comprises the following steps: performing separation and purification treatment on a heavy oil sample to obtain a purified asphaltene sample, performing structure and element characterization treatment on the purified asphaltene sample to obtain structure characteristic and element composition data of the asphaltene; constructing an oil-water interface molecular model, performing balance simulation treatment on the oil-water interface molecular model to obtain an interface system model; performing traction stretching simulation treatment on asphaltene molecules to obtain a plurality of initial configurations, performing umbrella-shaped sampling simulation and free energy calculation treatment on the plurality of initial configurations respectively to obtain free energy data; performing measurement treatment on the purified asphaltene sample to obtain interface tension data; and then performing verification and analysis treatment to obtain an evaluation result. The application realizes comprehensive evaluation of asphaltene adsorption interface stability, the result is accurate and reliable, and can provide technical support for oil-water interface stability regulation of an asphaltene-containing system.

The application provides a simulation method and system for diffusion behavior of nanoparticles in tissue gaps, and belongs to the field of molecular dynamics simulation, and comprises the following steps: constructing a multi-component coarse-grained molecular model; performing energy minimization on the multi-component coarse-grained model by using a conjugate gradient method, and obtaining an initial configuration with stable energy by setting a convergence tolerance; maintaining a constant temperature condition by using a Langevin heat bath under a canonical ensemble, performing molecular dynamics equilibrium simulation on the initial configuration to obtain the diffusion behavior of nanoparticles in tissue gaps, and recording motion trajectory data of the nanoparticles; obtaining mean square displacement (MSD) of the nanoparticles according to the motion trajectory data, and plotting MSD-t curves by corresponding MSD and simulation time t; performing linear fitting on the MSD-t curves and solving, to obtain a diffusion coefficient of the nanoparticles in the tissue gaps. The application analyzes the interaction between the nanoparticles and the solid-liquid two-phase medium from the molecular level, and provides a powerful microscopic research tool for elucidating the diffusion mechanism of the nanoparticles.