5 results about "Elementary reaction" patented technology

A kind of zirconium alloy water environment corrosion microscopic mechanism analysis method based on ab initio molecular dynamics, 1, construct the multi-phase interface model of metal substrate model and corrosion medium layer model combination, obtain the size information of simulation box;2, set simulation parameters for multi-phase interface model;3, carry out geometry structure optimization to multi-phase interface model and eliminate local internal stress, then carry out ab initio molecular dynamics simulation, obtain atomic evolution track and corrosion product structure;4, carry out data post-processing and statistical analysis to ab initio molecular dynamics simulation result, obtain corrosion elementary reaction path and calculate reaction energy barrier, the interaction mechanism of corrosion group and surface is analyzed by DFT method.The method can complete accurate zirconium alloy corrosion process dynamic simulation under periodic boundary condition, has higher calculation precision and is more reasonable to the description of interatomic force in system, and can also analyze the interaction mechanism between alloy and corrosion medium from atomic electronic scale.

The present application relates to a kind of molecular structure perception chemical reaction kinetics equation symbol regression method, for solving the problem that existing symbol regression technique ignores species chemical information, causes poor modeling effectiveness.The method adopts encoder-decoder architecture, and the encoding part is provided with double branch: one branch is handled concentration time series by Transformer, another branch utilizes graph neural network to encode molecular graph, and structural characteristics are extracted.After bimodal feature fusion, it is directly returned to the kinetics equation of ordinary differential equation form by the Transformer decoder with cross attention mechanism.Training data is generated by synthesis: based on the data set of elementary reaction, SMILES is converted into molecular graph, and the kinetics equation is deduced according to mass action law, and then concentration trajectory is generated by random sampling and numerical integration, and training sample comprising molecular graph, trajectory and equation is formed.The present application significantly improves the accuracy, interpretability and data utilization efficiency of symbol regression in reaction kinetics modeling.

This invention discloses a method for extracting reaction kinetic parameters from experiments for polymer reaction simulation. The method includes setting the optimization range of elementary reactions and related parameters, obtaining experimental molecular weight distribution curves, setting parameters for a high-dimensional search optimization algorithm and kinetic Monte Carlo simulation parameters, uniformly sampling the combination of reaction kinetic parameters, performing kinetic Monte Carlo simulation to obtain simulated molecular weight distribution curves, calculating the root mean square error between the simulated and experimental molecular weight distribution curves, and updating the combination of reaction kinetic parameters using a high-dimensional search optimization algorithm. This invention can optimize and fit reaction kinetic parameters within the assumed reaction mechanism based solely on the polymer molecular weight distribution curve obtained from a single polymerization experiment. The obtained reaction kinetic parameters can be directly used to predict the results of the next batch of polymerization reactions. Furthermore, through multiple iterations of experiments and simulations, the prediction accuracy of the reaction kinetic parameters can be continuously optimized.

This invention relates to the field of combustion dynamics technology, and provides a method for modeling the combustion dynamics of nano-aluminum particles based on molecular reaction dynamics. The method includes: S1 constructing a nano-aluminum particle model; S2 establishing an oxidation combustion reaction system; S3 analyzing molecular trajectories; S4 extracting reaction paths; S5 determining gas-phase reaction kinetic parameters; S6 determining surface reaction kinetic parameters; S7 constructing a heterogeneous combustion kinetic mechanism; and S8 verifying and outputting simulation results. This invention directly extracts reaction paths through molecular dynamic trajectories in the reaction force field, reducing the subjectivity of relying entirely on artificially preset elementary reactions. It supplements key gas-phase and surface reaction parameters through quantum chemical calculations and density functional theory calculations, improving the physicochemical basis of the mechanism parameters. By coupling gas-phase and surface reactions into a heterogeneous combustion kinetic mechanism, it more completely describes the structural evolution process of aluminum nanoparticles from melting, rapid oxidation, partial oxidation to equilibrium.

This invention discloses a comprehensive and detailed reaction mechanism for natural gas / air and its development method. The comprehensive and detailed reaction mechanism includes 290 gas-phase components and 3339 gas-phase elementary reactions, 1 bulk component and 2 surface sites, and 56 soot particle surface reactions. This invention is based on the IDT of chain alkane oxidation, the concentration distribution of small-molecule gas-phase components and large-molecule PAHs of soot nucleation precursors in fuel-rich BSF ethylene flames, the distribution characteristics of soot SVF and PND in fuel-rich BSF and CDF ethylene flames, and the NO content of BSF methane flames under different equivalence ratios. x NO concentration distribution and the reaction of syngas / ammonia in different lean combustion atmospheres x A multidimensional validation study of PK_CNS was conducted, comparing various aspects such as concentration change characteristics. Based on the high consistency between predicted and experimental values, the excellent predictive performance of PK_CNS was verified, and it can be extended to describe the combustion process of natural gas in flame-heated furnaces.