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Found 4 papers, 4 papers with code
Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation
Combustion is a complex chemical system which involves thousands of chemical reactions and generates hundreds of molecular species and radicals during the process.
Neural Network Based in Silico Simulation of Combustion Reactions
Through further development, the algorithms in this study can be used to explore and discovery reaction mechanisms of many complex reaction systems, such as combustion, synthesis, and heterogeneous catalysis without any predefined reaction coordinates and elementary reaction steps.
ReacNetGenerator: an Automatic Reaction Network Generator for Reactive Molecular Dynamic Simulations
However, the analysis of the MD trajectories which contain thousands of species and reaction pathways has become a major obstacle to the application of reactive MD simulation in large-scale systems.
DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
Materials 3, 023804] and is capable of generating uniformly accurate deep learning based PES models in a way that minimizes human intervention and the computational cost for data generation and model training.
Computational Physics
