[HTML][HTML] Insights into the thermal stability and conversion of carbon-based materials by using ReaxFF reactive force field: Recent advances and future directions

S AlAreeqi, D Bahamon, K Polychronopoulou, LF Vega - Carbon, 2022 - Elsevier
Molecular simulations based on reactive force-fields (ReaxFF) have been applied as a
powerful tool for exploring the dynamics evolution of complex carbonaceous materials. A …

Recent advances for improving the accuracy, transferability, and efficiency of reactive force fields

I Leven, H Hao, S Tan, X Guan, KA Penrod… - Journal of chemical …, 2021 - ACS Publications
Reactive force fields provide an affordable model for simulating chemical reactions at a
fraction of the cost of quantum mechanical approaches. However, classically accounting for …

[HTML][HTML] Machine learning for combustion

L Zhou, Y Song, W Ji, H Wei - Energy and AI, 2022 - Elsevier
Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …

Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation

J Zeng, L Cao, M Xu, T Zhu, JZH Zhang - Nature communications, 2020 - nature.com
Combustion is a complex chemical system which involves thousands of chemical reactions
and generates hundreds of molecular species and radicals during the process. In this work …

NewtonNet: a Newtonian message passing network for deep learning of interatomic potentials and forces

M Haghighatlari, J Li, X Guan, O Zhang, A Das… - Digital …, 2022 - pubs.rsc.org
We report a new deep learning message passing network that takes inspiration from
Newton's equations of motion to learn interatomic potentials and forces. With the advantage …

Transferable machine learning interatomic potential for bond dissociation energy prediction of drug-like molecules

E Gelzinyte, M Öeren, MD Segall… - Journal of Chemical …, 2023 - ACS Publications
We present a transferable MACE interatomic potential that is applicable to open-and closed-
shell drug-like molecules containing hydrogen, carbon, and oxygen atoms. Including an …

Ab initio neural network MD simulation of thermal decomposition of a high energy material CL-20/TNT

L Cao, J Zeng, B Wang, T Zhu… - Physical Chemistry …, 2022 - pubs.rsc.org
CL-20 (2, 4, 6, 8, 10, 12-hexanitro-2, 4, 6, 8, 10, 12-hexaazaisowurtzitane, also known as
HNIW) is one of the most powerful energetic materials. However, its high sensitivity to …

Accurate large-scale simulations of siliceous zeolites by neural network potentials

A Erlebach, P Nachtigall, L Grajciar - npj Computational Materials, 2022 - nature.com
The computational discovery and design of zeolites is a crucial part of the chemical industry.
Finding highly accurate while computational feasible protocol for identification of …

A reactive molecular dynamics study of HCN oxidation during pressurized oxy-fuel combustion

D Hong, X Guo, C Wang - Fuel Processing Technology, 2021 - Elsevier
In the present work, HCN oxidation during pressurized oxy-fuel combustion is studied using
reactive molecular dynamics (ReaxFF MD) simulations. The effects of CO 2, pressure, and O …

Exploring the chemical space of linear alkane pyrolysis via deep potential generator

J Zeng, L Zhang, H Wang, T Zhu - Energy & fuels, 2020 - ACS Publications
Reactive molecular dynamics (MD) simulation is a powerful tool to study the reaction
mechanism of complex chemical systems. Central to the method is the potential energy …