Monomeric Neural Network Potential for General Covalent Molecules: Linear Alkanes as an Example

electronic energies and reliably captures key molecular properties, including torsional potential energy profiles, harmonic vibrational frequencies, and vibrational power spectra obtained from molecular dynamics simulations. Importantly, MB-PIPNet demonstrates a substantial advantage in computational efficiency over other MLP models for combined energy and force evaluations. These results establish MB-PIPNet as a scalable and efficient framework for constructing MLPs, providing an additional route for large-scale quantum and classical simulations of complex molecular systems.

Authors

Institutions

Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2026-04-27
DOI
https://doi.org/10.1021/acs.jctc.6c00290
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Monomeric Neural Network Potential for General Covalent Molecules: Linear Alkanes as an Example

Qi Yu, Ruitao Ma, Dong Hui Zhang, Xinze Li et al.
Journal of Chemical Theory and Computation
Machine Learning in Materials Science
article

Monomeric Neural Network Potential for General Covalent Molecules: Linear Alkanes as an Example

Qi Yu, Ruitao Ma, Dong Hui Zhang, Xinze Li, Chen Qu
article en

Abstract

electronic energies and reliably captures key molecular properties, including torsional potential energy profiles, harmonic vibrational frequencies, and vibrational power spectra obtained from molecular dynamics simulations. Importantly, MB-PIPNet demonstrates a substantial advantage in computational efficiency over other MLP models for combined energy and force evaluations. These results establish MB-PIPNet as a scalable and efficient framework for constructing MLPs, providing an additional route for large-scale quantum and classical simulations of complex molecular systems.

Journal of Chemical Theory and Computation
Dalian Institute of Chemical Physics (CN), Chinese Academy of Sciences (CN), Fudan University (CN), ECSI Fibrotools (United States) (US)
National Natural Science Foundation of China, Shanghai Municipal Commission of Economy and Informatization
Affordable and clean energy
Openalex Percentile: Top 9%
Machine Learning in Materials Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Monomeric Neural Network Potential for General Covalent Molecules: Linear Alkanes as an Example — Qi Yu, Ruitao Ma, et al. · Journal of Chemical Theory and Computation (2026) | TGRS Research Map | TGRS