lab-cosmo/flashmd
A universal ML model to predict molecular dynamics trajectories with long time steps
FlashMD significantly accelerates molecular dynamics simulations, enabling you to model material behavior over much longer timescales than traditional methods. It takes your initial molecular structure and desired simulation conditions as input and generates predicted molecular trajectories, showing how atoms move and interact over time. This tool is for materials scientists, computational chemists, and researchers who need to simulate atomic-level processes but are limited by the computational cost and short timescales of conventional MD.
Use this if you need to simulate molecular dynamics trajectories for materials systems over extended time periods (nanoseconds to microseconds) without sacrificing accuracy.
Not ideal if you require absolute, exact energy conservation throughout your simulation or if you are working with highly reactive or complex biological systems without careful validation.
Stars
41
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 01, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/lab-cosmo/flashmd"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
deepmodeling/deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
chemprop/chemprop
Message Passing Neural Networks for Molecule Property Prediction
mir-group/nequip
NequIP is a code for building E(3)-equivariant interatomic potentials
Acellera/moleculekit
MoleculeKit: Your favorite molecule manipulation kit
CederGroupHub/chgnet
Pretrained universal neural network potential for charge-informed atomistic modeling...