npj Comput. Mater.: Efficient Machine Learning Protocol For Accelerating Trajectory Surface Hopping Dynamics
Our recent article in npj Computational Materials presents an efficient ML protocol for accelerating trajectory surface …
Tag: MLatom
Meet OMNI-P2x — the First Universal ML Potential for Excited States!
Are universal machine learning potentials for excited states possible? Such a potential would be a major …
Meet OMNI-P2x — the First Universal ML Potential for Excited States! Read more →
Highlights of the Year 2024! Last Weekly Update?
Another year flew by like a comet. And what a year it was! This year was …
Highlights of the Year 2024! Last Weekly Update? Read more →
ML-enhanced Fast and Interpretable Simulation of IR Spectra
Theoretical IR (infrared) spectroscopy is a powerful tool for assisting chemical structure identification. However, approaches based on …
ML-enhanced Fast and Interpretable Simulation of IR Spectra Read more →
Adv. Sci.: The Best DFT Functional Is the Ensemble of Functionals
Density functional theory (DFT) methods are by far the most popular approaches for electronic structure calculations. …
Adv. Sci.: The Best DFT Functional Is the Ensemble of Functionals Read more →
JOC: Surprising dynamics phenomena in the Diels–Alder reaction of C60 uncovered with AI
Recently, we published a paper in JOC about the surprising dynamics phenomena in the Diels–Alder reaction …
JOC: Surprising dynamics phenomena in the Diels–Alder reaction of C60 uncovered with AI Read more →
JCTC: Physics-informed active learning for accelerating quantum chemical simulations
Recently, we published a paper in JCTC about the end-to-end physics-informed active learning with data-efficient construction of machine …
JCTC: Physics-informed active learning for accelerating quantum chemical simulations Read more →
One-year overview: from MLatom 3.0 to 3.10
A year ago, we released MLatom 3, making MLatom the fully-fledged Python package. This shift endowed …
JCTC: Surface hopping dynamics with QM and ML methods
XACS team in collaboration with Mario Barbatti and groups in Warsaw University and Zhejiang lab has …
JCTC: Surface hopping dynamics with QM and ML methods Read more →
JPCL | Tell Machine Learning Potentials What They Are Needed For: Simulation-Oriented Training
A machine learning potential with low error in the potential energies does not guarantee good performance …