Materials design with MLatom for ammonia separation and storage
We used our MLatom package to develop a machine learning approach for designing materials based on …
Materials design with MLatom for ammonia separation and storage Read more →
Method Development
One-Shot Trajectory Learning of Open Quantum Systems Dynamics
In the work published in the Journal of Physical Chemistry Letters, we have proposed a one-shot trajectory …
One-Shot Trajectory Learning of Open Quantum Systems Dynamics Read more →
Toward Chemical Accuracy in Predicting Enthalpies of Formation with General-Purpose Data-Driven Methods
In our work published in the Journal of Physical Chemistry Letters, we investigate the performance of …
AIQM1 paper is top 25 most downloaded Nature Communications articles in chemistry and materials sciences published in 2021
Our AIQM1 paper is one of the 25 most downloaded Nature Communications articles in chemistry and …
Speeding up quantum dissipative dynamics of open systems with kernel methods
In the work published in New Journal of Physics, we combine machine learning (ML) with the …
Speeding up quantum dissipative dynamics of open systems with kernel methods Read more →
Artificial intelligence makes accurate quantum chemical simulations more affordable
We have developed artificial intelligence-enhanced quantum mechanical method 1 (AIQM1), which can be used out of …
Artificial intelligence makes accurate quantum chemical simulations more affordable Read more →
MLatom 2: Introducing a Platform for Atomistic Machine Learning
We are happy to introduce MLatom 2: a major release of our integrative platform for user-friendly …
MLatom 2: Introducing a Platform for Atomistic Machine Learning Read more →
Machine Learning for Absorption Cross Sections
Paper Bao-Xin Xue, Mario Barbatti*, Pavlo O. Dral*, Machine Learning for Absorption Cross Sections, J. Phys. Chem. A 2020, 124, 7199–7210. DOI: 10.1021/acs.jpca.0c05310.Preprint …
Next Step: TB-SEMO Methods?
Johannes Margraf and I have published our perspective on what semiempirical molecular orbital (SEMO) methods are …
MLatom 1.0
MLatom 1.0 release of my package for atomistic simulations with machine learning is now available.