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 …
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Predicting the future of excitation energy transfer in light-harvesting complex with artificial intelligence-based quantum dynamics
In the work published in Nature Communications, we have developed a blazingly fast artificial intelligence (AI)-based …
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 …
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VIB5 database with accurate ab initio quantum chemical molecular potential energy surfaces
We report global potential energy surfaces (PESs) database VIB5 of 5 molecules of astrophysical interest which …
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 →
SMLQC-2021 is over. Viva SMLQC!
Symposium on Machine Learning in Quantum Chemistry 2021 (SMLQC-2021) has been a huge success with many …
Which Machine Learning Potential to Choose?
Lost in the sea of all machine learning potentials? Our overview and recommendations based on balanced …
Welcome New Members of Our Group!
Fuchun Ge, Ran Wang, and Linqiang Wei join our group starting this month. Welcome! Fuchun officially …
Open PhD and Master Positions in 2022
The group of Dr. Pavlo Dral in College of Chemistry and Chemical Engineering at Xiamen University …