Congratulations to Bao-Xin Xue with the defense of his Master thesis!
The man behind machine learning-nuclear ensemble approach graduated! Congratulations to Baoxin, my very first graduate student! We wish him best of luck in his future endeavors!
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 learning (OSTL) approach that allows an ultrafast prediction of 10-ps-long quantum dynamics of an open quantum system just in 70 milliseconds. OSTL approach takes …
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Plenary lecture at ANSCSE25
It has been a great pleasure to give a plenary lecture at the 25th International Annual Symposium on Computational Science and Engineering (ANSCSE25). I was talking about AI/ML in computational chemistry, how our MLatom can help with it, and introduced …
MLatom joins Xiamen Atomistic Computing Suite
We are very happy to announce that MLatom joins Xiamen Atomistic Computing Suite (XACS) which allows us to provide much better service to the theoretical and computational chemistry community. We marked the inception of XACS by holding a local workshop …
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 the general-purpose data-driven methods ANI-1ccx and AIQM1 in the calculation of enthalpies of formation. Extensive benchmark tests show that these two methods can achieve …
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 quantum dynamics (QD) approach with applications to excitation energy transfer in the well-known Fenna–Matthews–Olson (FMO) complex found in green sulfur bacteria.
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 materials sciences published in 2021! #NCOMTop25 The full list: https://www.nature.com/collections/gagdjjgcgj AIQM1 paper: https://www.nature.com/articles/s41467-021-27340-2 How to use AIQM1 method with MLatom: http://MLatom.com/AIQM1
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 numerically exact hierarchical equations of motion (HEOM) approach, propagating quantum dynamics of a two-state system (spin-boson model) with only ca. 10% of the HEOM …
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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 was used to produce rovibrational spectra approaching spectroscopic accuracy and contains state-of-the-art, high-level energies and energy gradients. This database can be used to develop …
Open post-doc position
The group of Associate Professor Pavlo O. Dral is looking for a post-doc with a proven track record of the development, implementation, and application of theoretical chemistry methods for solid-state simulations. Pavlo O. Dral副教授课题组，拟招聘博士后一名，欢迎具有固态模拟理论化学方法的开发、实践和应用方面研究经历并有志于科学研究的青年才俊加盟。