Our work published in Scientific Data presents the WS22 database, which contains 10 flexible organic molecules of increasing complexity in chemical composition and accessible conformations. The WS22 database provides 1.18 million equilibrium and non-equilibrium molecular geometries together with many quantum …
In our work published in the Journal of Chemical Physics, we investigate the performance of AIQM1 on reaction barrier heights. Our benchmark results show that, with the built-in uncertainty quantification, the accuracy of confident AIQM1 predictions outperforms its baseline ODM2* method, …
Materials can simultaneously absorb not just one but two photons and molecules with strong two-photon absorption (TPA) are important in many fields such as unconverted laser, photodynamic therapy, and 3D printing. In our work published in Advanced Science (open access), …
Explaining and Predicting Two-Photon Absorption with Machine Learning Read more »
Artificial Intelligence Chemistry, a new chemical journal launched by Elsevier, with international peer review and online open access, is now officially open to submissions. MLatom founder and XACS co-founder Professor Pavlo O. Dral joins the Editorial Board of this new …
It is time for drawing up conclusions for the year and here is my brief overview of our group’s third year. 2022 will come down in history as a tumultuous year with major global events which couldn’t not affect me …
We are happy to announce that our brand-new manual for MLatom@XACS is now online at http://mlatom.com/manual/. Our new manual is re-designed to make it much easier to find what you need. We also greatly updated it with additional information, useful tips, …
Yuxinxin Chen (master student), Yeyun Chen (co-supervised PhD student) and Yaohuang Huang (research assistant) join our group this semester. Welcome! Yuxinxin Chen continues her education in our group as a master student and explores the application of AIQM1 in reaction …
Recently, Machine Learning (ML) is increasingly used for fast and accurate propagation of quantum dissipative dynamics including our works for the two-state system and seven-site FMO complex. The studies carried out so far demonstrated the use of different ML models …
Mario Barbatti, his group and collaborators published an update on Newton-X – a popular open-source platform for surface hopping and nuclear ensembles. An update include extension of the Newton-X platform to supervised (with our MLatom platform) and unsupervised learning (with ulamdyn). The paper is also open access and appeared in the Journal of Chemical Theory and Computation.
The book “Quantum Chemistry in the Age of Machine Learning” guides aspiring beginners and specialists in this exciting field by covering topics ranging from basic concepts to comprehensive methodological details in machine learning, quantum chemistry, and their combinations in a …
Book “Quantum Chemistry in the Age of Machine Learning” Read more »