My review ‘AI in computational chemistry through the lens of a decade-long journey’ was published open access as an invited Feature Article in Chemical Communication. It gives a perspective on the progress of AI tools in computational chemistry through the …

Chem. Commun. Feature Article: “AI in computational chemistry through the lens of a decade-long journey” Read more »

AI-accelerated nonadiabatic dynamics reduces the cost of the ab initio simulations of nonlinear time-resolved spectra. We have developed a robust protocol and demonstrated its feasibility for calculating stimulated emission contributions in transient absorption pump–probe and 2D electronic spectra of pyrazine. …

Artificial-Intelligence-Enhanced On-the-Fly Simulation of Nonlinear Time-Resolved Spectra Read more »

Our editorial on the Special Topic “Modern semiempirical methods” was published in JCP. We overview contributions and overview the trends in the development and applications of semiempirical quantum mechanical methods. The contributions include improvements in the formalism of the method …

Editorial on the Special Topic “Modern semiempirical methods” published in JCP Read more »

Location: Xiamen University, China Duration: 2 years (with possible 1-year extension) Xiamen University is offering a fully-funded 2-year postdoctoral research position in the field of machine learning-based simulations of condensed matter. This opportunity is available within the research group of …

Postdoc in Machine Learning-Based Simulations of Condensed Matter Read more »

The 2nd edition of the International Symposium on Machine Learning in Quantum Chemistry, SMLQC 2023, is approaching and will be held from November 29 to December 1 in Uppsala, Sweden. See the symposium’s website https://www.smlqc2023.com/ for more information. The deadline …

SMLQC 2023: The 2nd International Symposium on Machine Learning in Quantum Chemistry Read more »

Molecular dynamics simulations are widely used to study molecules and materials and lots of effort is put into making these simulations obey the physical laws. Energy conservation law is obviously one of the most important laws that MD should respect. …

Energy-conserving molecular dynamics is not energy conserving! Read more »

We have introduced a concept of 4D-spacetime atomistic AI models that learn how the molecule changes in time. We demonstrate that this concept is feasible by developing the 4D-spacetime GICnet models that directly predict the atomic coordinates of a molecule …

Beyond 3D-Machine Learning Interatomic Potentials: Meet 4D-Spacetime Atomistic Artificial Intelligence Models Read more »