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 »

Single-point calculations can be performed with various models and methods in MLatom including: For more details on the models in MLatom, please check an overview. Here we will illustrate how to calculate isomerization energy of sugar in ISOL24 with different types of methods …

Tutorial on single-point calculations with MLatom@XACS Read more »

Pavlo O. Dral, Fuchun Ge, Yi-Fan Hou, Peikun Zheng, Yuxinxin Chen, Mario Barbatti, Olexandr Isayev, Cheng Wang, Bao-Xin Xue, Max Pinheiro Jr, Yuming Su, Yiheng Dai, Yangtao Chen, Lina Zhang, Shuang Zhang, Arif Ullah, Quanhao Zhang, Yanchi Ou. MLatom 3: A …

MLatom 3 for AI-enhanced computational chemistry: JCTC paper and online tutorial Read more »

Equivariant potentials are the (relatively) new kid on the block with promising high accuracy in published benchmarks. One of them is MACE which we now added to the zoo of machine learning potentials available through the interfaces in MLatom. See …

Bringing the power of equivariant NN potential through the interface of MACE to MLatom@XACS Read more »