AI-enhanced computational chemistry
In our latest tutorial we show how MLatom can be used to simulate UV/vis spectra via single-point convolution and nuclear-ensemble approach (NEA). ML can also be used to increase precision of the NEA spectra at reduced cost. You can watch the detailed introduction and demonstration in the video. All …
Theoretical IR (infrared) spectroscopy is a powerful tool for assisting chemical structure identification. However, approaches based on quantum chemical calculations suffer from either high computational cost (e.g., density functional theory, DFT) or insufficient accuracy (semi-empirical methods). Hence, we introduce a new …
ML-enhanced Fast and Interpretable Simulation of IR Spectra Read more »
AIQM2 is the long-awaited successor of the highly successful AIQM1 (see Nat. Commun. paper). It has overall improved accuracy and much better performance for transition states, where it produces high-quality geometries and barrier heights: it is better than B3LYP/6-31G* but orders of …
AIQM2 is out: better and faster than B3LYP for reaction simulations! Read more »
A year ago, we released MLatom 3, making MLatom the fully-fledged Python package. This shift endowed MLatom with much of its current flexibility that also allowed us to rapidly do method development and new implementations: in one year we had …
Quasi-classical molecular dynamics (also known as quasi-classical trajectories (QCT)) accounts for the zero-point energy (ZPE) in contrast to classical dynamics and is very popular in studying chemical reactions (see, e.g., works by Houk et al. in PNAS 2012, 109, 12860 and J. Am. …
Quasi-classical trajectories to study reaction mechanisms like in PNAS and JACS papers! Read more »
MLatom 3.4.0 has been released on 29.03.2024. This release is a major release with usability improvements: Contributed to this release: Pavlo O. Dral, Yuxinxin Chen, Fuchun Ge, and Yi-Fan Hou.
MLatom@XACS makes AI-enhanced computational chemistry more accessible and supports both ground- and excited-state simulations with quantum mechanical methods, machine learning, and their combinations. We are happy to announce that we will release the new upgraded version of MLatom 3.3.0 that …
Surface hopping dynamics with MLatom is coming: Join online broadcast! Read more »
We are happy to announce that MLatom 3.2.0 is released on 19.03.2024. See the full release notes for details. How to get it? Download zip, check this version on PyPI and GitHub. pip install mlatom==3.2.0 What’s new? This is a major release with many new features, …
We have released the version 3.1.1 of MLatom with improvements in the performance and bug fixes.
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 …