I have presented on March 20, 2024, the ongoing journey towards making excited-state simulations more accessible with the help of AI/ML. The video recordings and abstract of my talk at VISTA are now available online. About VISTA The bi-weekly seminar …
VISTA: Towards more accessible excited-state simulations with AI Read more »
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 »
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 …
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. …
The capabilities of MLatom 3 are described in the paper published in the J. Chem. Theory Comput. which was converted into an interactive online manual. See also the video overview.
We have got many interesting submissions to the Special Issue ‘Artificial Intelligence in Computational Chemistry’ and some papers are already online. Many authors requested more time for submission, so we are pleased to extend it to two more months. There …
Alkyne-embedding [11]cycloparaphenylene ([11]CPPs) was functionalized with electron-donating, -neutral, and -withdrawing aryl substituents to yield a series of nanolassos via click chemistry. We used our state-of-the-art, artificial intelligence-enhanced quantum mechanical method 1 (AIQM1) to thoroughly analyze the electronic and photophysical properties of these …
Large Cycloparaphenylene Nanolassos Characterized with AIQM1 Read more »
By Pavlo O. Dral and Arif Ullah (the views and opinions expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the authors’ affiliated institutions) Preprints are available on Zenodo …
Call for urgent regulations on artificial intelligence Read more »
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.
We have developed artificial intelligence-enhanced quantum mechanical method 1 (AIQM1), which can be used out of the box for very fast quantum chemical calculations with the accuracy of the gold-standard coupled-cluster method. Read more »