Surging efforts and fast progress in AI methods for photochemistry and photophysics make it difficult to track the current state of the art. We cover the recent developments in this field in the chapter on Machine learning methods in photochemistry …
Chapter “Machine Learning Methods in Photochemistry and Photophysics” Read more »
In a recent article published in Frontiers in Physics, we introduce QD3SET-1, a database consisting of 8 data sets that provide the time-evolved population and coherence dynamics for two widely studied systems: the so-called spin-boson model and FMO complex. The …
QD3SET-1: A Database with Quantum Dissipative Dynamics Data Sets Read more »
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 …
Check out the themed collection and our editorial on Insightful machine learning for physical chemistry in PCCP – it was a pleasure for me to guest edit it with Aurora Clark, Olexandr Isayev, and Isaac Tamblyn. Happy reading!
Activation of methane and its conversion to added-value products is an important topic which requires chemical solutions with high yields and selectivity. In our recent collaborative study, we present the oxidation of methane to methanol using nitrogen dioxide as a …
The second edition of the International Symposium on Machine Learning in Quantum Chemistry will be held in person in Uppsala from 29 Nov. to 1 Dec. 2023. More updates to follow on the Symposium website smlqc2023.com!
Artificial Intelligence Chemistry – a new open-access journal – has launched a special issue Artificial intelligence in computational chemistry. Submissions to the special issue are open until July 31, 2023. Articles submitted to this issue will be published free of …
Special Issue on Artificial intelligence in computational chemistry Read more »
Peikun Zheng, the main developer of AIQM1 and contributor to many other methods and studies, successfully defended his PhD! We wish him all the best in his future! Peikun was my first PhD student, co-supervised with Prof. Wei Wu. Thus, …
Congratulations to Peikun, Wudi, Shuang, Yifan, and Yanchi with successful graduations! Read more »
We improved (p)KREG models for an accurate representation of molecular potential energy surfaces (PESs) by including gradient information explicitly in their formalism. Our models are better or on par with other state-of-the-art machine learning models as we show on extensive …
(p)KREG Models for Accurate Molecular Potential Energy Surfaces Read more »
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 »