Unifying views on catalyst deactivation

AJ Martín, S Mitchell, C Mondelli, S Jaydev… - Nature Catalysis, 2022 - nature.com
Berzelius stated that catalysts remain unaltered in their reaction environment. However,
catalyst deactivation always becomes noticeable at certain timescales, frequently hindering …

Computational discovery of transition-metal complexes: from high-throughput screening to machine learning

A Nandy, C Duan, MG Taylor, F Liu, AH Steeves… - Chemical …, 2021 - ACS Publications
Transition-metal complexes are attractive targets for the design of catalysts and functional
materials. The behavior of the metal–organic bond, while very tunable for achieving target …

Self-driving laboratories for chemistry and materials science

G Tom, SP Schmid, SG Baird, Y Cao, K Darvish… - Chemical …, 2024 - ACS Publications
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

Artificial intelligence for science in quantum, atomistic, and continuum systems

X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie… - arXiv preprint arXiv …, 2023 - arxiv.org
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Computational ligand descriptors for catalyst design

DJ Durand, N Fey - Chemical reviews, 2019 - ACS Publications
Ligands, especially phosphines and carbenes, can play a key role in modifying and
controlling homogeneous organometallic catalysts, and they often provide a convenient …

Hybrid machine learning approach to predict the site selectivity of iridium-catalyzed arene borylation

E Caldeweyher, M Elkin, G Gheibi… - Journal of the …, 2023 - ACS Publications
The borylation of aryl and heteroaryl C–H bonds is valuable for the site-selective
functionalization of C–H bonds in complex molecules. Iridium catalysts ligated by bipyridine …

Organic reactivity from mechanism to machine learning

K Jorner, A Tomberg, C Bauer, C Sköld… - Nature Reviews …, 2021 - nature.com
As more data are introduced in the building of models of chemical reactivity, the mechanistic
component can be reduced until 'big data'applications are reached. These methods no …

Automated in silico design of homogeneous catalysts

M Foscato, VR Jensen - ACS catalysis, 2020 - ACS Publications
Catalyst discovery is increasingly relying on computational chemistry, and many of the
computational tools are currently being automated. The state of this automation and the …

Exploration of reaction pathways and chemical transformation networks

GN Simm, AC Vaucher, M Reiher - The Journal of Physical …, 2018 - ACS Publications
For the investigation of chemical reaction networks, the identification of all relevant
intermediates and elementary reactions is mandatory. Many algorithmic approaches exist …

Exploring paths of chemical transformations in molecular and periodic systems: An approach utilizing force

S Maeda, Y Harabuchi - Wiley Interdisciplinary Reviews …, 2021 - Wiley Online Library
This article provides an overview on an automated reaction path search method called
artificial force induced reaction (AFIR). The AFIR method induces various chemical …