Machine learning for electrocatalyst and photocatalyst design and discovery

H Mai, TC Le, D Chen, DA Winkler… - Chemical …, 2022 - ACS Publications
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

New horizons for catalysis disclosed by supramolecular chemistry

G Olivo, G Capocasa, D Del Giudice… - Chemical Society …, 2021 - pubs.rsc.org
The adoption of a supramolecular approach in catalysis promises to address a number of
unmet challenges, ranging from activity (unlocking of novel reaction pathways) to selectivity …

Electric fields in catalysis: From enzymes to molecular catalysts

NG Léonard, R Dhaoui, T Chantarojsiri, JY Yang - ACS catalysis, 2021 - ACS Publications
Electric fields underlie all reactions and impact reactivity by interacting with the dipoles and
net charges of transition states, products, and reactants to modify the free energy landscape …

Quantitative structure–selectivity relationships in enantioselective catalysis: past, present, and future

AF Zahrt, SV Athavale, SE Denmark - Chemical reviews, 2019 - ACS Publications
The dawn of the 21st century has brought with it a surge of research related to computer-
guided approaches to catalyst design. In the past two decades, chemoinformatics, the …

Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

S Gallarati, R Fabregat, R Laplaza, S Bhattacharjee… - Chemical …, 2021 - pubs.rsc.org
Hundreds of catalytic methods are developed each year to meet the demand for high-purity
chiral compounds. The computational design of enantioselective organocatalysts remains a …

Mechanistic Inference from Statistical Models at Different Data-Size Regimes

DM Lustosa, A Milo - ACS Catalysis, 2022 - ACS Publications
The chemical sciences are witnessing an influx of statistics into the catalysis literature.
These developments are propelled by modern technological advancements that are leading …

From Single Metals to High‐Entropy Alloys: How Machine Learning Accelerates the Development of Metal Electrocatalysts

X Fan, L Chen, D Huang, Y Tian… - Advanced Functional …, 2024 - Wiley Online Library
The rapid advancement of high‐performance computing and artificial intelligence
technology has opened up novel avenues for the development of various metal …

Rerouting the organocatalytic benzoin reaction toward aldehyde deuteration

SC Gadekar, V Dhayalan, A Nandi, IL Zak… - ACS …, 2021 - ACS Publications
Reactive intermediates are key to halting and promoting chemical transformations; however,
due to their elusive nature, they are not straightforwardly harnessed for reaction design …

Revisiting the Paradigm of Reaction Optimization in Flow with a Priori Computational Reaction Intelligence

P Bianchi, JCM Monbaliu - Angewandte Chemie, 2024 - Wiley Online Library
The use of micro/meso‐fluidic reactors has resulted in both new scenarios for chemistry and
new requirements for chemists. Through flow chemistry, large‐scale reactions can be …

Small Data Can Play a Big Role in Chemical Discovery

H Shalit Peleg, A Milo - Angewandte Chemie, 2023 - Wiley Online Library
The chemistry community is currently witnessing a surge of scientific discoveries in organic
chemistry supported by machine learning (ML) techniques. Whereas many of these …