Scientific discovery in the age of artificial intelligence

H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu… - Nature, 2023 - nature.com
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

Graph neural networks for materials science and chemistry

P Reiser, M Neubert, A Eberhard, L Torresi… - Communications …, 2022 - nature.com
Abstract Machine learning plays an increasingly important role in many areas of chemistry
and materials science, being used to predict materials properties, accelerate simulations …

Machine learning for a sustainable energy future

Z Yao, Y Lum, A Johnston, LM Mejia-Mendoza… - Nature Reviews …, 2023 - nature.com
Transitioning from fossil fuels to renewable energy sources is a critical global challenge; it
demands advances—at the materials, devices and systems levels—for the efficient …

Water electrolysis

AJ Shih, MCO Monteiro, F Dattila, D Pavesi… - Nature Reviews …, 2022 - nature.com
Electrochemistry has the potential to sustainably transform molecules with electrons
supplied by renewable electricity. It is one of many solutions towards a more circular …

[HTML][HTML] Water electrolysis: from textbook knowledge to the latest scientific strategies and industrial developments

M Chatenet, BG Pollet, DR Dekel, F Dionigi… - Chemical society …, 2022 - pubs.rsc.org
Replacing fossil fuels with energy sources and carriers that are sustainable, environmentally
benign, and affordable is amongst the most pressing challenges for future socio-economic …

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 …

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 …

Review of carbon support coordination environments for single metal atom electrocatalysts (SACS)

W Song, C **ao, J Ding, Z Huang, X Yang… - Advanced …, 2024 - Wiley Online Library
This topical review focuses on the distinct role of carbon support coordination environment
of single‐atom catalysts (SACs) for electrocatalysis. The article begins with an overview of …

Bridging the complexity gap in computational heterogeneous catalysis with machine learning

T Mou, HS Pillai, S Wang, M Wan, X Han… - Nature Catalysis, 2023 - nature.com
Heterogeneous catalysis underpins a wide variety of industrial processes including energy
conversion, chemical manufacturing and environmental remediation. Significant advances …

C2+ Selectivity for CO2 Electroreduction on Oxidized Cu-Based Catalysts

H Li, Y Jiang, X Li, K Davey, Y Zheng… - Journal of the …, 2023 - ACS Publications
Design for highly selective catalysts for CO2 electroreduction to multicarbon (C2+) fuels is
pressing and important. There is, however, presently a poor understanding of selectivity …