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Scientific discovery in the age of artificial intelligence
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …
and accelerate research, hel** scientists to generate hypotheses, design experiments …
Graph neural networks for materials science and chemistry
Abstract Machine learning plays an increasingly important role in many areas of chemistry
and materials science, being used to predict materials properties, accelerate simulations …
and materials science, being used to predict materials properties, accelerate simulations …
Machine learning for a sustainable energy future
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 …
demands advances—at the materials, devices and systems levels—for the efficient …
Water electrolysis
Electrochemistry has the potential to sustainably transform molecules with electrons
supplied by renewable electricity. It is one of many solutions towards a more circular …
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
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 …
benign, and affordable is amongst the most pressing challenges for future socio-economic …
Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
reducing the impact of global warming, and providing solutions to environmental pollution …
Self-driving laboratories for chemistry and materials science
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …
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 …
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
Heterogeneous catalysis underpins a wide variety of industrial processes including energy
conversion, chemical manufacturing and environmental remediation. Significant advances …
conversion, chemical manufacturing and environmental remediation. Significant advances …
C2+ Selectivity for CO2 Electroreduction on Oxidized Cu-Based Catalysts
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 …
pressing and important. There is, however, presently a poor understanding of selectivity …