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 …
Machine learning interatomic potentials as emerging tools for materials science
Atomic‐scale modeling and understanding of materials have made remarkable progress,
but they are still fundamentally limited by the large computational cost of explicit electronic …
but they are still fundamentally limited by the large computational cost of explicit electronic …
Design and optimization of catalysts based on mechanistic insights derived from quantum chemical reaction modeling
Until recently, computational tools were mainly used to explain chemical reactions after
experimental results were obtained. With the rapid development of software and hardware …
experimental results were obtained. With the rapid development of software and hardware …
Critical review of machine learning applications in perovskite solar research
B Yılmaz, R Yıldırım - Nano Energy, 2021 - Elsevier
The astonishing progress achieved in perovskite solar cells in recent years has coincided
with the growing interest in machine learning (ML) for material discovery, and the number of …
with the growing interest in machine learning (ML) for material discovery, and the number of …
Machine learning in materials design and discovery: Examples from the present and suggestions for the future
JE Gubernatis, T Lookman - Physical Review Materials, 2018 - APS
We provide a brief discussion of “What is machine learning?” and then give a number of
examples of how these methods have recently aided the design and discovery of new …
examples of how these methods have recently aided the design and discovery of new …
2D oxide nanomaterials to address the energy transition and catalysis
CJ Heard, J Čejka, M Opanasenko… - Advanced …, 2019 - Wiley Online Library
Abstract 2D oxide nanomaterials constitute a broad range of materials, with a wide array of
current and potential applications, particularly in the fields of energy storage and catalysis …
current and potential applications, particularly in the fields of energy storage and catalysis …
Artificial intelligence for photonics and photonic materials
D Piccinotti, KF MacDonald, SA Gregory… - Reports on Progress …, 2020 - iopscience.iop.org
Artificial intelligence (AI) is the most important new methodology in scientific research since
the adoption of quantum mechanics and it is providing exciting results in numerous fields of …
the adoption of quantum mechanics and it is providing exciting results in numerous fields of …
Machine learning‐aided crystal facet rational design with ionic liquid controllable synthesis
Crystallographic facets in a crystal carry interior properties and proffer rich functionalities in a
wide range of application areas. However, rational prediction, on‐demand customization …
wide range of application areas. However, rational prediction, on‐demand customization …
Application of Advanced Vibrational Spectroscopy in Revealing Critical Chemical Processes and Phenomena of Electrochemical Energy Storage and Conversion
The future of the energy industry and green transportation critically relies on exploration of
high-performance, reliable, low-cost, and environmentally friendly energy storage and …
high-performance, reliable, low-cost, and environmentally friendly energy storage and …
Role of artificial intelligence in chemistry
N Choudhary, R Bharti, R Sharma - Materials Today: Proceedings, 2022 - Elsevier
Recently, artificial intelligence is one of the most cited areas in chemistry. Chemistry and
Artificial Intelligence are inextricably linked! Artificial Intelligence and Chemistry applications …
Artificial Intelligence are inextricably linked! Artificial Intelligence and Chemistry applications …