[HTML][HTML] Application of machine learning in optimizing proton exchange membrane fuel cells: a review

R Ding, S Zhang, Y Chen, Z Rui, K Hua, Y Wu, X Li… - Energy and AI, 2022 - Elsevier
Proton exchange membrane fuel cells (PEMFCs) as energy conversion devices for
hydrogen energy are crucial for achieving an eco-friendly society, but their cost and …

[HTML][HTML] Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

R Ding, J Chen, Y Chen, J Liu, Y Bando… - Chemical Society …, 2024 - pubs.rsc.org
Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry
for the creation and optimization of electrocatalysts, which enhance key electrochemical …

How machine learning can accelerate electrocatalysis discovery and optimization

SN Steinmann, Q Wang, ZW Seh - Materials Horizons, 2023 - pubs.rsc.org
Advances in machine learning (ML) provide the means to bypass bottlenecks in the
discovery of new electrocatalysts using traditional approaches. In this review, we highlight …

Rational design of atomically dispersed metal site electrocatalysts for oxygen reduction reaction

K Wan, T Chu, B Li, P Ming, C Zhang - Advanced Science, 2023 - Wiley Online Library
Future renewable energy supply and a cleaner Earth greatly depend on various crucial
catalytic reactions for the society. Atomically dispersed metal site electrocatalysts (ADMSEs) …

Machine learning-assisted exploration of the intrinsic factors affecting the catalytic activity of ORR/OER bifunctional catalysts

N Ma, Y Zhang, Y Wang, C Huang, J Zhao… - Applied Surface …, 2023 - Elsevier
Oxygen reduction reaction and oxygen evolution reaction are pivotal in energy conversion.
Herein, we systematically studied the catalytic performance of Pt-doped dual transition metal …

Screening of single transition metal substitution in two-dimensional Mo2CTx MXene electrocatalyst with ultrahigh activity for oxygen reduction reaction

X Chen, Y Zhang, S Lin, H Zhang, X Zhao - Surfaces and Interfaces, 2023 - Elsevier
The growing family of two-dimensional transition-metal carbides, nitrides, and carbonitrides
(MXenes) have received increasing attention for electrocatalysis. In this work, the activity of …

Screening of transition metal-based MOF as highly efficient bifunctional electrocatalysts for oxygen reduction and oxygen evolution

X Chen, Y Li, X Zhao - Surfaces and Interfaces, 2023 - Elsevier
Designing efficient oxygen reduction reaction (ORR) and oxygen evolution reaction (OER)
electrocatalysts is momentous for energy storage and conversion, as well as sustainable …

Spontaneous internal electric field in heterojunction boosts bifunctional oxygen electrocatalysts for zinc–air batteries: theory, experiment, and application

Y Yao, J Wu, Q Feng, K Zeng, J Wan, J Zhang, B Mao… - Small, 2023 - Wiley Online Library
Heterojunctions are a promising class of materials for high‐efficiency bifunctional oxygen
electrocatalysts in both oxygen reduction reaction (ORR) and oxygen evolution reaction …

First-principles screening of Pt doped Ti2CNL (N= O, S and Se, L= F, Cl, Br and I) as high-performance catalysts for ORR/OER

N Ma, Y Wang, Y Zhang, B Liang, J Zhao, J Fan - Applied Surface Science, 2022 - Elsevier
Develo** high-activity and low-cost oxygen reduction reaction (ORR) and oxygen
evolution reaction (OER) bifunctional catalysts is strategic to metal-air batteries. Herein …

[HTML][HTML] The role of machine learning in carbon neutrality: Catalyst property prediction, design, and synthesis for carbon dioxide reduction

Z Wang, Z Sun, H Yin, H Wei, Z Peng, YX Pang, G Jia… - eScience, 2023 - Elsevier
Achieving carbon neutrality is an essential part of responding to climate change caused by
the deforestation and over-exploitation of natural resources that have accompanied the …