The reformation of catalyst: From a trial-and-error synthesis to rational design

L Wang, J Wu, S Wang, H Liu, Y Wang, D Wang - Nano Research, 2024 - Springer
The appropriate catalysts can accelerate the reaction rate and effectively boost the efficient
conversion of various molecules, which is of great importance in the study of chemistry …

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 …

Machine learning for high-entropy alloys: Progress, challenges and opportunities

X Liu, J Zhang, Z Pei - Progress in Materials Science, 2023 - Elsevier
High-entropy alloys (HEAs) have attracted extensive interest due to their exceptional
mechanical properties and the vast compositional space for new HEAs. However …

[HTML][HTML] Battery safety: Machine learning-based prognostics

J Zhao, X Feng, Q Pang, M Fowler, Y Lian… - Progress in Energy and …, 2024 - Elsevier
Lithium-ion batteries play a pivotal role in a wide range of applications, from electronic
devices to large-scale electrified transportation systems and grid-scale energy storage …

Exploring the specificity of nanozymes

H Fan, R Zhang, K Fan, L Gao, X Yan - ACS nano, 2024 - ACS Publications
Nanozymes, nanomaterials exhibiting enzyme-like activities, have emerged as a prominent
interdisciplinary field over the past decade. To date, over 1200 different nanomaterials have …

Recent progress and future prospects on all-organic polymer dielectrics for energy storage capacitors

QK Feng, SL Zhong, JY Pei, Y Zhao, DL Zhang… - Chemical …, 2021 - ACS Publications
With the development of advanced electronic devices and electric power systems, polymer-
based dielectric film capacitors with high energy storage capability have become particularly …

Machine learning: new ideas and tools in environmental science and engineering

S Zhong, K Zhang, M Bagheri, JG Burken… - … science & technology, 2021 - ACS Publications
The rapid increase in both the quantity and complexity of data that are being generated daily
in the field of environmental science and engineering (ESE) demands accompanied …

Explainable machine learning in materials science

X Zhong, B Gallagher, S Liu, B Kailkhura… - npj computational …, 2022 - nature.com
Abstract Machine learning models are increasingly used in materials studies because of
their exceptional accuracy. However, the most accurate machine learning models are …

Machine learning aided design and optimization of thermal metamaterials

C Zhu, EA Bamidele, X Shen, G Zhu, B Li - Chemical Reviews, 2024 - ACS Publications
Artificial Intelligence (AI) has advanced material research that were previously intractable,
for example, the machine learning (ML) has been able to predict some unprecedented …