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 …
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 …
Cu-Zn-based alloy/oxide interfaces for enhanced electroreduction of CO2 to C2+ products
ZY Zhang, H Tian, L Bian, SZ Liu, Y Liu… - Journal of Energy …, 2023 - Elsevier
The electrochemical CO 2 reduction reaction to produce multi-carbon (C 2+) hydrocarbons
or oxygenate compounds is a promising route to obtain a renewable fuel of high energy …
or oxygenate compounds is a promising route to obtain a renewable fuel of high energy …
Emerging low-nuclearity supported metal catalysts with atomic level precision for efficient heterogeneous catalysis
X Zheng, B Li, Q Wang, D Wang, Y Li - Nano research, 2022 - Springer
Supported atomically dispersed metal catalysts (ADMCs) have received enormous attention
due to their high atom utilization efficiency, mass activity and excellent selectivity. Single …
due to their high atom utilization efficiency, mass activity and excellent selectivity. Single …
High-entropy alloys in electrocatalysis: from fundamentals to applications
High-entropy alloys (HEAs) comprising five or more elements in near-equiatomic
proportions have attracted ever increasing attention for their distinctive properties, such as …
proportions have attracted ever increasing attention for their distinctive properties, such as …
Design concept for electrocatalysts
Y Wang, X Zheng, D Wang - Nano Research, 2022 - Springer
Metal-based electrocatalysts with different sizes (single atoms, nanoclusters, and
nanoparticles) show different catalytic behaviors for various electrocatalytic reactions …
nanoparticles) show different catalytic behaviors for various electrocatalytic reactions …
Four generations of high-dimensional neural network potentials
J Behler - Chemical Reviews, 2021 - ACS Publications
Since their introduction about 25 years ago, machine learning (ML) potentials have become
an important tool in the field of atomistic simulations. After the initial decade, in which neural …
an important tool in the field of atomistic simulations. After the initial decade, in which neural …
Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis
Heterogeneous electrocatalysis lies at the center of various technologies that could help
enable a sustainable future. However, its complexity makes it challenging to accurately and …
enable a sustainable future. However, its complexity makes it challenging to accurately and …
Multi‐sites electrocatalysis in high‐entropy alloys
High‐entropy alloys (HEAs) have attracted widespread attention in electrocatalysis due to
their unique advantages (adjustable composition, complex surface, high tolerance, etc.) …
their unique advantages (adjustable composition, complex surface, high tolerance, etc.) …
Emerging Strategies for CO2 Photoreduction to CH4: From Experimental to Data‐Driven Design
The solar‐energy‐driven photoreduction of CO2 has recently emerged as a promising
approach to directly transform CO2 into valuable energy sources under mild conditions. As a …
approach to directly transform CO2 into valuable energy sources under mild conditions. As a …