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 …
Reshaping the material research paradigm of electrochemical energy storage and conversion by machine learning
H Yang, Z He, M Zhang, X Tan, K Sun, H Liu, N Wang… - …, 2023 - Wiley Online Library
Abstract For a “Carbon Neutrality” society, electrochemical energy storage and conversion
(EESC) devices are urgently needed to facilitate the smooth utilization of renewable and …
(EESC) devices are urgently needed to facilitate the smooth utilization of renewable and …
Advancement of modification engineering in lean methane combustion catalysts based on defect chemistry
R Qiu, W Wang, Z Wang, H Wang - Catalysis Science & Technology, 2023 - pubs.rsc.org
The direct emission of lean methane (0.1–1.0 vol%) into the atmosphere causes a serious
greenhouse effect and energy waste. Catalytic methane combustion technology has great …
greenhouse effect and energy waste. Catalytic methane combustion technology has great …
Understanding the hydrogen evolution reaction activity of doped single-atom catalysts on two-dimensional GaPS4 by DFT and machine learning
As a zero-carbon fuel, hydrogen can be produced via electrochemical water splitting using
clean electric energy by the hydrogen evolution reaction (HER) process. The ultimate goal of …
clean electric energy by the hydrogen evolution reaction (HER) process. The ultimate goal of …
Electrolyte Effect on Electrochemical CO2 Reduction to Multicarbon Products
The ever-growing environmental concern has yielded the electrocatalytic carbon dioxide
reduction (eCO2R) center of research attention, as it offers a possible pathway to achieve …
reduction (eCO2R) center of research attention, as it offers a possible pathway to achieve …
Zinc–Air Flow Batteries at the Nexus of Materials Innovation and Reaction Engineering
XH Liu, X Liu, HJ Peng - Industrial & Engineering Chemistry …, 2023 - ACS Publications
Electrically rechargeable zinc–air flow batteries (ZAFBs) remain promising candidates for
large-scale, sustainable energy storage. The implementation of a flowing electrolyte system …
large-scale, sustainable energy storage. The implementation of a flowing electrolyte system …
Charge recombination dynamics in a metal halide perovskite simulated by nonadiabatic molecular dynamics combined with machine learning
Z Zhang, J Wang, Y Zhang, J Xu… - The Journal of Physical …, 2022 - ACS Publications
Nonadiabatic coupling (NAC) plays a central role in driving nonadiabatic dynamics in
various photophysical and photochemical processes. However, the high computational cost …
various photophysical and photochemical processes. However, the high computational cost …
A Route Map of Machine Learning Approaches in Heterogeneous CO2 Reduction Reaction
Machine learning (ML) with its indigenous predicting ability has been influential in the
current scientific world and has enabled a paradigm shift in the field of CO2 reduction …
current scientific world and has enabled a paradigm shift in the field of CO2 reduction …
Rational design of catalysts with earth‐abundant elements
Catalysis has played a crucial role in energy sustainability, environment control, and
chemical production, while the design of high‐performance catalysts is a key scientific …
chemical production, while the design of high‐performance catalysts is a key scientific …
Rational ensemble design of alloy catalysts for selective ammonia oxidation based on machine learning
High-throughput computation and machine learning studies are conducted for the rational
design of ensembles of alloy catalysts for selective catalytic oxidation of NH3 (NH3-SCO) …
design of ensembles of alloy catalysts for selective catalytic oxidation of NH3 (NH3-SCO) …