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 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 …
Gas diffusion electrodes, reactor designs and key metrics of low-temperature CO2 electrolysers
CO2 emissions can be recycled via low-temperature CO2 electrolysis to generate products
such as carbon monoxide, ethanol, ethylene, acetic acid, formic acid and propanol. In recent …
such as carbon monoxide, ethanol, ethylene, acetic acid, formic acid and propanol. In recent …
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 …
Multiscale CO2 Electrocatalysis to C2+ Products: Reaction Mechanisms, Catalyst Design, and Device Fabrication
Electrosynthesis of value-added chemicals, directly from CO2, could foster achievement of
carbon neutral through an alternative electrical approach to the energy-intensive …
carbon neutral through an alternative electrical approach to the energy-intensive …
Machine learning–enabled high-entropy alloy discovery
High-entropy alloys are solid solutions of multiple principal elements that are capable of
reaching composition and property regimes inaccessible for dilute materials. Discovering …
reaching composition and property regimes inaccessible for dilute materials. Discovering …
Technologies and perspectives for achieving carbon neutrality
Global development has been heavily reliant on the overexploitation of natural resources
since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other …
since the Industrial Revolution. With the extensive use of fossil fuels, deforestation, and other …
Rational design of electrocatalytic carbon dioxide reduction for a zero-carbon network
Electrocatalytic CO2 reduction has attracted much attention for its potential application in
CO2 mitigation and fuel production. During the past two decades, the electrocatalytic …
CO2 mitigation and fuel production. During the past two decades, the electrocatalytic …
Interpretable machine learning for knowledge generation in heterogeneous catalysis
Most applications of machine learning in heterogeneous catalysis thus far have used black-
box models to predict computable physical properties (descriptors), such as adsorption or …
box models to predict computable physical properties (descriptors), such as adsorption or …
Stability Issues in Electrochemical CO2 Reduction: Recent Advances in Fundamental Understanding and Design Strategies
Electrochemical CO2 reduction reaction (CO2RR) offers a promising approach to close the
anthropogenic carbon cycle and store intermittent renewable energy in fuels or chemicals …
anthropogenic carbon cycle and store intermittent renewable energy in fuels or chemicals …