Heterogeneous catalysis underpins a wide variety of industrial processes including energy
conversion, chemical manufacturing and environmental remediation. Significant advances …

Efficient electrocatalysts are crucial for hydrogen generation from electrolyzing water.
Nevertheless, the conventional" trial and error" method for producing advanced …

Volcano plots and scaling relations are commonly used to design catalysts and understand
catalytic behavior. These plots are a useful tool due to their robust and simple analysis of …

The empirical aspect of descriptor design in catalyst informatics, particularly when
confronted with limited data, necessitates adequate prior knowledge for delving into …

The search for better and cheaper electrocatalysts is vital in the global transition to
renewable energy resources. High‐entropy alloys (HEAs) provide a near‐infinite number of …

Recent advancements in artificial intelligence and automation are transforming catalyst
discovery and design from traditional trial-and-error manual mode into intelligent, high …

Our objective is to search a large candidate set of covalent organic frameworks (COFs) for
the one with the largest equilibrium adsorptive selectivity for xenon (Xe) over krypton (Kr) at …

Sluggish oxygen evolution reaction (OER) in acid conditions is one of the bottlenecks that
prevent the wide adoption of proton exchange membrane water electrolyzer for green …

Machine learning (ML) is gaining popularity as a tool for materials scientists to accelerate
computation, automate data analysis, and predict materials properties. The representation of …

Utilizing interpretable machine learning techniques that exhibit both predictive and
informative capabilities enables the effective discovery of high-performance materials. In this …