The recent rise of computational, data-driven research has significant potential to accelerate
materials discovery. Automated workflows and materials databases are being rapidly …

Building metal materials with well-defined components and the monomer-genetic property is
one of the foremost challenges in chemistry and materials science. In recent years, metal …

Electrocatalytic nitrate reduction to NH 3 not only enables the recycling of nutrients from
nitrate wastewater but can also lead to complete nitrogen elimination when paired with an …

Subnanometric transition-metal (TM) clusters have attracted great attention due to their
unexpected physical and chemical properties, leastwise compared to their bulk …

Subnanometer noble metal clusters have enormous potential, mainly for catalytic
applications. Because a difference of only one atom may cause significant changes in their …

Platinum (Pt) is one of the most studied materials in catalysis today and considered for a
wide range of applications: chemical synthesis, energy conversion, air treatment, water …

A 2D black phosphorus/platinum heterostructure (Pt/BP) is developed as a highly efficient
photocatalyst for solar‐driven chemical reactions. The heterostructure, synthesized by …

We first report a global optimization approach based on GPU accelerated Deep Neural
Network (DNN) fitting, for modeling metal clusters at realistic temperatures. The seven-layer …

The electrocatalytic co-reduction of small carbonaceous and nitrogenous molecules recently
emerged as a promising strategy to mitigate carbon emissions, facilitate wastewater …

An atom-level ab initio understanding of the structural, energetic, and electronic properties of
nanoclusters with diameter size from 1 to 2 nm figures as a prerequisite to foster their …