Machine learning models are poised to make a transformative impact on chemical sciences
by dramatically accelerating computational algorithms and amplifying insights available from …

The design of heterogeneous catalysts relies on understanding the fundamental surface
kinetics that controls catalyst performance, and microkinetic modeling is a tool that can help …

Fast and accurate simulation of complex chemical systems in environments such as
solutions is a long standing challenge in theoretical chemistry. In recent years, machine …

We review the state-of-the-art in the theory of dissociative chemisorption (DC) of small gas
phase molecules on metal surfaces, which is important to modeling heterogeneous catalysis …

In this review, we comprehensively describe catalyzed multicomponent reactions (MCRs)
and the multiple roles of catalysis combined with key parameters to perform these …

Solvent effects have always been a non-negligible factor for aqueous catalytic reactions,
though few studies have been devoted towards the molecular understanding and impact of …

Autonomous computations that rely on automated reaction network elucidation algorithms
may pave the way to make computational catalysis on a par with experimental research in …

Hybrid discrete‐continuum approaches for solvation have been widely applied for diverse
problems in chemistry suck as pKa calculation in aqueous and nonaqueous solvents …

Furfural and hydroxymethylfurfural are promising platform molecules for manufacturing
chemicals and fuel components. These furanic compounds are the product of the acid …

A cross-linked molecularly imprinted polymer (MIP) was synthesized and functionalized by
metal oxide nanoparticles (TiO 2 and SiO 2) to form a potential cross-linked (MIP) …