How to Adopt the Next-Generation of Materials Screening for Catalysis Discovery
Published on 03-23-202203:54 PM by
qpham289| Updated on 03-23-202203:54 PM
Catalysts facilitate the creation of almost all synthetic materials we interact with everyday. New materials require new catalysts with enhanced and novel properties. Traditional synthetic approaches for materials discovery are expensive and slow. First-principles simulation has become a reliable tool for the prediction of structures, chemical mechanisms, and reaction energetics for the fundamental steps in homogeneous catalysis. Details of reaction coordinates for competing pathways can provide the fundamental understanding of observed catalytic activity, selectivity, and specificity. Such predictive capability raises the possibility for computational discovery and design of new catalysts with enhanced properties. Unfortunately, this is an arduous process that requires meticulous maintenance, specialized training, and accounting of hundreds of files and properties.
To facilitate the fundamental understanding, design, and discovery of novel catalysts, an automated enterprise solution was designed and developed for collaboration between synthetic and computational chemists on a single web-based platform.
Key Learning Objectives:
Discover the predictive capabilities of physics-based modeling in reactivity and catalysis.
See how automated high-throughput screening accelerates synthetic discovery.
Learn how a web-based platform can generate more ideas and drive innovation through the collaboration of computational and synthetic chemists.
Who Should Attend:
R&D Scientists designing novel materials
Brought to you by:
Thomas Mustard Scientific Lead of Catalysis and Reactivity, Schrödinger
Kelly McSweeney Contributing Editor, C&EN Media Group