Mechanistic Investigations and Search Directions for Catalyst Discovery
Author | : Saurabh Bhandari (Ph.D.) |
Publisher | : |
Total Pages | : 0 |
Release | : 2020 |
ISBN-10 | : OCLC:1396230303 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Mechanistic Investigations and Search Directions for Catalyst Discovery written by Saurabh Bhandari (Ph.D.) and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The transition towards a sustainable energy future hinges strongly on the effective deployment of renewable energy carriers. Wide-scale adoption of sustainable technologies requires major innovation in the development of storage materials that exhibit high energy density and of catalytic materials, that help facilitate the relevant chemical transformations to release the stored energy, in an efficient and cost-effective manner. Fundamental investigations aimed at elucidating detailed mechanistic understanding of such chemistries could greatly accelerate the discovery of favorable energy-storage and catalytic materials. In this dissertation, we utilize a combination of first-principles density functional theory (DFT) calculations, reaction kinetics experimentation, and coverage self-consistent mean-field microkinetic modeling to elucidate detailed atomistic-scale insights for the heterogeneously catalyzed chemistries. We emphasize on the importance of formulating computational models that closely-replicate the surface environment present on the catalyst under reaction conditions, an aspect which is oft-ignored in conventional investigations. Consideration of spectator induced coverage-effects were found to not only influence the energetics of the reaction network through lateral adsorbate-adsorbate repulsions, but more importantly alter the reaction pathway itself, by participating in the reaction mechanism. Our multi-faceted methodology yields an unbiased understanding of the reaction mechanism and enables us to develop a comprehensive picture of the in situ active site. In a broader context, our algorithmic approach provides a systematic framework for elucidating novel descriptions for the nature of the active site as well as reaction mechanisms, consequently providing a more rigorous basis for computational prediction of improved catalytic materials.