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Advancing Computational Approaches for Study and Design in Catalysis

Luber, Sandra (2018). Advancing Computational Approaches for Study and Design in Catalysis. CHIMIA International Journal for Chemistry, 72(7):508-513.

Abstract

Our group deals with the development of computational methods and their application to complex systems and processes. Emphasis is laid on accurate approaches derived from quantum mechanics, which we have used to investigate challenging questions in an interdisciplinary field encompassing chemistry, biology, physics, and materials science. In this review, we describe our recent activities for advancing computational approaches in catalysis. Moreover, our work for the study and design of catalysts for solar light-driven water splitting is summarized. The latter is a promising approach to face the world's increasing demand for sustainable energy storage and conversion. Emphasis is put on forefront methods for highly accurate electronic structure, sophisticated inclusion of environmental and dynamic effects and the derivation of structure–activity relationships for informed in silico design. This paves the way for the development of more efficient catalysts in close collaboration with experimental groups.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Department of Chemistry
Dewey Decimal Classification:540 Chemistry
Scopus Subject Areas:Physical Sciences > General Chemistry
Uncontrolled Keywords:General Chemistry, General Medicine
Language:English
Date:22 August 2018
Deposited On:14 Feb 2019 14:33
Last Modified:20 Sep 2024 01:34
Publisher:Swiss Chemical Society
ISSN:0009-4293
Additional Information:Copyright ©Swiss Chemical Society: CHIMIA, 72(7):508-513, 2018
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.2533/chimia.2018.508
PubMed ID:30158014
Project Information:
  • Funder: Swiss National Science Foundation
  • Grant ID: PP00P2 170667
  • Project Title:
  • Funder: University Research Priority Program
  • Grant ID: LightChEC
  • Project Title:
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