Spatial arrangement of dynamic surface species from solid-state NMR and machine learning-accelerated MD simulations. Issue 100 (30th November 2022)

• Record Type: Journal Article
• Authors: Kobayashi, Takeshi; Liu, Da-Jiang; Perras, Frédéric A.
• Is Part Of: Chemical communications. Volume 58:Issue 100(2022)
• Page Start: 13939
• Page End: 13942
• Publication Date: 2022-11-30
• Subjects: Chemistry -- Periodicals; 540
• DOI: 10.1039/d2cc05861h
• Languages: English
• ISSNs: 1359-7345

Abstract

Abstract : Arrangement of dynamic surface species is explored by experimental dipolar coupling measurements and the prediction of motionally-averaged coupling constant from machine learning-accelerated molecular dynamics simulations. Abstract : The surface arrangement of motional organic functionalities is explored by experimental dipolar coupling measurements and the prediction of motionally-averaged coupling constant from molecular dynamics simulations. The use of machine learning potentials was key to reaching the timescale required. The distance between dynamic surface species are important in cooperative heterogeneous catalysis.