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Title: ClusterFinder : a fast tool to find cluster structures from pair distribution function data
A novel automated high-throughput screening approach,ClusterFinder, is reported for finding candidate structures for atomic pair distribution function (PDF) structural refinements. Finding starting models for PDF refinements is notoriously difficult when the PDF originates from nanoclusters or small nanoparticles. The reportedClusterFinderalgorithm can screen 104to 105candidate structures from structural databases such as the Inorganic Crystal Structure Database (ICSD) in minutes, using the crystal structures as templates in which it looks for atomic clusters that result in a PDF similar to the target measured PDF. The algorithm returns a rank-ordered list of clusters for further assessment by the user. The algorithm has performed well for simulated and measured PDFs of metal–oxido clusters such as Keggin clusters. This is therefore a powerful approach to finding structural cluster candidates in a modelling campaign for PDFs of nanoparticles and nanoclusters.  more » « less
Award ID(s):
1922234
PAR ID:
10587228
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
International Union of Crystallographay
Date Published:
Journal Name:
Acta Crystallographica Section A Foundations and Advances
Volume:
80
Issue:
2
ISSN:
2053-2733
Page Range / eLocation ID:
213 to 220
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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