Premium
Automated oxidation‐state assignment for metal sites in coordination complexes in the Cambridge Structural Database
Author(s) -
Reeves Matthew G.,
Wood Peter A.,
Parsons Simon
Publication year - 2019
Publication title -
acta crystallographica section b
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.604
H-Index - 33
ISSN - 2052-5206
DOI - 10.1107/s2052520619013040
Subject(s) - scripting language , workflow , python (programming language) , computer science , database , oxidation state , valence (chemistry) , state (computer science) , data mining , chemistry , programming language , metal , organic chemistry
The Cambridge Structural Database (CSD) currently contains over 400 000 transition‐metal‐containing entries, however many entries still lack curated oxidation‐state assignments. Surveying and editing the remaining entries would be far too resource‐ and time‐intensive to be carried out manually. Here, a highly reliable automated workflow for oxidation‐state assignment in transition‐metal coordination complexes via CSD Python API (application programming interface) scripts is presented. The strengths and limitations of the bond‐valence sum (BVS) method are discussed and the use of complementary methods for improved assignment confidence is explored. In total, four complementary techniques have been implemented in this study. The resulting workflow overcomes the limitations of the BVS approach, widening the applicability of an automated procedure to more CSD entries. Assignments are successful for 99% of the cases where a high consensus between different methodologies is observed. Out of a total number of 54 999 unique metal atoms in a test dataset, the procedure yielded the correct oxidation state in 47 072 (86%) of cases.