Oxidation State Localized Orbitals: A Method for Assigning Oxidation States Using Optimally Fragment-Localized Orbitals and a Fragment Orbital Localization Index

Abstract

Oxidation states represent the ionic distribution of charge in a molecule, and are significant in tracking redox reactions and understanding chemical bonding. While e↵ective algorithms already exist based on formal Lewis structures, as well as using localized orbitals, they exhibit di↵erences in challenging cases where e↵ects such as redox non-innocence are at play. Given a density functional theory (DFT) calculation with chosen total charge and spin multiplicity, this work reports a new approach to obtaining fragment-localized orbitals that is termed oxidation state localized orbitals 1 (OSLO), together with an algorithm for assigning the oxidation state using the OSLOs and an associated fragment orbital localization index (FOLI). Evaluating the FOLI requires fragment populations, and for this purpose a new version of the intrinsic atomic orbital (IAO) scheme is introduced in which the IAOs are evaluated using a reference minimal basis formed from on-the-fly superposition of atomic density (IAO-AutoSAD) calculations in the target basis set, and at the target level of theory. The OSLO algorithm is applied to a range of challenging cases including high valent metal oxide complexes, redox non-innocent NO and dithiolate transition metal complexes, a range of carbene-containing TM complexes, and other examples including the potentially inverted ligand field in [Cu(CF 3 ) 4 ] . Across this range of cases, OSLO produces generally satisfactory results. Furthermore, in borderline cases, the OSLOs and associated FOLI values provide direct evidence of the emergence of covalent interactions between fragments that nicely complements existing approaches.

Revisiting Formal Copper(III) Complexes: Bridging Perspectives with Quasi‐d10 Configurations

“…and Hartwig, [1] produces four well‐localised d‐ orbitals with partial orbital charges at the metal approaching two (Figure 2c) i. e. an intrinsic d 8 configuration. This result supports a Cu(III) assignment, and is in agreement with other computational treatments, EOS, [20] LOBA, [19] and OSLO, [12b] as recently reported by Gimferrer et al ., [12] and also at our chosen level of theory (see SI for details). Notably this aligns with the spectroscopic analysis of Cutsail and co‐workers [12c] .…”

“…This approach is in line with the spirit of the LOBA method for computational OS assignment, [19] for which the need for better localised orbitals was recently underlined [12a] . and the more recent OSLO method, which uses a (modified) IBO basis [12b] . For the complex in question, our procedure, conceptually aligned with Sit et al [17] .…”

How reduced are nucleophilic gold complexes?

“…Similar conclusions have been reached by Salvador and co-workers when investigating transition metal complexes with Fischer and Schrock carbenes. [69][70][71][72] Future efforts to pin down the elusive OS concept may benefit from EN definitions capable of accounting for the molecular environment, such as the charge-dependent EN concept introduced by Sanderson [73][74][75] and pioneered by Pritchard [76][77][78][79][80] which provided the basis for more recent treatments of EN within conceptual DFT. 81,82…”

cell2mol: encoding chemistry to interpret crystallographic data

“…As opposed to these methods, cell2mol is able to provide a reliable and comprehensive interpretation of a unit cell, including the connectivity (C) and charge (Q) of all molecular species contained in crystallography files in a deterministic manner, meaning that it can be applied on individual.cif files with no preliminary training, as opposed to probabilistic models (i.e., MLbased 25 ). Additionally, it does not require any QC computation [32][33][34][35][36] , and offers complete data interoperability 37 . cell2mol provides the necessary information to set up any subsequent QC computation (including solid-state ones) or ML model, or to classify compounds/ligands based on charge, denticity (κ) -or hapticity (η)-or through any substructural search, thus retaining full control over the species included in the final datasets.…”