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doi: 10.1002/jcc.26062
pmid: 31503364
We present an interpretation of Fermi‐orbital descriptors (FODs) and argue that these descriptors carry chemical bonding information. We show that a bond order derived from these FODs agrees well with reference values, and highlight that optimized FOD positions used within the Fermi‐Löwdin orbital self‐interaction correction (FLO‐SIC) method correspond to expectations from Linnett's double‐quartet theory, which is an extension of Lewis theory. This observation is independent of the underlying exchange‐correlation functional, which is shown using the local spin density approximation, the Perdew–Burke–Ernzerhof generalized gradient approximation (GGA), and the strongly constrained and appropriately normed meta‐GGA. To make FOD positions generally accessible, we propose and discuss four independent methods for the generation of Fermi‐orbital descriptors, their implementation as well as their advantages and drawbacks. In particular, we introduce a re‐implementation of the electron force field, an approach based on the centers of mass of orbital densities, a Monte Carlo‐based algorithm, and a method based on Lewis‐like bonding information. All results are summarized with respect to future developments of FLO‐SIC and related methods. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 27 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |