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ZENODO
Software . 2020
Data sources: Datacite
ZENODO
Software . 2020
Data sources: ZENODO
ZENODO
Software . 2020
Data sources: ZENODO
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pyflosic/fodMC: fodMC release v.1.0.0

Authors: Kai Trepte; Sebastian Schwalbe; Jakob Kraus; Simon Liebing; Alex Johnson;

pyflosic/fodMC: fodMC release v.1.0.0

Abstract

Features Efficient generation of Fermi-orbital descriptors Generation typically takes seconds Allows for any kind of bond arrangement to be initialized One can distinguish different bond orders; important when the bond order is unclear (double bond, triple bonds, etc.) Minimal input: User only needs to provide information about multiple bonds All single bonds are automatically initialized Lone FODs are initialized automatically. This usually works well, but there are cases where it doesn't. Always double-check the generated guess! Highly symmetry guesses Trying to obtain the best possible starting guesses for FLO-SIC calculations Periodic boundary conditions are available Future developments Better structural motifs for core FODs (especially for transitions metals and beyond); current understanding of these systems is limited. Reduce/simplify user input

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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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