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Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2025
License: CC BY
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License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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modelforge curated dataset: Fe (II) dataset

Authors: Iacovella, Christopher; Chodera, John; Yan, Shuai;

modelforge curated dataset: Fe (II) dataset

Abstract

Modelforge Curated Fe (II) Dataset- 1000 conformer test set- Version: nc_1000_v1.1 This provides a modelforge curated hdf5 file for the Fe (II) dataset. This dataset contains 102 unique systems with a total of 1000 configurations (max of 10 configurations per system). The full dataset contains systems with elements: H, C, N, O, P, S, Cl, and Fe. This dataset is compatible with modelforge hdf5 schema 2. The full Fe(II) dataset includes 28834 total configurations Fe(II) organometallic complexes.Specifically, this includes 15568 HS geometries and 13266 LS geometries. These complexes originate from the Cambridge Structural Database (CSD) as curated by Nandy, et al. (Journal of Physical Chemistry Letters (2023), 14 (25), 10.1021/acs.jpclett.3c01214), and were filtered into “computation-ready” complexes, (those where both oxidation states and charges are already specified without hydrogen atoms missing in the structures), following the procedure outlined by Arunachalam, et al. (Journal of Chemical Physics (2022), 157 (18), 10.1063/5.0125700)The original Fe (II) dataset is available from github:https://github.com/Neon8988/Iron_NNPsThe modelforge dataset was curated from a forked release (no modifications made to the dataset, forked/released to ensure provenance). https://github.com/chrisiacovella/Iron_NNPs/releases/tag/2024Jan16 Citation to the original dataset:Modeling Fe(II) Complexes Using Neural NetworksHongni Jin and Kenneth M. Merz Jr.Journal of Chemical Theory and Computation 2024 20 (6), 2551-2558DOI: 10.1021/acs.jctc.4c00063 Properties included in the dataset: atomic_numbers positions "per_atom" "nanometer" forces "per_atom" "kilojoule_per_mole / nanometer" energies "per_system" "kilojoule_per_mole" total_charge "per_system" "elementary_charge" spin_multiplicities "per_system" mol_id "meta_data"

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selected citations
These citations are derived from selected sources.
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.
BIP!Impulse provided by BIP!
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Average
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