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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
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 . 2023
License: CC BY
Data sources: Datacite
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Dataset and Model for "Understanding the limits to short-range order suppression in many-component disordered rock salt lithium-ion cathode materials"

Authors: Squires, Alexander G.;

Dataset and Model for "Understanding the limits to short-range order suppression in many-component disordered rock salt lithium-ion cathode materials"

Abstract

Data and Model For "Understanding the limits to Short-range order Suppression in Many-Component Disordered Rock Salt Lithium-ion Cathode Materials" Paper DOI: 10.1039/D3TA02088F Raw data (VASP calculations) and production model for the associated paper. - `cluster_expansions` contains the final model used for the analysis in the paper. The model can be loaded using the `icet` cluster expansion package using ``` from icet import ClusterExpansion # requires the icet python package ce = ClusterExpansion.read("cluster_expansion.ce") ``` see the icet docs for how to manipulate this object: https://icet.materialsmodeling.org/ - `raw_data` contains the data used to fit the model. The calculation data contains the raw vasp calculations in tar.gz files, and each training generation has an associated `.json` files. The files contain Pymatgen ComputedStructureEntry objects. Probably the easiest way to load these into a python script is ``` from monty serialization import loadfn # requires the monty package training_data = loadfn("calculation_data.json") ``` - element references contains VASP calculations (stored as above) for the elemental reference calculations used to determine the formation energies of the training structures

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selected citations
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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).
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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.
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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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