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Dataset for UNEP-v1

Name: Dataset for UNEP-v1
Creator: Fan, Zheyong

Research datakeyboard_double_arrow_right Dataset 08 Nov 2023Publisher:Zenodo

Authors: Fan, Zheyong;

doi: 10.5281/zenodo.11533864 , 10.5281/zenodo.10081677 , 10.5281/zenodo.10081676

Dataset for UNEP-v1

- Summary
- Metrics

Abstract

Dataset for the paper: General-purpose machine-learned potential for 16 elemental metals and their alloys UNEP-v1 = version 1 of Unified NeuroEvolution Potential as implemented in GPUMD (https://gpumd.org/) INCAR: Input file of VASP for single-point DFT calculations nep.in: Input file of GPUMD for NEP training UNEP-v1-main.txt: The main UNEP-v1 model used in the paper ensemble-nep-models.zip: The ensemble of eight UNEP-v1 models trainset.zip: Training data 1-component: all the 1-component training data in extended XYZ format 2-component: all the 2-component training data in extended XYZ format combined-train-xyz: all the training data in a single extended XYZ file testset.zip: Test data for Fig 2 and Figs. S1-S17

Impact byBIP!

	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).	1
	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.	Average
	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.	Average

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