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README.md

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+---
+configs:
+- config_name: default
+  data_files: "main/*.parquet"
+license: gpl-3.0
+tags:
+- molecular dynamics
+- mlip
+- interatomic potential
+pretty_name: 23-Single-Element-DNPs RSCDD 2023-Re
+---
+# Dataset  
+23-Single-Element-DNPs RSCDD 2023-Re  
+### Description  
+Configurations of Re from Andolina & Saidi, 2023. One of 23 minimalist, curated sets of DFT-calculated properties for individual elements for the purpose of providing input to machine learning of deep neural network potentials (DNPs). Each element set contains on average ~4000 structures with 27 atoms per structure. Configuration metadata includes Materials Project ID where available, as well as temperatures at which MD trajectories were calculated.These temperatures correspond to the melting temperature (MT) and 0.25*MT for elements with MT < 2000K, and MT, 0.6*MT and 0.25*MT for elements with MT > 2000K.  
+<br>Additional details stored in dataset columns prepended with "dataset_".  
+### Dataset authors  
+Christopher M. Andolina, Wissam A. Saidi  
+### Publication  
+https://doi.org/10.1039/D3DD00046J  
+### Original data link 
+https://github.com/saidigroup/23-Single-Element-DNPs  
+### License  
+gpl-3.0  
+### Number of unique molecular configurations  
+5029  
+### Number of atoms  
+101248  
+### Elements included  
+Re  
+### Properties included  
+energy, atomic forces, cauchy stress  
+### Cite this dataset
+Andolina, C. M., and Saidi, W. A. _23-Single-Element-DNPs RSCDD 2023-Re_. ColabFit, 2023. https://doi.org/10.60732/1e0997f8