Dataset

23-Single-Element-DNPs_RSCDD_2023-Ti



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Name 23-Single-Element-DNPs_RSCDD_2023-Ti
Extended ID 23-Single-Element-DNPs_RSCDD_2023-Ti_AndolinaSaidi__DS_ofpcyxez6xsc_0
Description Configurations of Ti 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.
Authors Christopher M. Andolina
Wissam A. Saidi
Elements Ti (100.0%)
Number of Data Objects 5,436
Number of Configurations 5,665
Number of Atoms 153,659
Links https://doi.org/10.1039/D3DD00046J
https://github.com/saidigroup/23-Single-Element-DNPs
Configuration Sets by Name 23-Single-Element-DNPs_RSCDD_2023_Ti_initial — Initial training configurations of Ti from 23-Single-Element-DNPs_RSCDD_2023
23-Single-Element-DNPs_RSCDD_2023_Ti_adaptive — Adaptive training configurations of Ti from 23-Single-Element-DNPs_RSCDD_2023
Configuration Sets by ID CS_7omiqh2lk645_0
CS_cobjd30za0cu_0
Data Objects
ColabFit ID DS_ofpcyxez6xsc_0
Files colabfitspec.json

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