Dataset

OPoly26-train




Species content of dataset


Name :
OPoly26-train
Authors :
Daniel S. Levine, Nicholas Liesen, Lauren Chua, James Diffenderfer, Helgi I. Ingolfsson, Matthew P. Kroonblawd, Nitesh Kumar, Amitesh Maiti, Supun S. Mohottalalage, Muhammed Shuaibi, Brian Van Essen, Brandon M. Wood, C. Lawrence Zitnick, Samuel M. Blau, Evan R. Antoniuk
Description :
Training set of the Open Polymers 2026 (OPoly26) dataset. OPoly26 contains over 6.57 million density functional theory (DFT) calculations on cluster fragments of up to 360 atoms derived from polymeric systems, comprising over 1.2 billion total atoms. The dataset encompasses variations in monomer composition, polymerization degree, chain architectures, and solvation environments to improve machine learning model performance for polymer property prediction. Calculations were performed at the B97M-V/def2-SVP level of theory using ORCA.
Cite As :
Levine, D. S., Liesen, N., Chua, L., Diffenderfer, J., Ingolfsson, H. I., Kroonblawd, M. P., Kumar, N., Maiti, A., Mohottalalage, S. S., Shuaibi, M., Essen, B. V., Wood, B. M., Zitnick, C. L., Blau, S. M., and Antoniuk, E. R. "OPoly26-train." ColabFit, 2025. https://doi.org/None.
ColabFit ID :
Date Added :
2026-04-10
License :
FAIR Chemistry License
Downloads :
0
Num. Configurations :
6,104,876
Num. Atoms :
1,125,111,811
Calculated Property Types :
atomic_forces energy
Elements :
Al (0.0%) B (0.0%) Br (0.09%) C (39.15%) Ca (0.0%) Cl (0.4%) Co (0.0%) Cs (0.0%) Cu (0.0%) F (2.59%) Fe (0.0%) H (47.25%) I (0.05%) K (0.0%) La (0.0%) Li (0.0%) Mg (0.0%) N (3.03%) Na (0.0%) Ni (0.0%) O (6.8%) P (0.07%) S (0.55%) Sr (0.0%) Zn (0.0%)
Methods :
DFT-ωB97M-V
Software :
ORCA
Spec File :
Configuration Sets by Name :
Configuration Sets by ID :

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