danielwu0415/OPoly26-train

OPoly26-train数据集是Open Polymers 2026 (OPoly26)的训练集，包含超过6.57百万个密度泛函理论（DFT）计算，这些计算基于聚合物系统的簇片段，总计超过12亿个原子。数据集涵盖了单体组成、聚合度、链结构和溶剂环境的变化，旨在提高机器学习模型在聚合物属性预测中的性能。计算是在B97M-V/def2-SVP理论水平下使用ORCA进行的。数据集包含的元素有Al、B、Br、C、Ca、Cl、Co、Cs、Cu、F、Fe、H、I、K、La、Li、Mg、N、Na、Ni、O、P、S、Sr、Zn，属性包括能量和原子力。

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. The dataset includes elements such as Al, B, Br, C, Ca, Cl, Co, Cs, Cu, F, Fe, H, I, K, La, Li, Mg, N, Na, Ni, O, P, S, Sr, Zn, and properties like energy and atomic forces.