SAIT_semiconductors_ACS_2023_SiN_train

Training configurations from the SAIT_semiconductors_ACS_2023_SiN dataset. This dataset contains SiN, Si and N configurations from the SAIT semiconductors datasets. SAIT semiconductors datasets comprise two rich datasets for the important semiconductor thin film materials silicon nitride (SiN) and hafnium oxide (HfO), gathered for the development of MLFFs. DFT simulations were conducted under various conditions that include differing initial structures, stoichiometry, temperature, strain, and defects.

本数据集为SAIT_semiconductors_ACS_2023_SiN数据集的训练构型集合。其包含SAIT半导体数据集中的氮化硅（SiN）、单质硅（Si）与单质氮（N）原子构型。SAIT半导体数据集包含两组针对两类重要半导体薄膜材料——氮化硅（SiN）与氧化铪（HfO）的丰富数据集，专为机器学习力场（Machine Learning Force Field, MLFF）的开发工作收集。研究团队在多种条件下开展了密度泛函理论（Density Functional Theory, DFT）模拟，所涉及的条件包括不同初始结构、化学计量比、温度、应变以及缺陷类型。