colabfit/SAIT_semiconductors_ACS_2023_SiN_train

SAIT semiconductors ACS 2023 SiN训练数据集包含了来自SAIT semiconductors数据集的SiN、Si和N配置。该数据集是为了开发机器学习力场（MLFFs）而收集的，包含了重要的半导体薄膜材料硅氮化物（SiN）和铪氧化物（HfO）的两个丰富数据集。在不同的条件下（包括不同的初始结构、化学计量比、温度、应变和缺陷）进行了DFT模拟。数据集的列中附加了额外的详细信息，并以dataset_为前缀。数据集包含22510个独特的分子配置和1284467个原子，包括N和Si元素，属性包括能量、原子力和Cauchy应力。

The SAIT semiconductors ACS 2023 SiN train dataset contains SiN, Si, and N configurations from the SAIT semiconductors datasets. This dataset was gathered for the development of Machine Learning Force Fields (MLFFs) and consists of two rich datasets for the important semiconductor thin film materials silicon nitride (SiN) and hafnium oxide (HfO). DFT simulations were conducted under various conditions including different initial structures, stoichiometry, temperature, strain, and defects. Additional details are stored in dataset columns prepended with dataset_. The dataset includes 22,510 unique molecular configurations and 1,284,467 atoms, comprising the elements N and Si, and properties such as energy, atomic forces, and Cauchy stress.