colabfit/JARVIS_TinNet_N

JARVIS_TinNet数据集是JARVIS数据库的一部分，该数据库是一个联合自动化仓库，用于各种集成模拟。这个数据集包含了TinNet-N数据集中的配置，用于训练机器学习模型，旨在通过预测过渡金属表面的化学反应性来辅助催化剂设计。数据集中的吸附系统由{100}终止的基于铂的双金属表面组成，并掺杂第三种元素。JARVIS是一套工具和收集的数据集，旨在满足当前的物质设计挑战。数据集包含了329个独特的分子配置，共有6251个原子，包括了H、N、Ni等元素，并包含了吸附能量、原子力、Cauchy应力等属性。

The JARVIS_TinNet dataset is part of the JARVIS database, a joint automated repository for various integrated simulations. This dataset contains configurations from the TinNet-N dataset, assembled to train a machine learning model to assist catalyst design by predicting the chemical reactivity of transition-metal surfaces. The adsorption systems in this dataset consist of {100}-terminated Pt-based bimetallic surfaces doped with a third element. JARVIS is a suite of tools and collected datasets built to address current materials design challenges. The dataset includes 329 unique molecular configurations, with a total of 6251 atoms, encompassing elements such as H, N, Ni, and others, and includes properties like adsorption energy, atomic forces, and Cauchy stress.