Water, acetonitrile, and methanol MD simulations driven by many-body ML potentials

Input, output, and trajectories of molecular dynamics (MD) simulations of water, acetonitrile, and methanol. Simulations were driven by many-body machine learning (mbML) potentials including explicit 1-, 2-, and 3-body contributions. GDML, GAP, and SchNet models are provided in a separate repository. All simulations were performed in the atomic simulation environment (ASE). Analyses including radial distribution function (rdf) curves are provided here. <strong>Manifest</strong> The following simulations are included in this repository for each solvent. 1 ps hexamer NVE MD simulation driven by MP2/def2-TZVP (in ORCA v4.2.0), mbGDML, mbGAP, mbSchNet, and GFN2-xTB started with the same positions and velocities. Velocities were initialized at 298.15 K with a Maxwell-Boltzmann distribution. Periodic NVT MD simulation at 298.15 K for 10 or 30 ps with a 1 fs time step driven by mbGDML. These simulations contained 58 or <strong>137</strong> water molecules, <strong>67</strong> or 122 acetonitrile molecules, <strong>61</strong> methanol molecules. Systems that are not bolded were used for testing purposes.本数据集涵盖水、乙腈与甲醇的分子动力学（molecular dynamics, MD）模拟的输入数据、输出结果及模拟轨迹。所有模拟均采用包含显式1体、2体与3体相互作用项的多体机器学习（many-body machine learning, mbML）势场驱动。GDML、GAP及SchNet模型已在独立代码仓库中提供。所有模拟均通过原子模拟环境（atomic simulation environment, ASE）完成。本仓库同时提供径向分布函数（radial distribution function, rdf）曲线等分析结果。 <strong>数据集清单</strong> 本仓库针对每种溶剂包含以下两类模拟： 1. 以MP2/def2-TZVP（运行于ORCA v4.2.0）、mbGDML、mbGAP、mbSchNet及GFN2-xTB势场驱动的1ps六聚体NVE系综MD模拟，所有模拟均采用完全一致的初始位置与初始速度。初始速度通过麦克斯韦-玻尔兹曼分布在298.15K下生成。 2. 以mbGDML势场驱动的周期性NVT系综MD模拟，模拟温度为298.15K，时长为10ps或30ps，时间步长为1fs。此类模拟体系分别包含58个或<strong>137</strong>个水分子、<strong>67</strong>个或122个乙腈分子、<strong>61</strong>个甲醇分子。未标注粗体的体系被用作测试集。