Data for: On-the-Fly Non-adiabatic Molecular Dynamics Reveals Dissociation Mechanisms of Multiply-Charged Molecules
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Title: Theoretical Trajectories and Experimental Data Overview This dataset contains both the theoretical non-adiabatic molecular dynamics (NAMD) trajectories and the experimental measurements used to investigate the dissociation mechanisms of multiply-charged molecules (e.g., CO2^3+). File Contents The dataset consists of two main files: Data.hdf5 (Theoretical Simulations): Contains the raw NAMD trajectories simulated using the SHARC program. It has been parsed into a highly structured HDF5 file. It includes time-dependent 3D nuclear coordinates (in Å), velocities (in a.u.), and energy tables (in eV) for thousands of trajectories across different initial electronic states. data.xlsx (Experimental Data): Contains the experimental data obtained via COLTRIMS reaction microscope, including the Kinetic Energy Release (KER) spectra and the data points used to construct the experimental Dalitz plots. File Format and Structure The data is provided in standard HDF5 format (Data.hdf5). The file is organized hierarchically by initial electronic state and trajectory ID: /{state_name}/{trajectory_name}/ (e.g., /Doublet_0/traj_0001/). Global Attributes (Root Level) created_at: Timestamp of file creation. units_geometry: Angstrom (Å) units_velocity: Atomic units (a.u.) Group Contents (Per Trajectory) For each individual trajectory group, the following datasets and attributes are provided: 1. Datasets (Time-dependent variables) geometry: 3D nuclear coordinates at each time step. Shape: (N_steps, N_atoms, 3). Unit: Å. velocity: 3D nuclear velocities at each time step. Shape: (N_steps, N_atoms, 3). Unit: a.u. energy_table: Time-evolution of various energies (Kinetic, Potential, Total, and specific electronic states). Shape: (N_steps, N_columns). Unit: eV. The column headers are stored in the columns attribute of this dataset. expec_out_raw: The raw string content of the SHARC expec.out file. 2. Attributes (Metadata & Extracted Properties) elements: Array of atomic symbols (e.g., ['O', 'C', 'O']). atomic_masses: Array of atomic masses. multiplicity: Spin multiplicity of the initial state (e.g., Doublet). nstep: Total number of simulated time steps. delta_energy: The calculated kinetic energy difference between the final and initial steps, used as a proxy for Kinetic Energy Release (KER). Unit: eV. nfrag: Number of molecular fragments at the final simulation step (determined using a distance cutoff of 3.5 Å). frag_list: A simple string representation of the final fragments (e.g., CO, O). frag: Detailed JSON string containing the indices and elements of each final fragment. How to Read the Data You can explore the file structure and contents visually using graphical HDF5 readers such as HDFView. For automated analysis, you can easily load this dataset using the h5py and numpy libraries in Python: import h5py # Open the HDF5 filewith h5py.File("Data.hdf5", "r") as h5: # Access a specific trajectory from a specific state traj = h5["Doublet_0"]["traj_0001"] # 1. Read static attributes elements = traj.attrs["elements"] ker_ev = traj.attrs["delta_energy"] final_fragments = traj.attrs["frag_list"] print(f"Fragments: {final_fragments} | KER: {ker_ev:.2f} eV") # 2. Read time-dependent datasets geom = traj["geometry"][:] # Shape: (Steps, Atoms, 3) in Angstrom vel = traj["velocity"][:] # Shape: (Steps, Atoms, 3) in a.u. # 3. Read the energy table and its column names energy_data = traj["energy_table"][:] energy_columns = traj["energy_table"].attrs["columns"]
# 数据集标题：理论轨迹与实验数据集 ## 概述 本数据集包含用于研究多电荷分子（如CO₂³⁺）解离机制的理论非绝热分子动力学（non-adiabatic molecular dynamics, NAMD）轨迹与实验测量数据。 ## 文件内容 本数据集包含两个主要文件： ### Data.hdf5（理论模拟文件） 包含使用SHARC程序模拟得到的原始非绝热分子动力学轨迹，已解析为结构严谨的HDF5文件。其涵盖数千条不同初始电子态下的轨迹的含时三维核坐标（单位：埃，Å）、速度（单位：原子单位，a.u.）以及能量表（单位：电子伏特，eV）。 ### data.xlsx（实验数据文件） 包含通过COLTRIMS反应显微镜获取的实验数据，涵盖动能释放（Kinetic Energy Release, KER）谱以及用于构建实验达利兹图（Dalitz plots）的数据点。 ## 文件格式与结构 数据以标准HDF5格式（Data.hdf5）提供，文件按初始电子态与轨迹ID进行层级化组织，路径格式为`/{state_name}/{trajectory_name}/`（例如`/Doublet_0/traj_0001/`）。 ### 全局属性（根级别） - `created_at`：文件创建时间戳 - `units_geometry`：埃（Å） - `units_velocity`：原子单位（a.u.） ### 单轨迹组内容 针对每个独立的轨迹组，提供以下数据集与属性： #### 1. 数据集（含时变量） - `geometry`：各时间步的三维核坐标，形状为(N_steps, N_atoms, 3)，单位：Å - `velocity`：各时间步的三维核速度，形状为(N_steps, N_atoms, 3)，单位：a.u. - `energy_table`：各类能量的时间演化数据（包括动能、势能、总能量以及特定电子态能量），形状为(N_steps, N_columns)，单位：eV。该数据集的列标题存储于其自身的attrs属性中 - `expec_out_raw`：SHARC程序expec.out文件的原始字符串内容 #### 2. 属性（元数据与提取属性） - `elements`：原子符号数组（例如`['O', 'C', 'O']`） - `atomic_masses`：原子质量数组 - `multiplicity`：初始态的自旋多重度（例如二重态，Doublet） - `nstep`：模拟的总时间步数 - `delta_energy`：计算得到的最终与初始时间步的动能差值，用作动能释放（KER）的替代指标，单位：eV - `nfrag`：模拟最终步的分子片段数（通过3.5 Å的距离截断值判定） - `frag_list`：最终片段的简易字符串表示（例如`CO, O`） - `frag`：包含各最终片段的索引与元素信息的详细JSON字符串 ## 数据读取方法 可通过HDFView等图形化HDF5阅读器直观探索文件结构与内容。若需自动化分析，可借助Python中的h5py与numpy库轻松加载该数据集： python import h5py # 打开HDF5文件 with h5py.File("Data.hdf5", "r") as h5: # 从指定电子态中访问特定轨迹 traj = h5["Doublet_0"]["traj_0001"] # 1. 读取静态属性 elements = traj.attrs["elements"] ker_ev = traj.attrs["delta_energy"] final_fragments = traj.attrs["frag_list"] print(f"片段：{final_fragments} | KER：{ker_ev:.2f} eV") # 2. 读取含时数据集 geom = traj["geometry"][:] # 形状：(步数, 原子数, 3)，单位：埃 vel = traj["velocity"][:] # 形状：(步数, 原子数, 3)，单位：原子单位 # 3. 读取能量表及其列名 energy_data = traj["energy_table"][:] energy_columns = traj["energy_table"].attrs["columns"]
