A database of synthetic inelastic neutron scattering spectra from molecules and crystals
<p>This database contains simulated inelastic neutron scattering (INS) spectra for 10,000+ inorganic crystals and 20,000+ organic molecules. The INS database for inorganic crystals is based on the phonon database at Kyoto University by Atsushi Togo (http://phonondb.mtl.kyoto-u.ac.jp/). The INS database for organic molecules is based on the QM8 dataset (http://quantum-machine.org/datasets/).</p> <p>Entry lists can be found in crystals.dat and molecules.dat. After unzipping the tar.gz files, data for each structure model can be found in a subfolder. </p> <p>For the inorganic crystal database, each subfolder contains five files: a structure.cif file for the crystal structure, a vis_inc_0K.csv file containing the simulated VISION/TOSCA spectra, a powder_2Dmesh_coh_0K.csv file containing the simulated powder S(Q,E), a vis_nwdos.csv file containing the neutron weighted PDOS, a vis_dos.csv file containing the true PDOS, and a gamma_modes.xyz file containing the displacements of gamma point phonons for visualization (with Jmol, http://jmol.sourceforge.net/).</p> <p>For the QM8 molecular database, there are five files in each subfolder: an INFO-* file containing the SMILES string as well as the IUPAC name (if available) for this molecule, a *.com file containing the input for Gaussian simulation (which also contains the atomic coordinates), a *vis_inc_0K.csv file containing the simulated INS spectra, a *.xyz file containing the atomic displacement of each vibrational modes (can be visualized with Jmol), and a *modes.csv file containing the calculated INS intensity for each normal mode. </p> <p>A python script (plot_ins.py) to plot the INS data files is provided<br> Usage: plot_ins.py *.csv {-s [1,2] -x [0:100] -y [0:100] -z [0:2.5]}<br> -s : spectrum index, -x/y/z : range to plot </p> <p><br> The manual for the OCLIMAX software used for INS simulations is also provided for reference.</p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 0
- Engagement
- 4