Codes
GNNOpt
An ensemble-embedding graph neural network for direct prediction of optical spectra from crystal structures.
Input: Crystal structure data (e.g. cif file)
Output: Complex dielectric function, absorption coefficient, complex refractive index, and reflectance.
Machine learning: Equivariant graph neural networks.
Applications: Screening photovoltaic and quantum materials.
Published paper: N. T. Hung, R. Okabe, A. Chotrattanapituk and M. Li, Ensemble-embedding graph neural network for direct prediction of optical spectra from crystal structure, arXiv:2406.16654
QERaman
An open-source program for computing the first-order resonance Raman spectroscopy based on Quantum ESPRESSO.
In the QERaman program, the complex values of Raman tensors are calculated based on the quantum description of the Raman scattering from calculations of electron-photon and electron-phonon matrix elements, which are obtained by using the modified Quantum ESPRESSO. Our program also calculates the resonant Raman spectra as a function of incident laser energy for linearly- or circularly-polarized light. The program will be a helpful tool for experimentalists who want a theoretical tool for understanding the observed resonance Raman spectra for a linearly- or circularly polarized light. All codes, examples, and scripts are available on the GitHub repository.
Published paper: N. T. Hung, J. Huang, Y. Tatsumi, T. Yang, and R. Saito, QERaman: An open-source program for calculating resonance Raman spectra based on Quantum ESPRESSO, Comput. Phys. Commun. 295, 108967 (2024).