XenonPy is a high-throughput material exploration framework based on machine learning technologies. This library can generate various chem/phys descriptors for machine learning to explore materials in virtual environment. Descriptors in matminer can be also used. Model training is done by PyTorch. Visualization tool for descriptor and transfer learning framework are also provided.
An open-source application for visualization of crystal structures and grid data that runs on most UNIX and UNIX-like platforms. This application can visualize calculation results from the following electronic structure packages: GAUSSIAN, CRYSTAL, Quantum Espresso (PWscf), WIEN2k, FHI98MD. Three-dimensional data such as electron densities and local potentials as well as Fermi surfaces can be visualized using this application.
An application for prediction of stable and metastable structures from a chemical composition. This application applies the revolutionary algorithm to structure prediction by using various external energy calculators (VASP, GULP, Quantum Espresso, CASTEP).
xTAPP is a first-principles plane-wave pseudo-potential code. It computes band structure and electronic states with high precision for a wide range of materials including metals, oxide surfaces, solid interfaces, and so forth. It has support tools and visualization of output and input, is available as a massively parallel computer using OpenMP, MPI, and GPGPU.