Projects

Generates custom features for analyzing complex crystal structures. These features capture detailed geometric and structural information, such as polyhedron volumes, edge distortions, and atomic distances, focusing on specific sites.

Command-line interface to preprocess, analyze, and visualize data using a variety of machine learning models, including both unsupervised (PCA, clustering) and supervised (classification) learning methods. See the demo here!

Generates geometric features of interatomic distances, atomic environment information, and coordination numbers.

Generates chemical compositional features and provides tools for filtering, sorting, and merging data.

Visualizes binary compounds on periodic tables and recommending elements for novel compound discovery.

Parses .cif files based on structure type and creates a CSV table with site compositions, and heat maps for each site (up to 5 sites) and a heat map for compositions.

Python package for CIF high-throughput analysis.

Command-line Python application designed for high-throughput extraction of minimum bond length and atomic mixing information from CIFs.

This is an interactive software done in jupyter notebook for user-ease. It will plot a single chosen experimental XRD file and allow you to compare it against proposed structures from CIFs.

Automates the steps involved in performing LMTO calculations. The code will take a list of CIFs as input and for each structure in the list, an LMTO calculation will be performed including optimization, band structure, and density of states. The outputs are saved as easily-manageable CSVs.

Parses .csv files produced by the high-throughput LMTO package and automatically produces easily readable & aesthetically pleasing plots ready for publication, posters or presentations. Run the plotter.py file and input the path.

Tutorial to using VASP for running density functional theory calculations in solid-state chemistry.