Python python toolset for Structure-Informed Property and Feature Engineering with Neural Networks. It offers unique advantages through (1) effortless extensibility, (2) optimizations for ordered, dilute, and random atomic configurations, and (3) automated model tuning.

An interface between the Materials Project software suite and the Schrodinger Python API, designed to allow for high-throughput execution of Jaguar and AutoTS calculations for molecular thermodynamics and kinetics.

ALLM: Active Learning for Accelerated Design of Layered Materials

JSON schemas and examples representing structural data, characteristic properties, modeling workflows and related data about materials standardizing the diverse landscape of information

Exabyte.io platform documentation containing a detailed explanation of the entities, and their relationship, as well as a list of hands-on video tutorials.

ExPrESS: Exabyte Property Extractor, Sourcer, Serializer. A python package allowing to extract and standardize materials data from native format for physics-based simulation engines.