Python for Glass Genomics (PyGGi) is a package for accelerating innovations in the field of glasses and ceramics. It uses state-of-the-art machine learning algorithms and computational techniques to enable the users in designing novel glasses and understanding the composition-property relationships.Get Started About PyGGi
- Oct 21, 2020: PyGGi pro 2.0:
Updated of version of downloadable package PyGGi pro 2.0 will be available soon for sale. This updated version will house all the three apps Bank, Seer and Zen with additional features. A free version of the same package with limited features will be made available soon. Do purchase the software and contribute to the PyGGi project.
- Oct 14, 2020: Revamped PyGGi website with three new apps:
We are glad to share that we have launched a significantly re-vamped website for PyGGi. This package now houses three apps, namely, PyGGi Bank (a repository for glass data with more than 50,000 compositions), PyGGi Seer (a machine-learning based property prediction tool), and PyGGi Zen (a meta-heuristic optimization package for accelerated glass design). All these packages are freely available for the entire glass community through the web-version. Moreover, we are trying to build a community through the PyGGi Forum. The downloaded version is being updated to include these features as well.
- Sep 3, 2020: Gandhian Young Technological Innovation Award 2020:
We announce with great pleasure that PyGGi has been selected for the Gandhian Young Technological Innovation (GYTI) Award 2020. It is a national award established by SRISTI (Society for Research and Initiatives for Sustainable Technologies and Institutions) for student projects which address an important social, environmental or technological problem faced by masses or disadvantaged people/sectors/spaces or micro and small enterprises or have the potential to impact a pressing national need.
- Aug 31, 2020: PyGGi Version 1.1 Released:
We are pleased to announce the launch of an updated version of PyGGi. We have added 3 more properties for prediction in this version and improved the prediction models overall. Refer to the documentation for more details.
Explore composition-property database of glasses collected from literature
Predict glass properties as a function of the glass composition
Discover new glass compositions based on target properties and compositional constraints
Explore published works and images from glass literature
Download the compatible version of PyGGi for different operating system as per requirements.