Materials Graph Library

We are excited to announce that Materials Graph Library (matgl), our Deep Graph Library/PyTorch reimplementation of the MatErials Graph Network (MEGNet) and Materials 3-body Graph Network (M3GNet) models, is now ready for widespread beta testing! We finally achieved near-feature parity with the original implementations in Tensorflow after months of hard work. The new MatGL includes retrained models of the M3GNet universal potential and the MEGNet formation energy and multi-fidelity band gap models. We have also taken the trouble to include example notebooks to get users started quickly. We believe this new implementation will be more future-proof and extensible. Feedback/issue reports are definitely welcome. This is a collaborative effort between the Materials Virtual Lab and Intel Labs.

Associate Editor of ACS Materials Letters

ACS Materials Letters

Prof Ong has been appointed Associate Editor of ACS Materials Letters with effect from Feb 1 2022. ACS Materials Letters publishes high quality and urgent papers on the forefront of fundamental and applied research, at the interface between materials and other disciplines, such as chemistry, engineering and biology. Papers that showcase multidisciplinary and innovative materials research addressing global challenges are especially welcome.

The Materials Virtual Lab is proud to announce the launch of, a website of curated models, software and datasets for AI in materials science. Here, you will find web applications implementing on-the-fly prediction of properties using our MEGNet and other models, open-source software frameworks for building your own AI models, as well as curated datasets for reproducible materials AI research.

Editorial Board of iScience

Prof Ong has been appointed to the Editorial Board of iScience. iScience is a new interdisciplinary, open-access journal by Cell Press that publishes basic and applied research that advances a specific field across life, physical, and earth sciences. Check out their latest articles at

Sr2LiAlO4 – A novel earth-abundant phosphor with excellent color quality

Our paper on “Mining Unexplored Chemistries for Phosphors for High-Color-Quality White-Light-Emitting Diodes” has been published in Joule. Using supercomputers and data mining, we identified Sr2LiAlO4, the first known Sr-Li-Al-O quaternary crystal, as a highly promising phosphor material in low-cost, high-color-quality white LEDs. Eu2+ and Ce3+-activated Sr2LiAlO4 phosphors exhibit broad green-yellow and blue emissions, respectively, with excellent thermal quenching resistance of > 88% intensity at 150oC. A prototype phosphor-converted white LED utilizing Sr2LiAlO4-based phosphors yields an excellent color rendering index exceeding 90. This work is a collaboration between the Materials Virtual Lab (UCSD), McKittrick group (UCSD) and Im group (Chonnam University). The lead authors are Zhenbin Wang, Jungmin Ha and Yoon Hwa Kim. More information about this work can be found in the Jacobs School of Engineering News as well as Science Daily,, etc.


Meet the newest member of our group, Pythia@Mavrl. Named after the famed oracle of antiquity, Pythia is a GPU-based deep learning machine from Lambda Labs. Our lab will be utilizing Pythia to develop cutting edge models for materials property prediction and discovery.

Scialog: Advanced Energy Storage Team Award

Prof Ong’s team is one of six teams selected for the Scialog Advanced Energy Storage Team Awards by the Research Corporation (Rescorp) for Science Advancement. This project is a collaboration with Prof Scott Warren of University of North Carolina at Chapel Hill and Prof Zhenxing Feng of Oregon State University to develop high-voltage dual-ion batteries. More information can be found in the Rescorp press release.