6 citations · 22 across the 34 of their papers we have counts for
4 papers · 1 filter
Machine Learning Framework for Magnetic Candidate Discovery in Cerium-Based Compounds
Joshua A. Torres, Yaser M. Banad, Benjamin O. Tayo +1
Cerium (Ce), the most abundant lanthanide, offers significant potential for addressing shortages in high-performance magnetic materials, particularly through the discovery of compo…
Physics adapted generative AI for metal insulator transition materials under label scarcity
Gourab Datta, Sarah Sharif, Zhisheng Shi +1
Metal-insulator-transition (MIT) materials are promising candidates for switchable electronics, neuromorphic hardware, and reconfigurable photonics, yet experimentally verified exa…
Synthesizability Prediction of Crystalline Structures with Structure-Aware Feature Learning and Uncertainty Quantification
Danial Ebrahimzadeh, Sarah Sharif, Yaser Mike Banad
Predicting which hypothetical inorganic crystals can be experimentally realized remains a central challenge in accelerating materials discovery. SyntheFormer is a positive-unlabele…
Accelerated Discovery of Vanadium Oxide Compositions: A WGAN-VAE Framework for Materials Design
Danial Ebrahimzadeh, Sarah S. Sharif, Yaser M. Banad
The discovery of novel materials with tailored electronic properties is crucial for modern device technologies, but time-consuming empirical methods hamper progress. We present an…