NEWS RELEASES

Lehigh University researchers are pioneering AI-driven advancements in materials science with an $800,000 grant from the U.S. Department of Energy. Led by Dr. Chinedu Ekuma, the project focuses on developing interpretable machine learning models to predict material properties more efficiently. Key innovations include physics-guided machine learning, scalable AI for material predictions, integration with diffusion models, and an open-source computing platform for global accessibility. This research aims to accelerate breakthroughs in semiconductors, aerospace materials, battery technology, climate modeling, and healthcare. 

Italy’s Phlegraean Fields is a hotspot of volcanic activity — an ever-shifting landscape pocketed with acidic hot springs. This huge caldera is a part of the Campanian volcanic arc, which includes Mount Vesuvius, whose eruption wiped out the Roman city of Pompeii in 79 C.E. Yet, despite the hostile and scalding conditions of this environment, some microorganisms thrive. And researchers at Michigan State University are taking notice, hoping to uncover new information about how a particular alga survives in such extreme conditions.

In a new paper published in Plant Physiology, researchers in the MSU-DOE Plant Research Laboratory and the Walker lab — in collaboration with the Shachar-Hill lab of the Department of Plant Biology — are studying Cyanidioschyzon merolae, or C. merolae, and its unique ability to photosynthesize its own food. Understanding how C. merolae operates in such extreme conditions can help scientists better extrapolate — or improve upon — the process of photosynthesis, a function vital to all life on Earth.

MIT researchers developed an automated system to help programmers increase the efficiency of their deep learning algorithms by simultaneously leveraging two types of redundancy in complex data structures: sparsity and symmetry.