Literature searches, simulations, and practical experiments have been part of the materials science toolkit for decades, but the last few years have seen an explosion of machine learning-driven ...

Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning. Our lab in the Department of Materials ...

NASA’s Transformational Tools and Technologies project integrates AI, advanced materials, and computational methods to accelerate aerospace design and improve aircraft and space systems.

You’ll tackle projects in computational materials design (from high-throughput modeling and phase-diagram simulations to training machine-learning models on experimental signals such as UV–Vis/IR) ...

Material science, at its core, is an interdisciplinary field focusing on the discovery and design of new materials. It combines elements of physics, chemistry and engineering to understand and ...

Researchers have used machine learning to design nano-architected materials that have the strength of carbon steel but the lightness of Styrofoam. The team describes how they made nanomaterials with ...

Schematic diagrams illustrating the atomic arrangement of an MoS₂ specimen observed using 4D-STEM, showing atomic-scale mapping in real-space coordinates x and y and corresponding diffraction patterns ...

Laser-based metal processing enables the automated and precise production of complex components, whether for the automotive industry or for medicine. However, conventional methods require time- and ...

Materials testing is critical in product development and manufacturing across various industries. It ensures that products can withstand tough conditions in their ...