For more than half a century, materials scientists have struggled with how to simulate the complexity of polymer materials.
Texas A&M researchers developed an AI-guided alloy discovery workflow that speeds up the design of heat-resistant metals.
Morning Overview on MSN
An AI trained on decades of lab data just designed a better battery material — compressing a decade of trial and error into a single afternoon
In late 2023, a robotic laboratory at Lawrence Berkeley National Laboratory ran nonstop for 17 days without a single human ...
From writing emails to generating computer code, much of the artificial intelligence prevalent in our daily lives has ...
Built to handle 500,000 collisions per second, the Electron-Ion Collider is integrating AI into everything from beam tuning ...
Spread the loveThe landscape of scientific inquiry is constantly evolving, and recent advancements in reverse thermal diffusion are reshaping our understanding of material sciences. Researchers have ...
Brain-stimulating contact lenses are as effective as Prozac at treating depression in mice via retinal pathways.
Abstract: This paper designs an intelligent prediction model using machine learning technology. By collecting data and extracting features of various parameters of material interface properties (such ...
A material processing machine works alongside a loader, transforming large piles into more manageable material. With continuous movement and controlled operation, the system keeps the workflow steady ...
This atomistic model showing the coexistence of two solid phases of NiTi: austenite (blue), stable at higher temperatures, and martensite (brown), stable at lower temperatures. The martensite region ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results