Computational modeling guides development of new materials
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
Chemical engineers use neural networks to discover the properties of metal-organic frameworks, for catalysis and other applications.
A new machine-learning technique could pinpoint potential power grid failures or cascading traffic bottlenecks in real time.
Discovery shows for the first time that multiferroic properties can exist in a two-dimensional material; could lead to more efficient magnetic memory devices.
Thermal span in a layered compound promises applications in next-generation electrical switches and nonvolatile memory.
The new substance is the result of a feat thought to be impossible: polymerizing a material in two dimensions.
The findings could redefine the kinds of particles that were abundant in the early universe.
The discovery could offer a route to smaller, faster electronic devices.
Tenth annual US C3E Women in Clean Energy Symposium focuses on equity and justice in the clean-energy transition.
The new molecule can improve the yield of reactions for generating pharmaceuticals and other useful compounds.
New research on ancient Roman concrete inspires durable and sustainable modern constructions.
New findings might help inform the design of more powerful MRI machines or robust quantum computers.
With MIGHTR, PhD student W. Robb Stewart aims to speed construction of new nuclear plants to help decarbonize the economy.
Radioactive molecules are sensitive to subtle nuclear phenomena and might help physicists probe the violation of the most fundamental symmetries of nature.
By making the microbes more tolerant to toxic byproducts, researchers show they can use a wider range of feedstocks, beyond corn.
Faculty from the departments of Physics and of Nuclear Science and Engineering faculty were selected for the Early Career Research Program.