Computational and Data Sciences

Materials scientists can learn a lot about a sample material by shooting lasers at it. With nonlinear optical microscopy — a specialized imaging technique that looks for a change in the color of intense laser light — researchers can collect data on how the light interacts with the sample and, through time-consuming and sometimes expensive analyses, characterize the material’s structure and other properties. Now, researchers at Penn State have developed a computational framework that can interpret the nonlinear optical microscopy images to characterize the material in microscopic detail.

UNIVERSITY PARK, Pa. — A new twist on a classic material could advance quantum computing and make modern data centers more energy efficient, according to a team led by researchers at Penn State.   

Barium titanate, first discovered in 1941, is known for its powerful electro-optic properties in bulk, or three-dimensional, crystals. Electro-optic materials like barium titanate act as bridges between electricity and light, converting signals carried by electrons into signals carried by photons, or particles of light.  

UNIVERSITY PARK, Pa. — Projects developed by Felecia Davis, associate professor of architecture in the College of Arts and Architecture’s Stuckeman School, and student researchers in her Computational Textiles Lab (SOFTLAB) in the Stuckeman Center for Design Computing (SCDC) are featured in two exhibitions this week in different parts of the world.