ORNL’s Allard named Microanalysis Society Fellow

Larry Allard, a distinguished research staff member at the Department of Energy’s Oak Ridge National Laboratory, has been named a Fellow of the Microanalysis Society. Bestowed annually, the distinction recognizes eminent scientists, engineers and technologists in the field of microanalysis of materials and related phenomena. Allard is one of only three fellows chosen for the 2022 class.


Sensor research helps fight wildfires

As climate change leads to larger and more frequent wildfires, researchers at the Department of Energy’s Oak Ridge National Laboratory are using sensors, drones and machine learning to both prevent fires and reduce their damage to the electric grid. Engineers are honing technology to remotely sense electrical arcing and faulty equipment, as well as the direction of spreading fires.


Humble named director of the Quantum Science Center

Travis Humble has been named director of the Quantum Science Center headquartered at the Department of Energy’s Oak Ridge National Laboratory. The QSC is a multi-institutional partnership that spans industry, academia and government institutions and is tasked with uncovering the full potential of quantum materials, sensors and algorithms.


Twardy appointed to GEM board of directors

The National GEM Consortium, one of the premier organizations for the best and brightest underrepresented minority STEM talent in the country, has appointed ORNL Chief of Staff Lindsey Twardy as a member of its board of directors.

As a GEM board member, Twardy joins a team of 17 other leaders representing institutions and corporations across the STEM field, such as the Georgia Institute of Technology, NASA and IBM.


Automating neutron experiments with AI

Oak Ridge National Laboratory researchers are developing a first-of-its-kind artificial intelligence device for neutron scattering called Hyperspectral Computed Tomography, or HyperCT. The fully automated, AI-driven platform can rotate a sample in almost any direction, eliminating the need for human intervention and significantly reducing lengthy experiment times.