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How artificial intelligence can transform US energy infrastructure
Surprisingly, changing isotope masses of molybdenum in a single layer of semiconductor molybdenum disulfide was found to shift the color of light emitted when the layer was illuminated. The study revealed the potential of isotope engineering to design new technologies in 2D materials. Credit: Chris Rouleau/ORNL, U.S. Dept. of Energy
Tweaking isotopes sheds light on semiconductors
The Linac Coherent Light Source at DOE’s SLAC National Accelerator Laboratory in California reveals the structural dynamics of atoms and molecules through X-ray snapshots at ultrafast timescales. Pictured here is the LCLS-II tunnel. Credit: Jim Gensheimer/SLAC National Accelerator Laboratory
ORNL, SLAC team up for biology projects

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An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Energy – Building a better thermostat

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

ORNL researchers are developing a method to print low-cost, high-fidelity, customizable sensors for monitoring power grid equipment. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Sensors – Printing on the fly

A method developed at Oak Ridge National Laboratory to print high-fidelity, passive sensors for energy applications can reduce the cost of monitoring critical power grid assets.