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Three 51�ԹϺ��� Davis researchers will receive funding from the of the U.S. Department of Energy, the department announced May 27. They are among 83 researchers at U.S. universities and national laboratories funded by the program this year. The awards are of $150,000 for summer salary and research expenses each year, and are intended to last for five years.

The 51�ԹϺ��� Davis recipients are:

Roopali Kukreja, assistant professor of materials science and engineering, College of Engineering

This project will use new, advanced X-ray techniques to study the electronic, magnetic and structural properties of quantum materials at an atomic scale and over very fast timescales. Quantum materials are potential candidates for use in energy-efficient computing, but because quantum behavior emerges at very small length scales they are difficult to study. The project will make use of Department of Energy user facilities such as the National Synchrotron Light Source II, Linac Coherent Light Source (LCLS) and LCLS II, Advanced Photon Source and Advanced Light Source.

James Letts, assistant professor of molecular and cellular biology, College of Biological Sciences

Letts’ project will characterize the mitochondrial protein complexes and supercomplexes that allow plants to generate chemical energy by mitochondrial respiration. A deep understanding of the structure and function of these complexes will give insights into bioenergy conversion. It will also generate new knowledge and hypotheses about how plants generate energy, advancing the field of plant respiration and bioenergetics and furthering our understanding of other aspects of plant biology.

Aditya Thakur, assistant professor of computer science, College of Engineering

High-performance computing applications have become essential for data collection and simulations in many fields of science. Machine learning can speed up computing applications, but integrating machine learning into applications is challenging. Thakur plans to develop AutoNeurify, an end-to-end system that automatically infuses learning into existing applications, allowing scientists to more readily access the latest advances in machine learning.

“Maintaining our nation’s brain trust of world-class scientists and researchers is one of DOE’s top priorities — and that means we need to give them the resources they need to succeed early on in their careers,” said U.S. Secretary of Energy Jennifer M. Granholm in a news release announcing the awards. “These awardees show exceptional potential to help us tackle America’s toughest challenges and secure our economic competitiveness for decades to come.”

To be eligible, a researcher must be an untenured, tenure-track assistant or associate professor at a U.S. academic institution or a full-time employee at a national laboratory, who received a Ph.D. within the past 10 years.