The Department of Energy’s Office of Science has selected five Oak Ridge National Laboratory scientists for Early Career Research Program awards.
Since its inception in 2010, the program bolsters national scientific discovery by supporting early career researchers in fields pertaining to the Office of Science's eight major program offices: Advanced Scientific Computing Research, Biological and Environmental Research, Basic Energy Sciences, Fusion Energy Sciences, High Energy Physics, Nuclear Physics, Accelerator R&D and Production and Isotope R&D and Production.
Award eligibility is typically restricted to scientists in the first 10 years of their careers, though this year’s eligibility was extended to 12 years considering complications from the COVID-19 pandemic. Many researchers complete their most formative work in these early career years.
“Supporting America’s scientists and researchers early in their careers will ensure the United States remains at the forefront of scientific discovery,” said U.S. Secretary of Energy Jennifer M. Granholm. “The funding announced today gives the recipients the resources to find the answers to some of the most complex questions as they establish themselves as experts in their fields.”
A total of 93 scientists nationwide, employed across 12 DOE national laboratories and 48 universities, will receive funding through this year’s program.
“Support for these talented researchers is vital to ORNL’s goal of furthering the nation’s scientific priorities,” ORNL Interim Director Jeff Smith said. “Their scientific contributions will help in addressing challenges in quantum materials and computing, environmental systems and fusion energy.”
The ORNL researchers receiving awards include:
Matthew Brahlek, an R&D staff scientist in the Materials Science and Technology Division, was selected by the Basic Energy Sciences program for his proposal, “Epitaxially Imposed Control of Chiral Transport Phenomena.”
Due to their exotic states, materials with chiral symmetry, or a lack of mirror symmetry, offer key advantages in quantum-based technologies. To fully exploit their properties, however, scientists must simultaneously control a material’s underlying symmetry and dimensionality. In this project, Brahlek will create new chiral systems by combining dissimilar materials at the atomic level as atomically thin crystalline films. These new materials will allow for targeted control of symmetry and dimensionality to enable the discovery of new exotic superconductors and unusual low dimensional states. The resulting fundamental design principles established will drive the development of a new generation of quantum materials.
Jack Cahill, an R&D associate scientist in the Biosciences Division, was selected by the Biological and Environmental Research Program for his proposal, “Elucidation and Validation of Genes Associated with Biological Nitrification Inhibition in Populus.”
Nitrogen use efficiency, the amount of nitrogen used by a crop compared to the amount of nitrogen added, greatly impacts natural carbon sequestration. Bioenergy crops typically have low nitrogen use efficiency – as much as 70% of added nitrogen is lost as waste – which leads to poor carbon sequestration. Biological nitrification inhibitor molecules released from plants prevent such nitrogen loss by slowing nitrification processes. With this proposal, Cahill will conduct experiments to identify genes associated with such molecules in common bioenergy crop poplar, analyze nitrification in the soil surrounding poplar roots and ultimately improve crops’ efficiency and carbon sequestration.
Eugene Dumitrescu, a staff research scientist in the Computational Science and Engineering Division, was selected by the Advanced Scientific Computing Research program for his proposal, “MLRep4QC3: Multi-Linear Representations for Quantum Characterization, Control, and Computation.”
Quantum processes have greatly expanded the boundaries of modern science, but scientists lack high-level operational methods for controlling quantum states. Dumitrescu aims to accelerate computational science by identifying where quantum control is possible with classical computing resources. To overcome scalability problems with prior models, Dumitrescu will develop multi-linear representation, or MLRep, algorithms, powerful tools to represent quantum states and minimize computational requirements for quantum characterization. Dumitrescu will then assess the quality of quantum processes and demonstrate the feasibility of MLRep algorithms for controlling quantum states. Finally, the algorithms will be compiled into a linear algebra package evaluating classical computing’s potential in quantum control.
Takaaki Koyanagi, an R&D staff scientist in the Materials Science and Technology Division, was selected by the Fusion Energy Sciences Program for his proposal, “Mechanistic framework for additive manufacturing of highly radiation-resistant SiC components.”
Despite its potential as a carbon-free energy source, fusion power still faces several challenges, including a need for irradiation-resistant components. Koyanagi aims to develop these critical parts by combining the benefits of silicon carbide, a promising material for fusion energy system components, with the flexibilities of additive manufacturing. Specifically, Koyanagai will use binder jet 3D printing and chemical vapor infiltration of silicon carbide, a novel process developed at ORNL, to additively manufacture components. He will determine the products’ ideal microstructure for fusion through neutron irradiation experiments at ORNL’s High Flux Isotope Reactor, high-throughput processing and machine learning data analysis.
Dan Lu, a senior staff scientist in the Computational Sciences and Engineering Division, was selected by the Biological and Environmental Research program for her proposal, “Integrating Machine Learning Models into E3SM for Understanding Coastal Compound Flooding.”
Coastal urban regions have a unique importance to economic and environmental health. Because of population increases and coastal development, these areas are acutely threatened by the risk of severe flooding. Further research is needed to understand backwater effects, which occur when downstream water levels are higher than river water levels and are often responsible for coastal flooding. To address this need, Lu will use DOE’s Energy Exascale Earth System Model, or E3SM, alongside machine learning methods to create a data- and physics-driven river model for evaluating backwater effects and modeling floods, with the goal of establishing reliable predictions to mitigate floods.
Awardees will receive a combined $135 million across five years to cover salary and research expenses. The final details for each project award are subject to final grant and contract negotiations between DOE and the awardees.
UT-Battelle manages ORNL for the Department of Energy’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States. The Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science. — Alexandra DeMarco
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