
Filter News
Area of Research
News Type
News Topics
- (-) 3-D Printing/Advanced Manufacturing (13)
- (-) Artificial Intelligence (9)
- (-) Chemical Sciences (9)
- (-) Fusion (9)
- (-) Nanotechnology (6)
- Advanced Reactors (2)
- Big Data (12)
- Bioenergy (23)
- Biology (27)
- Biomedical (13)
- Biotechnology (7)
- Buildings (10)
- Clean Water (7)
- Composites (3)
- Computer Science (14)
- Coronavirus (6)
- Critical Materials (2)
- Cybersecurity (6)
- Energy Storage (13)
- Environment (40)
- Exascale Computing (3)
- Frontier (3)
- Grid (7)
- High-Performance Computing (11)
- Hydropower (2)
- Isotopes (13)
- ITER (1)
- Machine Learning (10)
- Materials (9)
- Materials Science (15)
- Mathematics (5)
- Mercury (4)
- Microscopy (11)
- National Security (17)
- Neutron Science (10)
- Nuclear Energy (16)
- Partnerships (2)
- Physics (16)
- Polymers (5)
- Quantum Computing (1)
- Quantum Science (5)
- Security (7)
- Simulation (8)
- Summit (2)
- Transportation (12)
Media Contacts

As the focus on energy resiliency and competitiveness increases, the development of advanced materials for next-generation, commercial fusion reactors is gaining attention. A recent paper examines a promising candidate for these reactors: ultra-high-temperature ceramics, or UHTCs.
Troy Carter, director of the Fusion Energy Division at Oak Ridge National Laboratory, leads efforts to make fusion energy a reality, overseeing key projects like MPEX and fostering public-private collaborations in fusion research.
Dave Weston studies how microorganisms influence plant health and stress tolerance, using the Advanced Plant Phenotyping Laboratory to accelerate research on plant-microbe interactions and develop resilient crops for advanced fuels, chemicals and

Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment.

The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.

As a mechanical engineer in building envelope materials research at ORNL, Bryan Maldonado sees opportunities to apply his scientific expertise virtually everywhere he goes, from coast to coast. As an expert in understanding how complex systems operate, he’s using machine learning methods to control the process and ultimately optimize performance.

Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.

Brittany Rodriguez never imagined she would pursue a science career at a Department of Energy national laboratory. However, after some encouraging words from her mother, input from key mentors at the University of Texas Rio Grande Valley, or UTRGV, and a lot of hard work, Rodriguez landed at DOE’s Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory.

Early career scientist Frankie White's was part of two major isotope projects at the same time he was preparing to be a father. As co-lead on a team that achieved the first synthesis and characterization of a radium compound using single crystal X-ray diffraction and part of a team that characterized the properties of promethium, White reflects on the life-changing timeline at work, and at home.

John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.