Feature Articles

Scientists at the Department of Energy’s Oak Ridge National Laboratory and the University of Cincinnati achieved a breakthrough in understanding the vulnerability of microbes to the butanol they produce during fermentation of plant biomass. The discovery could pave the way for more efficient production of domestic fuels, chemicals and materials.

Argonne researchers used the lab’s Aurora exascale supercomputer to perform large-scale simulations of the universe, providing a testing ground to investigate Dark Energy Spectroscopic Instrument’s potentially game-changing observations of dark energy.

The 1,000 Scientist AI Jam brought together DOE researchers at Argonne and eight other labs to explore models from OpenAI and Anthropic and understand AI’s potential to accelerate discoveries in energy, materials science, medicine and more.

Daniel Haskel of the lab’s Photon Sciences directorate has been selected to represent Argonne in the 2025 cohort of DOE’s Oppenheimer Science and Energy Leadership Program (OSELP).

Researchers at Georgia State University used the Summit supercomputer to study an elaborate molecular pathway called nucleotide excision repair, or NER. They built a computer model of a critical NER component called the pre-incision complex, or PInC, which plays a key role in regulating DNA repair processes in the latter stages of the NER pathway. Decoding NER’s sophisticated sequence of events and the role of PInC in the pathway could provide key insights into developing novel treatments and preventing conditions that lead to premature aging and certain types of cancer.

A cutting-edge project to test “fusion blanket” technologies is taking shape, with the Idaho National Laboratory (INL) leading the charge to create a critical component of a fusion reactor.

ALBUQUERQUE, N.M. — What if plastics could self-destruct when their time as a useful product ends? Scientists at Sandia National Laboratories are exploring this concept in one of their latest projects.

Advances in automation, robotics, artificial intelligence (AI), and machine learning (ML) are transforming how research is done at NSLS-II, streamlining workflows, enhancing productivity, and alleviating workloads for both users and staff.