Date/Time
Date(s) - 10/03/2024
1:55 pm - 2:55 pm
Location
Rhines 125
Categories
Abstract
In an era of increasing global instability, the prospect of finding nuclear devices or materials outside of regulatory control is an ever-increasing concern, while the threat of a nuclear detonation becomes a sobering reality that we may face. In this threat filled landscape, nuclear forensics emerges as means to decipher fundamental questions: what is it? Where did it come from? How did it get there?
Within nuclear forensics, there are two domains, framed in the context of a nuclear device, pre-detonation and post-detonation. Pacific Northwest National Laboratory (PNNL) is one a few laboratories tasked with stewarding US capabilities that investigate materials in both domains.
In this talk, the broader topic of nuclear forensics will be discussed as it pertains to PNNL, however further focus will be applied to the post-detonation domain. We will highlight the efforts of a highly diverse multidisciplinary team examining a pursuit to improve the nuclear data, a foundational underpinning of nuclear forensics, of several high impact isotopes. These nuclear data examinations explore fission products yields, single isotope decay schemes, both radiochemically separated and unseparated with a variety of radiation spectroscopic techniques including advanced coincidence systems.
Bio
Nic Uhnak, Ph.D.
Staff Scientist and Team Lead
Pacific Northwest National Laboratory
Dr. Nic Uhnak is a staff scientist at Pacific Northwest National Laboratory. He attended undergraduate at Boise State University, studying Chemistry, where he discovered a love for radiochemistry. He furthered his education at Washington State University, where he studied inorganic chemistry, which focused on trivalent f element separations for nuclear fuel reprocessing.
Dr. Uhnak joined PNNL as a NTNFC (National Technical Nuclear Forensics Center) Postdoctoral Fellow shortly after his defense. During his 8-year tenure at PNNL, he has focused on chemical separations associated with nuclear forensics, currently leading efforts to create ML/AI enabled predictive separations models, as well leads the PNNL efforts to improve fundamental nuclear data, as well as a leading member of the operational nuclear forensics team.