Overview

The Nuclear Forensics Transformational Innovation (NFTI) initiative has been working to dramatically reduce forensics timelines by fundamentally changing the nuclear material analysis process. By utilizing micro sampling and analysis, Pacific Northwest National Laboratory is working on new methods to generate material forensics samples in more concentrated, smaller volumes, and on approaches to employ parallel and automated sample processing that will accelerate timelines while minimizing expert intervention. To further streamline and tailor the new process for different types of nuclear events, the NFTI team is developing chemistry models and artificial intelligence-assisted data analysis tools to enable autonomous optimization of critical steps.

Research Area 1 (Post Detonation)

Researchers and Topic Areas

• Kirby Hobbs – Advancing Mass Spectrometry for Airborne Atomic Detection in Nuclear Forensics (Thrust Area 4)
• Ben McDonald – Microsample Identification with Autoradiography (Thrust Area 1)
• Karen Noyes – Microchemistry Separations (Thrust Area 2)
• Bruce Pierson and Brian Archambault – Leveraging AI/ML to Automate the Analysis, Interpretation, and Reporting of Spectroscopic Radiation Detector Data (Thrust Area 4)
• Matthew RisenHuber – Microdissolution (Thrust Area 2)
• Nic Uhnak – Process Modeling/Experimental Data for Model V&V (Thrust Area 3)
• Seth Wood – Autonomous Microparticle Extraction System (Thrust Area 2)
• Mindy Zimmer – Exploring Volatility through Microanalysis (Thrust Area 1) 

Research Area 2 (Pre Detonation)

Researchers and Topic Areas

• Connor Hilton – Material Production and Measurements of Properties Across Scales Modeling

Past Topic Areas

• Alex Hagen – Machine Learning Processing of Multimodal Data
• Ken Wagnon – Evaluating Properties for Microsample Identification

Project Advisors

• Edgar Buck
• Judah Friese
• Eirik Krogstad
• John Wacker