Part 2 of 2 Parts (Please read Part 1 first)
The remnants of a nuclear explosion will include many elements, including much of the periodic table with several different chemical forms of many of them. Uranium, strontium, iron and cerium would definitely be present. Analysis usually includes putting the materials into an aqueous bath such as nitric acid, then doing a series of tedious chemical separations to learn more about each component.
In the new research, the team used AI-enabled high-performance computing to simulate the complex computational chemistry involved and to determine some chemical properties of the debris. These included calculations of what are referred to as stability constants. Those numbers aid scientists in understanding the strengths of bonds between ions or molecules to form molecular complexes, how likely these complexes will stick together or break apart, and how energy flows in such a complex system. Many such calculations taken together help scientists use chemical separations that allow them to understand exactly what they’re looking at, what happened and where materials came from.
The team showed that their AI model is able to explore and calculate the properties of a huge number of possible molecular combinations, far more than could be explored in the laboratory.
Hadi Dinpajooh is a computational chemist and an author on the paper “Generative AI calculates in many dimensions at once, in a way that is difficult for a person. The model allows us to significantly reduce the timeline to explore all the possibilities.”
The PNNL scientists believe that this sort of chemical separation modeling driven by AI would benefit other difficult questions involving nuclear science. One example is the production of medical isotopes such as molybdenum-99, which is used to help diagnose cancer and other serious health conditions. Molybdenum-99 is produced by the fission process and requires chemical separations like those the team is exploring.
The mathematics of such nuclear analyses are challenging. PNNL teamed with Microsoft to deploy Azure Quantum Elements which is a cloud computing resource. That system utilized powerful computer chips from NVIDIA, including two hundred and thirty NVIDIA H100 GPUs. Altogether, combined with other computing resources, the team used fifty-five terabytes of RAM to work through the questions. This is an analysis which represented just one step in the long chain of analyses that would be deployed after a nuclear detonation.
The technical management for the PNNL-Microsoft collaboration was led by computer scientist Paul Rigor. His expertise bridged the gap between the project’s research demands and the computing infrastructure that Microsoft provided.
Uhnak said, “This first paper along these lines is a baby step, but it’s an important step. Anything we can do to speed up the process of analysis is a win.”
Research on nuclear devices and debris is one part of a major ongoing program on nuclear forensics at PNNL. It is a critical component of the nation’s capability to analyze nuclear and radioactive materials and events, including the complex science involved in nuclear explosions.