SHINE Tapped for DOE Genesis Mission to Automate Nuclear Fuel Recycling

The company will spearhead a Phase I project titled "AI-Guided Fuel Cycle Facility Optimization" in partnership with Argonne National Laboratory. The initiative aims to move beyond manual, iterative engineering by deploying an AI-enabled system that simultaneously balances performance, waste management, and product quality. By layering new machine learning capabilities over Argonne’s established AMUSE and ARTEMIS modeling tools, SHINE intends to identify superior recycling configurations for the nation’s 95,000-metric-ton stockpile of used nuclear fuel.

Beyond its lead role, SHINE is joining the Prometheus consortium, an Idaho National Laboratory-led effort that pools data across the nuclear sector to standardize AI applications in energy. This dual involvement allows the firm to refine its own commercial pilot processes—which leverage chemistry already validated at its Chrysalis medical isotope facility—while contributing to a broader national infrastructure for nuclear deployment. CEO Greg Piefer noted that the project focuses on merging commercial radiochemistry data with advanced computational tools to shorten development cycles. If the pilot succeeds, the AI-driven methodology could be scaled to manage wider segments of the nuclear fuel cycle.