Labs

SEAR — Sustainable and Efficient Allocation of Resources

The SEAR Lab studies energy and critical mineral systems and the communities they serve — end to end and back, from extraction through manufacturing and deployment to end-of-life recovery. The lab builds the physical, digital, and institutional infrastructure that lets organizations allocate limited resources sustainably, efficiently, and resiliently.

• Physical: reverse logistics and bench-scale critical-metal recovery from end-of-life batteries; battery degradation, charge/discharge characterization, and cell assembly; microgrid prototyping.
• Digital: energy-system and critical-mineral supply-chain models linked through mathematical optimization, simulation, AI/machine learning, and design-of-computer-experiments surrogates, with specialized analytics (GIS, LCA, TEA).
• Institutional: community deployment through state and federal energy policy — from weatherization workforce pilots to critical-mineral trade policy analysis.

SEAR is part of an interdisciplinary ecosystem including RAID, COSMOS (Center for Stochastic Modeling, Optimization, and Statistics), and the Pulsed Power Energy Lab.

RAID — RFID and Auto-ID Deployment Laboratory

The RAID Lab is one of the most comprehensively equipped RFID research facilities in the country, with dedicated healthcare, logistics, and digital twin research cells. Its core conviction: what cannot be tracked cannot be managed, and what cannot be managed cannot be improved. RFID bridges the physical and digital layers — it turns physical presence into digital signal without line-of-sight, without contact, and at a cost that scales.

The portfolio spans a full arc of RFID in high-stakes environments:

• Pharmaceutical supply chain tracking from manufacturer to patient to prevent diversion and counterfeiting
• Smart pill research — ingestible, biocompatible RFID sensors for in-vivo monitoring
• RFID systems preventing retained surgical instruments
• RTLS patient and medication tracking using smart shelves, wristbands, and hospital bedding
• Materials tracking for the International Space Station
• Methods: tag and antenna characterization, set-cover optimization for reader placement, GIS spatial analytics, and machine learning for anomaly detection — a stack now being adapted to community-level naloxone distribution