Postdoctoral Researcher
Anthony Cheng is an ORISE Postdoctoral Fellow with the National Energy Technology Laboratory, with a visiting appointment at the WE3 Lab at Stanford. He received his PhD from Carnegie Mellon University in Engineering and Public Policy. His research focuses on understanding manufacturing and commercialization of technologies needed in the energy transition, with a particular emphasis on critical minerals supply chains, with a previous emphasis on electric vehicle batteries; his current focus is on unconventional sources and processing pathways for security-relevant critical minerals. His work incorporates technoeconomic, life-cycle, material flow, and optimization methods to evaluate engineering systems in policy-relevant contexts. He will join the faculty of the School of Industrial Systems and Engineering at Georgia Tech in Fall 2027.
Team Members
Overview
Critical minerals like lithium, cobalt, and rare earth elements are essential to the energy transition, yet current supply chains are geographically concentrated, environmentally costly, and vulnerable to market fluctuations. Our group develops techno-economic models to evaluate both conventional and emerging extraction pathways for these materials. A core focus is lithium extraction, where we compare the cost, energy intensity, and scalability of conventional evaporation-pond brine processing against direct lithium extraction (DLE) technologies for unconventional brine sources such as geothermal brines. As part of this effort, we partner with teams developing electrodialysis-based lithium extraction technologies under separate DOE-funded projects, evaluating their techno-economic performance and scale-up potential relative to conventional and other DLE approaches. We also contribute to the HERMES consortium (Hastening the Exploration & Recovery of Minerals from Earth Energy Systems), an initiative to quantify the potential value of critical minerals contained in waste resources across the United States in diverse resource and market combinations, including coal refuse, coal ash, mine tailings, acid mine drainage, and red mud. Working alongside our colleagues in the SLAC National Accelerator Laboratory and six other national labs, we model and evaluate production processes and their costs, integrating AI and data-driven methods, with the broader goal of identifying which waste-to-mineral pathways are worth pursuing at scale.
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