Clara Drysdale is an undergraduate student in the Department of Mechanical Engineering at Stanford University. She is interested in translating research into scalable solutions through tools like techno-economic analysis and process optimization. She is currently building a cost optimization model for conventional lithium extraction from solar evaporation ponds.
Team Members
Overview
Municipal and industrial water treatment facilities face increasingly complex technology decisions for treating nontraditional waters, water reuse, and resource recovery. Current tools provide limited capability to rigorously compare alternatives, predict performance under variable conditions, or justify R&D and pilot investments. This results in conservative design decisions, costly and time-intensive piloting programs, and missed opportunities for innovation. WaterTAP is an open-source, physics-based modeling framework for designing and evaluating advanced water treatment systems. WaterTAP process models are built within an optimization framework to solve for cost-optimal design and operation. WaterTAP enables researchers and engineers to simulate complex treatment trains; screen and prioritize technologies for piloting; integrate facility data into predictive models; and quantify the value of innovation.
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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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