Advanced separation process for resource extraction and recycling

Clean energy depends on critical minerals such as Li, Co, Ni, and rare earth elements, yet their extraction and recycling are often energy-intensive and environmentally harmful.

We aim to develop advanced separation processes that reduce energy cost and environmental impact, by integrating device design and process optimization to harness renewable energy for spontaneous separation.

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Designing novel membrane materials with artificial intelligence

Membranes are key to many separation processes, but are often limited by the selectivity–permeability trade-off, fouling, weak mechanics, and poor stability in harsh conditions.

We aim to design high-performance membranes using AI-driven materials discovery. In particular, 2D polymers—with tunable and ordered pores—offer a promising platform that, combined with process engineering, can overcome the shortcomings of conventional membranes.

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Smart tracers for chemical reactor monitoring

Tracers are essential for reactor analysis, but conventional passive tracers cannot resolve the spatiotemporal distribution of internal fields. In battery recycling, for example, concentration-field information is crucial for tracking reaction progress and ensuring complete cathode regeneration.

We aim to develop smart tracers that respond to external stimuli to map reactant concentration fields in flow reactors. Through parallel fabrication and integration, as well as theory development, these tracers will enable non-invasive, spatiotemporal monitoring across diverse reactors.

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