Process modeling predicts optimal performance for reactive separations in wastewater, highlighting key electrocatalysis insights.
Reactive separations systems that leverage the nitrate reduction reaction (NO3RR) promise to extract value from nitrate-laden wastewater treatment by refining nitrate pollutants into ammonia products. Despite recent fundamental advances in NO3RR electrocatalysis and some proof-of-concept demonstrations of promising reactive separations unit processes, a rational approach to scale-up and deployment of these critically needed technologies remains elusive. This imperative is challenged by the impure and variable nature of nitrate-laden wastewaters. To address these challenges, and to narrow the broad engineering design space for electrocatalytic nitrate refining (that necessarily includes integrated processes for nitrogen extraction, conversion, and recovery), we pursue process modeling that bridges subunit kinetic behavior with overall process performance. In this work, we establish characteristic rate equations for the subunit processes that comprise a reactive separation called electrocatalyst-in-a-box (ECaB), which facilitates nitrate reduction in an engineered environment separate from wastewater. Integrating these equations into a continuous ECaB process model predicts performance and lays the groundwork for further optimization toward practical application in wastewater treatment. The model also enables technoeconomic analysis that facilitates comparison of component- and subunit process-level cost contributions to the overall system and provides a benchmark for reactive separations against conventional wastewater nitrogen treatment. In sum, this work provides a framework to translate fundamental unit process studies toward integrated reactive separation system design, and to uncover unit process insights within the context of an integrated system to prioritize research and development needs in membrane, catalysis, and reactor design research.
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Miller et al. (2025) studied this question.
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