Reveals improved design framework for bipolar membranes, suggesting enhanced performance for energy and water systems.
Bipolar nanoporous membranes/nanochannels are used in water desalination and energy-harvesting systems that provide clean water and green energy, respectively. The ever-growing need requires that the performance of these systems be constantly improved. Since the underlying physics are still not fully understood, the empirical optimization process remains slow and inefficient. Utilizing a combination of theoretical tools and numerical simulations, we created a novel and robust framework to improve the design of these systems. We show that the system’s response is determined by an interplay of the applied voltage and a parameter ( η ) that depends on the geometry and surface charge densities of both charged regions. At low voltages, we show that the response is mostly determined by η such that the η -dependence can be represented by a simplified phase space. At high voltages, we show that this phase space becomes oversimplified. To demonstrate this, we conduct a systematic scan of this phase space, which spans a range of membrane configurations, from unipolar channels featuring a single charged region to bipolar channels composed of positively and negatively charged segments. We compare our numerically simulated current-voltage responses to those predicted by three known existing theoretical models, which are limiting scenarios within the phase space, and explain the observed deviations. Our findings underscore the need for a more comprehensive framework to capture the broad range of observed behaviors. Nonetheless, these same findings can be utilized to reduce the time/resource-intensive optimization process and improve the data interpretation of experiments and simulations of these systems. • Simulations of bipolar membranes over a broad parametric range yield novel insights. • Our investigations reveal that most analytical models oversimplify the response. • Our results yield a new framework to rapidly improve the design of these systems.
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Sharvit et al. (2026) studied this question.
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