Bipolar membrane electrolyzers enable high single-pass CO2 electroreduction to multicarbon products

Abstract

In alkaline and neutral MEA CO2 electrolyzers, CO2 rapidly converts to (bi)carbonate, imposing a significant energy penalty arising from separating CO2 from the anode gas outlets. Here we report a CO2 electrolyzer uses a bipolar membrane (BPM) to convert (bi)carbonate back to CO2, preventing crossover; and that surpasses the single-pass utilization (SPU) limit (25% for multi-carbon products, C2+) suffered by previous neutral-media electrolyzers. We employ a stationary unbuffered catholyte layer between BPM and cathode to promote C2+ products while ensuring that (bi)carbonate is converted back, in situ, to CO2 near the cathode. We develop a model that enables the design of the catholyte layer, finding that limiting the diffusion path length of reverted CO2 to ~10 μm balances the CO2 diffusion flux with the regeneration rate. We report a single-pass CO2 utilization of 78%, which lowers the energy associated with downstream separation of CO2 by 10× compared with past systems.

Zero-Gap Electrochemical CO2 Reduction Cells: Challenges and Operational Strategies for Prevention of Salt Precipitation

“…Some approaches have used a weakly acidic buffer layer to increase the pH to a point where CO 2 electrolysis is favorable again. 56,65,67 Such results motivate further reinvestigation into acidic CO 2 electrolysis catalysts.…”

“…In literature, the reversed-bias BPM approach has been used in a number of scenarios with the primary intent to increase CO 2 utilization within CO 2 electrolysis systems. ,,− If a higher fraction of CO 2 is used for the electrochemical reaction, then less CO 2 can be permanently converted into carbonate salts. Interestingly, the BPM configuration does not avoid carbonate formation which could lead to salt formation but instead provides a means of neutralizing the formed carbonate with protons prior to the anions migrating through the cation and anion exchange layers.…”

From Single Crystal to Single Atom Catalysts: Structural Factors Influencing the Performance of Metal Catalysts for CO2 Electroreduction

“…The autonomous learning capability of AI-based algorithms offers improved predictability at a fraction of the (computational) cost. Examples have already shown the great potential of using machine learning to discover and optimize the composition, structure, and additive of Cu-based catalysts for the CO 2 RR. ,− Incorporation of multiscale modeling at the device level would be a prerequisite to translate such computational studies to real-world applications, however . Thus, stronger ties between experimentalists and theorists could reap the benefit of symbiotic efforts in which theory guides catalyst design and experiment offers data for the improvement of the predictive power of the algorithm.…”

“…87,177−180 Incorporation of multiscale modeling at the device level would be a prerequisite to translate such computational studies to real-world applications, however. 181 Thus, stronger ties between experimentalists and theorists could reap the benefit of symbiotic efforts in which theory guides catalyst design and experiment offers data for the improvement of the predictive power of the algorithm.…”

Membrane electrode assembly design to prevent CO2 crossover in CO2 reduction reaction electrolysis

“…The CO 2 RR electrolyzer utilizing (a) a bipolar membrane (BPM) and (b) a cation exchange membrane (CEM). Copyright: Modified from ref 6. ., used under CC BY.…”