Decoding Carbon Pathways in a Bicarbonate-Fed Zero-Gap Electrolyzer
Franz Bommas a, Kai junge Puring a
a Fraunhofer Institute for Environmental, Safety, and Energy Technology UMSICHT, Osterfelderstr. 3, Oberhausen, Germany
Materials for Sustainable Development Conference (MATSUS)
Proceedings of MATSUS Fall 2026 Conference (MATSUSFall26)
C3 Current bottlenecks of the industrial application of CO2 electrolysis
Palma, Spain, 2026 October 26th - 30th
Organizers: Balazs Endrodi and Kevinjeorjios Pellumbi
Oral, Franz Bommas, presentation 325
Publication date: 22nd July 2026

The direct electrochemical conversion of bicarbonate-based carbon capture solutions represents a promising approach for integrated carbon capture and utilization (CCU), as it enables CO₂ conversion without energy-intensive CO₂ desorption, purification, and compression steps. However, achieving scalable operation requires a detailed understanding of carbon transport, crossover phenomena, and process stability under industrially relevant conditions.

In this work, we present a versatile single-pass zero-gap electrolyzer platform for the systematic investigation of bicarbonate-fed electrochemical CO₂ reduction. The developed setup enables operation across a broad range of process parameters, including catholyte flow rates from 5 to 50 mL min⁻¹, temperatures from ambient up to 80 °C, stoichiometric ratios (λ) ranging from approximately 100 down to values near 5 — thereby approaching conditions typical for gas-fed CO₂ electrolysis — and current densities from 80 to 500 mA cm⁻². The platform is compatible with both cation exchange membrane (CEM) and bipolar membrane (BPM) configurations, allowing the evaluation of different proton delivery mechanisms and reaction environments at the cathode.

A key focus of this work is the comprehensive assessment of carbon balances during single-pass operation. By quantifying the carbon distribution between cathode and anode compartments, crossover phenomena and process limitations are identified under varying operating conditions. The resulting dataset is further used to develop a data-driven black-box model that correlates readily measurable parameters — such as pH and conductivity — with electrolyzer performance metrics. This approach enables predictive monitoring of system operation and supports the identification of deviations from optimal conditions, including electrolyte depletion, mass transport limitations, or changes in product selectivity. 

The presented methodology provides a framework for the improved understanding, optimization, and process control of reactive carbon electrolyzer systems, supporting their transition toward scalable and robust reactor concepts.

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