CO<sub>2</sub> Electroreduction to C<sub>2</sub> / C<sub>2</sub>+ Products Using Membrane Electrode Assembly
Bibliographic record
Abstract
Considering the global average, 2018 experienced the highest concentration of CO2 in atmosphere (approximately 407 ppm). Although several policies and regulations are in action, annual CO2 in atmosphere is still on the rise for past decades. As an outcome, anthropogenic CO2 generation and subsequent atmospheric emission are key issues under global sustainability challenges. Moreover, this CO2 is also related to other irreversible effects which are climate change, ozone layer and fossil fuel depletion. Consequently, tons of researches involving significant CO2 reduction and conversion to assets are on the track. Currently, research efforts on electrochemical reduction of CO2 using alkaline flow cell configuration is at the forefront for its compact and flexible nature without the need of ancillary equipment. In this configuration, alkaline electrolyte, catalyst and the diffused CO2 establish a three-phase reaction interface enabling highly selective electroreduction of CO2 to various C2/C2+ fuels and chemical feedstocks. However, there are some major challenges associated with this configuration, including low CO2 conversion efficiency due to carbonate salt formation, catalyst poisoning due to impurity deposition, and electrode flooding. In this work, we have studied a robust cell configuration i.e., zero-gap membrane electrode assembly (MEA), wherein cathode and anode are separated by solid polymer electrolyte (ion-exchange membrane). Here cell operation and reaction kinetics are similar to liquid phase flow cell except exclusion of catholyte. Recent studies have revealed that removal of catholyte certainly overcomes the aforesaid limitations of liquid phase flow cell. In this context, here, we utilized a zero-gap gas-phase electrolyzer (MEA) for electrochemical CO2 reduction to multi-carbon products, including ethylene and ethanol. Instead of traditional carbon-based gas diffusion electrode (GDE), here, we utilized porous PTFE based GDE for stable CO2 reduction reaction. Copper nanoparticles, sputter coated on porous PTFE sheet, anion exchange membrane (AEM) and nickel foam (i.e., anode) are used to develop the MEA. A 5 cm2 stainless steel electrolyzer (MEA) was used for this study. Preliminary results show a faradaic efficiency for C2H4 (~55%) at current density (~50 mA/cm2) at -2.5 V vs Ag/AgCl with 5 M KOH as anolyte. We will report on the effect of catalyst modification, membrane, reaction environment including effect of humidity, CO2 flowrate and anolyte on the overall cell performance i.e., energy efficiency and CO2 conversion efficiency. Keywords: CO2 Electroreduction, Renewable Fuels, Membrane Electrode Assembly, Current Density, Faradaic Efficiency
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".