In Situ Techniques for Quinone-Mediated Electrochemical Carbon Capture and Release in Aqueous Environments
Bibliographic record
Abstract
We present two novel experimental techniques designed to quantify the contributions of nucleophilicity-swing and pH-swing mechanisms to carbon capture in the electrochemical aqueous quinone-based CO2 capture process. Through thermodynamic analysis, we elucidate the intricate interplay between these two mechanisms, and emphasize the critical role of understanding this interplay in the material discovery cycle for carbon capture applications. This insight prompts the development of two innovative in situ techniques. The first technique capitalizes on discernible voltage signature differences between quinone, and quinone-CO2 adducts. By incorporating a reference electrode into the carbon capture cell setup, we apply this method to investigate bis[3-(trimethylammonio)propyl]-anthraquinones (BTMAPAQs). Our findings reveal the isolated contributions of nucleophilicity-swing and pH-swing mechanisms to overall carbon capture capacity under varying wait times and CO2 partial pressures. The second method is developed based on our finding that the adduct form of the quinone exhibits a fluorescence emission from an incident light at wavelengths distinct from the fluorescence of the reduced form, enabling differentiation through optical band-pass filtering at each unique fluorescent signature. Thus, we introduce a non-invasive, in situ approach using fluorescence microscopy, providing the unique capability to distinguish between oxidized, reduced, and adduct species with sub-second time resolution at single digit micrometer resolution. This powerful technique holds significant promise for studying such systems, representing an advancement in our ability to understand carbon capture processes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".