High‐Performance Zero‐Gap Glycerol‐Fed Electrolyzer for C <sub>3</sub> Chemicals and Hydrogen Production
Bibliographic record
Abstract
ABSTRACT The electrochemical oxidation of biomass‐derived glycerol offers a promising low‐voltage alternative to water oxidation in electrolyzers, enabling the co‐production of hydrogen and value‐added chemicals. However, achieving high conversion rates at current densities above 300 mA cm −2 remains challenging due to the rapid deactivation of platinum‐based catalysts. Here, we present a membrane electrode assembly (MEA) featuring a platinum‐decorated nickel foam (Pt/NiF) anode that sustains operation for 24 h at 500 mA cm −2 with an average cell voltage of just 1.21 V, outperforming all previously reported glycerol‐fed electrolyzers operating below 1.5 V. The system exhibits >88% selectivity toward C3 products, achieving 227 mA cm −2 partial current density for lactic acid and 9% single‐pass glycerol conversion. In situ impedance spectroscopy identifies voltage‐dependent regimes linked to platinum hydroxide formation, glycerol oxidation, and oxygen evolution. Systematic variation of electrolyte composition and temperature reveals an optimized window (1.2–1.4 V, 55–65°C) for sustained performance. Under these conditions, a single 24 h cycle co‐generates ∼175 mmol of H 2 and 45 mmol of C3 products. These results establish new operational and mechanistic benchmarks for efficient, low‐voltage electrochemical valorization of biomass‐derived polyols at industrially relevant rates.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".