Graphene-Oxide-Modified Metal-Free Cathodes for Glycerol/Bleach Microfluidic Fuel Cells
Bibliographic record
Abstract
Glycerol is an abundant, inexpensive fuel for miniaturized fuel cells with practical power output. Glycerol electrooxidation is coupled to a cathodic reaction, usually oxygen reduction on noble-metal-based catalysts. However, the slow kinetics of oxygen reduction on nonprecious metal catalysts has limited its applications. Here, we propose the use of hypochlorous acid (HClO from bleach) as a potential liquid oxidant and graphene oxide (GO)-modified carbon paper as a metal-free cathode. GO with high oxidation levels is synthesized and used for in situ flowing deposition on a carbon paper cathode. This unique GO deposition method leads to a homogeneous “blanket” coverage of the wetted fibers exposed to the flow, increasing the active surface area by 3.8 times. The prototype mixed-media microfluidic fuel cell with electrodes in a flow-through configuration featuring glycerol electrooxidation coupled to HClO reduction on GO-modified carbon paper shows 1.72 V open-circuit voltage, 354 mA cm –2 maximum current density, and 110 mW cm –2 peak power density. This unprecedented performance proves that a well-designed in situ electrode modification can be applied to reach high power density without the use of noble metals.
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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) | 0.001 | 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".