Study on the effect of calcium hypochlorite and air as mixed oxidant and a synthesized low cost <scp>Pd‐Ni</scp> / <scp>C</scp> anode electrocatalyst for electrooxidation of glycerol in an air breathing microfluidic fuel cell
Bibliographic record
Abstract
Abstract In the present work, glycerol‐based air breathing microfluidic fuel cell (μFC) is investigated. The noble metal Pd and non‐noble metal Ni‐based bimetallic synthesized electrocatalyst (Pd‐Ni/C) were used for glycerol electrooxidation and commercial Pt/C HSA was used as cathode electrocatalyst. The anolyte is glycerol mixed with KOH electrolyte. The atmospheric air and calcium hypochlorite mixture are used as oxidant in cathode and catholyte, respectively. Acetylene black carbon is used as electrocatalyst support with low metal loading of 20 wt% Pd and Ni at their different weight ratios (Pd/Ni) of 16:4, 10:10, and 4:16 to synthesize bimetallic Pd‐Ni/C anode electrocatalysts. The crystal structure of the synthesized electrocatalyst was determined by X‐ray diffraction (XRD) analysis. The surface morphology and surface concentration of synthesized electrocatalyst were determined by scanning electron microscopy (SEM) and energy dispersive X‐ray spectroscopy (EDX), respectively. The particle size of synthesized electrocatalyst was determined by transmission electron microscopy (TEM) analysis. The electrochemical activity of Pd‐Ni/C was investigated by cyclic voltammetry analysis. The electrocatalyst Pd‐Ni (10:10)/C gives higher electrocatalytic activity for glycerol electrooxidation compared to other ratios of electrocatalyst. A single air breathing μFC is investigated using various key parameters where air alone as oxidant gives open circuit voltage (OCV) of 0.42 V and maximum power density of 1.27 mW/cm 2 . While using calcium hypochlorite and air as mixed oxidant, the OCV was increased to 0.72 V and maximum power density increased to 3.43 mW/cm 2 , which are 1.71 and 2.7 times, respectively, more than that of air as oxidant only .
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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) | 0.000 | 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".