Synthesis of low cost cathode electrocatalyst <scp>Pt‐Ni</scp> / <scp> C <sub>AB</sub> </scp> using <scp>DMSO</scp> as a solvent for low temperature proton exchange membrane fuel cell application
Bibliographic record
Abstract
Abstract In the present study, low cost platinum based bimetallic electrocatalyst Pt‐Ni/C AB with varying Pt to Ni atomic ratios 3:1, 1:1, and 1:3 were successfully synthesized for oxygen reduction reaction (ORR) of the developed proton exchange membrane fuel cell (PEMFC). The solvothermal process was adopted for the synthesis of Pt‐Ni(3:1)/C AB , Pt‐Ni(1:1)/C AB , and Pt‐Ni(1:3)/C AB using dimethyl sulfoxide (DMSO) as solvent at a temperature of 190°C which is very close to the boiling point. The Pt‐Ni/C AB exhibited the highest activity for the ORR in half‐cell and single cell PEMFC performance. The electrocatalysts Pt‐Ni(1:3)/C AB appeared with smallest crystalline FCC structures having crystallite size of 8.33 nm. The transmission electron microscopy (TEM) analysis also show that the Pt‐Ni(1:3)/C AB has smallest particle size of 1.67 ± 0.45 nm. The cyclic voltammetry (CV) analysis shows Pt‐Ni(1:3)/C AB electrocatalyst offers less activation loss at ORR peak at a potential of 0.16 V as compared to Pt‐Ni(3:1)/C AB (ORR peak – 0.12) and Pt‐Ni(1:1)/C AB (ORR peak – 0.11). The synthesized Pt‐Ni(1:3)/C AB produced a maximum power density of 18.86 mW/cm 2 at a maximum current density of 44.8 mA/cm 2 with an open‐circuit voltage of 0.914 V at a room temperature of 33°C. The power density improved around 1.34 times when the cell temperature was raised from 33 to 70°C. The Pt‐Ni(1:3)/C AB cathode electrocatalyst could be used as economical to substitute costly commercial pure platinum based electrocatalyst.
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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".