Manganese-Based Non-Precious Metal Catalyst for Oxygen Reduction in Acidic Media
Bibliographic record
Abstract
Non-precious metal catalysts (NPMCs) based on manganese (Mn) are prepared by heat treating polyaniline (PANI), manganese acetate and Ketjenblack EC300J (KJ) carbon supports. Using a heat treatment temperature of 950 o C, followed by an acid leaching and second heat treatment step, Mn-PANI-KJ catalysts are found to provide onset and half-wave potentials of ca . 0.90 and 0.77 V vs. RHE, respectively, in 0.5 M H 2 SO 4 electrolyte. After 5,000 cycles of electrochemical durability testing, Mn-PANI-KJ demonstrates a half-wave potential loss of only ca . 20 mV, superior to the 80 mV loss for our previously developed iron (Fe)-PANI-KJ catalyst. Increased surface nitrogen concentrations and relative ratios of pyridinic to graphitic nitrogen species were observed at increased Mn-PANI-KJ preparation temperatures, along with the evolution of graphene-like and graphitic nanoshell structures.
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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".