One‐Dimensional<scp>Pt</scp>Nanostructures for Polymer Electrolyte Membrane Fuel Cells
Bibliographic record
Abstract
This chapter discusses the achievements on the controlled synthesis of different shaped platinum (Pt) nanostructures with uniform size and shape distribution through several approaches. The synthetic challenge is to develop approaches to those predetermined nanostructures with high-level controls of uniformity in size, shape, and composition if Pt alloys are desired. The chapter also discusses the influence of different shapes of Pt nanostructures on the kinetics of both cathodic and anodic reactions relevant for polymer electrolyte membrane fuel cells (PEMFCs). It analyses some of the important parameters such as surface area, exposure crystallographic planes, density of atomic steps, and kinks responsible for this shape-dependent electrocatalytic behavior. The chapter focuses on the syntheses of one-dimensional (1D) Pt nanowires and nanotubes and their use as electrocatalysts in PEMFCs. The carbon-supported Pt nanowires could be readily processed as electrocatalysts for fuel cell applications.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".