<scp>TEM</scp>investigation of the effects of cycling on electrochemically stable hybrid<scp>Pt@NbOx</scp>nanocatalysts
Bibliographic record
Abstract
Renewable energies and fuel cell technologies will likely play a major role in reducing our dependency on fossil fuels. In particular, proton exchange membrane fuel cells (PEMFCs) are suitable for use in both domestic and automotive applications. This sophisticated technology requires a functional nanostructured material that contains platinum to catalyse both the hydrogen oxidation reaction (HOR) and the oxygen reduction reaction (ORR) to produce water, electricity, and heat. [1] Unfortunately, in spite of their remarkable potential, the high cost and degradation of platinum‐based catalytic materials have been a barrier to widespread adoption of this type of technology. Reducing platinum content while simultaneously improving the durability will therefore require novel approaches in the catalyst design and its characterization at nanoscale level. [2] Transmission Electron Microscopy (TEM) techniques have continued to play a major role in the design and characterization of PEMFC materials. Using an aberration‐corrected microscope (Titan cubed 80‐300), we investigated the structural stability over the lifetime of a proposed fuel cell cathode material containing nano‐particulate platinum on a NbOx‐carbon hybrid support. The characterization of this material included a series of ex‐situ TEM analyses before or after accelerated stress tests that cycled the sample 30,000 times between 0.6 and 1.0 V in an electrochemical cell. The histograms shown in Fig1a and b reveal that some metal particle coarsening occurred during the 30,000‐cycle test. The as‐prepared catalyst contained 1–5 nm particles, the majority of which were determined to be bimetallic, as determined by electron energy loss spectroscopy (EELS), with some Pt‐rich particles and Nb‐rich grains (Fig. 1c). After 30,000 cycles, microanalysis data confirms that the cycling treatment caused some agglomeration of the small Pt‐rich particles. Analysis of the EELS oxygen K ionization edge indicates that multiple niobium oxidation states are present in the system, predominantly Nb(V) before electrochemical cycling (Fig 1c). Although conventional image comparisons between the initial and final state of the hybrid catalyst suggest that the Pt particle size increased marginally, in order to obtain an improved understanding of the material's degradation, morphological and structural evolution of the particles and hybrid support were tracked using the so‐called Identical Location TEM technique [3]. The results in figure 2 indicate that no large‐scale degradation of the hybrid support took place, suggesting carbon corrosion was minimized. In addition, only minor changes occurred to the average particle size, demonstrating the excellent stability of the metallic particles. These findings demonstrate that highly dispersed Pt/NbOxon carbon support material is a promising electrocatalyst for PEMFC.
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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) | 0.003 | 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".