Highly Porous and Preferentially Oriented {100} Platinum Nanowires and Thin Films
Bibliographic record
Abstract
Abstract Highly {100} oriented Pt deposits were prepared by electrodeposition from a 10 mM HCl, 100 mM KCl and Na2PtCl6.xH2O electrolyte. The deposits were prepared in the form of thin films and array of nanowires. A qualitative assessment of the proportion of {100} oriented Pt surfaces was obtained through X‐ray diffraction measurements and cyclic voltammetry in 0.5 M H2SO4. The effect of the deposition potential, Edep, temperature of the electrolyte, Tdep, platinum salt concentration [Na2PtCl6.xH2O], and nature of the substrate were investigated. It was shown that the proportion of {100} oriented Pt surfaces reaches a maximum for Edep = ‐0.35 V vs SCE. Moreover, this proportion increases steadily as Tdep and [Na2PtCl6.xH2O] are decreased from 75 to 25 °C and from 2.5 to 0.25 mM, respectively. Scanning electron microscopy and high‐resolution transmission electron microscopy micrographs indicate that the more oriented samples are made of pine tree‐like structures that are effectively single crystals, and that the growth facets appear to be close to the {001} plane. This observation also clearly indicates that the plane exposed during the CV experiment is also {001}. As suggested by these micrographs, the films and nanowires are highly porous and roughness factors as large as 1000 were obtained on highly {100} oriented Pt nanowires. The predominance of {100} facets is attributed to their energetically favoured growth in the presence of hydrogen, and is shown to be significantly enhanced when the mass transport of Pt4+ is limited. Due to the predominance of {100} facets, the normalized electrocatalytic activity (μA cm−2Pt) for the electro‐oxidation of hydrazine and ammonia is higher than non‐oriented polycrystalline Pt by a factor of 4 and 2.7, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".