Bibliographic record
Abstract
Abstract A variety of bimetallic Ni–Ir catalysts were synthesised by preforming nanoparticles in the presence of polyvinylpyrrolidone, followed by deposition on γ‐alumina and high‐temperature polymer removal. The Ni–Ir (1:1 molar ratio) nanoparticles prepared by the hydrogen‐sacrificial technique (Ir reduction on the preformed Ni nanoparticles with surface Ni hydride) allowed increasing indane ring opening activity per total amount of Ir as compared to monometallic Ir. The simultaneous reduction of Ni and Ir precursors was not as efficient. The catalysts were characterised with UV/Vis spectroscopy, TEM, temperature‐programmed reduction, CO 2 temperature‐programmed desorption, CO diffuse reflectance Fourier transform spectroscopy, X‐ray photoelectron spectroscopy and CHN analysis. The study only explored the catalyst’s metal function and allows saving rare and expensive iridium without loss of its outstanding performance as a ring‐opening catalyst.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 | 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 teacher head, 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".