Measurement of Palladium Crust Thickness on Catalysts by Optical Microscopy and Image Analysis
Bibliographic record
Abstract
Selective hydrogenation is an important process in petrochemistry to purify feedstock for polymer synthesis. For this process, catalysts containing metallic palladium deposited with an eggshell distribution on porous alumina are usually employed. For this kind of catalyst, the activity is known to be in close relation with the thickness of the palladium crust. As palladium oxide is brown and alumina is white, the palladium distribution in a catalyst bead before the reduction step can be characterized by optical microscopy. We propose an original and automatic procedure of optical image analysis to obtain a fast and robust method to measure the mean crust thickness of a catalyst batch and the corresponding standard deviation. The approach is validated by two different methods. First, we compared the crust thickness with those obtained by electron probe microanalysis. Then, catalytic tests of four samples with varying palladium crust thicknesses were performed and confirmed the expected correlation between activity and crust thickness measured by optical microscopy coupled with image analysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".