Patent Literature on Epoxidation of Propylene Over Silver Catalysts Using Molecular Oxygen – A Critical Industrial Review
Bibliographic record
Abstract
Abstract We summarize the patent literature related to the direct oxidation of propylene‐to‐propylene oxide (DOPO) over silver catalysts. Inventions claiming new compositions, preparation methods, and/or alternative process options are illustrated with data sampled from patent documents. Early claims focused on powders of silver (silver oxide) alloyed with and/or surface‐modified with one‐two promoterswhere silver was in large excess (>80 wt%). In the following decades, inventors refined their approach and pursued alternative bulk synthetic methods supplemented with impregnation to produce formulationscontaining lower amounts of silver in combination with various other transition metals, halides, alkalis and/or alkaline earth elements. Simultaneously, process development has facilitated increased PO selectivity via the co‐feeding of water and/or carbon dioxide at volume percent levels combined with smaller ppmV concentrations of organic chlorides and nitrogenoxides. At the end we briefly discuss how non‐catalytic oxidative routes to propylene oxide provide additional insights for new catalyst development. While these approaches hardly exceed 60 % PO selectivity, they may shed light on design criteria for catalysts capable of achieving that goal. Success in the field will require strong fundamental understanding of the activation of dioxygen on catalytic surfaces to define design requirements for silver catalystswith high selectivity to PO via direct oxidation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".