An in situ spatially resolved analytical technique to simultaneously probe gas phase reactions and temperature within the packed bed of a plug flow reactor
Bibliographic record
Abstract
This paper reports the detailed description and validation of a fully automated, computer controlled analytical method to spatially probe the gas composition and thermal characteristics in packed bed systems. As an exemplar, we have examined a heterogeneously catalysed gas phase reaction within the bed of a powdered oxide supported metal catalyst. The design of the gas sampling and the temperature recording systems are disclosed. A stationary capillary with holes drilled in its wall and a moveable reactor coupled with a mass spectrometer are used to enable sampling and analysis. This method has been designed to limit the invasiveness of the probe on the reactor by using the smallest combination of thermocouple and capillary which can be employed practically. An 80 μm (O.D.) thermocouple has been inserted in a 250 μm (O.D.) capillary. The thermocouple is aligned with the sampling holes to enable both the gas composition and temperature profiles to be simultaneously measured at equivalent spatially resolved positions. This analysis technique has been validated by studying CO oxidation over a 1% Pt/Al2O3 catalyst and the spatial resolution profiles of chemical species concentrations and temperature as a function of the axial position within the catalyst bed are reported.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".