Improved Kinetic Data Acquisition Using An Optically Accessible Catalytic Plate Reactor with Spatially-Resolved Measurement Techniques. Case of Study: CO2 Methanation
Bibliographic record
Abstract
Modelling and optimization of chemical reactors require a good understanding of the reactions mechanism with the corresponding kinetic description. Therefore, high quality kinetic data are needed, which can be challenging to obtain, especially for fast and highly exothermic reactions such as the CO2 methanation. Traditionally, kinetic studies rely on measuring the exit gas composition (1 data point per species and experiment) using differential reactors with diluted catalyst beds and reactants to avoid temperature change. Therefore, an optically accessible catalytic channel reactor was designed, which allowed for the chance to gather spatially-resolved information on axial gas composition and catalyst surface temperature, specifically by means of a movable sampling capillary and shortwave infrared-thermography (SWIR), respectively. A catalyst coated plate was placed at the bottom of the channel, while a set of two quartz glass plates covers the top. In the current study 35 data points per gas species were collect for 1 experiment conducted under laminar flow conditions at 425 °C. Catalyst surface temperature determined via a SWIR camera was not influenced by polyatomic molecules partaking in the reaction and thus did not falsify the kinetic data. The catalyst mass distribution along the reactor axis was determined, enabling the development of a correct reactor model for kinetic parameter estimation and model discrimination.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".