Evolution and Enabling Capabilities of Spatially Resolved Techniques for the Characterization of Heterogeneously Catalyzed Reactions
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The development and optimization of catalysts and catalytic processes requires knowledge of reaction kinetics and mechanisms. In traditional catalyst kinetic characterization, the gas composition is known at the inlet, and the exit flow is measured to determine changes in concentration. As such, the progression of the chemistry within the catalyst is not known. Technological advances in electromagnetic and physical probes have made visualizing the evolution of the chemistry within catalyst samples a reality, as part of a methodology commonly known as spatial resolution. Herein, we discuss and evaluate the development of spatially resolved techniques, including the evolutions and achievements of this growing area of catalytic research. The impact of such techniques is discussed in terms of the invasiveness of physical probes on catalytic systems, as well as how experimentally obtained spatial profiles can be used in conjunction with kinetic modeling. Furthermore, some aims and aspirations for further evolution of spatially resolved techniques are considered.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".