Mössbauer Spectroscopy and Catalytic Reaction Studies of Chrysotile-Catalyzed Steam Reforming of Benzene
Bibliographic record
Abstract
Chrysotile, a naturally occurring iron-bearing magnesium hydroxide phyllosilicate found in mine and milling residue heaps from southern Québec, was tested for its potential use as a tar-cracking catalyst in biomass steam gasification. Interspersed within the chrysotile mineral, magnetite impurities were recognized to confer tar-cracking catalytic properties to the material. Chrysotile steam-reforming activity was probed using benzene model tar compound at various temperatures, gas hourly space velocities, and catalyst pretreatments. The activity of air-calcined chrysotile (converted to hematite-containing forsterite) was benchmarked against that of olivine catalyst with nearly equal iron content. Mössbauer spectroscopy combined with temperature programmed reduction studies, syngas yield, and benzene conversion responses enabled recognizing the role of the various oxidation states and coordination environments of iron as a function of pretreatment conditions of the catalyst. The study’s findings were rationalized in terms of iron deportment and BET specific surface area of the minerals to explain the 5-fold increase of benzene conversion and syngas yield of chrysotile over olivine for similar gas hourly mass space velocities, temperatures, and particle sizes.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".