Role of Water and Kaolinite on the Conversion Rate and Reaction Pathways during Thermal Conversion of α-Methylstyrene at 400 °C
Bibliographic record
Abstract
Research examining the impact of water and mineral matter on the thermal conversion of crude oil has indicated that retaining these components during treatment affects cracking, hydrogen transfer, and addition reactions. However, the complex nature of a reaction medium containing crude oil poses a challenge in relating the influence of water and minerals to particular reaction pathways. To enhance understanding of the specific contributions of water and minerals to reaction chemistry during thermal conversion, a practical approach is to make use of simpler model systems to capture relevant information for petroleum processing. The current study explored the impact of water and kaolinite on the reaction rates and pathways during the thermal conversion of a model system comprising α-methylstyrene (AMS), tetralin, and n -pentadecane at 400 °C for 1, 5, 10, and 30 min. The effect of kaolinite at different concentrations was also compared to that of rutile and quartz during the conversion of AMS alone. Water and kaolinite, individually and collectively, affected the reaction rates. Water suppressed the AMS conversion rates, but no evidence was found that water affected reaction pathways. Kaolinite increased the conversion rates of both AMS and tetralin, while also enhancing the formation rates of cumene and naphthalene. This suggested that kaolinite somehow favored hydrogen transfer during the treatment. The presence of kaolinite also increased the formation rates of benzene by dealkylation and the tricyclic AMS dimer 1,1,3-trimethyl-3-phenyl indane, indicating that kaolinite was catalytically active, influencing reaction pathways by promoting cationic conversion. The adsorption of water on the surface of kaolinite appeared to contribute to reduced reaction rates when reacting AMS in the presence of both water and kaolinite. The deposition of carbonaceous material on kaolinite suggested that the mineral is rapidly fouled during the conversion.
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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 | 0.000 | 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) | 0.000 | 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".