Methane Upgrading of Acetic Acid as a Model Compound for a Biomass-Derived Liquid over a Modified Zeolite Catalyst
Bibliographic record
Abstract
The technical feasibility of coaromatization of acetic acid derived from biomass and methane was investigated under mild reaction conditions (400 °C and 30 bar) over silver-, zinc-, and/or gallium-modified zeolite catalysts. On the basis of GC-MS, Micro-GC, and TGA analysis, more light aromatic hydrocarbons, less phenol formation, lower coke production, and higher methane conversion are observed over 5%Zn-1%Ga/ZSM-5 catalyst in comparison with catalytic performance over the other catalysts. Direct evidence of methane incorporation into aromatics over 5%Zn-1%Ga/ZSM-5 catalyst is witnessed in 1 H, 2 H, and 13 C NMR spectra, revealing that the carbon from methane prefers to occupy the phenyl carbon sites and the benzylic carbon sites, and the hydrogen of methane favors the aromatic and benzylic substitutions of product molecules. In combination with the 13 C NMR results for isotopically labeled acetic acid ( 13 CH 3 COOH and CH 3 13 COOH), it can be seen that the methyl and carbonyl carbons of acetic acid are equally involved in the formation of ortho, meta and para carbons of the aromatics, whereas the phenyl carbons directly bonded with alkyl substituent groups and benzylic carbons are derived mainly from the carboxyl carbon of acetic acid. After various catalyst characterizations by using TEM, XRD, DRIFT, NH 3 -TPD, and XPS, the excellent catalytic performance might be closely related to the highly dispersed zinc and gallium species on the zeolite support, moderate surface acidity, and an appropriate ratio of weak acidic sites to strong acidic sites as well as the fairly stable oxidation state during acetic acid conversion under a methane environment. Two mechanisms of the coaromatization of acetic acid and methane have also been proposed after consulting all the collected data in this study. The results reported in this paper could potentially lead to more cost-effective utilization of abundant natural gas and biomass.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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".