Enhanced adsorption of toluene on thermally activated ZIF-67: Characterization, performance, and modeling insights
Bibliographic record
Abstract
The zeolitic imidazolate framework-67 (ZIF-67) has been explored for the dynamic adsorption of toluene vapor. We synthesized ZIF-67 through a straightforward room-temperature process and characterized it using XRD, FT-IR, DLS, and SEM techniques. The synthesized ZIF-67 possessed a Brunauer–Emmett–Teller (BET) surface area of 1578.7 m 2 /g and 0.76 μm particle size. Thermal activation under various conditions revealed that ZIF-67, activated in dry air at 250 °C, demonstrated optimal adsorption efficacy. Its adsorption capacity, time of breakthrough, and time of equilibration were 414.5 mg/g, 420 min, and 795 min, respectively. We investigated the impact of diverse operational parameters on adsorption through breakthrough curve analysis. An increase in the toluene concentration from 100 to 1000 ppm enhanced the adsorption capacity from 171 to 414 mg/g, while breakthrough time decreased from 1260 min to 462 min, respectively. Our findings show that increasing relative humidity from 0 to 70 % reduced 53.7 % in adsorption capacity and 46.3 % in breakthrough time. The competitive adsorption of toluene and ethylbenzene revealed that ZIF-67 had a higher selectivity for toluene adsorption. A 98 % adsorbent's regeneration efficiency at the first cycle reveals its reusability. The experimental data were successfully fitted to the Yan, Thomas, and Yoon-Nelson models to describe the adsorption process. The statistical validation of the model parameters confirms their reliability for estimating adsorption parameters, thus facilitating the design of fixed-bed adsorption columns for practical applications.
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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".