Preparation and selective adsorption performance of F‐modified <scp>ZSM</scp> ‐5 zeolite for m‐cresol and p‐cresol
Bibliographic record
Abstract
Abstract M‐cresol and p‐cresol, typically produced as mixtures in industrial processes, are crucial chemical intermediates. However, their separation is challenging due to their similar structures and properties. ZSM‐5 zeolite has shown potential as an adsorbent for separation, while the performance is yet to be improved. In this study, ZSM‐5‐F(x) was synthesized via hydrothermal method, incorporating F − ions during the synthesis process. The adsorption behaviour of m‐cresol and p‐cresol on ZSM‐5‐F(x) was investigated through static experiments, with ZSM‐5‐F(8) demonstrating the highest selectivity (9.01). Both ZSM‐5‐F(0) and ZSM‐5‐F(8) were characterized using XRD, scanning electron microscopy (SEM), and Brunauer‐Emmett‐Teller (BET) techniques. In addition, the introduction of F − ions increased the material's electronegativity, as demonstrated by the change in zeta potential from 53.22 to −45.93 mV. Single‐component adsorption of m‐cresol or p‐cresol on ZSM‐5‐F(0) and ZSM‐5‐F(8) respectively were investigated in detail. The adsorption of m‐cresol on ZSM‐5‐F(8) showed a non‐monotonic phenomenon with a significant decrease after 0.06 mol/L. The thermodynamic parameters including Δ G , Δ H , and Δ S were calculated accordingly. All the values |Δ G |, |Δ H |, and |Δ S | of both components on ZSM‐5‐F(8) were greater than those on ZSM‐5‐F(0), suggesting that the introduction of F − ions facilitated the adsorption. Competitive adsorption experiments on both ZSM‐5‐F(0) and ZSM‐5‐F(8) were conducted at 298.2 K. The results indicated that the selectivity α p/m on ZSM‐5‐F(8) increased with increasing initial concentration and laid between 13 and 14. After seven consecutive regeneration cycles, the selectivity (α p/m ) only decreased to 13. This study suggests that ZSM‐5‐F(8) could be a promising adsorbent for m‐cresol and p‐cresol in industrial applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".