Removal of BTX Compounds from Wastewaters Using Template Free MFI Zeolitic Membrane
Bibliographic record
Abstract
MFI zeolite membranes were prepared on porous α-alumina substrates, using secondary growth of nano-seeded layers. The resulting membranes were characterized by means of Scanning Electron Microscopy (SEM), X-Ray Diffractometry (XRD), and pervaporation performance tests for separation of Benzene, Toluene and Xylene (BTX) mixture from contaminated water. The morphology, thickness, homogeneity, crystal preferential orientation and permeation properties of these membranes have been studied in relation to the seed layers. Successful separation of BTX mixture from water was performed by using the manufactured MFI zeolite membrane. The influence of temperature, feed concentration on the membrane separation efficiency systematically investigated. The total permeation fluxes were found to increase with increase in temperature and feed concentration. The separation factors increased with increasing feed concentration and decreased with increasing in temperature.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.030 | 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".