Application of tree biochar in PDMS pervaporation membranes
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this study, three kinds of biomass materials (lodgepole pine bark, larch wood, larch bark) were used to prepare biochar (BB), and the prepared products as fillers were mixed with polydimethylsiloxane (PDMS) for preparing composite membranes which were used for separating ethanol from water by pervaporation (PV). In accordance with the experiment results, the lodgepole pine bark BB was the best filler for the selective membrane to ethanol. The silane coupling agents NH 2 (CH 2 ) 3 Si(OC 2 H 5 ) 3 (KH‐550) and CH 2 =CH‐Si(OCH 3 ) 3 (YDH‐171) were applied in the modification of lodgepole pine bark BB. And the separation performances of the BB/PDMS composite membranes were researched in detail. The results showed that the permeability (flux and separation factor) of composite membranes has been significantly improved with the addition of modified BB. YDH‐171 was more effective than KH‐550. The optimum PV performances (the separation factor 11.3 and the corresponding flux 227.25 g m −2 h −1 ) were obtained by adding 3 wt. % modified BB for a 10 wt. % and 40°C ethanol solution. This study indicated the potential application of BB nanoparticles in preparing pervaporation separation membrane.
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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 it