Optimization of the PDMS/biochar nanocomposite membranes using the response surface methodology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract To improve the separation performance of the polydimethylsiloxane (PDMS)/bark biochar (BB) nanocomposite membranes used for alcohol/water separation, the preparation conditions of these composite membranes were analyzed and optimized. In this study, we investigated the following preparation parameters: the BB pyrolysis temperature, the weight ratio of the silane coupling agent (KH-550) to bark biochar (BB), and the BB loading amount. The regression equations were established between these three preparation parameters and the final pervaporation (PV) performance characteristics of the composite membranes. The membranes performed the best under the following optimal preparation conditions: a BB pyrolysis temperature of 407°C; a silane coupling reagent/BB weight ratio of 0.86, and a BB loading amount of 3.36 wt%. According to the results of the regression analysis, a maximum permeation flux of 221.2 g·m −2 ·h −1 and a maximum selective factor of 21.3 was obtained when the feed temperature for the 5 wt% alcohol solution was set at 40°C.
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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 | 0.002 | 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