Preparation and Characterization of PMMA and its Derivative via RAFT Technique in the Presence of Disulfide as a Source of Chain Transfer Agent
Bibliographic record
Abstract
Poly(methyl methacrylate) (PMMA) were synthesized by using chain transfer agents(CTA), S-1-Dodecyl-S′-(α,α′-dimethyl-α-acetic acid) trithiocarbonate (MTTCD), S,S′-bis (2-hydroxyethyl-2′-dimethylacrylate) trithiocarbonate (BDATC), 2-cyanoprop-2-yl dithiobenzoate (CPDB) respectively, through the reversible addition fragmentation chain transfer (RAFT) polymerization under a range of synthesis conditions. The results indicated that the structure of the end-group of RAFT agents had significant effects on the ability to control polymerization. Compared with MTTCD and CPDB, BDATC can provide better control over the relative molecular mass, distribution and polymerization of PMMA. The derived well-controlled block copolymer PMMA-b-PDMAEMA and PMMA-b-PDMAEA were also successfully prepared by using N, N-dimethylaminoethy acrylate (DMAEA) or N, N-dimethylaminoethyl methacrylate (DMAEMA) as the second monomer. The chemical composition and structure of the products were characterized by FTIR, 1HNMR, XRD and DSC. CO2 and N2 permeation performance of the PMMA-b-PDMAEA/PS composite membranes were tested at different pressure. The results showed that the resulted composited membrane had a CO2 permeation rate of 3.68×10-5cm3 (STP) cm-2s-1cmHg-1, a N2 permeation rate of 1.78×10-7 cm3 (STP) cm-2s-1cmHg-1 and an ideal CO2/ N2 selectivity of 206.6 at a feed gas pressure of 7.6 cmHg and 30 oC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".