Effects of oxidant and dopants on the properties of cellulose/PPy conductive composite hydrogels
Bibliographic record
Abstract
ABSTRACT Cellulose/Polypyrrole (PPy) composite hydrogels were prepared by in situ chemically oxidative polymerization of pyrrole in the cellulose matrix. Ferric chloride (FeCl3) was used as an oxidant and four sulfonic compounds were used as dopants in order to investigate the effects on the properties of cellulose/PPy conductive composite hydrogels. The extent of polymerization of PPy was determined by the amount of the oxidant and the composite hydrogels with oxidant at 0.3M−0.5M exhibited the higher conductivities for the intrachain and interchain conductivities of conductive polymers; the fracture stress of the composite hydrogels could be up to 26.25 MPa with a strain of 86.8% when the oxidant was at 0.5M. Doping is an efficient way to improve the conductivity of the composite hydrogels and four kinds of dopant were compared in this work. Long alkane chain and side group in dopants can increase the steric hindrance of PPy polymerization which resulted in the lower conductivity of the composite hydrogels compared to dopants with smaller steric hindrance. The conductivity of the composite hydrogel firstly increased and then decreased with the concentration of dopants from 0.1M to 1.0M in this work. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016, 133, 43759.
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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".