Towards a More Conductive and Stronger Cellulose-CNTs Composite Film through Controlling the Texture
Bibliographic record
Abstract
Dispersion state of carbon nanotubes (CNTs) in cellulose nanofibrils (CNFs) film at variant sonication time in the presence of sodium dodecyl sulfate (SDS) has been studied in this work. The sonication was extended up to 120 min, and the CNF-CNTs-SDS suspension’s viscosity was measured at different times. Overall, viscosity of CNF-CNTs-SDS suspension decreased continuously as sonication continued except for the period of 60–75 min, where an increase in the viscosity was observed. Based on morphological investigations, the partial dispersion of particles at the early stage of sonication (i.e. up to 60 min) was followed by coagulation or reagglomeration of the particles during 60–75 min and increasing sonication time by 120 min led to improved dispersion of CNTs in CNFs. Likewise, the electrical conductivity and tensile strength obeyed the same trend due to improved CNTs-CNFs film’s network (30–60 and 75–120 min) and the corresponding reduction (60–75 min) caused by the partial agglomeration of CNT and CNF moieties. These findings highlight that sonication time is not a straightforward parameter and should be elaborated to reach the desired dispersion.
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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".