Fabrication of Transparent Nanocellulose Paper from Plant Sources for Energy Devices
Bibliographic record
Abstract
Over the past decades, electronic waste has accumulated and has increased by 21% in the last five \nyears. Recently, a UN report founded that the world dumped a gross record of 53.6 million tonnes \nof e-waste across last year. In the past, electronics had limitations due to their size constraint but \nwith technological growth, electronics have now become a prominent part of the waste stream. \nPlastic substrates such as polyethylene (PET) and polycarbonate (PC) has been used pervasively \nin electronic devices. But due to their low co-efficient of thermal expansion (CTE), low \nrecyclability and immense levels of pollution, a new state-of-art technology the cellulose \nnanopaper (CNP) has shown immense potential to replace plastic as a substrate in optoelectronics. \nBio-derived decomposable electronics have exhibited great prospective to reduce the \nenvironmental footprint and avoid the surplus amounts of plastic based waste. \nThis project reports about a nanopaper fabricated from self-assembled network structure from \nnanoscale building blocks known as cellulose nanofibers (CNF). Nanofibers from two distinct \nsources were tested – (a) Cannabis sativa - Hemp (b) Softwood – Pine. Hemp CNFs provided by \nIND Hemp, United States in association with Tangho Green Inc., Canada was prepared via alkaline \nand acid hydrolysis along with high compression grinding and a cellulose purity of 97% was \nobtained. Pine CNFs were purchased from Forestry Department of University of Maine, USA had \na >98% purity spectrum. A comprehensive study of CNP’sstructure-property relationship has been \nestablished under different processing conditions such as temperature of drying and CNF \ngrammage, through characterization analyses. Two main nanopaper fabrication techniques of \nSolution Casting and Vacuum Filtration were studied in detail. Secondary objective comprised of \noptimizing optical properties of CNPs by adding polymers like Poly (vinyl alcohol) (PVA) and \nPolymethyl methacrylate (PMMA). Both PVA and PMMA showed considerable compatibility \nwith CNF as a way of making them transparent. \nThe project was rounded off by incorporating Silver Nanowires (AgNWs) which was chosen as a \nconductive nano-filler due to its well-expressed aspect ratio. AgNWs showed high conductivity \nwith increasing its loading density (mg/cm2 \n) or grammage. The films showed a resistivity as low \nas 9.45 ohm.µm with higher grammage of nanowire added. The results showed that nanocellulose \nchanged their nature from insulator to conductor after addition of conductive materials. Moreover, \niv \nthe highest conductivity around 1.05 kS/cm was obtained with maximum amounts of nanowire \ndeposited. \nThis work solely presents a trend for the application of this conductive nanopaper in foldable or \nflexible electronics such as solar cells, OLEDS, electrodes or electronic skin for \nelectrophysiological monitoring.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".