Evidence map›Paper›PMID 34771218›Full record

ArticlePolymers2021

Polylactic Acid Cellulose Nanocomposite Films Comprised of Wood and Tunicate CNCs Modified with Tannic Acid and Octadecylamine.

Matthew J Dunlop, Ronald Sabo, Rabin Bissessur, Bishnu Acharya

Abstract read
In one paragraph

Article in Polymers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Matthew J DunlopFaculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada.
Ronald SaboUSDA Forest Service, Forest Product Laboratory, Madison, WI 53726, USA.
Rabin BissessurDepartment of Chemistry, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada.
Bishnu AcharyaFaculty of Sustainable Design Engineering, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada.

Funding

Fisheries and Oceans Canada AFF-PEI-34Natural Sciences and Engineering Research Council RGPIN-2016-05728
6 · The paper itself

Abstract

Herein, a one-pot strategy was used to prepare hydrophobic cellulose nanocrystals (CNCs) surface-modified with tannic acid and octadecylamine. By this strategy, CNCs derived from wood (W-CNC) and tunicates (T-CNC) were modified in situ and incorporated into a polylactic acid (PLA) matrix using two methods, without first drying the CNCs. Films of PLA-CNC nanocomposites were prepared both by solution casting and by wet compounding in a thermo-kinetic mixer, followed by melt extrusion. Various properties of these PLA nanocomposites were evaluated herein, along with an assessment of how these properties vary with the type of CNC reinforcement. Cast films with a hybrid mixture of wood and tunicate CNCs displayed improved mechanical properties compared to either wood or tunicate CNCs, but extruded films did not show this hybrid effect. The water vapor permeability of the extruded nanocomposite films with 1% CNCs was reduced by as much as 60% compared to the PLA films. The composite films also showed enhanced biodegradation compared to neat PLA films. These results demonstrate that wet compounded PLA composites produced with wood or tunicate CNCs modified using a one-pot, water-based route have improved barrier and biodegradation properties, indicating a potential for packaging applications without having to dry the CNCs.

Indexed as

cellulose nanocrystalsextrusionnanocompositespolymer–matrix compositestunicates

Identifiers

PMID34771218
PMCPMC8588324

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.