Evidence map›Paper›PMID 41682131›Full record

ArticlePolymers2026

Development of Sustainable Red Algae-Sisal Fiber Composite Films via Doctor Blading.

Matthew Richards, Joshua Baird, Noah Serda, Vuong Do, Yanika Schneider

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Matthew RichardsDepartment of Chemical and Materials Engineering, San Jose State University, One Washington Square, San Jose, CA 95192, USA.
Joshua BairdDepartment of Chemical and Materials Engineering, San Jose State University, One Washington Square, San Jose, CA 95192, USA.
Noah SerdaDepartment of Chemical and Materials Engineering, San Jose State University, One Washington Square, San Jose, CA 95192, USA.
Vuong DoDepartment of Chemical and Materials Engineering, San Jose State University, One Washington Square, San Jose, CA 95192, USA.
Yanika SchneiderDepartment of Chemical and Materials Engineering, San Jose State University, One Washington Square, San Jose, CA 95192, USA.ORCID 0000-0001-6806-3049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the properties of red algae (RA) biocomposite films reinforced with natural sisal fibers and plasticized with glycerol. The polymer was extracted from locally sourced red seaweed and combined sisal fibers at varying fiber loadings (0-45 wt%) using the doctor blading technique. Composite films were analyzed using a variety of methods to evaluate the chemical composition, thermal behavior and mechanical performance. Infrared spectroscopy confirmed the presence of kappa-carrageenan as the dominant polysaccharide in the RA matrix, whereas elemental analysis verified the dilution of sulfur content and enrichment of carbon with increasing fiber incorporation. Thermal stability increased with fiber loading, peaking at 30 wt% sisal fiber before decreasing slightly at 45 wt% due to poor fiber dispersion. Mechanical testing demonstrated an optimal balance between strength and flexibility at 30 wt% sisal fiber, with a 37% increase in strength compared to the pure RA film. Overall, the findings demonstrate that sisal fiber reinforcement enhances the structural integrity and stability of RA-based films, supporting their potential as biodegradable alternatives to petroleum-based plastics.

Indexed as

biocompositedoctor bladingkappa-carrageenanmechanical analysisred algae polymersisal fibersthermal analysis

Identifiers

PMID41682131
PMCPMC12899586

What OpenQuestion holds

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Registered trials

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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.