Evidence map›Paper›PMID 38005016›Full record

ArticleMaterials (Basel, Switzerland)2023

Eco-Friendly Multilayer Coating Harnessing the Functional Features of Curcuma-Based Pigment and Rice Bran Wax as a Hydrophobic Filler.

Massimo Calovi, Stefano Rossi

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Massimo CaloviDepartment of Industrial Engineering, University of Trento, Via Sommarive 9, 38123 Trento, Italy.ORCID 0000-0001-6179-4842
Stefano RossiDepartment of Industrial Engineering, University of Trento, Via Sommarive 9, 38123 Trento, Italy.ORCID 0000-0001-7214-4634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work aims to highlight the multiple features shown by curcuma-based pigment and rice bran wax, which can be selectively employed as bio-based additives for the realization of multilayer wood coatings with multiple functionalities, harnessing the capabilities of the two environmentally friendly fillers, in line with current environmental sustainability trends. The role of the two green materials on the morphology of the composite layers was examined through observations employing scanning electron and optical microscopy, revealing a strong alteration of the film's appearance, both its color and reflectivity. Additionally, their influence on the paint's resilience was assessed by exposing the samples to UV-B radiation and consecutive thermal shocks. The coating displayed a clear and uniform change in color because of substantial curcuma powder photo-degradation but it remained exceptionally stable when subjected to thermal stresses. Moreover, the protective properties of the coatings were evaluated by conducting liquid resistance tests and water uptake tests, while the hardness and the abrasion resistance of the coatings were assessed to evaluate the effect of the additives on the mechanical properties of the coatings. In conclusion, this study showcases the promising joint action of curcuma-based pigment and rice bran wax in multilayer coatings. This combination offers vibrant yellow tones and an appealing appearance to the paint, enhances the surface's water-repellent properties, and improves the mechanical resistance of the coatings.

Indexed as

curcumaenvironmentally friendly additivegreen coatingrice bran waxwood paint

Identifiers

PMID38005016
PMCPMC10671901

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.