Evidence map›Paper›PMID 40731428›Full record

ArticleMaterials (Basel, Switzerland)2025

Application of Food Waste in Biodegradable Composites: An Ecological Alternative in Tribology.

Łukasz Wojciechowski, Zuzanna Sydow, Karol Bula, Tomasz Runka

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. 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

4 authors.

Łukasz WojciechowskiInstitute of Machines and Motor Vehicles, Poznań University of Technology, 60-965 Poznań, Poland.ORCID 0000-0003-3682-6368
Zuzanna SydowInstitute of Machines and Motor Vehicles, Poznań University of Technology, 60-965 Poznań, Poland.ORCID 0000-0003-3705-5366
Karol BulaInstitute of Material Technology, Poznań University of Technology, 60-965 Poznań, Poland.ORCID 0000-0002-0957-8066
Tomasz RunkaInstitute of Materials Research and Quantum Engineering, Poznań University of Technology, 60-965 Poznań, Poland.ORCID 0000-0002-0965-2676

Funding

the Ministry of Science and Higher Education, Poland 0613/SIGR/2403
6 · The paper itself

Abstract

Biodegradable composite materials enhanced with food waste for tribological applications are proposed in this article. Polymer materials used as matrices included polypropylene and polylactic acid, which, according to the manufacturers' claims, were made entirely or partially from biodegradable raw materials. Additionally, the matrices were enhanced with three types of waste materials: powders derived from cherry and plum stones, and pomace extracted from flax seeds. The composites differed in the percentage content of filler (15 or 25 wt.%) and particle size (d < 400 µm or d > 400 µm). Thirty-minute block-on-ring friction tests were performed to determine frictional behaviour (when pairing with steel), and the wear mechanisms were analysed using optical microscopy and scanning electron microscopy, supplemented with Raman spectroscopy. A notable effect of cherry and plum stone fillers was observed as a reduction in motion resistance, as measured by the friction coefficient. This reduction was evident across all material configurations in polypropylene-based composites and was significant at the lowest concentrations and granulation in polylactic acid composites. The effect of flaxseed pomace filler was ambiguous for both composite bases.

Indexed as

abrasive and adhesive wearbiodegradable compositescoefficient of frictionfood wasteself-lubricationtribological materials

Identifiers

PMID40731428
PMCPMC12300166

What OpenQuestion holds

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LicenceCC BY
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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.