Evidence map›Paper›PMID 40684022›Full record

ArticleScientific reports2025

Optimization of tribo-mechanical properties of kenaf/jute-SiC hybrid composites using integrated grey-fuzzy approach.

Aravindh Murugan, Debabrata Barik, Rasan Sarbast Faisal, Makeshkumar Mani, Milon Selvam Dennison, Seepana Praveenkumar, Saravanan Rajendran

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Article
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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

7 authors.

Aravindh MuruganDepartment of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, 641021, India.
Debabrata BarikDepartment of Mechanical Engineering, Karpagam Academy of Higher Education, Coimbatore, 641021, India. debabrata93@gmail.com.
Rasan Sarbast FaisalDepartment of Petroleum Engineering, College of Engineering, Knowledge University, Erbil, 44001, Iraq.
Makeshkumar ManiDepartment of Mechanical Engineering, KPR Institute of Engineering and Technology, Coimbatore, 641407, India.
Milon Selvam DennisonDepartment of Mechanical Engineering, Kampala International University, Western Campus, Ishaka-Bushenyi, Uganda. milon.selvam@kiu.ac.ug.
Seepana PraveenkumarDepartment of Nuclear and Renewable Energy, Ural Federal University, Ekaterinburg, 620002, Russia.
Saravanan RajendranInstituto de Alta Investigación, Universidad de Tarapacá, Arica, 1000000, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An increasing need for wear-resistant hybrid materials has prompted researchers to develop alternative materials that comprise different reinforcements and fillers. In recent studies, the combination of natural fibers and ceramic fillers has resulted in hybrid composites with improved tribological characteristics for automotive and aircraft applications. Even though natural fibers have some disadvantages, the combined effect of natural fibers and ceramics with suitable multi-response optimization techniques can overcome the limitations and provide a composite with enhanced mechanical and tribological properties at minimal cost. This paper explores the wear behavior of silicon carbide (SiC) filled kenaf/jute-based hybrid composite. In addition, a multi-response optimization technique combining the fuzzy model interference system and grey relation analysis (GRA) is adopted in the current work. Design of experiments was carried out with the Taguchi L27 orthogonal array (OA) to yield the minimum wear rate and coefficient of friction (COF). This study demonstrated that the highest gray relational grade (GRG) and gray fuzzy grade (GFG) value of 0.804 and 0.801, respectively to obtain the optimal operating parameters of 1 wt% SiC, 30 wt% reinforcement, 1500 m sliding distance, 1.5 m/s sliding speed, and 15 N load. Scanning electron microscope (SEM) revealed worn-out surface mechanisms, fine debris, and the ploughing effect, which play a significant role in begetting the desired wear characteristics. Furthermore, the best combination of particulate hybrid composite was tested for mechanical characteristics in dry and wet conditions.

Indexed as

AI with GFGAI with GRGHybrid compositesKenaf/jute-SiCMechanical propertiesTribological characteristics

Identifiers

PMID40684022
PMCPMC12276226

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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.