Hybrid experimental and machine learning approach for optimizing abrasive wear of microcrystalline cellulose modified hemp/bamboo fiber composites.

S J Davis Hans, M Muthukumaran, K Kumaresan, V G Pradeep Kumar, Dayanand M Goudar, Subraya Krishna Bhat

Abstract read

In one paragraph

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 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.

Optimizing abrasive wear in sustainable MCC reinforced hemp bamboo epoxy composites for tribological applications.Scientific reports · 2026
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

6 authors.

S J Davis HansDepartment of Mechanical Engineering, Jansons Institute of Technology, Coimbatore, India. s.j.davishans@jit.ac.in.ORCID http://orcid.org/0000-0001-9406-1282

M MuthukumaranDepartment of Mechanical Engineering, Jansons Institute of Technology, Coimbatore, India.ORCID https://orcid.org/0000-0002-3397-3576

K KumaresanDepartment of Mechanical Engineering, Park College of Technology, Coimbatore, India.ORCID https://orcid.org/0000-0002-6711-7786

V G Pradeep KumarDepartment of Mechanical Engineering, JSS Science and Technology University, Mysuru, 570006, India.ORCID https://orcid.org/0009-0003-9690-8127

Dayanand M GoudarDepartment of Mechanical Engineering, Tontadarya College of Engineering, Gadag, 582101, India.ORCID https://orcid.org/0000-0002-0085-401X

Subraya Krishna BhatDepartment of Mechanical and Industrial Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India. sk.bhat@manipal.edu.ORCID http://orcid.org/0000-0003-1798-3480

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this work, hemp/bamboo hybrid fabric-epoxy composites reinforced with 0-9 wt% microcrystalline cellulose (µCC) is examined for their abrasive wear behavior. Compression molding was used to create composites with 0, 3, 6, and 9 wt% µCC. In accordance with ASTM G65 guidelines, wear tests were conducted under controlled dry sand abrasion. Using a Taguchi L

Indexed as

Abrasive wear predictionHemp/bamboo-epoxy compositesMachine learningMicrocrystalline cellulose

Identifiers

PMID41298651

DOI10.1038/s41598-025-26396-0

PMCPMC12658126

What Socratic 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 Socratic graph.