Evidence map›Paper›PMID 41012205›Full record

ArticlePolymers2025

Finite Element Analysis and Experimental Investigation on the Machinability of PMMA/CNT Composites via Nanosectioning.

Guoyu Fu, Jia Ge, Hao Li, Fengzhen Sun, Weizhou Wu

Abstract read
In one paragraph

Article in Polymers, 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

5 authors.

Guoyu FuKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300072, China.ORCID 0000-0003-4074-7590
Jia GeSchool of Mechanical and Aerospace Engineering, Queen's University Belfast, Belfast BT9 5AH, UK.
Hao LiKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300072, China.
Fengzhen SunSchool of Mechanical Engineering, Tongji University, 4800 Cao'an Road, Shanghai 201804, China.
Weizhou WuKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300072, China.

Funding

National Natural Science Foundation of China 52375461National Natural Science Foundation of China 52405509
6 · The paper itself

Abstract

In this study, an innovative modeling approach has been proposed to demonstrate the removal mechanisms of Polymethyl Methacrylate (PMMA) reinforced with randomly distributed carbon nanotubes (CNTs) during nanosectioning. The viscoplastic behavior of the matrix polymer was described using the Mulliken-Boyce model and the distribution of the CNTs in the matrix was modeled using the random sequential adsorption (RSA) method. The effects of cutting thickness and CNT loading on the machinability of the nanocomposites are explored. Subsequent experiments were conducted to validate the modeling. It reveals that the addition of CNT increases the resistance to cutting, compared to the malleable matrix. Although the primary strain distribution for both plain PMMA and PMMA/CNT composites aligns closely, discernible disparities between the two materials emerge. A force augmentation is anticipated whenever a nanotube interacts with the cutting tool, which causes surface protrusions and sub-surface damage. The addition of CNT with a loading lower than 1.0 wt% does not change the mechanisms of chip formation, but the addition of 1.0 wt% CNTs increases cutting force by approximately 32%. This work provides a feasible approach and framework to numerically model the nanosectioning of CNT-reinforced thermoplastics.

Indexed as

carbon nanotubes (CNTs)Mulliken–Boyce modelnanosectioningpolymer nanocomposites

Identifiers

PMID41012205
PMCPMC12473824

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.