Evidence map›Paper›PMID 34832809›Full record

ArticleMicromachines2021

Surface Integrity and Friction Performance of Brass H62 Textured by One-Dimensional Ultrasonic Vibration-Assisted Turning.

Xianfu Liu, Jianhua Zhang, Li Li

Abstract read
In one paragraph

Article in Micromachines, 2021. 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

3 authors.

Xianfu LiuSchool of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0003-2050-9958
Jianhua ZhangKey Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education of China, School of Mechanical Engineering, Shandong University, Jinan 250061, China.
Li LiSchool of Mechanical Engineering, Shandong University of Technology, Zibo 255000, China.

Funding

National Natural Science Foundation of China 51475275
6 · The paper itself

Abstract

The processing method, one-dimensional ultrasonic vibration-assisted turning (1D UVAT), is a potential and efficient way for fabricating a micro-textured surface. This paper aims at exploring the surface integrity and friction performance of brass H62 textured by the 1D UVAT. Four micro-textured surfaces with a specific distribution, size, and shape of dimples were fabricated by optimizing processing parameters, and the corresponding surface topography, subsurface microstructure, and surface roughness were observed and analyzed. A series of friction tests were carried out under oil-lubricating conditions to research the friction performance of micro-textured surfaces. The results show that the reason for the deviation between theoretical and experimental values of dimple depth was further revealed by observing the corresponding subsurface microstructure. The surface roughness of the micro-textured surfaces prepared is related to the number of micro-dimples per unit area and dimple size, which is greater than the surface generated by conventional turning. Compared with the polished surface and micro-grooved surface, the micro-textured surfaces have better friction performance with a lower frictional coefficient (COF) and wear degree. For the micro-textured surface fabricated by 1D UVAT, the number of micro-dimples per unit area has a great effect on the friction performance, and choosing a larger number is more conducive to improving the friction performance under the oil-lubricating condition. Consequently, this study proves that the proposed 1D UVAT can be a feasible candidate for preparing a micro-textured surface with better tribological property.

Indexed as

dimple profilefriction performancemicro-textured surfacesubsurface microstructureultrasonic vibration-assisted turning

Identifiers

PMID34832809
PMCPMC8622952

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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.