.png){kind=icon}
.png){kind=icon}
Return
Machining under MQL conditions: analysis of aerosol formation parameters and copper nanoparticle size on the surface topography of the Ti6Al4V titanium alloy
.png){kind=icon}
OA
AI
R
N
M
M
DOI：10.1016/j.jmrt.2026.06.164.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this work, nanofluids containing 22, 35, 65, and 80 nm copper nanoparticles at a concentration of 0.5 wt% were used during MQL turning of Ti6Al4V alloy. The influence of varying air and lubricant flow rates over wide ranges (E = 0.388–1.182 g/min and P = 10–40 l/min) on the surface topography of Ti6Al4V alloy after turning was investigated. Although the effects of lubricant flow rate and air flow rate in MQL-assisted machining have already been considered in previous studies, their combined role with Cu nanoparticle size in nanofluid-assisted MQL turning of Ti6Al4V has not been sufficiently investigated. The obtained results were contrasted with dry turning and machining under MQL without nanoparticles. A Pareto-chart-based analysis of standardized effects revealed a significant effect of Cu nanoparticle size on selected 3D surface topography parameters. On the basis of the machined surface topography analysis, it was concluded that the MQL + Cu method with a nanoparticle size of 22 nm was the most effective cooling/lubricating condition in terms of surface quality, with a regular arrangement of valleys and peaks as opposed to other methods. SEM/EDS chip analysis additionally showed that copper-containing deposits were mainly observed on chips obtained after machining with 22 nm Cu nanoparticles, indicating more effective transport of smaller nanoparticles into the cutting zone. Finally, the use of 22 nm Cu nanoparticles reduced the selected 3D surface roughness parameters by about 28% to 30% compared with dry conditions and by 17% to 21% compared with MQL conditions.
Keywords:
MQL
Nanofluids
Cu nanoparticles
Surface topography
Chip morphology
Ti6Al4V
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.6
Papers:
1.7W
Citations:
6.8W
Organization
Cited Papers