Abstract
Conventional aluminum (Al) and its alloys have been replaced by aluminum matrix composites (AMCs) due to their superior properties in the recent years. There are several attractive candidates as reinforcement for aluminum composites such as Al2O3, B4C and SiC. Nowadays, carbon based materials such as graphite, carbon nanotubes (CNTs) and graphene have attracted much attention owing to their above mentioned mechanical and physical properties. In this study, the wear behavior of Al graphene nanoplatelets (GNPs) composites reinforced with up to 2 wt.-% GNP were investigated. The addition of graphene up to 1 wt.-% decreased coefficient of friction. Experimental data were used to develop linear and nonlinear models. The experimental results are in good agreement with the results of the simulations based on the identified models.
Kurzfassung
Konventionelles Aluminium (Al) und seine Legierungen wurden in den letzten Jahren durch Aluminiummatrix-Komposite (AMC) aufgrund ihrer hervorragenden Eigenschaften ersetzt. Für die Verstärkung der Aluminium-Komposite existieren verschiedene attraktive Komponenten, wie beispielsweise Al2O3, B4C und SiC. Heute gewinnen kohlenstoffbasierte Materialien, wie beispielsweise Graphit, Carbon-Nanoröhrchen und Graphen eine hohe Beachtung wegen der oben erwähnten mechanischen und physikalischen Eigenschaften. In der diesem Beitrag zugrunde liegenden Studie wurde das Verschleißverhalten von Al-GNP Kompositen untersucht, die mit bis zu 2 wt.-% GNP verstärkt wurden. Die Zugabe von bis zu 1 wt.-% GNP verringerte den Reibkoeffizient. Die experimentellen Ergebnisse wurden verwendet, um lineare und nichtlineare Modelle zu entwickeln. Die experimentellen Ergebnisse sind in guter Übereinstimmung mit den Resultaten der Simulationen, die basierend auf den identifizierten Modellen durchgeführt wurden.
References
1 U.Abdullahi, M. A.Maleque, U.Nirmal: Wear mechanisms map of CNT-Al nano-composite, Procedia Engineering68 (2013), pp. 736–74210.1016/j.proeng.2013.12.247Search in Google Scholar
2 M.Bastwros, G. Y.Kim, C.Zhu, K.Zhang, S.Wang, X.Tang, X.Wang: Effect of ball milling on graphene reinforced Al6061 composite fabricated by semi-solid sintering, Composites Part B60 (2014), pp. 111–11810.1016/j.compositesb.2013.12.043Search in Google Scholar
3 M.Rashad, F.Pan, ATang, M.Asif, S.Hussain, J.Gou, J.Mao: Improved strength and ductility of magnesium with addition of aluminum and graphene nanoplatelets, Journal of Industrial and Engineering Chemistry23 (2015), pp. 243–25010.1016/j.jiec.2014.08.024Search in Google Scholar
4 D. K.Lim, T.Shibayanagi, A. P.Gerlich: Synthesis of multi-walled CNT reinforced aluminium alloy composite, Materials Science and Engineering A507 (2009), pp. 194–19910.1016/j.msea.2008.11.067Search in Google Scholar
5 D. K.Perez-Bustamante, C. D.Gomez-Esparza, I.Estrada-Guel, M.Miki-Yoshida, L.Licea-Jimenez, S. A.Perez-Garcia, R.Martinez-Sanchez: Microstructural and mechanical characterization of Al-MWCNT composites produced by mechanical milling, Materials Science and Engineering A502 (2009), No. 1–2, pp. 159–16310.1016/j.msea.2008.10.047Search in Google Scholar
6 Y.Shimizu, S.Miki, T.Soga, I.Itoh, H.Todoroki, T.Hosono, K.Sakaki, T.Hayashi, Y. A.Kim, M.Endo, S.Morimoto, A.Koide: Multi-walled carbon nanotube-reinforced magnesium alloy composites, Scripta Materialia58 (2008), pp. 267–27010.1016/j.scriptamat.2007.10.014Search in Google Scholar
7 S. J.Yan, S. L.Dai, X. Y.Zhang, C.Yang, Q. H.Hong, J. Z.Chen, Z. M.Lin: Investigating aluminum alloy reinforced by graphene nanoflakes, Materials Science and Engineering A612 (2014), pp. 440–44410.1016/j.msea.2014.06.077Search in Google Scholar
8 M.Rashad, F.Pan, A.Tang, M.Asif: Effect of graphene nanoplatelets addition on mechanical properties of pure aluminum using a semi-powder method, Progress in Natural Science: Materials International24 (2014), pp. 101–10810.1016/j.pnsc.2014.03.012Search in Google Scholar
9 W.Zhai, X.Shi, J.Yao, A. M. M.Ibrahim, Z.Xu, Q.Zhu, Y.Xiao, L.Chen, Q.Zhang: Investigation of mechanical and tribological behaviors of multilayer graphene reinforced Ni3Al matrix composites, Composites Part B70 (2015), pp. 149–15510.1016/j.compositesb.2014.10.052Search in Google Scholar
10 C.Zhang, H.Zhang: Modelling and prediction of tool wear using LS-SVM in milling operation, International Journal of Computer Integrated Manufacturing29 (2016), pp. 76–9110.1080/0951192X.2014.1003408Search in Google Scholar
11 I.Istif, O.Isin, E.Uzunsoy, D.Uzunsoy: Non-linear modelling of PM brake lining wear behaviour, Materials Testing54 (2012), pp. 45–4810.3139/120.110295Search in Google Scholar
12 I.Istif, O.Isin, E.Uzunsoy, D.Uzunsoy: Linear model for PM brake lining material wear behaviour, Materials Testing52 (2010), pp. 795–79910.3139/120.110192Search in Google Scholar
13 F. S.Rashed, T. S.Mahmoud: Prediction of wear behaviour of A356/SiCp MMCs using neural networks, Tribology International42 (2009), pp. 642–64810.1016/j.triboint.2008.08.010Search in Google Scholar
14 C. S.Ramesh, A. R.Khan, N.Ravikumar, P.Savanprabhu: Prediction of wear coefficient of Al6061-TiO2 composites, Wear259 (2005), pp. 602–60810.1016/j.wear.2005.02.115Search in Google Scholar
15 D.Aleksendric: Neural network prediction of brake friction materials wear, Wear268 (2010), pp. 117–12510.1016/j.wear.2009.07.006Search in Google Scholar
16 I.Istif, O.Isin, D.Uzunsoy, T.Peng, I.Chang: Prediction of wear behavior of aluminum alloy reinforced with carbon nanotubes using nonlinear identification, SAE Technical Paper 2014-01-0947 (2014) 10.4271/2014-01-0947Search in Google Scholar
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