Fundamentals of Tribology - Correlation between Wear Characteristics and Material Properties - (FUNDTRIBO)
Zusammenfassung der Projektergebnisse
The tribological properties of the designed PEEK composites were tested systematically in different scales, i.e. large scale (contact area of 40 mm x 40 mm), macro scale (contact area of 4 mm x 4 mm), and micro/nano scale (single asperity contact). Meanwhile, an artificial neural network (ANN) was used to compare the friction and wear properties of PEEK composites on the investigated scales. It is revealed that the friction and wear properties of PEEK composites depended not only on the material component and sliding conditions, but also on the geometrical scale (specimen size). Under the same sliding conditions, melting was found in the large scale tribological tests, while it didn't occur in macro scale tests. Correspondingly, the matrix showed the best wear resistance in large scale tests, while it exhibited the highest wear rate in macro scale tribological tests. Wear mechanism analysis revealed that the wear resistance of the materials depended largely on the interface between carbon fibers and the matrix in macro scale tests, and the incorporation of nano SiO2 particles facilitated the transfer of filler particles to the counterpart surface, which was beneficial for the improvement of tribological properties of polymeric composites. In large scale tests, nano SiO2 might have a polishing effect on both the carbon fibers and the counterpart asperities, which accounted for the lower friction coefficient and better wear resistance of the nanocomposite. In addition, nano scratch tests revealed a lower friction coefficient for the carbon fibers than for the PEEK matrix. Furthermore, tribological studies in single asperity contact revealed that the geometry of asperities exerted much influence on the friction behavior. For the modeling of the tribological behaviors of the PEEK based materials, a novel artificial neural network approach was employed to make very accurate predictions on the friction coefficient (cof) and wear rate (ws), and Tribomaps are introduced to the tribology society. By means of these Tribomaps, we were able to discriminate which of all our PEEK materials works best for ws or cof under varying conditions (speed (v) & pressure (p)) including the possibility to test not yet engineered material formulations. Regarding cof, we found a small dependency of v and a high dependency of p for all materials. Referring to ws a higher dependency of v could be observed. In general, reinforced materials show a better performance for high values of v and p whereas conventional PEEK is the choice for low values. Differences in laboratory test conditions and real working conditions make it an open question to investigate scale effects on the tribological performance of polymeric materials. The present study aimed to address this problem by collaborative investigation in European level and made great progress approaching the goal. Future research can be focused on the scale effects on the tribological properties of currently used polymeric components under specified industrial conditions, and the establishment of correlation between different scales. Another point is to study the possible synergistic effects between fillers and their dependency on scale. The developed network model makes it possible to investigate effects of not yet tested material compositions and test conditions: Based on the Fundtribo project data, it is now possible to accomplish some kind of "backward simulation", a simulation of the friction coefficients and wear rates that are driven by all possible material compound proportions in small step sizes. This strategy may help in the design and preparation of polymeric composites with desired tribological properties for given load conditions.
Projektbezogene Publikationen (Auswahl)
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Influence of different Load Collectives on the Wear Behavior of PEEK-based Tribo-Materials = Einfluss verschiedener Belastungskollektive auf das Verschleißverhalten von PEEK-basierten Tribowerkstoffen. Tribologie-Fachtagung Göttingen, Bd. 1.2011, S.17.
Englert M.; Römer C.; Lin L., Schlarb AK.; Wagner C.; Reuscher B.; Kopnarski M.:
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Tailoring the tribological behavior of polymer sliding systems by the incorporation of fillers. Taishan Academic Forum. Qingdao, China, 4 November 2011,
Schlarb, A.K.
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Tribology of PEEK-based Composites. Joint ICTP-FANAS Conference on Trends in Nanotribology, Trieste, Italy, 12 September 2011.
Schlarb, A.K.
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An Approach for Successful Compounding of Nanocomposites in Large-Scale Scale Prpduction. Masterbatch Asia 2012, Singapore, 26 March 2012.
Schlarb, A.K.
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Processing Controlled Properties of Thermoplastic-based Nanocomposites. ECCM15 – 15TH European Conference on Composite Materials, Venice, Italy, 24-28 June 2012, 5 pp.
Lin, L.Y.; Schlarb, A.K.
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A novel Neural Network approach for modeling tribological properties of polyphenylene sulfide reinforced on different scales. In K. Friedrich, AK. Schlarb, Tribology of Polymeric Nanocomposites: Friction and Wear of Bulk Materials and Coatings, 2nd Edition, Elsevier, 2013, pp. 779–793.
M. Busse, A.K. Schlarb
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Mechanical and thermal behaviours of polyetheretherketone-based multi-scale composites. Journal of Composite Materials, vol. 47. 2013, no. 17, pp. 2087-2096.
Lin, L.Y; Tlatlik, H.; Gralla, R.; Igartua, M.A.; de Baets, P.; Schlarb, A.K.
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Tribology of Polymeric Nanocomposites: Friction and Wear of Bulk Materials and Coatings, 2nd Edition, Elsevier, 2013, E-book ISBN 9780444594648, 832 p.
K. Friedrich, A.K. Schlarb
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Influence of solid lubricants on tribological properties of polyetheretherketone(PEEK). Tribology International, Vol.103. 2016, pp. 45–57.
V. Rodriguez, J. Sukumaran, A.K. Schlarb, P. De Baets
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Reciprocating sliding wear behaviour of PEEK-based hybrid composites. Wear, Vol. 362–363. 2016, pp. 161–169.
V. Rodriguez, J. Sukumaran, A.K. Schlarb, P. De Baets
