OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Introduction Polymers have recently replacedmetals in tribological applications because of their numerous advantages, including self-lubrication, chemical stability, low density, and biocompatibility. This transformation in tribo-system components has increased the demand for the development of high-performance and costeffective polymer composites. PTFE has emerged as a most prominent choice for applications such as mining, automotive, aerospace, electrical, and electronics industries [1]. With its unique combination of properties, such as a low coefficient of friction, exceptional chemical inertness, high thermal stability, and non-stick characteristics, PTFE effectively minimizes friction and wear by establishing a thin transfer film on the contacting surface. This ability of PTFE, along with its thermal and chemical stability, makes it suitable for various industrial applications where wear performance is required [2]. However, pure PTFE alone cannot withstand the demands of tribological applications. Therefore, researchers have explored the addition of various fillers to reinforce pure PTFE, improving its mechanical and tribological performance. The most used fillers are carbon, glass, graphite, bronze, MoS2, alumina, PEEK (polyetheretherketone), and potassium titanate whisker (PTW) [3]. The researchers also studied advanced fillers such as ekonol, polyether sulphone, and poly-p-phenyleneterephthalamide (PPDT) fibers for their potential benefits [4]. Carbon is a widely used filler because it increases the wear resistance of the base material and significantly increases the tensile strength, impact strength, and hardness [3]. This improvement of PTFE properties is achieved with the incorporation of carbon at a concentration of 15 to 30 % by volume [4]. The addition of carbon makes PTFE more suitable for high load and temperature applications. Glass, when added to PTFE, enhances hardness and tensile strength, improving the load-carrying capacity and wear resistance of the base material [5]. It also provides resistance to deformation and dimensional stability under high load and temperature conditions [6]. This ensures the improved performance of glass-filled PTFE composites in applications like bearings, seals, gaskets, and guide rails etc. [7]. Similarly, the load-bearing capacity, thermal stability, and wear resistance of PTFE are found to be improved with the addition of bronze at a concentration of 40 to 60 % by volume [8]. Researchers observed that the addition of bronze to PTFE provides stable frictional behavior and extends the service life of the components in applications such as seals, bearings, and bushings [9–10]. Further improvement in composite properties is achieved by adding molybdenum disulfide (MoS2) at a concentration of 5 % by volume, making it a promising candidate for automotive applications [11–13]. It is reported that the performance of polymer composites is influenced by several operating parameters, such as normal load, contact area, sliding speed, counterpart topology, and temperature [14–18]. These parameters are responsible for the formation of a stable film on the counterpart, which reduces the surface interaction, and eventually reduces the wear [19]. Similarly, few parameters (temperature and load) initiate the degradation of the composites and affect its behavior under certain conditions. Hence, it is required to study these parameters, and they shall be optimized to improve the performance of the composite [20]. It is also evident that these parameters affect the fundamental adhesion phenomenon of polymer composites, which affects its wear behavior. Tribological study has traditionally employed experimental methods to evaluate wear and friction in materials. However, these studies are time-consuming, resource-intensive, and often possess constraints regarding identifying factors influencing wear mechanisms. Numerical modelling, particularly finite element analysis (FEA) in conjunction with Archard’s wear model, has emerged as an efficient way to supplement experimental research [21]. These models allow researchers to simulate the wear process, predict the outcome under various operating circumstances, and optimize material design before physical testing. It is evident that FEA is an extremely versatile and powerful tool for wear simulation. Under dynamic load and environmental conditions, FEA provides comprehensive analysis of stress distribution, deformation, and wear development [22]. It enables researchers to investigate local wear phenomena and understand the wear mechanism in greater detail. The studies reflect that the predictive capabilities of the wear model are improved by combining Archard’s law with FEA [23–24]. In the present study, a numerical approach has been considered based on the Archard model, and the results are validated using experimental analysis. The
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