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<p>This study explores the tribological behavior of Cu–Zn–Al shape memory alloys (SMAs) through a systematic optimization approach based on an L9 orthogonal array design. Four alloy compositions (CZA13, CZA21, CZA22, and CZA23) were evaluated under varied combinations of load, sliding speed, and sliding distance to understand the interplay between alloy chemistry, microstructure, and the shape memory effect (SME) in determining wear resistance. Among the tested alloys, CZA22 exhibited the most superior wear performance, attributed to its high copper content (76 wt%) and a martensitic microstructure that provided enhanced ductility, thermal conductivity, and a high SME of 97%, enabling efficient surface self-healing during cyclic loading. CZA23, with the highest SME (98%), also demonstrated favorable wear resistance under moderate conditions, whereas CZA13 and CZA21 showed moderate to poor performance, respectively, due to their less optimized phase structure and lower SME. Frictional force trends and wear rate measurements indicated that load was the most significant factor affecting wear, followed by sliding distance and speed. Taguchi analysis effectively identified optimal operating conditions and revealed strong correlations between composition, SME, and tribological stability. The study emphasizes the critical role of tailored alloy design and phase stability in enhancing the wear performance of SMAs. These findings not only provide a deeper mechanistic understanding of wear behavior in Cu–Zn–Al SMAs but also offer practical guidance for selecting and optimizing these materials for advanced engineering applications, particularly in actuators, dampers, and systems subjected to dynamic mechanical stresses.</p>

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Tribological Evolution of Cu–Zn–Al Shape Memory Alloys: Insights Through Systematic Optimization

  • 期刊论文

  • 发表日期：

    2025年8月8日

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  • N. Lokesh,
  • A. G. Shivasiddaramaiah,
  • U. S. Mallik,
  • S. R. Manohara

摘要

This study explores the tribological behavior of Cu–Zn–Al shape memory alloys (SMAs) through a systematic optimization approach based on an L9 orthogonal array design. Four alloy compositions (CZA13, CZA21, CZA22, and CZA23) were evaluated under varied combinations of load, sliding speed, and sliding distance to understand the interplay between alloy chemistry, microstructure, and the shape memory effect (SME) in determining wear resistance. Among the tested alloys, CZA22 exhibited the most superior wear performance, attributed to its high copper content (76 wt%) and a martensitic microstructure that provided enhanced ductility, thermal conductivity, and a high SME of 97%, enabling efficient surface self-healing during cyclic loading. CZA23, with the highest SME (98%), also demonstrated favorable wear resistance under moderate conditions, whereas CZA13 and CZA21 showed moderate to poor performance, respectively, due to their less optimized phase structure and lower SME. Frictional force trends and wear rate measurements indicated that load was the most significant factor affecting wear, followed by sliding distance and speed. Taguchi analysis effectively identified optimal operating conditions and revealed strong correlations between composition, SME, and tribological stability. The study emphasizes the critical role of tailored alloy design and phase stability in enhancing the wear performance of SMAs. These findings not only provide a deeper mechanistic understanding of wear behavior in Cu–Zn–Al SMAs but also offer practical guidance for selecting and optimizing these materials for advanced engineering applications, particularly in actuators, dampers, and systems subjected to dynamic mechanical stresses.