<p>This review summarizes recent progress on the microstructure evolution and wear performance of laser-cladded high-entropy alloy (HEA) coatings. We first analyze how process parameters—such as laser power, scanning speed and powder composition—govern melt-pool thermal history and resultant microstructures (phase constitution, grain size, precipitates/carburides, dislocation density). We then review principal strengthening mechanisms (solid-solution, grain refinement, precipitation/second-phase, dislocation and amorphization) and their contributions to hardness and wear resistance. The roles of ceramic reinforcements, self-lubricating phases, and auxiliary treatments in tailoring tribological behavior are discussed. Finally, we evaluate the prospects of multi-field coupled testing, numerical simulation and machine-learning approaches for wear prediction and process optimization, and outline key challenges and future directions. This review aims to provide guidance for the design and process optimization of wear-resistant laser-cladded HEA coatings.</p>

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Review on wear resistance of laser cladding high entropy alloy coating

  • Kunjie Li,
  • Xuefeng Yang,
  • Yanguang Gu,
  • Maolong Chen,
  • Junbei Ma,
  • Yansheng Liu

摘要

This review summarizes recent progress on the microstructure evolution and wear performance of laser-cladded high-entropy alloy (HEA) coatings. We first analyze how process parameters—such as laser power, scanning speed and powder composition—govern melt-pool thermal history and resultant microstructures (phase constitution, grain size, precipitates/carburides, dislocation density). We then review principal strengthening mechanisms (solid-solution, grain refinement, precipitation/second-phase, dislocation and amorphization) and their contributions to hardness and wear resistance. The roles of ceramic reinforcements, self-lubricating phases, and auxiliary treatments in tailoring tribological behavior are discussed. Finally, we evaluate the prospects of multi-field coupled testing, numerical simulation and machine-learning approaches for wear prediction and process optimization, and outline key challenges and future directions. This review aims to provide guidance for the design and process optimization of wear-resistant laser-cladded HEA coatings.