Functionally Graded Metallic Materials Via Additive Manufacturing: Research Progress on Processing, Challenges, and Applications

Abstract

Functionally graded metallic materials (FGMMs) represent an innovative category of metals, characterized by gradual variations in structure or composition, achieved by combining different elements. FGMMs differ from traditional materials as they enable the combination of diverse properties in a spatially tailored manner, offering extraordinary combinations of advanced functionalities. The unique capabilities of FGMMs make them highly desirable for various applications across different industries. The initiation of additive manufacturing (AM) has significantly progressed the advance of FGMMs by aiding specific control over material gradients, complex geometries, and optimized material utilization. This review delivers a comprehensive overview of FGMMs, including their fundamental principles, metallic alloys (alloys based on Al, Ti, Fe, superalloys, and emerging high-entropy alloys), and their integration with AM technologies. Challenges related to thermophysical mismatches, thermal stresses, and process monitoring are addressed with potential solutions. Further, Key modeling and simulation approaches, such as thermodynamic modeling, thermal-mechanical simulations, and machine learning-based design, are discussed in detail to highlight their role in optimizing FGMM performance. This review provides an in-depth exploration of recent advancements in FGMMs, highlighting their classifications, modeling and computational approaches, applications, challenges, and future prospects. The article includes a detailed analysis of the microstructure, texture, mechanical properties, and their applications in various sectors. It aims to benefit both general readers seeking an understanding of FGMMs and researchers dedicated to advancing this transformative field. © 2025 Elsevier B.V., All rights reserved.