Additive manufacturing of bimetallic structures: Process challenges, interfacial engineering, and emerging intelligent approaches

Bimetallic structures (BS) have emerged as a promising solution for next-generation components requiring location-specific functionality, high structural integrity, and enhanced service performance. Conventional fabrication methods, including welding, brazing, and diffusion bonding, often fail to produce defect-free interfaces owing to thermal mismatches, residual stress accumulation, and the formation of brittle intermetallic compounds (IMCs). In recent years, additive manufacturing (AM) has offered a transformative alternative by enabling precise layer-by-layer deposition and compositional control, facilitating the fabrication of functionally graded and site-tailored bimetallic components. This review provides a comprehensive analysis of the processing-structure-property relationships in AM-fabricated bimetallic structures, emphasizing the mechanisms of residual stress generation, IMC formation, grain boundary misorientation, and interfacial instability. It further evaluates mitigation strategies such as optimized deposition paths, interlayer and diffusion-barrier design, post-deposition treatments, and compositional grading that have demonstrated significant improvements in interfacial bonding strength and mechanical reliability. Moreover, the review discusses recent advances in machine learning (ML) and thermodynamic modeling for their potential to enable predictive process control and intelligent design optimization. Although the industrial adoption of AI/ML-assisted AM remains in its early stages, their integration promises accelerated parameter optimization, defect minimization, and improved reproducibility. By synthesizing current progress and identifying research gaps, this review outlines key opportunities for the scalable, defect-minimized, and data-driven fabrication of high-performance bimetallic additive manufactured structures (BAMS).