Szczegóły publikacji
Opis bibliograficzny
Powder-based additive manufacturing of functionally graded materials: delivery systems, gradient control, and computational modeling of powder spreading / Łukasz ŁACH, Dmytro SVYETLICHNYY // Powder Technology ; ISSN 0032-5910 . — 2027 — vol. 487 pt. 1 art. no. 123391, s. 1–21. — Bibliogr. s. 17–21, Abstr. — Publikacja dostępna online od: 2026-10-22
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 170974 |
|---|---|
| Data dodania do BaDAP | 2026-11-02 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.powtec.2026.123391 |
| Rok publikacji | 2027 |
| Typ publikacji | przegląd |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Powder Technology |
Abstract
Powder-based additive manufacturing (AM) of functionally graded materials (FGMs) enables unprecedented spatial control of the composition and microstructure of multifunctional components. This review critically examines powder delivery systems, gradient-control techniques, and computational modeling approaches essential for FGM fabrication. The major AM platforms: laser powder bed fusion, directed energy deposition, wire arc additive manufacturing, and electron beam powder bed fusion, are systematically compared for gradient resolution, scalability, and defect propensity. Multi-material powder delivery systems, including multi-hopper feeders, vibratory mechanisms, and real-time blending architectures, are evaluated for gradient fidelity and segregation control. Critical process parameters, including, laser power modulation, scanning strategy, and thermal management are analyzed across platforms, revealing persistent challenges in interfacial bonding and defect formation at dissimilar material boundaries. Metallurgical mechanisms at compositional interfaces — solidification mode transitions, solute redistribution, and brittle intermetallic phase formation — are identified as direct causal drivers of interfacial cracking and delamination, mechanistically distinct from process parameter effects. The emerging potential of high-entropy and medium-entropy alloy systems as FGM base materials is discussed alongside the challenges of thermodynamic database completeness and gradient path planning in high-dimensional composition spaces. Computational frameworks employing discrete element method simulations coupled with computational fluid dynamics, and machine learning approaches, are assessed for predicting powder spreading behavior and gradient formation dynamics. Significant gaps persist in synchronized simulation–experiment pipelines, standardized qualification protocols for spatially varying properties, FGM-specific training datasets, and robust multi-material handling with adaptive feedback. Strategic research priorities spanning data infrastructure, interface-aware alloy design, surrogate modeling, closed-loop process control, and qualification framework development define the critical path towards industrially deployable FGM components.
