Process driven self-organisation in laser powder bed fusion of copper coated diamond
Laser powder bed fusion (LPBF) of metal-diamond composites remains fundamentally limited by the extreme thermal gradients imposed by diamond. Here we demonstrate, for the first time, the LPBF of copper-coated diamond revealing previously inaccessible melt-pool behaviour. A narrow conduction-mode process window (150–220 J/mm 3 ) where single tracks exhibit <2.5% porosity and predictable geometric scaling was identified. Systematic single-track mapping reveals a unified thermo-fluidic response described by a vector regression model linking track geometry, porosity, particle assimilation and bonding to energy density. Multi-track experiments uncover six distinct morphological regimes, including a remarkable and previously unreported self-organised sub-micron porous lattice that emerges exclusively within a narrow 113–141 J/mm 3 window. This polygonal network (0.5–2 μm pores; 0.2–0.8 μm ligaments) forms through capillary-driven breakup of transient molten Cu films confined between overlapping tracks. By coupling classical van-der-Waals thin-film instability theory to LPBF specific melt-pool constraints, we derive the Robinson-Arjunan scaling law that predicts the lattice wavelength consistent with experimental observations. At higher energies, lattice coarsening, densification and keyhole-dominated porosity emerge. The results establish LPBF as not merely a consolidation route but a self-organisation platform for metal-diamond systems enabling engineered sub-micron architectures and tunable interfacial morphologies unattainable in monolithic metals. This work opens a new domain in additive manufacturing where feedstock design and melt-pool physics jointly govern hierarchical microstructure formation. • LPBF of copper-coated diamond demonstrated • Narrow conduction window yields micro/nano level porosity. • Self-organised sub-micron porous lattice • Thin-film instability drives polygonal lattice formation. • Robinson–Arjunan scaling law predicts lattice.
Authors
- Manpreet Singh (ORCID: https://orcid.org/0000-0002-8218-328X)
- Martin Appiah
- C.T. Walker
- Aaron Vance (ORCID: https://orcid.org/0000-0002-7770-5370)
- Chameekara T. Wanniarachchi (ORCID: https://orcid.org/0000-0002-9421-2551)
- Arun Arjunan (ORCID: https://orcid.org/0000-0001-5493-0957)
- John Robinson (ORCID: https://orcid.org/0000-0001-6858-2367)
- Ahmad Baroutaji (ORCID: https://orcid.org/0000-0002-4717-1216)
- Abul Arafat (ORCID: https://orcid.org/0000-0003-3232-4184)
- Oluwarotimi Lawal
- Niki Zakeri
Institutions
- University of Wolverhampton (GB)
- Prince Mohammad bin Fahd University (SA)
- Oclaro (United Kingdom) (GB)
- Analytics Engines (United Kingdom) (GB)
Publication Details
- Journal
- Diamond and Related Materials
- Published
- 2026-03-31
- DOI
- https://doi.org/10.1016/j.diamond.2026.113591
- Primary Topic
- Additive Manufacturing Materials and Processes
- Type
- article
- Field-Weighted Citation Impact
- 0.00