Engineers at the Georgia Institute of Technology have conducted one of the first systematic studies of how interface strategies shape part quality in hybrid additive manufacturing that combines wire- and powder-based directed energy deposition (DED). The research, published in npj Advanced Manufacturing, evaluated seven sample configurations and found that while machining surfaces improved density, as-printed interfaces sometimes performed equally well or better in toughness, underscoring the trade-offs facing industrial users.
The experiments paired ER70S-6 mild steel deposited by arc-based DED (DED-arc) with H13 tool steel deposited by laser powder DED (DED-LP). Four interface strategies were tested: mapping the laser standoff plane to the arc surface, applying a least-squares best-fit plane, selecting the maximum surface height as a reference, and machining the arc surface. Each was combined with either a parallel (“with lay”) or perpendicular (“against lay”) orientation for the first powder-based layer. Across these configurations, the DED-LP process’s self-regulating effect reduced surface flatness variation by as much as 55% compared with the underlying DED-arc surface. Yet surface contaminants, such as silicates and oxides inherent to arc welding, lowered density from 99.5% in the machined sample to as low as 92.4% in the unprocessed cases.
Porosity analysis revealed pores between 100 and 425 μm when DED-LP was deposited directly on contaminated surfaces, compared with no large pores in the machined control. Hardness mapping showed sharp transitions from ~650 HV in the H13 layer to ~200 HV in the steel substrate when deposited against lay, versus more gradual transitions when deposited with lay, indicating differences in intermixing. Charpy impact testing highlighted the complexity of these effects.
Absorbed energies ranged from 105 J in the machined sample to 145 J in a non-machined configuration, showing that higher density did not automatically translate to better toughness. Statistical analysis confirmed this: density had only a weak negative correlation with toughness (−0.46), while arc flatness exhibited a strong positive correlation (0.93), meaning rougher arc surfaces increased toughness by boosting the proportion of ductile ER70S-6 in the cross-section.
Directed energy deposition has become a central technique for large-scale metal additive manufacturing. Wire-arc systems provide deposition rates above 200 mm³/s, making them effective for rapid bulk builds, but they create uneven surfaces with millimeter-scale deviations. Powder-based laser systems operate at slower rates around 20 mm³/s, but deliver feature sizes below 0.6 mm and support a broader array of materials, from stainless steels to high-entropy alloys.
A distinctive advantage of DED-LP is its self-regulating effect, which stabilizes layer height by dynamically adjusting powder capture efficiency. Combining these processes—arc for structural bulk and powder for localized detail—offers clear industrial value, but the interface between the two has been poorly understood. Prior studies combining powder bed fusion and DED showed that mismatched roughness and oxidation at the interface can cause defects that undermine hardness and crack resistance. The Georgia Tech study builds on this by directly comparing interface strategies in macro-scale hybrid DED.
The findings suggest that machining or cleaning arc surfaces provides predictable density and geometric uniformity, but is not always essential for mechanical resilience. In several cases, samples deposited on as-printed surfaces with contaminants displayed equal or higher Charpy toughness than the machined control, reflecting the influence of ductile ER70S-6 fractions. For high-value, low-volume parts such as tooling dies, where fatigue life is critical, machining or thorough cleaning may be justified. For lower-value, high-volume production, strategies such as best-fit planes without machining could deliver sufficient performance at reduced cost and cycle time.
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Featured image shows surface form comparison for different testing conditions as evaluated using optical profilometry. Image via Georgia Institute of Technology.
