Assessing the mechanical properties of the machining-induced deformation region in Ni-based alloy GH3535 via micropillar compression
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Machining is an essential process in manufacturing high-performance components from Ni-based superalloys, yet it inevitably introduces a shallow surface region of severe plastic deformation with a gradient microstructure. The mechanical properties of this region are critical for component integrity and long-term service performance but cannot be assessed via conventional tensile testing due to its limited volume. This study presents a novel methodology to characterize the depth-dependent mechanical properties of the machining-induced deformation layer in GH3535 alloy. Micropillars with diameters ranging from 1 mu m to 3.5 mu m were fabricated at precise depths from the machined surface using focused ion beam (FIB) milling following controlled electrochemical polishing. Uniaxial micro-compression tests revealed a significant gradient in flow stress, increasing from similar to 1400 MPa in the unaffected bulk to over similar to 2400 MPa in the surface. This strength enhancement is directly correlated with the gradient in microstructure, which shows a transition from coarse grains to severely deformed grains and nano-grains near the surface. Across all subsurface conditions, the micropillars exhibit size-dependent strengthening, with both the magnitude of size effect and the dominant deformation behavior governed by the local microstructural state. The response transitions from dislocation-mediated plasticity in the bulk-like subsurface to grain-boundary- and defect-constrained deformation in the near-surface region, establishing a clear microstructure property relationship within the machined layer. These results demonstrate that micropillar compression provides a robust, quantitative approach for assessing mechanical property gradients in surfacemodified Ni-based alloys and deliver essential data for predictive modelling and machining optimization aimed at controlling surface integrity in high reliability components.










