Effect of surface roughness in the determination of the mechanical properties of material using nanoindentation test

A quantitative model is proposed for the estimation of macro-hardness using nanoindentation tests. It decreases the effect of errors related to the non-reproducibility of the nanoindentation test on calculations of macro-hardness by taking into account the indentation size effect and the surface roughness. The most innovative feature of this model is the simultaneous statistical treatment of all the nanoindentation loading curves. The curve treatment mainly corrects errors in the zero depth determination by correlating their positions through the use of a relative reference. First, the experimental loading curves are described using the Bernhardt law. The fitted curves are then shifted, in order to simultaneously reduce the gaps between them that result from the scatter in the experimental curves. A set of shift depths, Δhc, is therefore identified. The proposed approach is applied to a large set of TiAl6V4 titanium-based samples with different roughness levels, polished by eleven silicon carbide sandpapers from grit paper 80 to 4,000. The result reveals that the scatter degree of the indentation curves is higher when the surface is rougher. The standard deviation of the shift Δhc is linearly connected to the standard deviation of the surface roughness, if the roughness is high-pass filtered in the scale of the indenter (15 µm). Using the proposed method, the estimated macro-hardness for eleven studied TiAl6V4 samples is in the range of 3.5–4.1 GPa, with the smallest deviation around 0.01 GPa, which is more accurate than the one given by the Nanoindentation MTS™ system, which uses an average value (around 4.3 ± 0.5 GPa). Moreover, the calculated Young's modulus of the material is around 136 ± 20 GPa, which is similar to the modulus in literature