A Load-Controlled Grid Nanoindentation Approach for Enhanced Microstructure Characterization

Abstract

Nanoindentation is a powerful technique for characterizing material properties at the nanoscale, but the indentation size effect (ISE) can impact accuracy and repeatability. This study investigates the ISE in grid nanoindentation using strain gradient plasticity theory and experimental validation with fused silica and OFC. Results demonstrate that decreasing indentation depth leads to plasticity strengthening, a phenomenon we analyze through dislocation accumulation models. We present a plasticity hardening model that accurately explains the observed ISE curves across different domain configurations. Notably, load-controlled mesh nanoindentation significantly improves the accuracy of the ISE analysis by narrowing the confidence interval from 5% to 0.34% for the conventional model compared to the conventional depth-controlled method. Furthermore, our analysis of OFC reveals a distinct "bending effect" in the ISE trend, with three distinct nano-hardness distribution clusters identified through statistical analysis. This finding shows that grid nanoindentation can characterize the intrinsic micromechanical properties of various microstructural domains.

Keywords: Hardness, Indentation Size Effect, Grid Nanoindentation, Statistical analysis