Elastic modulus identification of particles in particulate composite through nanoindentation

The characterization of the constitutive behavior of embedded particles is crucial for the mechanical analysis of functional particulate composites. However, current methods for identifying the elastic parameters through instrumented indentation tests lack robust theoretical foundations. In this study, a series-connection analytical model was proposed to determine the Young's modulus of the embedded particles based on the Oliver-Pharr (OP) model. Additionally, a simplified regression function was derived from the complete analytical model. To validate the accuracy of these methods in estimating the Young's modulus, 2D indentation simulations were conducted. Furthermore, in order to facilitate practical engineering applications, a data processing strategy was developed and implemented to determine the statistical value of the Young's modulus for LiNixMnyCozO2 (NMC) particles in the cathode of a Lithium-ion battery (LIB). Moreover, data obtained from continuous stiffness measurement (CSM) of a single embedded NMC particle were utilized to verify the reliability of the simplified regression function. The simplified regression function was found to possess significant engineering potential in related studies, as it enables a quick and reliable approximation of the Young's modulus of embedded particles without requiring detailed experimental information.