A multiscale indentation-based technique to correlate acoustic emission with deformation mechanisms in complex alloys

Abstract

Conventional methodologies to link damage evolution with the activation of deformation mechanisms typically require destructive testing and post-mortem analysis. More recently, mechanical testing combined with acoustic emission analysis has provided a method to fingerprint multiple active deformation mechanisms. However, correlating different acoustic emission signals with active deformation sources remains a non-trivial task due to the simultaneous activation of sources during mechanical testing. Here, we demonstrate a multiscale indentation-based technique to isolate dislocation and martensitic transformation sources in the acoustic emission data of a complex alloy. For this purpose, the acoustic emission signals from macro- and microindentation experiments are compared with microscopy and crystallographic analysis of deformed microstructures. A key feature of this method is the selective activation of the martensitic transformation during microindentation, which enables separate fingerprinting of this deformation mechanism. An unsupervised k mean clustering methodology is leveraged to classify acoustic emission waveforms into clusters, which facilitates the detection of shared deformation mechanisms across different tests. The results of this study provide a rapid non-destructive tool to correlate acoustic emission sources with deformation mechanisms in complex alloys.