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

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.