Multibranches of acoustic emission as identifier for deformation mechanisms in additively manufactured 316L stainless steel

The multiple collapse mechanisms of complex materials produced by additive manufacturing (AM) were identified by measurements of the acoustic emission (AE) of the samples under tension. A perfect correlation between AE avalanches and deformation mechanisms is shown to hold in the extremely complex AM metallic materials such as 'as-built' and 'stress-relieved' AM 316L stainless steel (SS). The main criterion is that multibranches of the energy-amplitude scaling in AE proves the coexistence of several deformation mechanisms. The as-built AM 316L SS shows three branches in the energy-amplitude scaling of AE signals, which originate from dislocation movements, twinning-detwinning processes and stress-induced martensitic transformations. After stressrelieving annealing at 600 degrees C for 1 h, two branches remain visible with the dominant deformation mechanisms of dislocation movement and twinning-detwinning. The energy exponent of dislocation avalanches is epsilon = 1.6, which is not affected by the heat treatment. The twinning-detwinning exponent increases from 1.8 to 2.0 after annealing. The avalanche behavior of the martensitic transformation shows power laws with energy exponents near epsilon = 1.65 in stress-induced martensite in as-built AM 316L SS and epsilon = 1.8 for strain-induced martensite in stress-relieved AM 316L SS. This multibranching phenomenon can, thus, be used to identify the mechanisms underlying the deformation of AM-alloys and facilitates online monitoring of deformation processes.

Automated summary

The study identifies multiple collapse mechanisms of complex materials produced by additive manufacturing through measurements of acoustic emission. The correlation between acoustic emission avalanches and deformation mechanisms is shown to hold in complex AM metallic materials. The multibranching phenomenon can be utilized to identify deformation mechanisms in AM alloys and enable online monitoring of deformation processes.