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Acoustic emission, AE, spectroscopy identifies dislocation avalanches and crack propagation in high-purity Cu with self-stabilized dislocation networks. These samples were produced by additive manufacturing where thermal gradients form cellular structures. These structures confine avalanches of dislocation movements (∼confined dislocations) with an energy exponent ε = 1.82 ± 0.04. Free dislocation movement follows force-integrated mean-field behavior with ε = 1.6 ± 0.02. Additional crack propagation under tension exhibits a critical failure exponent of ε = 1.45 ± 0.01. These three mechanisms combine to generate sample failure under tension. We use this example to demonstrate how different avalanche mechanisms can be disentangled in AE spectroscopy of additive manufactured metal and how the specific self-stabilized dislocation networks influence these avalanche dynamics. [ABSTRACT FROM AUTHOR]

Intermittent avalanches in a multitude of materials are characterized by acoustic emission, AE, where local events lead to strain relaxations and generate shock waves (so-called "jerks"), which are measured at the sample surface. The bane of this approach is that several avalanche mechanisms may contribute to the same AE spectrum so that a detailed analysis of each individual contribution becomes virtually impossible. It is, hence, essential to develop tools to separate signals from different dynamical processes, such as ferroic domain switching, collapse of porous inclusions, dislocation movements, entanglements, and so on. Particularly, difficult cases are dynamical microstructures in fcc alloys where the AE signal strength is weak. Nevertheless, using profile analysis of AE signals, we can distinguish between two mechanisms, namely, dislocation movements and dynamic entanglements in fcc 316L stainless steel. In this approach, we are able to measure the statistical AE durations of both subsets separately. The fingerprint for superposed avalanches with different durations is seen by the scaling between the energy E and the maximum amplitude A of each avalanche E ∼ Ax with x = 2. While the same exponent x applies for both mechanisms, the scaling relation shows two branches with different absolute energy values. The two mechanisms are then confirmed by separating the energy distributions P(E) ∼ E−ε for the two mechanisms with ε = 1.55 for dislocation movements and ε = 1.36 for entanglements. [ABSTRACT FROM AUTHOR]

The investigation of acoustic emission (AE) reveals mixing of avalanche processes in porous 316L stainless steel. One avalanche mechanism relates to the movement of dislocations, the other to crack propagation. Both mechanisms occur under different external tensions: small tension dislodges dislocations while crack propagation occurs at much higher tension close to the mechanical failure point. In an intermediate overlap regime, both effects occur simultaneously. The avalanche related power laws show a mixing behavior where the higher avalanche exponents form an upper limit for the mixing curve and the lower exponent is approached asymptotically for strong AE signals. The power law probability distribution functions, show a characteristic upwards bend near the crossover between the two mechanisms. The three regimes, namely, the dislocation movement, mixing, and crack propagation, are confirmed by other avalanche characteristics: the sparseness of the AE spectra, the avalanche exponents of energy, amplitude, and duration. Only the crack propagation follows mean field predictions, while the dislocation movements (in confined spaces) deviates significantly from mean field behavior with much greater exponents than those predicted in this approximation. We demonstrate that apparent deviations from scale invariance are, in reality, the result of two superimposed avalanche processes whereby each of them remains scale invariant. The seeming deviations from scale invariance are actually superposition effects. [ABSTRACT FROM AUTHOR]