In this study, acoustic emission (AE) measurements on polycrystalline tin as a function of temperature at different driving rates under compression were carried out. It is shown that there is a definite difference between the acoustic emission characteristics belonging to twinning (low temperatures) as well as to dislocation slip (high temperatures). The stress averaged values of the exponents of the energy probability density functions decreased from $\epsilon$ = 1.45 ± 0.05 (−60 °C) to $\epsilon$ = 1.20 ± 0.15 (50 °C) at a driving rate of $\epsilon =0.15 {\mathrm{s}}^{-1}$, and the total acoustic energy decreased by three orders of magnitude with increasing temperature. In addition, the exponent γ in the scaling relation S_AE~D_AE^γ (S_AE is the area and D_AE is the duration) also shows similar temperature dependence (changing from γ = 1.78 ± 0.08 to γ = 1.35 ± 0.05), illustrating that the avalanche statistics belong to two different microscopic deformation mechanisms. The power law scaling relations were also analyzed, taking into account that the detected signal is always the convolution of the source signal and the transfer function of the system. It was obtained that approximate values of the power exponents can be obtained from the parts of the above functions, belonging to large values of parameters. At short duration times, the attenuation effect of the AE detection system dominates the time dependence, from which the characteristic attenuation time, τ_a, was determined as τ_a ≅ 70 μs.

Results of acoustic emission (AE) measurements, carried out during plastic deformation of polycrystalline Sn samples, are analyzed by the adaptive sequential k-means method. The acoustic avalanches, originating from different sources, are separated on the basis of their spectral properties, that is, sorted into clusters, presented both on the so-called feature space (energy-median frequency plot) and on the power spectral density (PSD) curves. We found that one cluster in every measurement belongs to background vibrations, while the remaining ones are clearly attributed to twinning as well as dislocation slips at −30 °C and 25 °C, respectively. Interestingly, fingerprints of the well-known “ringing” of AE signals are present in different weights on the PSD curves. The energy and size distributions of the avalanches, corresponding to twinning and dislocation slips, show a bit different power-law exponents from those obtained earlier by fitting all AE signals without cluster separation. The maximum-likelihood estimation of the avalanche energy ($\epsilon$) and size ($\tau$) exponents provide $\epsilon =1.57\pm 0.05$ (at −30 °C) and $\epsilon =1.35\pm 0.1$ (at 25 °C), as well as $\tau =1.92\pm 0.05$ (at −30 °C) and $\tau =1.55\pm 0.1$ (at 25 °C). The clustering analysis provides not only a manner to eliminate the background noise, but the characteristic avalanche shapes are also different for the two mechanisms, as it is visible on the PSD curves. Thus, we have illustrated that this clustering analysis is very useful in discriminating between different AE sources and can provide more realistic estimates, for example, for the characteristic exponents as compared to the classical hit-based approach where the exponents reflect an average value, containing hits from the low-frequency mechanical vibrations of the test machine, too.

General form of the well known-relation between the critical stress, necessary to start/finish martensite/austenite formation, and the test temperature is simply and plausibly obtained from our local equilibrium model of phase transformation [1], and compared to the classical forms of the Clausius-Clapeyron relation. Although in general, first of all because of the stress and temperature dependence of the transformation strain, εtr, the above relations are not inevitably linear, in most of the cases linear functions were observed. Using the results of our experiments carried out on single crystalline Cu-11.5wt%Al-5.0wt%Ni samples for the strain stress hysteretic loops at constant temperatures [2], the slopes of these functions are analyzed on the basis of the relations obtained and it is shown that these are different due to different stress dependence of the elastic energy contributions.