We report a crossover from chaotic to self-organized critical dynamics in the Portevin-Le Chatelier effect in single crystals of Cu-10% Al in tension as a function of the applied strain rate. For low and intermediate strain rates, we provide an unambiguous support for the existence of chaotic stress drops by showing the existence of a finite correlation dimension and a stable positive Lyapunov exponent. A surrogate data analysis rules out the possibility that the time series is due to a power law stochastic process. As the strain rate is increased, the distributions of stress drops and the time intervals between the stress drops change from peaked to power law type with an exponent close to unity reminiscent of self-organized critical state. A scaling relation compatible with self-organized criticality relates the various exponents. The absence of a finite correlation dimension and a stable positive Lyapunov exponent at the highest strain rate also supports the evidence of crossover.

The collective behavior of dislocations in jerky flow is studied in Al-Mg polycrystalline samples subjected to constant strain rate tests. Complementary dynamical, statistical, and multifractal analyses are carried out on the stress-time series recorded during jerky flow to characterize the distinct spatiotemporal dynamical regimes. It is shown that the hopping type B and the propagating type A bands correspond to chaotic and self-organized critical states, respectively. The crossover between these types of bands is identified by a large spread in the multifractal spectrum. These results are interpreted on the basis of competing scales and mechanisms.

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Jerky flow in dilute alloys, or the Portevin-Le Chatelier effect, is investigated using statistical analysis of time series characterizing the evolution of the plastic activity at distinct scales of observation, namely, the macroscopic scale of stress serrations and a mesoscopic scale pertaining to the accompanying acoustic emission. Whereas the stress serrations display various types of statistical distributions depending on the driving strain rate, including power-law, peaked and bimodal histograms, it is found that acoustic emission is characterized by power-law statistics of event size in all experimental conditions. The latter reflect intermittency and self-organization of plastic activity at a mesoscopic scale. This shift in the observed dynamics when the observation length scale is decreased is discussed in terms of the synchronization of small-scale events.