2 resultados para PHASE DISORDER

em Duke University


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The binary A(8)B phase (prototype Pt(8)Ti) has been experimentally observed in 11 systems. A high-throughput search over all the binary transition intermetallics, however, reveals 59 occurrences of the A(8)B phase: Au(8)Zn(dagger), Cd(8)Sc(dagger), Cu(8)Ni(dagger), Cu(8)Zn(dagger), Hg(8)La, Ir(8)Os(dagger), Ir(8)Re, Ir(8)Ru(dagger), Ir(8)Tc, Ir(8)W(dagger), Nb(8)Os(dagger), Nb(8)Rh(dagger), Nb(8)Ru(dagger), Nb(8)Ta(dagger), Ni(8)Fe, Ni(8)Mo(dagger)*, Ni(8)Nb(dagger)*, Ni(8)Ta*, Ni(8)V*, Ni(8)W, Pd(8)Al(dagger), Pd(8)Fe, Pd(8)Hf, Pd(8)Mn, Pd(8)Mo*, Pd(8)Nb, Pd(8)Sc, Pd(8)Ta, Pd(8)Ti, Pd(8)V*, Pd(8)W*, Pd(8)Zn, Pd(8)Zr, Pt(8)Al(dagger), Pt(8)Cr*, Pt(8)Hf, Pt(8)Mn, Pt(8)Mo, Pt(8)Nb, Pt(8)Rh(dagger), Pt(8)Sc, Pt(8)Ta, Pt(8)Ti*, Pt(8)V*, Pt(8)W, Pt(8)Zr*, Rh(8)Mo, Rh(8)W, Ta(8)Pd, Ta(8)Pt, Ta(8)Rh, V(8)Cr(dagger), V(8)Fe(dagger), V(8)Ir(dagger), V(8)Ni(dagger), V(8)Pd, V(8)Pt, V(8)Rh, and V(8)Ru(dagger) ((dagger) = metastable, * = experimentally observed). This is surprising for the wealth of new occurrences that are predicted, especially in well-characterized systems (e.g., Cu-Zn). By verifying all experimental results while offering additional predictions, our study serves as a striking demonstration of the power of the high-throughput approach. The practicality of the method is demonstrated in the Rh-W system. A cluster-expansion-based Monte Carlo model reveals a relatively high order-disorder transition temperature.

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We study networks of nonlocally coupled electronic oscillators that can be described approximately by a Kuramoto-like model. The experimental networks show long complex transients from random initial conditions on the route to network synchronization. The transients display complex behaviors, including resurgence of chimera states, which are network dynamics where order and disorder coexists. The spatial domain of the chimera state moves around the network and alternates with desynchronized dynamics. The fast time scale of our oscillators (on the order of 100ns) allows us to study the scaling of the transient time of large networks of more than a hundred nodes, which has not yet been confirmed previously in an experiment and could potentially be important in many natural networks. We find that the average transient time increases exponentially with the network size and can be modeled as a Poisson process in experiment and simulation. This exponential scaling is a result of a synchronization rate that follows a power law of the phase-space volume.