Thermally Activated Flux Motion in High-Tc-Superconductors

Abstract

The discovery of high-Tc superconductivity by Willer et al. [1] has led to a renewed interest in relaxation phenomena in superconductors. Large non-exponential relaxation effects in the magnetization M(t) of these new superconductors were reported by many investigators [1,2,3,4]. These observations, together with the presence of an irreversibility line which showed a close resemblance with the de Almeida-Thouless line in spin glasses, led to the assumption of a glassy state in high-Tc superconductors and to the suggestion [1,5] that M(t) ~ exp[-(t/τ)β], i.e. a Kohlrausch behaviour. Although this idea appeared quite reasonable for ceramic samples consisting of weakly linked superconducting grains, large relaxation effects were reported also for a single crystal [6] of YBa2Cu3O7−δ . Many authors, among which Rossel and Chaudhari [7], Hagen et al. [8], Yeshurun and Malozemoff [6] and Tinkham [9], pointed out that these relaxation effects might also arise from thermally activated flux motion (TAFM), which was known to occur in conventional superconductors, though on a much smaller scale. Anderson [10] and Beasley et al. [11] showed that in the limit where the activation energy E for TAFM is much larger than kT, the magnetic relaxation follows a logarithmic law. As a Kohlrausch behaviour with β ≪ 1 is difficult to distinguish from a logarithmic time dependence, it has not been possible yet to identify unambiguously the origin of the large magnetic relaxation effects observed in all high-Tc superconductors. Measurements by Rossel, Maeno and Morgenstern [12] of memory effects in the magnetic relaxation seem to indicate that glassy behaviour occurs only in relatively weak magnetic fields (B ≃ 0.2 T) at temperatures close to Tc.KeywordsActivation EnergyCritical Current DensityEpitaxial FilmMagnetic RelaxationRelaxation DataThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.