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Femtosecond x-ray diffraction reveals a liquid-liquid phase transition in phase-change materials
(2019)
In phase-change memory devices, a material is cycled between glassy and crystalline states. The highly temperature-dependent kinetics of its crystallization process enables application in memory technology, but the transition has not been resolved on an atomic scale. Using femtosecond x-ray diffraction and ab initio computer simulations, we determined the time-dependent pair-correlation function of phase-change materials throughout the melt-quenching and crystallization process. We found a liquid-liquid phase transition in the phase-change materials Ag4In3Sb67Te26 and Ge15Sb85 at 660 and 610 kelvin, respectively. The transition is predominantly caused by the onset of Peierls distortions, the amplitude of which correlates with an increase of the apparent activation energy of diffusivity. This reveals a relationship between atomic structure and kinetics, enabling a systematic optimization of the memory-switching kinetics.
A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space-time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods