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To understand the mechanism underlying the fast, reversible, phase transformation, information about the atomic structure and defects structures in phase change materials class is key. PCMs are investigated for many applications. These devices are chalcogenide based and use self heating to quickly switch between amorphous and crystalline phases, generating orders of magnitude differences in the electrical resistivity. The main challenges with PCMs have been the large power required to heat above crystallization or melting (for melt-quench amorphization) temperatures and limited reliability due to factors such as resistance drifts of the metastable phases, void formation and elemental segregation upon cycling. Characterization of devices and their unique switching behavior result in distinct material properties affected by the atomic arrangement in the respective phase. TEM is used to study the atomic structure of the metastable crystalline phase. The aim is to correlate the microstructure with results from electrical characterization, building on R vs T measurements on various thicknesses GST thin films. To monitor phase changes in real-time as a function of temperature, thin films are deposited directly onto Protochips carriers. The Protochips heating holders provides controlled temperature changes while imaging in the TEM. These studies can provide insights into how changes occur in the various phase transformations even though the rate of temperature change is much slower than the PCM device operation. Other critical processes such as void formation, grain evolution and the cause of resistance drift can thereby be related to changes in structure and chemistry. Materials characterization is performed using Tecnai F30 and Titan ETEM microscopes, operating at 300kV. Both the microscopes can accept the same Protochips heating holders. The K2 direct electron detector camera equipped with the ETEM allows high-speed video recording (1600 f/s) of structural changes occurring in these materials upon heating and cooling. In this presentation, we will describe the effect of heating thin films of different thickness and composition, the changes in crystallinity and grain size, and how these changes correlate with changes in the electrical properties of the films. We will emphasize that it is always important to use low-dose and/or beam blanking techniques to distinguish changes induced by the beam from those due to the heating or introduction of an electric current. 

Abstract. Concerns about food security under climate change motivate efforts to better understand future changes in crop yields.Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift.However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood.The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools.In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive.A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length.We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive.For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity.Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.