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Chalcogenide phase-change materials (PCMs) are regarded as the leading candidate for storage-class non-volatile memory and neuro-inspired computing. Recently, using the $TiTe_2$/$Sb_2Te_3$ material combination, a new framework - phase-change heterostructure (PCH), has been developed and proved to effectively suppress the noise and drift in electrical resistance upon memory programming, largely reducing the inter-device variability. However, the atomic-scale structural and chemical nature of PCH remains to be fully understood. In this work, we carry out thorough ab initio simulations to assess the bonding characteristics of the PCH. We show that the $TiTe_2$ crystalline nanolayers do not chemically interact with the surrounding $Sb_2Te_3$, and are stabilized by strong covalent and electrostatic Ti-Te interactions, which create a prohibitively high barrier for atomic migrations along the pulsing direction. We also find significant contrast in computed dielectric functions in the PCH, suggesting possible optical applications of this class of devices. With the more confined space and therefore constrained phase transition compared to traditional PCM devices, the recently introduced class of PCH-based devices may lead to improvements in phase-change photonic and optoelectronic applications with much lower stochasticity during programming.
Ge2Sb2Te5 and related phase change materials are highly unusual in that they can be readily transformed between amorphous and crystalline states using very fast melt, quench, anneal cycles, although the resulting states are extremely long lived at am
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We have investigated the electronic structure and the Fermi surface of SnO using density functional theory (DFT) calculations within recently proposed exchange-correlation potential (PBE+mBJ) at ambient conditions and high pressures up to 19.3 GPa wh
Changing the interlayer exchange coupling between magnetic layers in-situ is a key issue of spintronics, as it allows for the optimization of properties that are desirable for applications, including magnetic sensing and memory. In this paper, we uti