Resistive random access memory (ReRAM) has been considered the most promising next-generation nonvolatile memory. In recent years, the switching behavior has been widely reported, and understanding the switching mechanism can improve the stability and scalability of devices. We designed an innovative sample structure for in situ transmission electron microscopy (TEM) to observe the formation of conductive filaments in the Pt/ZnO/Pt structure in real time. The corresponding current-voltage measurements help us to understand the switching mechanism of ZnO film. In addition, high-resolution transmission electron microscopy (HRTEM) and electron energy loss spectroscopy (EELS) have been used to identify the atomic structure and components of the filament/disrupted region, determining that the conducting paths are caused by the conglomeration of zinc atoms. The behavior of resistive switching is due to the migration of oxygen ions, leading to transformation between Zn-dominated ZnO(1-x) and ZnO.
The Forming phenomenon is observed via in situ transmission electron microscopy in the Ag/Ta O /Pt system. The device is switched to a low-resistance state as the dual filament is connected to the electrodes. The results of energy dispersive spectrometer and electron energy loss spectroscopy analyses demonstrate that the filament is composed by a stack of oxygen vacancies and Ag metal.
Resistive random-access memory (ReRAM) has been of wide interest for its potential to replace flash memory in the next-generation nonvolatile memory roadmap. In this study, we have fabricated the Au/ZnO-nanowire/Au nanomemory device by electron beam lithography and, subsequently, utilized in situ transmission electron microscopy (TEM) to observe the atomic structure evolution from the initial state to the low-resistance state (LRS) in the ZnO nanowire. The element mapping of LRS showing that the nanowire was zinc dominant indicating that the oxygen vacancies were introduced after resistance switching. The results provided direct evidence, suggesting that the resistance change resulted from oxygen migration.
Hydrothermal synthesis is commonly used to produce a large area of ZnO nanowires because of its simple and inexpensive process. However, the mechanism of hydrothermal synthesis remains unknown. In this work, zinc acetate and HMTA dissolved in deionized water as a precursor solution were sealed in a liquid cell for observation by in situ transmission electron microscopy. The growth of ZnO nanowires was classified into two steps. The first step was the nucleation and growth of ZnO nanoparticles. The ZnO nanoparticles grew as a result of either isotropic monomer attachment on the {21̅ 1̅ 0} and {01̅ 10} surfaces or coalescence of nanoparticles in the same crystal arrangement. The second step was the anisotropic growth of ZnO nanoparticles into nanowires on the (0001) surface. Because the (0001) surface is Zn-terminated with positive charges that can attract the negatively charged monomers, i.e., [Zn(OH) 4 ] 2− ,the monomers tended to deposit on the (0001) surface, resulting in ZnO nanowires growing along the [0001] direction. Moreover, the growth of ZnO nanowires was identified to be a reactioncontrolled system. The direct observation of the dynamic process sheds light on the hydrothermal synthesis method.
The scaling down of switching media encounters high leakage current in the traditional oxide material based memristors, resulting in high power consumption of chips. Two-dimensional (2D) materials promise an ultimate device scaling down to atomic layer thickness. Herein, black phosphorus (BP) and its self-assembly phosphorous oxide (BP) memristors are constructed, which leverages the high on/off ratio operation of oxides and low leakage current of 2D materials with high performance. The memristors exhibit reproducible and reliable switching characteristics with the on/off ratio >107 and data retention >104 s. Depending on the high reproducibility, basic “AND” and “OR” gates have been constructed on flexible substrates. Moreover, on the basis of the symmetry and linearity of conductance in the devices, the neural network simulation for supervised learning presents an online learning accuracy of 91.4%. This work opens an avenue for future flexible electronics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.