The basic unit of information in filamentary-based resistive switching memories is physically stored in a conductive filament. Therefore, the overall performance of the device is indissolubly related to the properties of such filament. In this Letter, we report for the first time on the three-dimensional (3D) observation of the shape of the conductive filament. The observation of the filament is done in a nanoscale conductive-bridging device, which is programmed under real operative conditions. To obtain the 3D-information we developed a dedicated tomography technique based on conductive atomic force microscopy. The shape and size of the conductive filament are obtained in three-dimensions with nanometric resolution. The observed filament presents a conical shape with the narrow part close to the inert-electrode. On the basis of this shape, we conclude that the dynamic filament-growth is limited by the cation transport. In addition, we demonstrate the role of the programming current, which clearly influences the physical-volume of the induced conductive filaments.

The success of semiconductor electronics is built on the creation of compact, low-power switching elements that offer routing, logic, and memory functions. The availability of nanoscale optical switches could have a similarly transformative impact on the development of dynamic and programmable metasurfaces, optical neural networks, and quantum information processing. Phase change materials are uniquely suited to enable their creation as they offer high-speed electrical switching between amorphous and crystalline states with notably different optical properties. Their high refractive index has also been harnessed to fashion them into compact optical antennas. Here, we take the next important step by realizing electrically-switchable phase change antennas and metasurfaces that offer strong, reversible, non-volatile, multi-phase switching and spectral tuning of light scattering in the visible and near-infrared spectral ranges. Their successful implementation relies on a careful joint thermal and optical optimization of the antenna elements that comprise an Ag strip that simultaneously serves as a plasmonic resonator and a miniature heating stage.

The semiconductor industry continues to produce ever smaller devices that are ever more complex in shape and contain ever more types of materials. The ultimate sizes and functionality of these new devices will be affected by fundamental and engineering limits such as heat dissipation, carrier mobility and fault tolerance thresholds. At present, it is unclear which are the best measurement methods needed to evaluate the nanometre-scale features of such devices and how the fundamental limits will affect the required metrology. Here, we review state-of-the-art dimensional metrology methods for integrated circuits, considering the advantages, limitations and potential improvements of the various approaches. We describe how integrated circuit device design and industry requirements will affect lithography options and consequently metrology requirements. We also discuss potentially powerful emerging technologies and highlight measurement problems that at present have no obvious solution.

Filamentary-based oxide resistive memory is considered as a disruptive technology for nonvolatile data storage and reconfigurable logic. Currently accepted models explain the resistive switching in these devices through the presence/absence of a conductive filament (CF) that is described as a reversible nanosized valence-change in an oxide material. During device operation, the CF cycles billion of times at subnanosecond speed, using few tens of microamperes as operating current and thus determines the whole device’s performance. Despite its importance, the CF observation is hampered by the small filament size and its minimal compositional difference with the surrounding material. Here we show an experimental solution to this problem and provide the three-dimensional (3D) characterization of the CF in a scaled device. For this purpose we have recently developed a tomography technique which combines the high spatial resolution of scanning probe microscopy with subnanometer precision in material removal, leading to a true 3D-probing metrology concept. We locate and characterize in three-dimensions the nanometric volume of the conductive filament in state-of-the-art bipolar oxide-based devices. Our measurements demonstrate that the switching occurs through the formation of a single conductive filament. The filaments exhibit sizes below 10 nm and present a constriction near the oxygen-inert electrode. Finally, different atomic-size contacts are observed as a function of the programming current, providing evidence for the filament’s nature as a defects modulated quantum contact.

Recent advances in machine learning (ML) offer new tools to extract new insights from large data sets and to acquire small data sets more effectively. Researchers in nanoscience are experimenting with these tools to tackle challenges in many fields. In addition to ML's advancement of nanoscience, nanoscience provides the foundation for neuromorphic computing hardware to expand the implementation of ML algorithms. In this Mini Review, we highlight some recent efforts to connect the ML and nanoscience communities by focusing on three types of interaction: (1) using ML to analyze and extract new insights from large nanoscience data sets, (2) applying ML to accelerate material discovery, including the use of active learning to guide experimental design, and (3) the nanoscience of memristive devices to realize hardware tailored for ML. We conclude with a discussion of challenges and opportunities for future interactions between nanoscience and ML researchers.

No abstract

On the development of flexible electronics, a highly flexible nonvolatile memory, which is an important circuit component for the portability, is necessary. However, the flexibility of existing nonvolatile memory has been limited, e.g. the smallest radius into which can be bent has been millimeters range, due to the difficulty in maintaining memory properties while bending. Here we propose the ultra flexible resistive nonvolatile memory using Ag-decorated cellulose nanofiber paper (CNP). The Ag-decorated CNP devices showed the stable nonvolatile memory effects with 6 orders of ON/OFF resistance ratio and the small standard deviation of switching voltage distribution. The memory performance of CNP devices can be maintained without any degradation when being bent down to the radius of 350 μm, which is the smallest value compared to those of existing any flexible nonvolatile memories. Thus the present device using abundant and mechanically flexible CNP offers a highly flexible nonvolatile memory for portable flexible electronics.

The rapid cadence of MOSFET scaling is stimulating the development of new technologies and accelerating the introduction of new semiconducting materials as silicon alternative. In this context, 2D materials with a unique layered structure have attracted tremendous interest in recent years, mainly motivated by their ultra-thin body nature and unique optoelectronic and mechanical properties. The development of scalable synthesis techniques is obviously a fundamental step towards the development of a manufacturable technology. Metal-organic chemical vapor deposition has recently been used for the synthesis of large area TMDs, however, an important milestone still needs to be achieved: the ability to precisely control the number of layers and surface uniformity at the nano-to micro-length scale to obtain an atomically flat, self-passivated surface. In this work, we explore various fundamental aspects involved in the chemical vapor deposition process and we provide important insights on the layer-dependence of epitaxial MoS film's structural properties. Based on these observations, we propose an original method to achieve a layer-controlled epitaxy of wafer-scale TMDs.