CMOS-Integrated Ternary Content Addressable Memory using Nanocavity CBRAMs for High Sensing Margin.

The development of data-intensive computing methods imposes a significant load on the hardware, requiring progress toward a memory-centric paradigm. Within this context, ternary content-addressable memory (TCAM) can become an essential platform for high-speed in-memory matching applications of large data vectors. Compared to traditional static random-access memory (SRAM) designs, TCAM technology using non-volatile resistive memories (RRAMs) in two-transistor-two-resistor (2T2R) configurations presents a cost-efficient alternative. However, the limited sensing margin between the match and mismatch states in RRAM structures hinders the potential of using memory-based TCAMs for large-scale architectures. Therefore, this study proposes a practical device engineering method to improve the switching response of conductive-bridge memories (CBRAMs) integrated with existing complementary metal-oxide-semiconductor (CMOS) transistor technology. Importantly, this work demonstrates a significant improvement in memory window reaching 1.87 × 107 by incorporating nanocavity arrays and modifying electrode geometry. Consequently, TCAM cells using nanocavity-enhanced CBRAM devices can exhibit a considerable increase in resistance ratio up to 6.17 × 105, thereby closely approximating the sensing metrics observed in SRAM-based TCAMs. The improved sensing capability facilitates the parallel querying of extensive data sets. TCAM array simulations using experimentally verified device models indicate a substantial sensing margin of 65× enabling a parallel search of 2048 bits.

A Bioinspired Stretchable Sensory-Neuromorphic System.

Conventional stretchable electronics that adopt a wavy design, a neutral mechanical plane, and conformal contact between abiotic and biotic interfaces have exhibited diverse skin-interfaced applications. Despite such remarkable progress, the evolution of intelligent skin prosthetics is challenged by the absence of the monolithic integration of neuromorphic constituents into individual sensing and actuating components. Herein, a bioinspired stretchable sensory-neuromorphic system, comprising an artificial mechanoreceptor, artificial synapse, and epidermal photonic actuator is demonstrated; these three biomimetic functionalities correspond to a stretchable capacitive pressure sensor, a resistive random-access memory, and a quantum dot light-emitting diode, respectively. This system features a rigid-island structure interconnected with a sinter-free printable conductor, which is optimized by controlling the evaporation rate of solvent (≈160% stretchability and ≈18 550 S cm-1 conductivity). Devised design improves both areal density and structural reliability while avoiding the thermal degradation of heat-sensitive stretchable electronic components. Moreover, even in the skin deformation range, the system accurately recognizes various patterned stimuli via an artificial neural network with training/inferencing functions. Therefore, the new bioinspired system is expected to be an important step toward implementing intelligent wearable electronics.

Electromagnetic Analysis of Vertical Resistive Memory with a Sub-nm Thick Electrode.

Resistive random access memories (RRAMs) are a type of resistive memory with two metal electrodes and a semi-insulating switching material in-between. As the persistent technology node downscaling continues in transistor technologies, RRAM designers also face similar device scaling challenges in simple cross-point arrays. For this reason, a cost-effective 3D vertical RRAM (VRRAM) structure which requires a single pivotal lithography step is attracting significant attention from both the scientific community and the industry. Integrating an extremely thin plane electrode to such a structure is a difficult but necessary step to enable high memory density. In addition, experimentally verifying and modeling such devices is an important step to designing RRAM arrays with a high noise margin, low resistive-capacitive (RC) delays, and stable switching characteristics. In this work, we conducted an electromagnetic analysis on a 3D vertical RRAM with atomically thin graphene electrodes and compared it with the conventional metal electrode. Based on the experimental device measurement results, we derived a theoretical basis and models for each VRRAM design that can be further utilized in the estimation of graphene-based 3D memory at the circuit and architecture levels. We concluded that a 71% increase in electromagnetic field strength was observed in a 0.3 nm thick graphene electrode when compared to a 5 nm thick metal electrode. Such an increase in the field led to much lower energy consumption and fluctuation range during RRAM switching. Due to unique graphene properties resulting in improved programming behavior, the graphene-based VRRAM can be a strong candidate for stacked storage devices in new memory computing platforms.

Graphene-Edge Electrode on a Cu-Based Chalcogenide Selector for 3D Vertical Memristor Cells.

Resistive memristors are considered to be key components in the hardware implementation of complex neuromorphic networks because of their simplicity, compactness, and manageable power dissipation. However, breakthroughs with respect to both the selector material technology and the bit-cost-effective three-dimensional (3D) device architecture are necessary to provide sufficient device density while maintaining the advantages of a two-terminal device. Despite substantial progress in the scaling of the memristor devices, the scaling potential of the selector materials remains unclear. A majority of the selector materials are unlikely to form conductive filaments, and the effect of the highly concentrated electrical fields on such materials is not well understood. In this study, the atomically thin graphene edge in a 3D vertical memory architecture is utilized to study the effect of highly focused electrical fields on a CuGeS chalcogenide selector layer. We demonstrate that additional interface resistance can improve the nonlinearity and reduce leakage current by almost three orders of magnitude; however, even a relatively low Cu+ ion density can adversely affect leakage because of the highly asymmetric electrode configuration. This study presents a meaningful step toward understanding the characteristics of mobile ions in solid chalcogenide electrolytes and the potential for ultrascaled selector devices.