The three-dimensional (3D) cross-point array architecture is attractive for future ultra-high-density nonvolatile memory application. A bit-cost-effective technology path toward the 3D integration that requires only one critical lithography step or mask for reducing the bit-cost is demonstrated in this work. A double-layer HfOx-based vertical resistive switching random access memory (RRAM) is fabricated and characterized. The HfOx thin film is deposited at the sidewall of the predefined trench by atomic layer deposition, forming a vertical memory structure. Electrode/oxide interface engineering with a TiON interfacial layer results in nonlinear I-V suitable for the selectorless array. The fabricated HfOx vertical RRAM shows excellent performances such as reset current (<50 μA), switching speed (<100 ns), switching endurance (>10(8) cycles), read disturbance immunity (>10(9) cycles), and data retention time (>10(5) s @ 125 °C).

Neuromorphic computing is an attractive computation paradigm that complements the von Neumann architecture. The salient features of neuromorphic computing are massive parallelism, adaptivity to the complex input information, and tolerance to errors. As one of the most crucial components in a neuromorphic system, the electronic synapse requires high device integration density and low-energy consumption. Oxide-based resistive switching devices have been shown to be a promising candidate to realize the functions of the synapse. However, the intrinsic variation increases significantly with the reduced spike energy due to the reduced number of oxygen vacancies in the conductive filament region. The large resistance variation may degrade the accuracy of neuromorphic computation. In this work, we develop an oxide-based electronic synapse to suppress the degradation caused by the intrinsic resistance variation. The synapse utilizes a three-dimensional vertical structure including several parallel oxide-based resistive switching devices on the same nanopillar. The fabricated three-dimensional electronic synapse exhibits the potential for low fabrication cost, high integration density, and excellent performances, such as low training energy per spike, gradual resistance transition under identical pulse training scheme, and good repeatability. A pattern recognition computation is simulated based on a well-known neuromorphic visual system to quantify the feasibility of the three-dimensional vertical structured synapse for the application of neuromorphic computation systems. The simulation results show significantly improved recognition accuracy from 65 to 90% after introducing the three-dimensional synapses.

The large amount of hysteresis and threshold voltage variation in carbon nanotube transistors impedes their use in highly integrated digital applications. The origin of this variability is elucidated by employing a top-coated, hydrophobic monolayer to passivate bottom-gated devices. Compared to passivating only the supporting substrate, it is found that covering the nanotube channel proves highly effective and robust at improving device-to-device consistency-hysteresis and threshold voltage variation are reduced by an average of 84 and 53%, respectively. The effect of gate and drain-source bias on hysteresis is considered, showing strong dependence that must be accounted for when analyzing the effectiveness of a passivation layer. These results provide both key insight into the origin of variability in carbon nanotube transistors and a promising path for resolving this significant obstacle.

In this paper, we employed Ramen spectroscopy to monitor oxygen movement at the electrode/oxide interface by inserting single-layer graphene (SLG). Raman area mapping and single-point measurements show noticeable changes in the D-band, G-band, and 2D-band signals of the SLG during consecutive electrical programming repeated for nine cycles. In addition, the inserted SLG enables the reduction of RESET current by 22 times and programming power consumption by 47 times. Collectively, our results show that monitoring the oxygen movement by Raman spectroscopy for a resistive random access memory (RRAM) is made possible by inserting a single-layer graphene at electrode/oxide interface. This may open up an important analysis tool for investigation of switching mechanism of RRAM.

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