Single‐Atom Quantum‐Point Contact Switch Using Atomically Thin Hexagonal Boron Nitride

Nikam, Revannath Dnyandeo; Rajput, Krishn Gopal; Hwang, Hyunsang

doi:10.1002/smll.202006760

Cited by 37 publications

(56 citation statements)

References 40 publications

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“…In such cases, collaborating with other scientists or simply making no claim of endurance would be better than claiming a value without enough supported statistical data. Some papers showed a plot like the one in Figure a to demonstrate correct switching (which confirms that they have the required hardware), but they select not to measure R HRS and R LRS in every cycle. ,− This practice should be avoided, as measuring 10 6 cycles applying PVS with a duration of 1 μs would take only a few minutes or hours; if the device does not switch in 1 μs, it is not useful for most RS technologies.…”

Section: Discussion and Prospectsmentioning

confidence: 99%

Standards for the Characterization of Endurance in Resistive Switching Devices

et al. 2021

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Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to variability and reliability issues, which are usually evaluated through switching endurance tests. However, we note that most studies that claimed high endurances >106 cycles were based on resistance versus cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device. We recommend not to use such a characterization method because it is highly inaccurate and unreliable (i.e., it cannot reliably demonstrate that the device effectively switches in every cycle and it ignores cycle-to-cycle and device-to-device variability). This has created a blurry vision of the real performance of RS devices and in many cases has exaggerated their potential. This article proposes and describes a method for the correct characterization of switching endurance in RS devices; this method aims to construct endurance plots showing one data point per cycle and resistive state and combine data from multiple devices. Adopting this recommended method should result in more reliable literature in the field of RS technologies, which should accelerate their integration in commercial products.

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Section: Discussion and Prospectsmentioning

confidence: 99%

Standards for the Characterization of Endurance in Resistive Switching Devices

et al. 2021

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“…Most of the memristor structures have focused on reducing switching variability because implementing robust, deterministic digital or analog switching behavior is crucial for reliable computational operation. [1,2,[18][19][20][62][63][64][65][66][67][68] Figure 2b shows initial current-voltage (I-V) sweeps for the electroforming process of the fabricated SiO x nanorod memristive neurons as a function of θ. For the cases of 30° and 60°, the electroforming process was completed by using a single low-voltage sweep, where dramatic current drops were observed at 1.0 and 3.0 V, respectively.…”

Section: Electrical Characteristics and Probabilistic Switching Mechanism Of Sio X Nanorod Memristor Neuronsmentioning

confidence: 99%

Controllable SiO_x Nanorod Memristive Neuron for Probabilistic Bayesian Inference

et al. 2021

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Modern artificial neural network technology using a deterministic computing framework is faced with a critical challenge in dealing with massive data that are largely unstructured and ambiguous. This challenge demands the advances of an elementary physical device for tackling these uncertainties. Here, we designed and fabricated a SiOx nanorod memristive device by employing the glancing angle deposition (GLAD) technique, suggesting a controllable stochastic artificial neuron that can mimic the fundamental integrate‐and‐fire signaling and stochastic dynamics of a biological neuron. The nanorod structure provides the random distribution of multiple nanopores all across the active area, capable of forming a multitude of Si filaments at many SiOx nanorod edges after the electromigration process, leading to a stochastic switching event with very high dynamic range (≈5.15 × 1010) and low energy (≈4.06 pJ). Different probabilistic activation (ProbAct) functions in a sigmoid form are implemented, showing its controllability with low variation by manufacturing and electrical programming schemes. Furthermore, as an application prospect, based on the suggested memristive neuron, we demonstrated the self‐resting neural operation with the local circuit configuration and revealed probabilistic Bayesian inferences for genetic regulatory networks with low normalized mean squared errors (≈2.41 × 10‐2) and its robustness to the ProbAct variation.

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“…The h-BN based devices can show volatile threshold switching and nonvolatile memory switching at 1 nA and 1 µA, respectively. Recently Nikam et al [91] pointed out the possibility to control single atomic contact through h-BN based RRAM devices. Wafer-scale single grain Si 2 Te 3 based RRAM devices are reported by Giri et al [87] as shown in Figure 4c.…”

Section: Emerging 2d Materials Based Resistive Switching Devicesmentioning

confidence: 99%

Application of Resistive Random Access Memory in Hardware Security: A Review

Rajendran

Banerjee

Chattopadhyay

et al. 2021

Adv Elect Materials

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today, with the low power embedded devices deployed for sensing, actuating and running intelligent decision-making algorithms. The advancement in wireless communication technologies such as WiFi, Bluetooth low energy, 4G-LTE, LoRaWAN and recently 5G millimeter wave communication coupled with huge boost in the computing capabilities enable these devices to exchange and process data both at the edge and cloud. This intelligent environment is now widely explored as the Internet of Things (IoT). One of the primary concerns in this development is to security. Most of the available protocols and encryption techniques for device authentication and data transfer are purely software measures, thus presenting an opportunity for a determined attacker to bypass those with higher computing power or uncover the secrets through information leakages in physical forms. Furthermore, software-driven security demands high system resources, which is unavailable in resource-constrained IoT devices, therefore necessitating robust hardware security solutions that can be integrated into those devices. On the other hand, globalization of the semiconductor industry supply chain mandates a careful auditing and trust management during the fabrication and system integration process, which can very well benefit from the inherent randomness in the manufacturing processes. Hence, hardware security research today predominantly focuses on designing security primitives that tap onto the manufacturing variations, thereby constructing primitives like true random number generator (TRNG), physical unclonable function (PUF), and cryptographic hash functions.The emerging nonvolatile memory (NVM) devices such as resistive random access memory (RRAM), spin-transfer torque magnetic random-access memory (STT-MRAM), spin-orbit torque magnetic random-access memory (SOT-MRAM), and ferroelectric field-effect transistors (FeFET) are currently explored for building beyond Von Neumann architectures. Among them, RRAM is well established today. It is a two-terminal device commonly known for its metal-insulator-metal structure. This device technology's strength is the available wide range of functional materials that can be engineered for reliable resistive switching. It includes binary transition metal oxides, 2D materials likeNowadays, advancements in the design of trusted system environments are relying on security provided by hardware-based primitives, while replacing resource-hungry software security measures. Emerging nonvolatile memory devices are promising candidates to provide the required hardware security functionalities at very low area-energy-runtime budget. Resistive random access memory (RRAM) offers high-density integration with outstanding performance among the state-of-the-art nonvolatile memory devices. The RRAM device technology is currently getting significant attention from both academia and industry for constructing beyond Von Neumann architectures. This technology's strength is its scalable two-terminal structure, the availability of wide range...

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Single‐Atom Quantum‐Point Contact Switch Using Atomically Thin Hexagonal Boron Nitride

Cited by 37 publications

References 40 publications

Standards for the Characterization of Endurance in Resistive Switching Devices

Standards for the Characterization of Endurance in Resistive Switching Devices

Controllable SiO_x Nanorod Memristive Neuron for Probabilistic Bayesian Inference

Application of Resistive Random Access Memory in Hardware Security: A Review

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Single‐Atom Quantum‐Point Contact Switch Using Atomically Thin Hexagonal Boron Nitride

Cited by 37 publications

References 40 publications

Standards for the Characterization of Endurance in Resistive Switching Devices

Standards for the Characterization of Endurance in Resistive Switching Devices

Controllable SiOx Nanorod Memristive Neuron for Probabilistic Bayesian Inference

Application of Resistive Random Access Memory in Hardware Security: A Review

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Product

Resources

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Controllable SiO_x Nanorod Memristive Neuron for Probabilistic Bayesian Inference