Ultra-low Power Consumption Research Articles

Designing Sb<sub>2</sub>Te<sub>3</sub> heterophase homostructure

<p indent="0mm">Antimony sesquitelluride (Sb₂Te₃) is the most important hosting material for the development of high-performance phase-change memory and brain-like computing technology. This material has two crystalline phases, namely, the metastable cubic rock-salt structure with 1/6 atomic sites taken by randomly distributed vacancies, and the stable rhombohedral phase with layered structures and vacant gaps in hexagonal stacking. The former is an Anderson insulator (AI) and serves as the key ingredient for memory applications, while the latter is a prototypical topological insulator (TI). In this work, we propose a new heterophase homostructure concept for Sb₂Te₃, which in principle could utilize both the topologically protected surface state of the rhombohedral phase and the Anderson localization features of the cubic phase in the bulk interior to achieve ultralow-loss electron transport. To sustain the topological surface state, the edges of the device should be kept in rhombohedral phase with the thickness larger than <sc>~4 nm.</sc> The bulk interior of the sample should be transformed into cubic phase with strong electron localization. According to our density functional theory (DFT) results, the layered atomic building blocks for the two phases are quite similar, though their stacking sequence and degree of structural disorder are different. Thanks to the similar structure and mass density of the two phases, lattice mismatch is not expected to be present at the interface of the heterophase homostructure, superior to heterostructures made of different materials. To lend support to this heterophase homostructure concept, we have prepared a <sc>~500 nm</sc> thick rhombohedral Sb₂Te₃ thin film on a silicon substrate via molecular beam epitaxy (MBE) and made an attempt to induce the phase transition in its bulk interior. A cross-sectional specimen for transmission electron microscopy (TEM) experiments was prepared by a dual beam focused ion beam (FIB) system. The TEM specimen along the electron beam direction was <sc>~80 nm.</sc> For standard TEM observation in short time, the damage brought by electron beam is very limited. However, when the electron beam was focused in an exposure area of <sc>~120 nm</sc> or below inside an electron microscope with a fixed accelerating voltage of <sc>200 keV,</sc> visible structural changes in the Sb₂Te₃ specimen were observed. A gradual structural transition from the stable rhombohedral phase to the metastable cubic phase was observed under extensive electron beam irradiation over <sc>90 min.</sc> The<italic> in situ </italic>high-resolution TEM experiments revealed a clear vacancy disordering induced metastabilization process in the Sb₂Te₃ specimen, where Sb atoms from the atomic stacks diffused into the vacant gap layers in Sb₂Te₃ and eventually triggered a structural change from rhombohedral to cubic Sb₂Te₃. Our DFT calculations corroborated this picture, which showed a systematic increase in total energy as the vacant gap was gradually filled in rhombohedral Sb₂Te₃. The bonding environment of the Sb atoms in the gap for the two phases is entirely different. For the cubic phase, the Sb atoms in the gap are located as the center of octahedral structures with the bond angle of ~90°, which is consistent with the Sb atoms in the original rhombohedral and cubic phase. In stark contrast, the Sb atoms in the gap layers of rhombohedral phase are in a distorted bonding environment with bond angles of both ~110° and ~90°, leading to a large energy penalty for the rhombohedral phase. When the concentration of vacancies in the target layers reached 50%–70%, a change in stacking sequence from rhombohedral to cubic stacking was triggered. The critical vacancy concentration was mainly affected by the degree of compressive strain perpendicular to the target layers. In summary, we have discussed the design concept of a Sb₂Te₃ based heterophase homostructure and demonstrated that this structure could be free of lattice mismatch via <italic>in situ</italic> TEM experiments and DFT calculations. Finally, we provided some guidelines for practical synthesis of Sb₂Te₃ heterophase homostructure samples to explore the interaction between topological physics and Anderson localization of electrons, and to fabricate potential electronic devices of ultra-low power consumption.

Highly sensitive and selective H2S sensors with ultra-low power consumption based on flexible printed carbon-nanotube-thin-film-transistors

Flexible printed carbon-nanotube-thin-film-transistors (CNT-TFTs) with characteristics of low cost, low operating voltage, low power consumption, and signal amplification have great potential for emerging electronics powered by self-powered systems or low-power density thin-film solar cells. In this work, we have fabricated flexible printed CNT-TFTs using the printing process to selectively deposit semiconducting CNTs in device channels as channel materials, printed silver electrodes as side gates, and printed ion gel as the dielectric layer. The as-prepared TFTs exhibited an extremely high sensitivity to H2S (up to 1565% ppm-1) at room temperature (25 ℃) and the relative humidity (RH) of 5%, excellent signal amplification (response increased from 1% to 4045.5% towards 2 ppm H2S), ultra-low working power consumption (1.03 nW under 2 ppm H2S), excellent selectivity, fast response/recovery time (10 s/26 s) and great mechanical flexibility (stable after 10,000 times bending with 5 mm radius). The outstanding improvement of sensor characteristics was related to the enrichment and absorption of H2S by ionic liquids, and the resistor-mode device's response to 2 ppm H2S increased from ~1% to 80% after the device channel was covered by ion gel. To the best of our knowledge, our H2S sensors demonstrated the recorded low power consumption (1.03 nW) and high response (4045.4%) when exposed to 2 ppm H2S at room temperature, making our sensors a promising candidate for portable applications in gas detection.

Designing Conductive‐Bridge Phase‐Change Memory to Enable Ultralow Programming Power (Adv. Sci. 8/2022)

Conductive-Bridge Phase-Change Memory In article number 2103478, Ming Xu, Xiangshui Miao, Wei Zhang, En Ma, and co-workers design a conductive-bridge phase-change memory, forming self-patterned heterogeneous networks of crystalline and amorphous nanodomains. The switching proceeds via forming/breaking nanobridges that link up the crystalline domains into a conductive path, resulting in ultralow power consumptions for memory programming.

All-Electrical Control of Compact SOT-MRAM: Toward Highly Efficient and Reliable Non-Volatile In-Memory Computing.

Two-dimensional van der Waals (2D vdW) ferromagnets possess outstanding scalability, controllable ferromagnetism, and out-of-plane anisotropy, enabling the compact spintronics-based non-volatile in-memory computing (nv-IMC) that promises to tackle the memory wall bottleneck issue. Here, by employing the intriguing room-temperature ferromagnetic characteristics of emerging 2D Fe3GeTe2 with the dissimilar electronic structure of the two spin-conducting channels, we report on a new type of non-volatile spin-orbit torque (SOT) magnetic tunnel junction (MTJ) device based on Fe3GeTe2/MgO/Fe3GeTe2 heterostructure, which demonstrates the uni-polar and high-speed field-free magnetization switching by adjusting the ratio of field-like torque to damping-like torque coefficient in the free layer. Compared to the conventional 2T1M structure, the developed 3-transistor-2-MTJ (3T2M) cell is implemented with the complementary data storage feature and the enhanced sensing margin of 201.4% (from 271.7 mV to 547.2 mV) and 276% (from 188.2 mV to 520 mV) for reading “1” and “0”, respectively. Moreover, superior to the traditional CoFeB-based MTJ memory cell counterpart, the 3T2M crossbar array architecture can be executed for AND/NAND, OR/NOR Boolean logic operation with a fast latency of 24 ps and ultra-low power consumption of 2.47 fJ/bit. Such device to architecture design with elaborated micro-magnetic and circuit-level simulation results shows great potential for realizing high-performance 2D material-based compact SOT magnetic random-access memory, facilitating new applications of highly reliable and energy-efficient nv-IMC.

Centimeter-Sized Stable Zero-Dimensional Cs3Bi2I9 Single Crystal for Mid-Infrared Lead-Free Perovskite Photodetector

The detection of broadband spectroscopy is a huge challenge for modern optoelectronics, especially for extremely high- or low-energy photons. For metal halide perovskites significant progress has been made in high-energy photons such as X-rays, but there is little exploration of the perovskites in the high-performance detection of low-energy photons, especially mid- or far-infrared photons. Most infrared photodetectors suffer large dark currents, and perovskite photodetectors’ performances are significantly limited by ion migration. Here, a facile solution evaporation method is developed to grow a centimeter-scale zero-dimensional (0D), lead-free perovskite Cs3Bi2I9 single crystal for high-performance mid-infrared photodetectors with ultralow dark current drifts. The 0D Cs3Bi2I9 perovskite single crystal (PSC) photodetector shows an ultralow dark current drift (1.67 × 10–17 A cm–2 V–1 s–1, 9 orders of magnitude smaller than that of MAPbI3) and ultralow power consumption (smaller than 1 pA at 1 V bias) for greatly inhibited ion migration. The photodetector achieves effective photodetection from the ultraviolet to the mid-infrared (from 343 to 4000 nm) at room temperature based on the photoelectric and photobolometric effects with the best responsivity of 3.15 mA/W and detectivity of 8.7 × 108 jones at the wavelength of 343 nm at 0.033 mW/cm2. This work opens a door for low-dimensional perovskite-based mid-infrared detectors and provides a new path for the development of infrared perovskite photonics.

Graphene Porous Foams for Capacitive Pressure Sensing

Flexible pressure sensors are an attractive area of research due to their potential applications in biomedical sensing and wearable devices. Among flexible and wearable pressure sensors, capacitive pressure sensors show significant advantages, owing to their potential low cost, ultra-low power consumption, tolerance to temperature variations, high sensitivity, and low hysteresis. In this work, we develop capacitive flexible pressure sensors using graphene based conductive foams. In these soft and porous conductive foams, graphene is present either as a coating of the pores in the foam, inside the structure of the foam itself, or a combination of both. We demonstrate that they are durable and sensitive at low pressure ranges (<10 kPa). Systematic analysis of the different pressure sensors revealed that the porous foams with graphene coated pores are the most sensitive (~ 0.137/kPa) in the pressure range 0-6kPa. Additionally, we achieved very low limit of detection of 0.14 Pa, which is one of the lowest values reported. Further, we demonstrated the potential applications of our pressure sensors by showing detection of weak physiological signals of the body. Our work is highly relevant for research in flexible pressure sensors based on conductive foams as it shows the impact of different ways of incorporating conductive material on performance of pressure sensors.

An Ultra-Low Power Threshold Voltage Variable Artificial Retina Neuron

An artificial retina neuron is proposed and implemented by CMOS technology. It can be used as an image sensor in the Artificial Intelligence (AI) field with the benefit of ultra-low power consumption. The artificial neuron can generate signals in spike shape with pre-designed frequencies under different light intensities. The power consumption is reduced by removing the film capacitor. The comparator is adopted to improve the stability of the circuit, and the power consumption of the comparator is optimized. The power consumption of the proposed CMOS neuron circuit is suppressed. The ultra-low-power artificial neuron with variable threshold shows a frequency range of 0.8–80 kHz when the input current is varied from 1 pA to 150 pA. The minimum DC power is 35 pW when the input current is 5 pA. The minimum energy of the neuron is 3 fJ. The proposed ultra-low-power artificial retina neuron has wide potential applications in the field of AI.

New Era of Electroceuticals: Clinically Driven Smart Implantable Electronic Devices Moving towards Precision Therapy.

In the name of electroceuticals, bioelectronic devices have transformed and become essential for dealing with all physiological responses. This significant advancement is attributable to its interdisciplinary nature from engineering and sciences and also the progress in micro and nanotechnologies. Undoubtedly, in the future, bioelectronics would lead in such a way that diagnosing and treating patients’ diseases is more efficient. In this context, we have reviewed the current advancement of implantable medical electronics (electroceuticals) with their immense potential advantages. Specifically, the article discusses pacemakers, neural stimulation, artificial retinae, and vagus nerve stimulation, their micro/nanoscale features, and material aspects as value addition. Over the past years, most researchers have only focused on the electroceuticals metamorphically transforming from a concept to a device stage to positively impact the therapeutic outcomes. Herein, the article discusses the smart implants’ development challenges and opportunities, electromagnetic field effects, and their potential consequences, which will be useful for developing a reliable and qualified smart electroceutical implant for targeted clinical use. Finally, this review article highlights the importance of wirelessly supplying the necessary power and wirelessly triggering functional electronic circuits with ultra-low power consumption and multi-functional advantages such as monitoring and treating the disease in real-time.

Control of ferroelectric and ferromagnetic domains in BiFe0.9Co0.1O3 thin films by utilizing trailing fields

The effect of in-plane “trailing fields” caused by the scanning motion of a biased cantilever on ferroelectric and ferromagnetic domains of a BiFe0.9Co0.1O3 thin film was investigated. BiFe0.9Co0.1O3 is applicable for an ultra-low power consumption nonvolatile magnetic memory device because the magnetization is reversible by an electric field. In-plane polarization reversal was induced by the trailing field, which was approximately 1/6 of the electric field necessary for the polarization reversal using planar gap electrodes. The in-plane polarization direction of striped domain variants can be reversed by changing the slow scan direction of the cantilever keeping the bias voltage.

Design Aspects of a Single-Output Multi-String WLED Driver Using 40 nm CMOS Technology

This work presents various essential features and design aspects of a single-inductor, common-output, and multi-string White Light Emitting Diode (WLED) driver for low-power portable devices. High efficiency is one of the main features of such a device. Here, the efficiency improvement is achieved by selecting the proper arrangement of WLEDs and a proper sensing-circuit technique to determine the minimum, real-time, needed output voltage. This minimum voltage necessary to activate all WLEDs depends on the number of strings and the forward voltage drops among the WLEDs. Advanced CMOS technology is advantageous in mixed-signal environments such as WLED drivers. However, this process suffers from low on-resistance, which degrades the accuracy of the current sinks. To accommodate the above features and mitigate the low node process issue, a boost-converter that is single output with a load of a three-string arrangement, with 6 WLEDs each, is presented. The designed driver has an input voltage range of 3.2–4.2V. The proposed solution is realized with ultra-low power consumption circuits and verified using ADS tools utilizing 40 nm 1P9M TSMC CMOS technology. An inter-string current accuracy of 0.2% and peak efficiency of 91% are achieved with an output voltage up to 25 V. The integrated WLED driver circuitry enables a high switching frequency of 1MHz and reduces the passive elements’ size in the power stage.

Wafer-level hermetically sealed silicon photonic MEMS

The emerging fields of silicon (Si) photonic micro–electromechanical systems (MEMS) and optomechanics enable a wide range of novel high-performance photonic devices with ultra-low power consumption, such as integrated optical MEMS phase shifters, tunable couplers, switches, and optomechanical resonators. In contrast to conventional SiO 2 -clad Si photonics, photonic MEMS and optomechanics have suspended and movable parts that need to be protected from environmental influence and contamination during operation. Wafer-level hermetic sealing can be a cost-efficient solution, but Si photonic MEMS that are hermetically sealed inside cavities with optical and electrical feedthroughs have not been demonstrated to date, to our knowledge. Here, we demonstrate wafer-level vacuum sealing of Si photonic MEMS inside cavities with ultra-thin caps featuring optical and electrical feedthroughs that connect the photonic MEMS on the inside to optical grating couplers and electrical bond pads on the outside. We used Si photonic MEMS devices built on foundry wafers from the iSiPP50G Si photonics platform of IMEC, Belgium. Vacuum confinement inside the sealed cavities was confirmed by an observed increase of the cutoff frequency of the electro-mechanical response of the encapsulated photonic MEMS phase shifters, due to reduction of air damping. The sealing caps are extremely thin, have a small footprint, and are compatible with subsequent flip-chip bonding onto interposers or printed circuit boards. Thus, our approach for sealing of integrated Si photonic MEMS clears a significant hurdle for their application in high-performance Si photonic circuits.

Outstanding phase-change behaviors of GaGeSbTe material for phase-change memory application

In this paper, GaGST films with different Ga contents were prepared by co-sputtering of Ge3.4Sb2.3Te5 target and Ga2Ge3.8Sb2.3Te5 target to obtain a high-speed and low-power phase change material. The present data emphasize that compared with Ge2Sb2Te5, Ga0.4Ge3.5Sb2.3Te5 exhibits a higher crystallization temperature(193 °C) and better data retention ability (108 °C for 10 years). XPS results show that Ga and Sb combine to form GaSb, and it reduces the density change after crystallization of GaGST material to 2.7%. At the same time, it has a smaller grain size(∼5–10 nm) and a lower drift(<0.059). Furthermore, the behavior of reversible phase change can be realized by a 6 ns width electric pulse, and the power consumption under the action of this pulse only needs an ultra-low power consumption of 0.16pJ. The results of materials and devices show that Ga0.4Ge3.5Sb2.3Te5 is a very suitable material for phase-change memory(PCM).

Highly Sensitive and Flexible Capacitive Pressure Sensor Based on a Dual-Structured Nanofiber Membrane as the Dielectric for Attachable Wearable Electronics

Wearable devices are an indispensable part of modern life, and flexible capacitive pressure sensors as their luminous subset have assumed a significant role in this day and age owing to ultralow power consumption. In recent years, a fierce debate as well as numerous studies have been conducted to improve the sensitivity of capacitive pressure sensors, but a vital challenge of the mass production of a highly sensitive sensor by a low-cost method still remains. In this paper, to meet industrial demands, we propose a simple method to fabricate sandwich-structured capacitive pressure sensors on an industrial scale and at low cost; as the electrospinning collector, stainless steel screens with regular patterns and structures were utilized to gain the dielectric with both external microstructure and internal pores (dual structure). The prepared pressure sensor is composed of a thermoplastic-urethane electrospun nanofiber film, as a dielectric, in the middle and two conductive woven fabrics on the upper and lower sides as electrodes. Benefiting from the prolific air in the dielectric layer, the designed sensor demonstrates outstanding sensing performance, such as high sensitivity (0.28 kPa–1) in the low-pressure region (0–2 kPa), fast response/relaxation time (65/78 ms), and high-grade durability (1000 cycles). Moreover, the produced pressure sensor is employed for not only detecting human limb movements and object grasping but also detecting pressure distribution in sensor array state, so demonstrating the application potential in attachable wearable electronics.

Ultralow Power Consumption and Large Dynamic Range Synaptic Transistor Based on α-In2Se3 Nanosheets

Ultralow Power Consumption and Large Dynamic Range Synaptic Transistor Based on α-In₂Se₃ Nanosheets

Ferromagnetic resonance and magnetization switching characteristics of perpendicular magnetic tunnel junctions with synthetic antiferromagnetic free layers

Perpendicular magnetic tunnel junctions (pMTJs) with synthetic antiferromagnetic (SAF) free layers have attracted much interest for applications on spintronic memory devices with ultrafast speed and ultralow energy. In this work, SAF free layer pMTJs (SAF-pMTJs) were designed and fabricated, in which a Ru/Ta bilayer spacer is used to form the SAF structure. We first characterized the magnetization dynamics of the SAF free layer by using ferromagnetic resonance and found that the Gilbert damping constant of the SAF free layer is around 0.019. Then, in device level studies that span from 900 nm down to 200 nm lateral size, we observed a transition of the SAF free layer from a preferred antiparallel to parallel magnetic configuration at small device sizes, which can be explained by the increased dipole interaction. The impact of the operating current was also investigated. We report an extraordinarily strong dependence, up to 144.1 kOe per A/μm2, of the offset field on the applied current, suggesting an electric-field modulation on the interlayer exchange coupling of the SAF free layer. These results will be instructive to improve the understanding of material properties and device performance of SAF-pMTJs for ultrafast, ultralow-power consumption spintronic devices.

Photonic synapses with ultralow energy consumption for artificial visual perception and brain storage

The human visual system, dependent on retinal cells, can be regarded as a complex combination of optical system and nervous system. Artificial retinal system could mimic the sensing and processing function of human eyes. Optically stimulated synaptic devices could serve as the building blocks for artificial retinas and subsequent information transmission system to brain. Herein, photonic synaptic transistors based on polycrystalline MoS₂, which could simulate human visual perception and brain storage, are presented. Moreover, the photodetection range from visible light to near-infrared light of MoS₂ multilayer could extend human eyes’ vision limitation to near-infrared light. Additionally, the photonic synaptic transistor shows an ultrafast speed within 5 μs and ultralow power consumption under optical stimuli about 40 aJ, several orders of magnitude lower than biological synapses (50 ms and 10 fJ). Furthermore, the backgate control could act as emotional modulation of the artificial brain to enhance or suppress memory function, i.e. the intensity of photoresponse. The proposed carrier trapping/detrapping as the main working mechanism is presented for the device. In addition, synaptic functionalities including short synaptic plasticity, long synaptic plasticity and paired-pulse facilitation could be successfully simulated based on the prepared device. Furthermore, the large difference between short synaptic plasticity and long synaptic plasticity reveals the better image pre-processing function of the prepared photonic synapses. The classical Pavlovian conditioning associated with the associative learning is successfully implemented as well. Therefore, the efficient and rich functionalities demonstrate the potential of the MoS₂ synaptic device that integrates sensing-memory-preprocessing capabilities for realizing artificial neural networks with different emotions that mimic human retina and brain.

Spiking Sparse Recovery With Non-Convex Penalties

Sparse recovery (SR) based on spiking neural networks has been shown to be computationally efficient with ultra-low power consumption. However, existing spiking-based sparse recovery (SSR) algorithms are designed for the convex <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> -norm regularized SR problem, which often underestimates the true solution. This paper proposes an adaptive version of SSR, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , A-SSR, to optimize a class of non-convex regularized SR problems and analyze its global asymptotic convergence. The superiority of A-SSR is validated with synthetic simulations and real applications, including image reconstruction and face recognition. Furthermore, it is shown that the proposed A-SSR essentially improves the recovery accuracy by avoiding systematic underestimation and obtains over 4 dB PSNR improvement in image reconstruction quality and around 5% improvement in recognition confidence. At the same time, the proposed A-SSR maintains energy efficiency in hardware implementation. When implemented on the neuromorphic Loihi chip, our method consumes only about 1% of the power of the iterative solver FISTA, enabling applications under energy-constrained scenarios.

Optoelectronic neuromorphic devices and their applications

Conventional computers based on the von Neumann architecture are inefficient in parallel computing and self-adaptive learning, and therefore cannot meet the rapid development of information technology that needs efficient and high-speed computing. Owing to the unique advantages such as high parallelism and ultralow power consumption, bioinspired neuromorphic computing can have the capability of breaking through the bottlenecks of conventional computers and is now considered as an ideal option to realize the next-generation artificial intelligence. As the hardware carriers that allow the implementing of neuromorphic computing, neuromorphic devices are very critical in building neuromorphic chips. Meanwhile, the development of human visual systems and optogenetics also provides a new insight into how to study neuromorphic devices. The emerging optoelectronic neuromorphic devices feature the unique advantages of photonics and electronics, showing great potential in the neuromorphic computing field and attracting more and more attention of the scientists. In view of these, the main purpose of this review is to disclose the recent research advances in optoelectronic neuromorphic devices and the prospects of their practical applications. We first review the artificial optoelectronic synapses and neurons, including device structural features, working mechanisms, and neuromorphic simulation functions. Then, we introduce the applications of optoelectronic neuromorphic devices particularly suitable for the fields including artificial vision systems, artificial perception systems, and neuromorphic computing. Finally, we summarize the challenges to the optoelectronic neuromorphic devices, which we are facing now, and present some perspectives about their development directions in the future.

Efficient designs of high-speed combinational circuits and optimal solutions using 45-degree cell orientation in QCA nanotechnology

To fabricate digital logic circuits withsmaller size, ultra-low power consumption, high-speed, and reliable operation at high frequencies like THz. The quantum-dot cellular automata (QCA) are a novel nanoelectronics nano-technology. It is considered a resolution to the scaling problems in CMOS and VLSI technology. This paper will implement nanoscale-based adder, subtractor, and 1-bit comparator structures using QCA nanotechnology. It is being researched as a possible replacement for traditional CMOS technology. In this paper, we have proposed and investigated the cell rotation problem and provided optimal solutions of 45-degree cell arrangement with its appropriate position. The proposed QCA design effectively reduces the cell count and required area inμm2propagation delay and the complexity of the circuits. The proposed simulation-results of a two-input adder, subtractor, and 1-bit comparator architecture were examined and compared with existing designs using the QCADesigner-E tool. The proposed adder, subtractor and 1-bit comparators occupy design area of 21240.00 nm2 (0.02 um2), 21182.00 nm2 (0.02 um2) and 31284.00 nm2 (0.03 um2) respectively. The observed latency is 0.5 clock cycles for adder and sub, and 0.75 clock cycles for 1-bit comparators. In terms of used equal four-dots QCA cell of 21 cells for adder, sub, and 33 cells for 1-bit comparators circuits with applied synchronized QCA clock cycles methodology. The presented design in this paper will be useful for designing and explaining nano-devices for usage in various nanotechnology applications.

Memristive brain-like computing

With the rapid development of deep learning, the current rapid update and iteration of intelligent algorithms put forward high requirements for hardware computing power. Limited by the exhaustion of Moore’s law and the von Neumann bottleneck, the traditional CMOS integration cannot meet the urgent needs of hardware computing power improvement. The utilization of new device memristors to construct a neuromorphic computing system can realize the integration of storage and computing, and has the characteristics of extremely high parallelism and ultra-low power consumption. In this work, the device structure and physical mechanism of mainstream memristors are reviewed in bottom-to-top order firstly, and their performance characteristics are compared and analyzed. Then, the recent research progress of memristors to realize artificial neurons and artificial synapses is introduced, including the simulation of specific circuit forms and neuromorphic functions. Secondly, in this work, the structural forms of passive and active memristive arrays and their applications in neuromorphic computing, including neural network-based handwritten digits and face recognition, are reviewed. Lastly, the current challenges of memristive brain-like computing from the bottom to the top, are summarized and the future development of this field is also prospected.