Ultra-low Energy Consumption Research Articles

Ionic liquid gating control of planar Hall effect in Ni80Fe20/HfO2 heterostructures**Project supported by the National Natural Science Foundation of China (Grant Nos. 51671099 and 11974149), the Open Foundation Project of Jiangsu Key Laboratory of Thin Films (Grant No. KJS1745), the Program for Changjiang Scholars and Innovative Research Team in University, China (Grant No. IRT-16R35), and the Fundamental Research Funds for

We report a tunable transverse magnetoresistance of the planar Hall effect (PHE), up to 48% in the Ni80Fe20/HfO2 heterostructures. This control is achieved by applying a gate voltage with an ionic liquid technique at ultra-low voltage, which exhibits a gate-dependent PHE. Moreover, in the range of 0-V to 1-V gate voltage, transverse magnetoresistance of PHE can be continuously regulated. Ferromagnetic resonance (FMR) also demonstrates the shift of the resonance field at low gate voltage. This provides a new method for the design of the electric field continuous control spintronics device with ultra-low energy consumption.

Zero-power optoelectronic synaptic devices

Abstract Synaptic devices for neuromorphic computing have been recently on the fast track of development. One of the most prominent features of synaptic devices is their potentially ultra-low energy consumption. However, relatively large energy has always been consumed to induce the postsynaptic current (PSC) of a synaptic device up to now. Here, we demonstrate that synaptic devices can work without electrical power supply by taking advantage of the photovoltaic effect during optical stimulation. The optoelectronic synaptic devices with zero-power consumption are fabricated by using the hybrid structure of organometal halide perovskite and silicon nanocrystals (Si NCs). A series of important synaptic functionalities including excitatory PSC, paired-pulse facilitation (PPF), spike-number-dependent plasticity (SNDP), spike-rate-dependent plasticity (SRDP) and dynamic filtering are all successfully mimicked. In addition, arithmetic computing such as addition, subtraction, multiplication and division is realized with the current zero-power-consumption optoelectronic synaptic devices.

Low power high speed 3-bit multilevel resistive switching in TiO2 thin film using oxidisable electrode

Multilevel cell (MLC) capability of a memory device is an attractive alternative to realise high integration density of memory arrays. In addition, power efficient memory cell along with MLC capability has huge potential in neuromorphic computing and data storage applications. In this study low power, high speed and 3-bit multilevel bipolar resistance switching operation is reported in TiO2 thin films where copper is used as counter electrode. On account of using an oxidisable electrode, low programming voltages (∼+0.2 V, −0.1 V) along with low reset current (∼10 µA) are observed, thereby ensuing low power (∼µW) memory operation. Additionally, observation of fast switching (∼250 ns) translated to ultra-low energy (∼pJ) consumption. By varying compliance current (IC) from 25 µA to 1.6 mA during the set process, eight distinct non-volatile resistance states are reliably obtained, which showed statistically significant and non-overlapping resistance distribution. The multilevel resistive switching in Cu/TiO2/Pt device is explained by considering filamentary the widening phenomenon in the electrochemical metallization memory cell. Numerical calculations revealed that increase in the diameter of the metallic conducting filament from ∼3 nm to 70 nm with increasing IC is accountable for multiple low resistance states. The results of this study are promising towards realisation of emerging memory devices with low operating power, fast switching operation and high spatial density.

A spiking neuron constructed by the skyrmion-based spin torque nano-oscillator

Magnetic skyrmions are particle-like topological spin configurations, which can carry binary information and thus are promising building blocks for future spintronic devices. In this work, we investigate the relationship between the skyrmion dynamics and the characteristics of injected current in a skyrmion-based spin torque nano-oscillator, where the excitation source is introduced from a point nano-contact at the center of the nanodisk. It is found that the skyrmion will move away from the center of the nanodisk if it is driven by a spin-polarized current; however, it will return to the initial position in the absence of stimulus. Therefore, we propose a skyrmion-based artificial spiking neuron, which can effectively implement the leaky-integrate-fire operation. We study the feasibility of the skyrmion-based spiking neuron by using micromagnetic simulations. Our results may provide useful guidelines for building future magnetic neural networks with ultra-high density and ultra-low energy consumption.

Ultralow Power Wearable Heterosynapse with Photoelectric Synergistic Modulation.

Although the energy consumption of reported neuromorphic computing devices inspired by biological systems has become lower than traditional memory, it still remains greater than bio‐synapses (≈10 fJ per spike). Herein, a flexible MoS2‐based heterosynapse is designed with two modulation modes, an electronic mode and a photoexcited mode. A one‐step mechanical exfoliation method on flexible substrate and low‐temperature atomic layer deposition process compatible with flexible electronics are developed for fabricating wearable heterosynapses. With a pre‐spike of 100 ns, the synaptic device exhibits ultralow energy consumption of 18.3 aJ per spike in long‐term potentiation and 28.9 aJ per spike in long‐term depression. The ultrafast speed and ultralow power consumption provide a path for a neuromorphic computing system owning more excellent processing ability than the human brain. By adding optical modulation, a modulatory synapse is constructed to dynamically control correlations between pre‐ and post‐synapses and realize complex global neuromodulations. The novel wearable heterosynapse expands the accessible range of synaptic weights (ratio of facilitation ≈228%), providing an insight into the application of wearable 2D highly efficient neuromorphic computing architectures.

Digital filter polychromator for Thomson scattering applications

The paper describes the digital filter polychromator developed for Thomson scattering (TS) diagnostics. The device having ultra-low noise, high-speed detection system and up to 7 spectral channels is equipped with digitizer and single board computer for system control and data processing. The data acquisition system is capable to detect very short laser pulses of few ns width with low magnitude. This feature opens up new possibilities for the TS diagnostics design in modern fusion devices, which includes: operation with high background illumination, measurement of very low electron temperature and density at the plasma edge and scrape-off layer (SOL), separation of the TS signal and the stray light coming with a delay of several ns. The analysis of the TS signal waveform also gives a possibility to distinguish the TS and Mie scattering from the dust particles that is important for measurements in SOL. Owing to compactness and ultra-low energy consumption both optical and data processing units interfaced with optical Gigabit Ethernet were combined in a stand-alone device. Such all-in-one design with optical fiber input and optical digital output provides enhanced resistance to electromagnetic disturbances and simplify operation. A set of such polychromators can be mounted in a standard 19” rack and can be integrated with outer CODAC (Control, Data Access and Communication) system. Testing of the polychromators at the Globus-M2 tokamak has shown excellent performance of the developed serial devices.

Continuous-wave quantum dot photonic crystal lasers grown on on-axis Si (001)

Semiconductor III–V photonic crystal (PC) laser is regarded as a promising ultra-compact light source with unique advantages of ultralow energy consumption and small footprint for the next generation of Si-based on-chip optical interconnects. However, the significant material dissimilarities between III-V materials and Si are the fundamental roadblock for conventional monolithic III-V-on-silicon integration technology. Here, we demonstrate ultrasmall III-V PC membrane lasers monolithically grown on CMOS-compatible on-axis Si (001) substrates by using III-V quantum dots. The optically pumped InAs/GaAs quantum-dot PC lasers exhibit single-mode operation with an ultra-low threshold of ~0.6 μW and a large spontaneous emission coupling efficiency up to 18% under continuous-wave condition at room temperature. This work establishes a new route to form the basis of future monolithic light sources for high-density optical interconnects in future large-scale silicon electronic and photonic integrated circuits.

The Design of 3D-Interface Architecture in an Ultralow-Power, Electrospun Single-Fiber Synaptic Transistor for Neuromorphic Computing.

Synaptic electronics is a new technology for developing functional electronic devices that can mimic the structure and functions of biological counterparts. It has broad application prospects in wearable computing chips, human-machine interfaces, and neuron prostheses. These types of applications require synaptic devices with ultralow energy consumption as the effective energy supply for wearable electronics, which is still very difficult. Here, artificial synapse emulation is demonstrated by solid-ion gated organic field-effect transistors (OFETs) with a 3D-interface conducting channel for ultralow-power synaptic simulation. The basic features of the artificial synapse, excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and high-pass filtering, are successfully realized. Furthermore, the single-fiber based artificial synapse can be operated by an ultralow presynaptic spike down to -0.5 mV with an ultralow reading voltage at -0.1 mV due to the large contact surface between the ionic electrolyte and fiber-like semiconducting channel. Therefore, the ultralow energy consumption at one spike of the artificial synapse can be realized as low as ≈3.9 fJ, which provides great potential in a low-power integrated synaptic circuit.

A new approach to the fabrication of VO2 nanoswitches with ultra-low energy consumption.

A new approach for the formation of free-standing vertical resistive nanoswitches based on VO2 nanocrystals (NCs) with embedded conductive nanosharp Si tips is demonstrated in the present article. This approach consists in the chemical vapor deposition synthesis of VO2 NCs on the apices of sharp conductive nanotips formed on a Si substrate by the standard methods of planar silicon technology. The amplification of the electric field and current density at the tip apex inside a high-quality VO2 NC leads to a record-breaking reduction of switching voltage (by a factor of 20-70) in comparison with conventional geometry devices with planar contacts. Our pulse measurements showed that the extremely low energy equal to 4.2 fJ was consumed for the switching in such NCs, and the total number of switching cycles in one NC without degradation exceeded 1011. The proposed approach can be extended to the formation of large arrays of such nanoswitches. We showed that periodic arrays of individual VO2 NCs were selectively synthesized on sharp Si tips. The nanosizes of the switches, ultra-low power consumption for switching and the possibility of forming dense arrays of such objects make the fabricated nanoswitches promising devices for future neuromorphic systems.

A Quantum-Well Charge-Trap Synaptic Transistor With Highly Linear Weight Tunability

In this work, a novel synaptic transistor has been proposed and analyzed through technology computer-aided design (TCAD) simulation. The proposed device has merits of full-Si processing compatibility, short- and long-term plasticity, high energy efficiency, and linear and symmetric conductance adjustability. The proposed device consists of a quantum-well structure and a charge-trap unit for realizing both short- and long-term memories, respectively. The quantum-well charge-trap synaptic transistor (QW CTS) employs two independent gates to separate inference and weight adjustment operation. An optimally designed and validated QW CTS has demonstrated a highly linear and symmetric weight tunability, with an ultra-low energy consumption of ~1.5 fJ per synaptic event. The QW CTS can be a core element in the hardware-driven Si neuromorphic system.

Flexible full two-dimensional memristive synapses of graphene/WSe2-xOy/graphene.

van der Waals heterostructures realized by stacking different two-dimensional materials offer the possibility to design new devices with atomic-level precision. The realization of memristive synapses based on full two-dimensional materials provides an avenue for developing neuromorphic computing systems with excellent mechanical flexibility in future. Herein, we first develop the flexible full two-dimensional memristive synapse of graphene/WSe2-xOy/graphene exhibiting stable volatile resistive switching. The oxidation of WSe2 through O2 plasma treatment plays a key role in improving the memristive performance of the devices. And the switching behavior is associated with the migration of oxygen vacancies at the graphene/WSe2-xOy interface. Versatile synaptic functions have been realized, including short-term plasticity, long-term plasticity, the transition from short-term plasticity to long-term plasticity and high-pass temporal filtering, with ultralow energy consumption of ∼16.1 pJ per spike. The flexible full two-dimensional devices fabricated on flexible polyimide substrate show excellent mechanical flexibility, including a good endurance against repeatable bending of 1000 times and a bending strain of 2.5%.

Магнитоэлектроакустическая динамика в стрейнтронной ячейке памяти с произвольным доступом

Straintronic principle of nonvolatile magnetoelectric random access memory (MELRAM) draws much attention due to the prospects of ultra-low energy consumption in storage devices. The switching of magnetic moments by pulsed deformation of elastically coupled magnetic and piezoelectric subsystems is accompanied by excitation of acoustic oscillations in the memory cells. Oscillation period in nanoscale cells is comparable with the magnetic moment switching time, which can affect the information recording process. In the present paper the influence of acoustic excitations on the magnetic switching dynamics is studied by numerical modeling with application to a magnetostrictive cell 50×50×400 nm3 on a PMN-PT <011> substrate. Parameters of voltage control pulses that can insure reliable switching of magnetic states of the system are determined.

Light-triggered two-dimensional lateral homogeneous p-n diodes for opto-electrical interconnection circuits

The realization of light-triggered devices where light is used as external stimulus to control the device performances is a long-standing goal in modern opto-electrical interconnection circuits. In this work, it reveals that light illumination can induce the formation of p-n junctions along two-dimensional conduction channels. The results indicate that the dominant charge carrier type and density in black phosphorus (BP) conduction channel can be effectively modulated by the underlying cadmium sulfide (CdS) photo-gate layer under light illumination. This enables flexible switching of the working state between BP resistor and BP p-n diode in the designed semi-photo-gate transistor (SPGT) devices when switching the light on and off (ultra-low threshold light power). Simultaneously, the achieved BP p-n junctions also exhibit ultra-high photoresponsivity and evident photovoltaic properties. That is to say, light can be employed as external stimulus to define the BP p-n junctions, and in turn the p-n junctions will further convert the light into electrical power, showing all-in-one opto-electrical interconnection properties. Moreover, the SPGT device architecture is also applicable for construction of other ambipolar semiconductor-based (WSe2- and MoTe2-based) p-n diodes. Such universal all-in-one light-triggered lateral homogeneous p-n junctions with ultra-low energy consumption should open a new pathway toward novel optoelectronic devices and deliver various new applications.

Capacitive effect: An original of the resistive switching memory

Interplay between ions and electrons endows memristor with promising applications from the high density storages, memory logic gates to neuromorphic chips. The interplay-induced memristor evolution stage involving an original stage (non-standard faradic capacitance, NFC), transition stage (battery-like capacitance, BLC) and resistive switching state (RS) are discovered in the Ag|TiOx nanobelt|Ti device under different moisture levels. Generation, migration and interplay between ions and electrons are effectively restricted for the NFC observed in dry ambient. The OH− suspending on the surface Vo due to the H2O-based redox reaction results in the device evolving from the NFC to BLC under moisture circumstance. Strong interplay with ions, electron transfer and migration of OH− ions push the device into the RS state. Based on theory calculations, an energy band-based physical model is proposed to comprehend the evolution process. This work gives an insight into the moisture effect on the resistive switching behaviors and the evolution track of memristor, which is meaningful for construction neuromorphic chip with an ultralow energy consumption.

Flexible Femtojoule Energy-Consumption In-Ga-Zn-O Synaptic Transistors With Extensively Tunable Memory Time

A neuromorphic electronic system requires the component devices to not only mimic typical synaptic behaviors but also be energy-efficient, together with excellent uniformity and tunable memory time. For this purpose, we fabricated amorphous In-Ga-Zn-O (a-IGZO) thin-film transistors with plasma-enhanced atomic layer deposition AlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> :H dielectrics, successfully demonstrating typical synaptic behaviors, such as excitatory and inhibitory postsynaptic current, pair-pules facilitation, dynamic filter, learning and forgetting abilities and spike-timing dependent plasticity. In particular, such synaptic transistors exhibit ultralow energy consumption down to 3.18 fJ per synaptic event and tunable extensive memory time ranging from 76.6 ms to at least thousands of seconds. The ultralow energy consumption is realized by electron trapping and releasing at and near the interface between a-IGZO channel and AlO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">x</sub> :H dielectric under low voltages. By adjusting the concentration of oxygen vacancy defects in the a-IGZO domain adjacent to the interface by means of changing the growth temperature of the AlOx:H dielectrics, the memory time of the device can be further tuned on a large scale. Device flexibility was also demonstrated by fabricating the synaptic transistors onto polymer substrates at room temperature.

Tailoring the detection sensitivity of graphene based flexible smoke sensors by decorating with ceramic microparticles

The fire risks detection using reliable devices with compact design and ultralow energy consumption has been an important topic of research in the last years. Therefore, this work reports the fabrication and electrical characterization of flexible graphene sensors (FGSs) for smoke detection. For this, a flexible graphene composite with thickness of 1.0 ± 0.1 mm was fabricated using a mold-casting method and sensitized with Ruddlesden Popper perovskite (RPP) and TiO2 micro/nanoparticles for smoke detection purposes. The electrical characterization indicates that the sensors sensitized with the RPP microparticles present faster response times and lower recovery times than those sensitized with TiO2 nanoparticles. The main advantages of these sensors are: 1) They operate with very low power consumption (2−7 mW), and 2) they do not need to be in direct contact with the smoke source or fire source as reported in previous graphene based sensors. Thus, the flexible smoke sensors presented here offer new opportunities to develop a new generation of low cost and compact sensors which can be re-designed in the near future for detecting other types of gases for security purposes or medical applications.

A Cost-Aware Efficient RAM Structure Based on Quantum-Dot Cellular Automata Nanotechnology

Nowadays quantum-dot cellular automata (QCA) as a nanoscale transistor-less device technology have attained major attention for their prominent features. The circuits constructed by QCA technology owning remarkable decreasing in size, fast switching speed and ultra-low energy consumption. These features can be more different in varied memory structures. Random access memory (RAM) is a kind of data storage devices that allows data to be read or written it’s generally volatile, and used for data that change often. Due to the significance of memory in a digital system, designing and optimization of high-speed RAM in QCA nanotechnology is a substantial subject. So, this paper presents a new structure for QCA-based RAM cell by employing the 3-input rotated majority gate (RMG). Eventually, 1 × 4 RAM is designed by exerting the individual memory cell. The functionality of the proposed design is implemented and assessed using the QCADesigner simulator. The obtained results demonstrated that the designed QCA-based RAM cell is superior to previous structures in terms of delay and cell count.

Energy-Efficient Artificial Synapses Based on Oxide Tunnel Junctions.

The development of artificial synapses has enabled the establishment of brain-inspired computing systems, which provides a promising approach for overcoming the inherent limitations of current computer systems. The two-terminal memristors that faithfully mimic the function of biological synapses have intensive prospects in the neural network field. Here, we propose a high-performance artificial synapse based on oxide tunnel junctions with oxygen vacancy migration. Both short-term and long-term plasticities are mimicked in one device. The oxygen vacancy migration through oxide ultrathin films is utilized to manipulate long-term plasticity. Essential synaptic functions, such as paired pulse facilitation, post-tetanic potentiation, as well as spike-timing-dependent plasticity, are successfully implemented in one device by finely modifying the shape of the pre- and postsynaptic spikes. Ultralow femtojoule energy consumption comparable to that of the human brain indicates its potential application in efficient neuromorphic computing. Oxide tunnel junctions proposed in this work provide an alternative approach for realizing energy-efficient brain-like chips.

A Pulsed Thermal-Flow (PTF) Sensor Measures Velocity of Flow and Thermal Diffusivity

A prototype pulsed thermal-flow (PTF) sensor was designed, fabricated in micro-electro-mechanical system (MEMS) technology and tested on various gases. The objective of our development project was twofold: first, to realize a micro-sensor of low cost and ultra-low energy consumption that, secondly, accurately and rapidly measures gas flow velocities within a wide temperature range. The sensor of size 4.2 × 3.2 × 0.6 mm3 is of micro-beam type. It consists of one Joule heating element and several resistance thermometers at distinct distances from the heater. The heater is operated in a single short pulse mode of a fixed duration that can be chosen between 10 and 100 µs. Due to this ultra-short time of excitation, there is no natural convection during a run. For typical values of pulse width (30 µs) and heater power (6 mW), the energy per measurement is smaller than 0.2 µJ. Typically, the excess temperature of the heater is limited to 5 K. This relatively small overtemperature considerably reduces radiative heat transfers otherwise interfering with the process of measuring. The velocity of flow is determined by the time-of-flight technique of the imposed heat pulse as the tracer in a few milliseconds. The measurement uncertainty is preliminary assessed to be 1.5% within a range from 0 to 7 m/s. The working temperature may vary between − 100 and 300 °C. The sensor not only measures the velocity of flow but also the thermal diffusivity of the gas under test. The report provides a complete analytical model of the functional principle of the sensor, a numerical FEM analysis of the 2-dim. isotherms, the heat flow pattern of the active surface of the sensor and an empirical model to fit the temperature response of the thermometers. The latter one effectively supports the evaluation of the acquired data. Exemplary experimental results are presented for nitrogen, methane and the two gas binary mixtures 80CH4–20N2 and 80CH4–20H2. The results deviate from their analytically predicted values by at most ± 1%. To the best of our knowledge, the PTF-sensor operates at the lowest energy consumption known so far. This characteristic makes it the perfect flow sensor for battery-operated long-term flow velocity recording systems.

Electrospun ZnSnO Nanofibers for Neuromorphic Transistors With Ultralow Energy Consumption

Emulating the essential synaptic working principles using a three-terminal synaptic transistor has been an important research field in recent years. Electrospun metal oxide nanofibers have been regarded as promising blocks for large-area, low-cost, and one-dimensional (1D) electronic devices. In this letter, zinc-tin oxide (ZnSnO) nanofibers were fabricated by electrospinning, and the synaptic transistors based on ZnSnO nanofibers were integrated. To mimic the synaptic behavior of human brain, LiClO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sub> dissolved in polyethylene oxide was used as the gate electrolyte in the synaptic transistors. The plasticities, including short term and long term, are mimicked with the help of electrolyte ion dynamics under low and large bias voltage, and an energy consumption of as low as 0.44 pJ per event is observed. This work demonstrates a new approach for establishing the large-scale, energy-efficient 1D artificial synapses for neuromorphic networks.