Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely us...Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance.Here,for the first time,we present an organic memristor based on an electropolymerized dopamine-based memristive layer.This polydopamine-based memristor demonstrates the improve-ments in key performance,including a low threshold voltage of 0.3 V,a thin thickness of 16 nm,and a high parasitic capaci-tance of about 1μF·mm^(-2).By leveraging these properties in combination with its stable threshold switching behavior,we con-struct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage,whose spiking fre-quency increases with the increase of current stimulation analogous to a biological neuron.The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.展开更多
The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are uns...The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during operation.In this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/Pt-based bilayer selector and demonstrated the occurrence of a low leakage current(<1×10^(-11) A) and low distribution of the threshold voltage(Δ0.11 V).The bilayer structure could control the filament formation in the intermediate state through the insertion of an HfO_(x) tunneling barrier.By stacking a bilayer selector with NiO_(x)based resistive random-access memory,the leakage and programming currents of the device could be significantly decreased.For the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed structure.The maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/Pt/Ti/NiO_(x)/Pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).展开更多
Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimen...Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.展开更多
With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of...With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of data generated from the devices challenges the AIoT systems from information collection,storage,processing and communication.In the review,we introduce volatile threshold switching memristors,which can be roughly classified into three types:metallic conductive filament-based TS devices,amorphous chalcogenide-based ovonic threshold switching devices,and metal-insulator transition based TS devices.They play important roles in high-density storage,energy efficient computing and hardware security for AIoT systems.Firstly,a brief introduction is exhibited to describe the categories(materials and characteristics)of volatile TS devices.And then,switching mechanisms of the three types of TS devices are discussed and systematically summarized.After that,attention is focused on the applications in 3D cross-point memory technology with high storage-density,efficient neuromorphic computing,hardware security(true random number generators and physical unclonable functions),and others(steep subthreshold slope transistor,logic devices,etc.).Finally,the major challenges and future outlook of volatile threshold switching memristors are presented.展开更多
The impact of the variations of threshold voltage(V_(th))and hold voltage(V_(hold))of threshold switching(TS)selector in1 S1 R crossbar array is investigated.Based on ON/OFF state I–V curves measurements from a large...The impact of the variations of threshold voltage(V_(th))and hold voltage(V_(hold))of threshold switching(TS)selector in1 S1 R crossbar array is investigated.Based on ON/OFF state I–V curves measurements from a large number of Ag-filament TS selectors,V_(th)and V_(hold)are extracted and their variations distribution expressions are obtained,which are then employed to evaluate the impact on read process and write process in 32×321 S1 R crossbar array under different bias schemes.The results indicate that V_(th)and V_(hold)variations of TS selector can lead to degradation of 1 S1 R array performance parameters,such as minimum read/write voltage,bit error rate(BER),and power consumption.For the read process,a small V_(hold)variation not only results in the minimum read voltage increasing but it also leads to serious degradation of BER.As the standard deviation of V_(hold)and V_(th)increases,the BER and the power consumption of 1 S1 R crossbar array under 1/2 bias,1/3 bias,and floating scheme degrade,and the case under 1/2 bias tends to be more serious compared with other two schemes.For the write process,the minimum write voltage also increases with the variation of V_(hold)from small to large value.A slight increase of V_(th)standard deviation not only decreases write power efficiency markedly but also increases write power consumption.These results have reference significance to understand the voltage variation impacts and design of selector properly.展开更多
Low-power and low-variability artificial neuronal devices are highly desired for high-performance neuromorphic computing.In this paper,an oscillation neuron based on a low-variability Ag nanodots(NDs)threshold switchi...Low-power and low-variability artificial neuronal devices are highly desired for high-performance neuromorphic computing.In this paper,an oscillation neuron based on a low-variability Ag nanodots(NDs)threshold switching(TS)device with low operation voltage,large on/off ratio and high uniformity is presented.Measurement results indicate that this neuron demonstrates self-oscillation behavior under applied voltages as low as 1 V.The oscillation frequency increases with the applied voltage pulse amplitude and decreases with the load resistance.It can then be used to evaluate the resistive random-access memory(RRAM)synaptic weights accurately when the oscillation neuron is connected to the output of the RRAM crossbar array for neuromorphic computing.Meanwhile,simulation results show that a large RRAM crossbar array(>128×128)can be supported by our oscillation neuron owing to the high on/off ratio(>10^(8))of Ag NDs TS device.Moreover,the high uniformity of the Ag NDs TS device helps improve the distribution of the output frequency and suppress the degradation of neural network recognition accuracy(<1%).Therefore,the developed oscillation neuron based on the Ag NDs TS device shows great potential for future neuromorphic computing applications.展开更多
The spiking neural network(SNN),closely inspired by the human brain,is one of the most powerful platforms to enable highly efficient,low cost,and robust neuromorphic computations in hardware using traditional or emerg...The spiking neural network(SNN),closely inspired by the human brain,is one of the most powerful platforms to enable highly efficient,low cost,and robust neuromorphic computations in hardware using traditional or emerging electron devices within an integrated system.In the hardware implementation,the building of artificial spiking neurons is fundamental for constructing the whole system.However,with the slowing down of Moore’s Law,the traditional complementary metal-oxide-semiconductor(CMOS)technology is gradually fading and is unable to meet the growing needs of neuromorphic computing.Besides,the existing artificial neuron circuits are complex owing to the limited bio-plausibility of CMOS devices.Memristors with volatile threshold switching(TS)behaviors and rich dynamics are promising candidates to emulate the biological spiking neurons beyond the CMOS technology and build high-efficient neuromorphic systems.Herein,the state-of-the-art about the fundamental knowledge of SNNs is reviewed.Moreover,we review the implementation of TS memristor-based neurons and their systems,and point out the challenges that should be further considered from devices to circuits in the system demonstrations.We hope that this review could provide clues and be helpful for the future development of neuromorphic computing with memristors.展开更多
Artificial tactile perception system,as an emerging sensor technology,is expected to provide human-like touch sensing ability for robots,prosthetics,and smart wearable equipment.The introduction of neuromorphic device...Artificial tactile perception system,as an emerging sensor technology,is expected to provide human-like touch sensing ability for robots,prosthetics,and smart wearable equipment.The introduction of neuromorphic devices could observably increase efficiency and reduce circuit complexity during signal conversion and pulse encoding operations.Herein,we demonstrate a two-dimensional tellurene(Te)based threshold switching(TS)memristive device with low high resistance state variation,which is successfully applied for constructing an artificial nociceptive and emulating a leaky integrate-and-fire(LIF)neuron.Furthermore,a self-powered artificial tactile perception system is constructed by combining this LIF neuron and piezoelectric nanogenerator device,demonstrating a self-protection function under mechanical stimulation,i.e.,hand retraction reflex.The bioinspired artificial tactile perception system indicates the potential of developing next-generation bio-inspired electronics and human-machine interaction systems.展开更多
In dealing with the increasing power dissipation of electronic systems with increasing integration density,a field-effect transistor(FET)with steep switching slope that overcomes the thermionic limit is vital to achie...In dealing with the increasing power dissipation of electronic systems with increasing integration density,a field-effect transistor(FET)with steep switching slope that overcomes the thermionic limit is vital to achieve low-power operations.Here,we report two types of threshold switching(TS)FETs based on 2D Van der Waals heterostructures by virtue of the abrupt resistive switching of the hexagonal boron nitride(hBN)TS device.The common hBN dielectric layer functions as the switching medium for the TS device and the gate dielectric for the 2D FET enabling seamless integration of the hBN TS device and baseline 2D FET.TS FET in source configuration by connecting the TS device to the source terminal of the 2D FET offers an ultralow average subthreshold swing(SS)of 1.6mV/dec over six decades of drain current at room temperature and suppressed leakage current.TS FET in gate configuration by connecting the TS device to the gate terminal of the 2D FET also exhibits steep switching slope with ultralow SS of 10.6mV/dec.The proposed compact device structures integrating 2D FET and TS device provide a potential approach of monolithic integration toward next-generation low-power electronics.展开更多
Atomic layer deposition technique has been used to prepare tantalum nitride nanoparticles(TaN-NPs)and sandwiched between Al-doped HfO;layers to achieve ITO/HfAlO/TaN-NP/HfAlO/ITO RRAM device.Transmission electron micr...Atomic layer deposition technique has been used to prepare tantalum nitride nanoparticles(TaN-NPs)and sandwiched between Al-doped HfO;layers to achieve ITO/HfAlO/TaN-NP/HfAlO/ITO RRAM device.Transmission electron microscopy along with energy dispersive spectroscopy confirms the presence of TaN-NPs.X-ray photoelectron spectroscopy suggests that part of Ta N converted to tantalum oxynitride(TaO_(x)N_(y))which plays an important role in stable cycle-to-cycle resistive switching.Charge trapping and oxygen vacancy creation were found to be modified after the inclusion of Ta N-NPs inside RRAM structure.Also,HfAlO/TaO_(x)N_(y)interface due to the presence TaN-NPs improves the device-to-device switching reliability by reducing the probability of random rupture/formation of conductive filaments(CFs).DC endurance of more than 10^(3)cycles and memory data retention up to 10^(4)s was achieved with an insignificant variation of different resistance states.Multilevel conductance was attained by controlling RESET voltage with stable data retention in multiple states.The volatile threshold switching was monitored after controlling the CF forming at 200 nA current compliance with high selectivity of~10^(3).Synaptic learning behavior has been demonstrated by spike-rate-dependent plasticity(SRDP).Reliable potentiation and depression processes were observed after the application of suitable negative and positive pulses which shows the capability of the TaN–NPs based RRAM device for transparent synaptic devices.展开更多
Selector devices are indispensable components of large-scale memristor array systems.The thereinto,ovonic threshold switching(OTS)selector is one of the most suitable candidates for selector devices,owing to its high ...Selector devices are indispensable components of large-scale memristor array systems.The thereinto,ovonic threshold switching(OTS)selector is one of the most suitable candidates for selector devices,owing to its high selectivity and scalability.However,OTS selectors suffer from poor endurance and stability which are persistent tricky problems for applica-tion.Here,we report on a multilayer OTS selector based on simple GeSe and doped-GeSe.The experimental results show im-proving selector performed extraordinary endurance up to 1010 and the fluctuation of threshold voltage is 2.5%.The reason for the improvement may lie in more interface states which strengthen the interaction among individual layers.These develop-ments pave the way towards tuning a new class of OTS materials engineering,ensuring improvement of electrical perform-ance.展开更多
An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to bal...An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to balance the platform gravity.The two-way blower inflates and deflates the ballonet to regulate the buoyancy.Altitude adjustment is achieved by tracking the differential pressure difference(DPD),and a threshold switching strategy is used to achieve blower flow control.The vertical acceleration regulation ability is decided not only by the blower flow rate,but also by the designed margin of pressure difference(MPD).Pressure difference is a slow-varying variable compared with altitude,and it is adopted as the control variable.The response speed of the actuator to disturbance can be delayed,and the overshoot caused by the large inertia of the platform is inhibited.This method can maintain a high tracking accuracy and reduce the complexity of model calculation,thus improving the robustness of controller design.展开更多
Chalcogenide glass has a unique volatile transition between high‐and low‐resistance states under an electric field,a phenomenon termed ovonic threshold switching(OTS).This characteristic is extensively uti-lized in ...Chalcogenide glass has a unique volatile transition between high‐and low‐resistance states under an electric field,a phenomenon termed ovonic threshold switching(OTS).This characteristic is extensively uti-lized in various electronic memory and computational devices,particu-larly as selectors for cross‐point memory architectures.Despite its advantages,the material is susceptible to glass relaxation,which can result in substantial drifts in threshold voltage and a decline in off‐current performance over successive operational cycles or long storage time.In this study,we introduce an OTS device made from stoichio-metric Sb_(2)Se_(3) glass,which retains an octahedral local structure within its amorphous matrix.This innovative material exhibits outstanding OTS capabilities,maintaining minimal degradation despite undergoing over 10^(7) operating cycles.Via comprehensive first‐principles calculations,our findings indicate that the mid‐gap states in amorphous Sb_(2)Se_(3) predom-inantly stem from the atomic chains characterized by heteropolar Sb‐Se bonds.These bonds exhibit remarkable stability,showing minimal alteration over time,thereby contributing to the overall durability and consistent performance of the material.Our findings not only shed light on the complex physical origins that govern the OTS behavior but also lay the groundwork for creating or optimizing innovative electrical switching materials.展开更多
Memristors have been emerging as promising candidates for computing systems in post-Moore applications,particularly electrochemical metallizationbased memristors,which are poised to play a crucial role in neuromorphic...Memristors have been emerging as promising candidates for computing systems in post-Moore applications,particularly electrochemical metallizationbased memristors,which are poised to play a crucial role in neuromorphic computing and machine learning.These devices are favored for their high integration density,low power consumption,rapid switching speed,and significant on/off ratio.Despite advancements in various materials,achieving adequate electrical performance—characterized by threshold switching(TS)behavior,spontaneous reset,and low off-state resistance—remains challenging due to the limitations in conductance filament control within the nanoscale resistive switching layer.In this study,we introduce an efficient method to control the ZrO_(2) crystallinity for tunable volatility memristor by establishing the filament paths through a simple thermal treatment process in a single oxide layer.The effect of ZrO_(2) crystallinity to create localized filament paths for enhancing Ag migration and improving TS behavior is also investigated.In contrast to its amorphous counterpart,crystallized ZrO_(2) volatile memristor,treated by rapid thermal annealing,demonstrates a steep switching slope(0.21 mV dec^(–1)),a high resistance state(25 GΩ),and forming-free characteristics.The superior volatile performance is attributed to localized conductive filaments along lowenergy pathways,such as dislocations and grain boundaries.By coupling with enhanced volatile switching behavior,we believe that the volatility is finely tuned to function as short-term memory for reservoir computing,making it particularly well-suited for tasks such as audio and image recognition.展开更多
The intrinsic variability of memristor switching behavior can be used as a natural source of randomness,this variability is valuable for safe applications in hardware,such as the true random number generator(TRNG).How...The intrinsic variability of memristor switching behavior can be used as a natural source of randomness,this variability is valuable for safe applications in hardware,such as the true random number generator(TRNG).However,the speed of TRNG is still be further improved.Here,we propose a reliable Ag/SiNx/n-Si volatile memristor,which exhibits a typical threshold switching device with stable repeat ability and fast switching speed.This volatile-memristor-based TRNG is combined with nonlinear feedback shift register(NFSR)to form a new type of high-speed dual output TRNG.Interestingly,the bit generation rate reaches a high speed of 112 kb/s.In addition,this new TRNG passed all 15 National Institute of Standards and Technology(NIST)randomness tests without post-processing steps,proving its performance as a hardware security application.This work shows that the SiNx-based volatile memristor can realize TRNG and has great potential in hardware network security.展开更多
The recent development of three-dimensional semiconductor integration technology demands a key component-the ovonic threshold switching(OTS)selector to suppress the current leakage in the high-density memory chips.Yet...The recent development of three-dimensional semiconductor integration technology demands a key component-the ovonic threshold switching(OTS)selector to suppress the current leakage in the high-density memory chips.Yet,the unsatisfactory performance of existing OTS materials becomes the bottleneck of the industrial advancement.The sluggish development of OTS materials,which are usually made from chalcogenide glass,should be largely attributed to the insufficient understanding of the electronic structure in these materials,despite of intensive research in the past decade.Due to the heavy first-principles computation on disordered systems,a universal theory to explain the origin of mid-gap states(MGS),which are the key feature leading to the OTS behavior,is still lacking.To avoid the formidable computational tasks,we adopt machine learning method to understand and predict MGS in typical OTS materials.We build hundreds of chalcogenide glass models and collect major structural features from both short-range order(SRO)and medium-range order(MRO)of the amorphous cells.After training the artificial neural network using these features,the accuracy has reached~95%when it recognizes MGS in new glass.By analyzing the synaptic weights of the input structural features,we discover that the bonding and coordination environments from SRO and particularly MRO are closely related to MGS.The trained model could be used in many other OTS chalcogenides after minor modification.The intelligent machine learning allows us to understand the OTS mechanism from vast amount of structural data without heavy computational tasks,providing a new strategy to design functional amorphous materials from first principles.展开更多
Organic-inorganic hybrid perovskites (OHPs) are well-known as light-absorbing materials in solar cells and have recently attracted considerable attention for the applications in resistive switching memory. Previous st...Organic-inorganic hybrid perovskites (OHPs) are well-known as light-absorbing materials in solar cells and have recently attracted considerable attention for the applications in resistive switching memory. Previous studies have shown that ions can migrate to form a conductive channel in perovskites under an external voltage. However, the exact resistance mechanism for Ag or halogens which dominate the resistive behavior is still controversial. Here, we demonstrate a resistive switching memory device based on Ag/FA0.83MA0.17Pb(I0.82Br0.18)3/fluorine doped tin oxide (FTO). The migration of Ag cations and halide anions is demonstrated by energy dispersive X-ray spectroscopy (EDS) after the SET process (positive voltage on Ag). By comparing the I-V behavior of the Au-based devices, it is clear that the conductive channel formed by Ag is the main factor of the switching characteristics for Ag-based devices. Meanwhile, by controlling the appropriate SET voltage, two kinds of resistance characteristics of the analog switch and threshold switch can be realized in the Ag-based device. As a result, it may be possible to implement both data storage and neuromorphic computing in a single device.展开更多
基金support from the Beijing Natural Science Foundation-Xiaomi Innovation Joint Fund(No.L233009)National Natural Science Foundation of China(NSFC Nos.62422409,62174152,and 62374159)from the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2020115).
文摘Memristors have a synapse-like two-terminal structure and electrical properties,which are widely used in the construc-tion of artificial synapses.However,compared to inorganic materials,organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance.Here,for the first time,we present an organic memristor based on an electropolymerized dopamine-based memristive layer.This polydopamine-based memristor demonstrates the improve-ments in key performance,including a low threshold voltage of 0.3 V,a thin thickness of 16 nm,and a high parasitic capaci-tance of about 1μF·mm^(-2).By leveraging these properties in combination with its stable threshold switching behavior,we con-struct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage,whose spiking fre-quency increases with the increase of current stimulation analogous to a biological neuron.The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.
基金financially supported by the National Research Foundation of Korea (NRF)(No.2016R1A3B1908249)。
文摘The use of electrochemical-metallization-based volatile threshold switching selectors in cross-point arrays has been widely explored owing to their high on-off ratios and simple structure.However,these devices are unsuitable for cross-point architectures because of the difficulty in controlling the random filament formation that results in large fluctuations in the threshold voltage during operation.In this study,we investigated the unidirectional threshold transition characteristics associated with an Ag/GST/HfO_(x)/Pt-based bilayer selector and demonstrated the occurrence of a low leakage current(<1×10^(-11) A) and low distribution of the threshold voltage(Δ0.11 V).The bilayer structure could control the filament formation in the intermediate state through the insertion of an HfO_(x) tunneling barrier.By stacking a bilayer selector with NiO_(x)based resistive random-access memory,the leakage and programming currents of the device could be significantly decreased.For the crossbar array configuration,we performed equivalent circuit analysis of a one-selector oneresistor(1S1R) devices and estimated the optimal array size to demonstrate the applicability of the proposed structure.The maximum acceptable crossbar array size of the 1S1R device with the Ag/GST/HfO_(x)/Pt/Ti/NiO_(x)/Pt structure was 5.29×10^(14)(N^(2),N=2.3×10^(7)).
基金M.Zhu acknowledges support by the National Outstanding Youth Program(62322411)the Hundred Talents Program(Chinese Academy of Sciences)+1 种基金the Shanghai Rising-Star Program(21QA1410800)The financial support was provided by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB44010200).
文摘Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.
基金supported by the STI 2030—Major Projects(Grant No.2021ZD0201201)National Natural Science Foundation of China(Grant No.92064012)Hubei Province Postdoctoral Innovation Research Program(Grant No.0106182103)。
文摘With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of data generated from the devices challenges the AIoT systems from information collection,storage,processing and communication.In the review,we introduce volatile threshold switching memristors,which can be roughly classified into three types:metallic conductive filament-based TS devices,amorphous chalcogenide-based ovonic threshold switching devices,and metal-insulator transition based TS devices.They play important roles in high-density storage,energy efficient computing and hardware security for AIoT systems.Firstly,a brief introduction is exhibited to describe the categories(materials and characteristics)of volatile TS devices.And then,switching mechanisms of the three types of TS devices are discussed and systematically summarized.After that,attention is focused on the applications in 3D cross-point memory technology with high storage-density,efficient neuromorphic computing,hardware security(true random number generators and physical unclonable functions),and others(steep subthreshold slope transistor,logic devices,etc.).Finally,the major challenges and future outlook of volatile threshold switching memristors are presented.
基金Project supported by the MOST of China(Grant No.2016YFA0201801)the Beijing Advanced Innovation Center for Future Chip(ICFC)+2 种基金Beijing Municipal Science and Technology Project(Grant No.D161100001716002)the National Natural Science Foundation of China(Grant Nos.61674089,61674087,61674092,61076115,and 61774012)the Research Fund from Beijing Innovation Center for Future Chip(Grant No.KYJJ2016008)
文摘The impact of the variations of threshold voltage(V_(th))and hold voltage(V_(hold))of threshold switching(TS)selector in1 S1 R crossbar array is investigated.Based on ON/OFF state I–V curves measurements from a large number of Ag-filament TS selectors,V_(th)and V_(hold)are extracted and their variations distribution expressions are obtained,which are then employed to evaluate the impact on read process and write process in 32×321 S1 R crossbar array under different bias schemes.The results indicate that V_(th)and V_(hold)variations of TS selector can lead to degradation of 1 S1 R array performance parameters,such as minimum read/write voltage,bit error rate(BER),and power consumption.For the read process,a small V_(hold)variation not only results in the minimum read voltage increasing but it also leads to serious degradation of BER.As the standard deviation of V_(hold)and V_(th)increases,the BER and the power consumption of 1 S1 R crossbar array under 1/2 bias,1/3 bias,and floating scheme degrade,and the case under 1/2 bias tends to be more serious compared with other two schemes.For the write process,the minimum write voltage also increases with the variation of V_(hold)from small to large value.A slight increase of V_(th)standard deviation not only decreases write power efficiency markedly but also increases write power consumption.These results have reference significance to understand the voltage variation impacts and design of selector properly.
基金supported in part by China Key Research and Development Program(2016YFA0201800)the National Natural Science Foundation of China(91964104,61974081)。
文摘Low-power and low-variability artificial neuronal devices are highly desired for high-performance neuromorphic computing.In this paper,an oscillation neuron based on a low-variability Ag nanodots(NDs)threshold switching(TS)device with low operation voltage,large on/off ratio and high uniformity is presented.Measurement results indicate that this neuron demonstrates self-oscillation behavior under applied voltages as low as 1 V.The oscillation frequency increases with the applied voltage pulse amplitude and decreases with the load resistance.It can then be used to evaluate the resistive random-access memory(RRAM)synaptic weights accurately when the oscillation neuron is connected to the output of the RRAM crossbar array for neuromorphic computing.Meanwhile,simulation results show that a large RRAM crossbar array(>128×128)can be supported by our oscillation neuron owing to the high on/off ratio(>10^(8))of Ag NDs TS device.Moreover,the high uniformity of the Ag NDs TS device helps improve the distribution of the output frequency and suppress the degradation of neural network recognition accuracy(<1%).Therefore,the developed oscillation neuron based on the Ag NDs TS device shows great potential for future neuromorphic computing applications.
基金This work was supported in part by the Ministry of Science and Technology of China under Grant No.2017YFA0206102in part by the National Natural Science Foundation of China under Grant No.61922083+2 种基金by the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No.XDB44000000by the European Union’s Horizon 2020 Research and Innovation Program with Grant Agreement No.824164by the German Research Foundation Projects MemCrypto under Grant No.GZ:DU 1896/2-1 and MemDPU under Grant No.GZ:DU 1896/3-1.
文摘The spiking neural network(SNN),closely inspired by the human brain,is one of the most powerful platforms to enable highly efficient,low cost,and robust neuromorphic computations in hardware using traditional or emerging electron devices within an integrated system.In the hardware implementation,the building of artificial spiking neurons is fundamental for constructing the whole system.However,with the slowing down of Moore’s Law,the traditional complementary metal-oxide-semiconductor(CMOS)technology is gradually fading and is unable to meet the growing needs of neuromorphic computing.Besides,the existing artificial neuron circuits are complex owing to the limited bio-plausibility of CMOS devices.Memristors with volatile threshold switching(TS)behaviors and rich dynamics are promising candidates to emulate the biological spiking neurons beyond the CMOS technology and build high-efficient neuromorphic systems.Herein,the state-of-the-art about the fundamental knowledge of SNNs is reviewed.Moreover,we review the implementation of TS memristor-based neurons and their systems,and point out the challenges that should be further considered from devices to circuits in the system demonstrations.We hope that this review could provide clues and be helpful for the future development of neuromorphic computing with memristors.
基金supported by the National Science Fund for Distinguished Young Scholars(52025022)the funding from Jilin Province(20240210001GX)+1 种基金the Scientific Research Innovation Capability Support Project for Young Faculty(ZYGXQNJSKYCXNLZCXM-I10)the National Natural Science Foundation of China(U23A20568,51732003,52472149,52072065,and 52372137).
文摘Artificial tactile perception system,as an emerging sensor technology,is expected to provide human-like touch sensing ability for robots,prosthetics,and smart wearable equipment.The introduction of neuromorphic devices could observably increase efficiency and reduce circuit complexity during signal conversion and pulse encoding operations.Herein,we demonstrate a two-dimensional tellurene(Te)based threshold switching(TS)memristive device with low high resistance state variation,which is successfully applied for constructing an artificial nociceptive and emulating a leaky integrate-and-fire(LIF)neuron.Furthermore,a self-powered artificial tactile perception system is constructed by combining this LIF neuron and piezoelectric nanogenerator device,demonstrating a self-protection function under mechanical stimulation,i.e.,hand retraction reflex.The bioinspired artificial tactile perception system indicates the potential of developing next-generation bio-inspired electronics and human-machine interaction systems.
基金the financial support from the Natural Science Foundation of China(Nos.62274118,U2032147)Singapore National Research Foundation Investigatorship Program(No.NRF-NRFI08-2022-0009)+1 种基金Singapore MOE(No.MOE-T2EP50220-0001)the Science and Engineering Research Council of A*STAR(Agency for Science,Technology and Research)Singapore(No.A20G9b0135).
文摘In dealing with the increasing power dissipation of electronic systems with increasing integration density,a field-effect transistor(FET)with steep switching slope that overcomes the thermionic limit is vital to achieve low-power operations.Here,we report two types of threshold switching(TS)FETs based on 2D Van der Waals heterostructures by virtue of the abrupt resistive switching of the hexagonal boron nitride(hBN)TS device.The common hBN dielectric layer functions as the switching medium for the TS device and the gate dielectric for the 2D FET enabling seamless integration of the hBN TS device and baseline 2D FET.TS FET in source configuration by connecting the TS device to the source terminal of the 2D FET offers an ultralow average subthreshold swing(SS)of 1.6mV/dec over six decades of drain current at room temperature and suppressed leakage current.TS FET in gate configuration by connecting the TS device to the gate terminal of the 2D FET also exhibits steep switching slope with ultralow SS of 10.6mV/dec.The proposed compact device structures integrating 2D FET and TS device provide a potential approach of monolithic integration toward next-generation low-power electronics.
基金financially supported in part by National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIP)(2018R1C1B5046454)by the Dongguk University Research Fund of 2020。
文摘Atomic layer deposition technique has been used to prepare tantalum nitride nanoparticles(TaN-NPs)and sandwiched between Al-doped HfO;layers to achieve ITO/HfAlO/TaN-NP/HfAlO/ITO RRAM device.Transmission electron microscopy along with energy dispersive spectroscopy confirms the presence of TaN-NPs.X-ray photoelectron spectroscopy suggests that part of Ta N converted to tantalum oxynitride(TaO_(x)N_(y))which plays an important role in stable cycle-to-cycle resistive switching.Charge trapping and oxygen vacancy creation were found to be modified after the inclusion of Ta N-NPs inside RRAM structure.Also,HfAlO/TaO_(x)N_(y)interface due to the presence TaN-NPs improves the device-to-device switching reliability by reducing the probability of random rupture/formation of conductive filaments(CFs).DC endurance of more than 10^(3)cycles and memory data retention up to 10^(4)s was achieved with an insignificant variation of different resistance states.Multilevel conductance was attained by controlling RESET voltage with stable data retention in multiple states.The volatile threshold switching was monitored after controlling the CF forming at 200 nA current compliance with high selectivity of~10^(3).Synaptic learning behavior has been demonstrated by spike-rate-dependent plasticity(SRDP).Reliable potentiation and depression processes were observed after the application of suitable negative and positive pulses which shows the capability of the TaN–NPs based RRAM device for transparent synaptic devices.
基金supported by National Natural Science Foundation of China(Grant Nos.61974164,62074166,61804181,62004219,and 6200422).
文摘Selector devices are indispensable components of large-scale memristor array systems.The thereinto,ovonic threshold switching(OTS)selector is one of the most suitable candidates for selector devices,owing to its high selectivity and scalability.However,OTS selectors suffer from poor endurance and stability which are persistent tricky problems for applica-tion.Here,we report on a multilayer OTS selector based on simple GeSe and doped-GeSe.The experimental results show im-proving selector performed extraordinary endurance up to 1010 and the fluctuation of threshold voltage is 2.5%.The reason for the improvement may lie in more interface states which strengthen the interaction among individual layers.These develop-ments pave the way towards tuning a new class of OTS materials engineering,ensuring improvement of electrical perform-ance.
基金the National Natural Science Foundation of China(No.52175103)。
文摘An autonomous altitude adjustment system for a stratospheric satellite(StratoSat)platform is proposed.This platform consists of a helium balloon,a ballonet,and a two-way blower.The helium balloon generates lift to balance the platform gravity.The two-way blower inflates and deflates the ballonet to regulate the buoyancy.Altitude adjustment is achieved by tracking the differential pressure difference(DPD),and a threshold switching strategy is used to achieve blower flow control.The vertical acceleration regulation ability is decided not only by the blower flow rate,but also by the designed margin of pressure difference(MPD).Pressure difference is a slow-varying variable compared with altitude,and it is adopted as the control variable.The response speed of the actuator to disturbance can be delayed,and the overshoot caused by the large inertia of the platform is inhibited.This method can maintain a high tracking accuracy and reduce the complexity of model calculation,thus improving the robustness of controller design.
基金National Natural Science Foundation of China,Grant/Award Number:62174060National Science and Technology Major Project of China,Grant/Award Number:2022ZD0117600Hubei Key Laboratory of Advanced Memory,and the Fundamental Research Funds for the Central Universities,Grant/Award Number:2021GCRC051。
文摘Chalcogenide glass has a unique volatile transition between high‐and low‐resistance states under an electric field,a phenomenon termed ovonic threshold switching(OTS).This characteristic is extensively uti-lized in various electronic memory and computational devices,particu-larly as selectors for cross‐point memory architectures.Despite its advantages,the material is susceptible to glass relaxation,which can result in substantial drifts in threshold voltage and a decline in off‐current performance over successive operational cycles or long storage time.In this study,we introduce an OTS device made from stoichio-metric Sb_(2)Se_(3) glass,which retains an octahedral local structure within its amorphous matrix.This innovative material exhibits outstanding OTS capabilities,maintaining minimal degradation despite undergoing over 10^(7) operating cycles.Via comprehensive first‐principles calculations,our findings indicate that the mid‐gap states in amorphous Sb_(2)Se_(3) predom-inantly stem from the atomic chains characterized by heteropolar Sb‐Se bonds.These bonds exhibit remarkable stability,showing minimal alteration over time,thereby contributing to the overall durability and consistent performance of the material.Our findings not only shed light on the complex physical origins that govern the OTS behavior but also lay the groundwork for creating or optimizing innovative electrical switching materials.
基金National Research Foundation of Korea(NRF),Grant/Award Numbers:2021M3F3A2A01037738,RS-2023-00262880Korea Institute of Science and Technology(KIST),Grant/Award Number:2E32960。
文摘Memristors have been emerging as promising candidates for computing systems in post-Moore applications,particularly electrochemical metallizationbased memristors,which are poised to play a crucial role in neuromorphic computing and machine learning.These devices are favored for their high integration density,low power consumption,rapid switching speed,and significant on/off ratio.Despite advancements in various materials,achieving adequate electrical performance—characterized by threshold switching(TS)behavior,spontaneous reset,and low off-state resistance—remains challenging due to the limitations in conductance filament control within the nanoscale resistive switching layer.In this study,we introduce an efficient method to control the ZrO_(2) crystallinity for tunable volatility memristor by establishing the filament paths through a simple thermal treatment process in a single oxide layer.The effect of ZrO_(2) crystallinity to create localized filament paths for enhancing Ag migration and improving TS behavior is also investigated.In contrast to its amorphous counterpart,crystallized ZrO_(2) volatile memristor,treated by rapid thermal annealing,demonstrates a steep switching slope(0.21 mV dec^(–1)),a high resistance state(25 GΩ),and forming-free characteristics.The superior volatile performance is attributed to localized conductive filaments along lowenergy pathways,such as dislocations and grain boundaries.By coupling with enhanced volatile switching behavior,we believe that the volatility is finely tuned to function as short-term memory for reservoir computing,making it particularly well-suited for tasks such as audio and image recognition.
基金supported by the National Key R&D Plan“Nano Frontier”Key Special Project(Grant No.2021YFA1200502)Cultivation Projects of National Major R&D Project(Grant No.92164109)+12 种基金the National Natural Science Foundation of China(Grant Nos.61874158,62004056,and 62104058)the Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(Grant No.XDB44000000-7)Key R&D Plan Projects in Hebei Province(Grant No.22311101D)Hebei Basic Research Special Key Project(Grant No.F2021201045)the Support Program for the Top Young Talents of Hebei Province(Grant No.70280011807)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(Grant No.SLRC2019018)the Interdisciplinary Research Program of Natural Science of Hebei University(No.DXK202101)the Institute of Life Sciences and Green Development(No.521100311)the Natural Science Foundation of Hebei Province(Nos.F2022201054 and F2021201022)the Outstanding Young Scientific Research and Innovation Team of Hebei University(Grant No.605020521001)the Special Support Funds for National High Level Talents(Grant No.041500120001)the Advanced Talents Incubation Program of the Hebei University(Grant Nos.521000981426,521100221071,and 521000981363)the Science and Technology Project of Hebei Education Department(Grant Nos.QN2020178 and QN2021026).
文摘The intrinsic variability of memristor switching behavior can be used as a natural source of randomness,this variability is valuable for safe applications in hardware,such as the true random number generator(TRNG).However,the speed of TRNG is still be further improved.Here,we propose a reliable Ag/SiNx/n-Si volatile memristor,which exhibits a typical threshold switching device with stable repeat ability and fast switching speed.This volatile-memristor-based TRNG is combined with nonlinear feedback shift register(NFSR)to form a new type of high-speed dual output TRNG.Interestingly,the bit generation rate reaches a high speed of 112 kb/s.In addition,this new TRNG passed all 15 National Institute of Standards and Technology(NIST)randomness tests without post-processing steps,proving its performance as a hardware security application.This work shows that the SiNx-based volatile memristor can realize TRNG and has great potential in hardware network security.
基金National Key R&D Plan of China(Grant No.2019YFB2205100,2017YFB0701700)National Science and Technology Major Project of China(Grant No.2017ZX02301007-002)+2 种基金National Natural Science Foundation of China(Grant No.62174060)Fundamental Research Funds for the Central Universities,HUST(No.2021GCRC051)Hubei Key Laboratory of Advanced Memories.
文摘The recent development of three-dimensional semiconductor integration technology demands a key component-the ovonic threshold switching(OTS)selector to suppress the current leakage in the high-density memory chips.Yet,the unsatisfactory performance of existing OTS materials becomes the bottleneck of the industrial advancement.The sluggish development of OTS materials,which are usually made from chalcogenide glass,should be largely attributed to the insufficient understanding of the electronic structure in these materials,despite of intensive research in the past decade.Due to the heavy first-principles computation on disordered systems,a universal theory to explain the origin of mid-gap states(MGS),which are the key feature leading to the OTS behavior,is still lacking.To avoid the formidable computational tasks,we adopt machine learning method to understand and predict MGS in typical OTS materials.We build hundreds of chalcogenide glass models and collect major structural features from both short-range order(SRO)and medium-range order(MRO)of the amorphous cells.After training the artificial neural network using these features,the accuracy has reached~95%when it recognizes MGS in new glass.By analyzing the synaptic weights of the input structural features,we discover that the bonding and coordination environments from SRO and particularly MRO are closely related to MGS.The trained model could be used in many other OTS chalcogenides after minor modification.The intelligent machine learning allows us to understand the OTS mechanism from vast amount of structural data without heavy computational tasks,providing a new strategy to design functional amorphous materials from first principles.
基金the financial supports from the National Natural Science Foundation of China(51872036,51773025)Dalian Science and Technology Innovation Fund(2018J12GX033)National Key R&D Program of China(2017YFB0405604)
文摘Organic-inorganic hybrid perovskites (OHPs) are well-known as light-absorbing materials in solar cells and have recently attracted considerable attention for the applications in resistive switching memory. Previous studies have shown that ions can migrate to form a conductive channel in perovskites under an external voltage. However, the exact resistance mechanism for Ag or halogens which dominate the resistive behavior is still controversial. Here, we demonstrate a resistive switching memory device based on Ag/FA0.83MA0.17Pb(I0.82Br0.18)3/fluorine doped tin oxide (FTO). The migration of Ag cations and halide anions is demonstrated by energy dispersive X-ray spectroscopy (EDS) after the SET process (positive voltage on Ag). By comparing the I-V behavior of the Au-based devices, it is clear that the conductive channel formed by Ag is the main factor of the switching characteristics for Ag-based devices. Meanwhile, by controlling the appropriate SET voltage, two kinds of resistance characteristics of the analog switch and threshold switch can be realized in the Ag-based device. As a result, it may be possible to implement both data storage and neuromorphic computing in a single device.
