Conductivity Modulation Research Articles

Nonvolatile memory characteristics associated with oxygen ion exchange in thin-film transistors with indium-zinc oxide channel and HfO2-x gate oxide

Non-charge-storage-based nonvolatile memory characteristics associated with oxygen ion exchange are demonstrated in a thin-film transistor (TFT) composed of an indium-zinc oxide (IZO) channel and an oxygen-deficient HfO2–x gate oxide. A nonvolatile increase in drain current and a reduced threshold voltage are obtained upon application of positive gate voltage, with the opposite characteristics upon application of negative voltage. The device shows nonvolatile retention properties and suitable endurance properties after repeated operations. Modulation of channel conductance occurs as a results of oxygen ion exchange between the HfO2–x gate oxide and the IZO channel, which consequently alters the oxygen vacancy concentration in the IZO channel; these vacancies act as n-type dopants. For comparison, a device with a thin SiO2 layer inserted between the HfO2–x gate oxide and the IZO channel to prevent oxygen ion exchange shows only the increased threshold voltage upon application of a positive gate voltage as a result of electron charging. These results verify the conductance modulation mechanism associated with oxygen ion exchange at the interface of the HfO2–x gate oxide and the IZO channel. In addition, the nonvolatile memory characteristics of the device are indicative of its potential for non-charge-storage-based nonvolatile memory application.

Infrared Nano-Imaging of Electronic Phase across the Metal–Insulator Transition of NdNiO3 Films

NdNiO3 is a typical correlated material with temperature-driven metal–insulator transition. Resolving the local electronic phase is crucial in understanding the driving mechanism behind the phase transition. Here we present a nano-infrared study of the metal–insulator transition in NdNiO3 films by a cryogenic scanning near-field optical microscope. The NdNiO3 films undergo a continuous transition without phase coexistence. The nano-infrared signal shows significant temperature dependence and a hysteresis loop. Stripe-like modulation of the optical conductivity is formed in the films and can be attributed to the epitaxial strain. These results provide valuable evidence to understand the coupled electronic and structural transformations in NdNiO3 films at the nano-scale.

HfOx /AlOy Superlattice-Like Memristive Synapse.

The adjustable conductance of a two‐terminal memristor in a crossbar array can facilitate vector‐matrix multiplication in one step, making the memristor a promising synapse for efficiently implementing neuromorphic computing. To achieve controllable and gradual switching of multi‐level conductance, important for neuromorphic computing, a theoretical design of a superlattice‐like (SLL) structure switching layer for the multi‐level memristor is proposed and validated, refining the growth of conductive filaments (CFs) and preventing CFs from the abrupt formation and rupture. Ti/(HfOx/AlOy)SLL/TiN memristors are shown with transmission electron microscopy , X‐ray photoelectron spectroscopy , and ab initio calculation findings corroborate the SLL structure of HfOx/AlOy film. The optimized SLL memristor achieves outstanding conductance modulation performance with linearly synaptic weight update (nonlinear factor α = 1.06), and the convolutional neural network based on the SLL memristive synapse improves the handwritten digit recognition accuracy to 94.95%. Meanwhile, this improved synaptic device has a fast operating speed (30 ns), a long data retention time (≥ 104 s at 85 ℃), scalability, and CMOS process compatibility. Finally, its physical nature is explored and the CF evolution process is characterized using nudged elastic band calculations and the conduction mechanism fitting. In this work, as an example the HfOx/AlOy SLL memristor provides a design viewpoint and optimization strategy for neuromorphic computing.

Photoconductance from the Bent-to-Planar Photocycle between Ground and Excited States in Single-Molecule Junctions.

Single-molecule conductance measurements for 9,14-diphenyl-9,14-dihydrodibenzo[a,c]phenazine (DPAC) may offer unique insight into the bent-to-planar photocycle between the ground and excited states. Herein, we employ DPAC derivative DPAC-SMe as the molecular prototype to fabricate single-molecule junctions using the scanning tunneling microscope break junction technique and explore photoconductance dependence on the excited-state structural/electronic changes. We find up to ∼200% conductance enhancement of DPAC-SMe under continuous 340 nm light irradiation than that without irradiation, while photoconductance disappears in the case where structural evolution of the DPAC-SMe is halted through macrocyclization. The in situ conductance modulation as pulsed 340 nm light irradiation is monitored in the DPAC-SMe-based junctions alone, suggesting that the photoconductance of DPAC-SMe stems from photoinduced intramolecular planarization. Theoretical calculations reveal that the photoinduced structural evolution brings about a significant redistribution of the electron cloud density, which leads to the appearance of Fano resonance, resulting in enhanced conductance through the DPAC-SMe-fabricated junctions. This work provides evidence of bent-to-planar photocycle-induced conductance differences at the single-molecule level, offering a tailored approach for tuning the charge transport characteristics of organic photoelectronic devices.

Impact on on-resistance of p-n junction diodes by using heavily Ge-doped GaN substrate

The characteristics of p-n junction diodes on heavily Ge-doped substrates were compared with those on conventional Si-doped substrates. A large decrease in on-resistance was observed which greatly exceeded the component due to the lower resistance of the Ge-doped substrate. This result implied an occurrence of a strong conductivity modulation by the heavily doped substrate. Current-density dependence on the anode-electrode diameter could be minimized by the use of the substrate. No significant difference was observed in the breakdown voltage even when the doping concentration in the substrate was increased. It has been clarified that the heavily Ge-doped GaN substrate is essential for low on-resistance and large size GaN power devices.

Ultra-broadband perfect terahertz absorber with periodic-conductivity graphene metasurface

We present an interesting scheme of ultra-broadband perfect terahertz (THz) absorber with periodic-conductivity graphene metasurface, instead of the common metasurfaces of geometrically patterned graphene with uniform conductivity. By exploiting periodic modulation of graphene conductivity, the graphene metasurface absorber produces a sequence of dense high-order resonance modes with near-perfect absorption peaks. The density of resonant modes can be largely enhanced to perform an ultra-broadband even continuum absorption in THz regime with suppression of the modulation minimum of graphene conductivity. Under the resistive loss effect of graphene on the modes broadening, the THz perfect absorber can perform a record ultra-broadband of 3.71 THz, which covers more than one-third of the whole THz region of 0.1–10 THz. Such scheme of periodic-conductivity graphene metasurface is of interest in pushing forward to broadband THz absorber, which has promising application prospects in THz stealth, imaging and communication fields.

Neural Network Training With Asymmetric Crosspoint Elements.

Analog crossbar arrays comprising programmable non-volatile resistors are under intense investigation for acceleration of deep neural network training. However, the ubiquitous asymmetric conductance modulation of practical resistive devices critically degrades the classification performance of networks trained with conventional algorithms. Here we first describe the fundamental reasons behind this incompatibility. Then, we explain the theoretical underpinnings of a novel fully-parallel training algorithm that is compatible with asymmetric crosspoint elements. By establishing a powerful analogy with classical mechanics, we explain how device asymmetry can be exploited as a useful feature for analog deep learning processors. Instead of conventionally tuning weights in the direction of the error function gradient, network parameters can be programmed to successfully minimize the total energy (Hamiltonian) of the system that incorporates the effects of device asymmetry. Our technique enables immediate realization of analog deep learning accelerators based on readily available device technologies.

Adjustable shunt-current intensity circuit and system for current conduction treatment of epilepsy

In this paper, we developed a shunt-current intensity self-adjustable closed-loop control circuit system for current conduction treatment in temporal lobe epilepsy. To examine the dose-response relationship between conductive intensity and therapeutic outcomes of current conduction treatment, the control system consists of neural signal recording module for high-speed data rate acquisition, signal amplification and pre-processing, current shunt module for current conduction, data transmission and control module for real-time data communication with the personal computer and on-off of current conduction. Multithread and queue software architecture was implemented to ensure real-time data transmission, display and analysis by LabVIEW software. Results indicate that the input noise of the system is less than 2 [Formula: see text]Vrms, signal frequency bandwidth range is 1 Hz[Formula: see text]10 kHz, and the shunt-current detection range is 0.1–3000 [Formula: see text]A with the accuracy of above 99.985%, meeting the requirements for the detection of neural electrophysiological signal and the research on the dose-response relationship between conductive intensity and therapeutic outcomes of electronic conduction treatment.

Computer and experimental study of field-induced conductivity modulation in liquid crystal–carbon nanotubes system

In this study, the possibility of percolation system conductivity control by the applied electric field has been researched based on computer simulation and experimental measurements of electrical characteristics of liquid crystal–carbon nanotubes nanocomposite. It was found that electrical resistance of obtained nanocomposites decreases with increasing nanotube concentration. It is shown that the applied voltage reduces the resistance of the nanocomposite, which is likely associated with the change in the spatial orientation of nanotubes. Nanocomposites with 2–4% nanotube content show the maximum field-controlled relative change in resistance. The effect of concentration and orientation of the nanotubes on the percolation processes in the carbon nanotube system has been studied by computer simulations. The change in the percolation probability was revealed when limiting nanotube orientation angles that are controlled by the electrical field.

Experimental study of maghemite nanomaterials towards sustainable energy storage device application

In this paper, the facile synthesis and characterization aspects of maghemite nanoparticles has been presented, in the context of energy storage device technology. An experimental study of the structural, magnetic, optical and thermal properties of cobalt and zinc doped maghemite nanoparticles prepared by coprecipitation of ferrous, ferric, and the dopant precursors in water at different temperatures and pH of ammonium hydroxide solution has been done. The structural characterization establishes that all the samples have high surface area and are highly crystalline, 5–10 nm spherical nanoparticles with the cubic spinel structure. The magnetization curve is steeply linear with saturation magnetization in the tune of 60 emu/gm. The magnetic characterization reveals peculiar trends with zinc and cobalt doping, main features being the increase in the saturation magnetization, coercivity with doping, and thermal stability. The high sensitivity evident from magnetization features can be used for state estimation of the energy storage devices. In comparison to 2.2 eV of the bulk maghemite, the optical band gap of the nanoparticles has been calculated as 3.9 eV, which can be modulated up to 4.67 eV with the doping reported herein, thus establishing the conductivity modulation strength of the synthesized samples. The thermal gravimetric analysis establishes the thermal stability of the maghemite. The affordability of the maghemite electrode iron batteries will surely be helpful for scaling up the renewable energy storage technology.

No significant contribution of hole-trap-enhanced conductivity modulation in GaN p+n diodes formed on low-dislocation-density GaN substrates

Influences of hole traps on large forward current (I F) of GaN p+n diodes on low-dislocation-density (≤4 × 105 cm−2) GaN substrates were numerically investigated. As with the reported simulation of GaAs p+n diodes, hole traps were found to increase the electron concentration in the drift layer when forward voltage V F was increased. To reproduce the measured I F/V F characteristics, however, we had to assume an unrealistic electron mobility increasing with the electric field. We, therefore, concluded that sources other than hole traps were responsible for the reported enhancement of conductivity modulation in GaN p+n diodes.

Application of SiGe layer for reinforcing conductivity modulation in trench insulated gate bipolar transistor

In this work, an investigation for inserting a SiGe layer in an insulated-gate bipolar transistor (IGBT) has been performed to analyze the relation between on-state property and breakdown voltage (BV) with the help of technology computer-aided design simulation. For a carrier storage (CS) IGBT, which is widely studied for enhancing conductivity modulation by increasing hole density, the BV decreases by increased conductivity in the CS layer. However, by using the SiGe layer instead of the CS layer, the on-state property is improved with lower BV reduction than a CS IGBT due to the absence of impurity doping. Finally, an optimization for a Ge mole fraction is performed. Based on the results, it is found that the SiGe with 0.3 mole fraction shows the best performance because over 0.3 Ge mole fraction, the excessive energy band bending induced by over-accumulated holes makes low carrier velocity in the n-drift layer.

Dual Modulation of Single Molecule Conductance via Tuning Side Chains and Electric Field with Conjugated Molecules Entailing Intramolecular O•••S Interactions.

Herein, single‐molecule conductance studies of TBT1‐TBT6 which entails 1,4‐dithienylbenzene as the backbone and —SMe groups as the anchoring units, with the scanning tunneling microscope break junction (STM‐BJ) technique, are reported. The molecular conductance of TBT1 with intramolecular O•••S noncovalent interactions is enhanced by about one order of magnitude in comparison to their analogue TBT2 (which contains alkyl instead of alkoxy chains). By replacing the methoxy groups in TBT1 with extending alkoxy chains in TBT3, TBT4, and TBT5, the molecular backbones become twisted and as a consequence the single‐molecule conductance decreases gradually, showing that the intramolecular O•••S noncovalent interaction is influenced by the structural features of alkoxy chains. More importantly, the single‐molecule conductance of TBT3, TBT4, and TBT5 can be boosted by increasing the electric field applied to the molecular junctions. Remarkably, the conductance of TBT3, TBT4, and TBT5 can be reversibly modulated due to the conformational changes between twisted and planar ones by varying the electric field. These results demonstrate that molecules with intramolecular O•••S noncovalent interactions have the potential for in situ control of the electrical properties of molecular‐scale devices.

Flexible Mott Synaptic Transistor on Polyimide Substrate for Physical Neural Networks

AbstractFlexible synaptic devices that emulate biological synapses are the key to developing wearable intelligent equipment. However, there are still challenges to achieving multiple synaptic functions in flexible synaptic devices and realizing large‐scale production of synaptic devices. Herein, a flexible synaptic transistor on polyimide substrate is designed and fabricated using a solid‐state electrolyte gate and a VO2 Mott insulator thin film channel. Four orders conductance modulation is obtained in the VO2 thin film channel across the metal‐insulator transition. Several essential synaptic behaviors, including potentiation, depression, and short‐term/long‐term plasticity, are successfully demonstrated in this flexible synaptic device. More importantly, this synaptic transistor exhibits high cycling stability and good tolerance to bending deformation. A simulated artificial neural network built from this synaptic device achieves high recognition accuracy of 98% in the flat state and 92% in the bending state. In addition, this flexible device is fabricated on polyimide substrate by magnetron sputtering method, which has low cost and is compatible with modern semiconductor technology. This work can pave the way for large‐scale production of flexible synaptic Mott transistor devices.

High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors

Threshold switching (TS) memristors can be used as artificial neurons in neuromorphic systems due to their continuous conductance modulation, scalable and energy-efficient properties. In this paper, we propose a low power artificial neuron based on the Ag/MXene/GST/Pt device with excellent TS characteristics, including a low set voltage (0.38 V) and current (200 nA), an extremely steep slope (< 0.1 mV/dec), and a relatively large off/on ratio (> 103). Besides, the characteristics of integrate and fire neurons that are indispensable for spiking neural networks have been experimentally demonstrated. Finally, its memristive mechanism is interpreted through the first-principles calculation depending on the electrochemical metallization effect.

Numerical simulation of the interfacial stress between epoxy resin and metal conductor of power equipment during epoxy curing

There are many metal and epoxy resin interfacial structures in power equipments, which can generate interfacial stress concentrations and may induce accidents due to epoxy curing. In this paper, through simplifying interface structure into a coaxial cylindrical model, the formation mechanism of interfacial stress concentration of this interface structure was studied during epoxy resin curing process. The strain and temperature at the interface were measured by the strain and temperature measurement system. Then a model for calculating the interface stress distribution was established, including the heat conduction module, curing dynamics module and curing deformation module. The validity of the model was verified by comparing the calculated results with the measured results. In addition, the air gap defects at the interface, appearing after the curing process, were simulated. The results show that, after the curing process, the first principal stress at the centre of the interface gradually increases from the centre to the edge, reaching 41.06 and 40.20 MPa at the upper and lower edges respectively. The existence of air gap leads to partial discharge at low voltage. The calculation model can be extended to the stress prediction between the metal and epoxy resin in other power equipments.

Investigation of electronic stabilities and properties of Mn-doped Janus WSSe monolayer

In this paper, the impact of Mn doping on Janus WSSe monolayer (WSSe ML) is investigated to insight the electronic stabilities and properties using first-principle DFT method. The electronic stability of both (pristine and doped) WSSe ML is confirmed with the calculation of formation energy (Eform) and binding energy (Eb) respectively. The total density of states (TDOS) analysis depict that the pristine state of WSSe monolayer shows non-magnetic behaviour and magnetic behaviour is induced after doping of 6.25% Mn-atom in WSSe monolayer which is alignment with the charge distribution. The percentage (%) spin-polarization has been discussed to explore Mn-doped WSSe monolayer for the spintronic applications. The band structure shows bandgap modulation from 1.71 eV to 0.30 eV after the Mn doping in WSSe monolayer. Consequently, work function (WF) and electronic conductivity (σ) for pristine and Mn doped WSSe monolayer is altered to 0.12eV and room temperature conductivity increased with the factor of ∼1011 respectively. The modulation of electronic conductivity further results in higher Sensitivity. Lastly, the high ION/IOFF ratio has been discussed to explore Mn-doped WSSe monolayer for device switching application. The calculated results are in good contract with the available stated values.

Electronic and Lattice Thermal Conductivity Switching by 3D−2D Crystal Structure Transition in Nonequilibrium (Pb1−xSnx)Se

AbstractDynamic control of thermal transport in solid materials is highly desired for thermal management technology. However, the development of a material exhibiting large modulation of thermal conductivity (κ) by external stimuli remains a major challenge. Here, the large κ modulation is reported by the reversible 3D to 2D crystal structure transition in a nonequilibrium solid solution of (Pb1−xSnx)Se, where Pb2+ stabilizes a 3D cubic structure while Sn2+ does a 2D layered structure. The phase boundary of these phases is induced in (Pb0.5Sn0.5)Se bulk polycrystals by thermally quenching the high‐temperature solid solution phase. Through the 3D–2D phase transition, the 1/2.9‐times decrease of lattice κ (κlat.) is achieved by strong phonon scattering in the 2D layered structure, and the electronic κ (κele.) is also decreased by 5 orders of magnitude due to the electronic phase transition from a 3D high conductivity state to a 2D semiconducting state. The total κ (=κlat. + κele.) modulation ratio κ3D phase/κ2D phase = 3.6 is attained at 373 K. The present strategy will lead to a novel concept for designing thermal management materials through crystal‐structure dimensionality switch using nonequilibrium phase boundaries.

Advanced Nickel-Based Catalysts for Urea Oxidation Reaction: Challenges and Developments

The electrochemical urea oxidation reaction (UOR) is crucial for determining industrial and commercial applications of urea-based energy conversion devices. However, the performance of UOR is limited by the dynamic complex of the six-electron transfer process. To this end, it is essential to develop efficient UOR catalysts. Nickel-based materials have been extensively investigated owing to their high activity, easy modification, stable properties, and cheap and abundant reserves. Various material designs and strategies have been investigated in producing highly efficient UOR catalysts including alloying, doping, heterostructure construction, defect engineering, micro functionalization, conductivity modulation, etc. It is essential to promptly review the progress in this field to significantly inspire subsequent studies. In this review, we summarized a comprehensive investigation of the mechanisms of oxidation or poisoning and UOR processes on nickel-based catalysts as well as different approaches to prepare highly active catalysts. Moreover, challenges and prospects for future developments associated with issues of UOR in urea-based energy conversion applications were also discussed.

Spatially inhomogeneous operation of phase-change memory

Rapid changes in the electrical resistance depending on the phases (amorphous and crystal) are one of the most promising bases for universal memory. Phase-change region is spatially inhomogeneous during memory operation in a unit cell because Joule heat for the phase-change is generated at the interface between the metal and compounds. However, delicate optimization of the electrical and thermal properties at the interface is underexplored compared to the bulk. In this study, we modulate the electrical and thermal conductivities by incorporating oxygen in Ag-In-Sb-Te, superior memory compounds where oxygen is chosen for high accessibility and efficiency for the modulation of conductivity. We further analyze the oxidation and crystallization process at the atomic level. Based on the results, we successfully improve the memory performances such as speed, energy, signal ratio, and reliability simultaneously by inserting the oxygenated layer as an interfacial layer. Our study proves that there is considerable room to optimize memory performance at the interface.