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Since the discovery of graphene and its remarkable properties, researchers have actively explored advanced graphene-patterning technologies. While the etching process is pivotal in shaping graphene channels, existing etching techniques have limitations such as low speed, high cost, residue contamination, and rough edges. Therefore, the development of facile and efficient etching methods is necessary. This study entailed the development of a novel technique for patterning graphene through dry etching, utilizing selective photochemical reactions precisely targeted at single-layer graphene (SLG) surfaces. This process is facilitated by an excimer ultraviolet lamp emitting light at a wavelength of 172 nm. The effectiveness of this technique in selectively removing SLG over large areas, leaving the few-layer graphene intact and clean, was confirmed by various spectroscopic analyses. Furthermore, we explored the application of this technique to device fabrication, revealing its potential to enhance the electrical properties of SLG-based devices. One-dimensional (1D) edge contacts fabricated using this method not only exhibited enhanced electrical transport characteristics compared to two-dimensional contact devices but also demonstrated enhanced efficiency in fabricating conventional 1D-contacted devices. This study addresses the demand for advanced technologies suitable for next-generation graphene devices, providing a promising and versatile graphene-patterning approach with broad applicability and high efficiency.
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As there is an increasing need for an efficient solver of combinatorial optimization problems, much interest is paid to the Ising machine, which is a novel physics-driven computing system composed of coupled oscillators mimicking the dynamics of the system of coupled electronic spins. In this work, we propose an energy-efficient nano-oscillator, called OTSNO, which is composed of an Ovonic Threshold Switch (OTS) and an electrical resistor. We demonstrate that the OTSNO shows the synchronization behavior, an essential property for the realization of an Ising machine. Furthermore, we have discovered that the capacitive coupling is advantageous over the resistive coupling for the hardware implementation of an Ising solver by providing a larger margin of the variations of components. Finally, we implement an Ising machine composed of capacitively-coupled OTSNOs to demonstrate that the solution to a 14-node MaxCut problem can be obtained in 40 µs while consuming no more than 2.3 µJ of energy. Compared to a previous hardware implementation of the phase-transition nano-oscillator (PTNO)-based Ising machine, the OTSNO-based Ising machine in this work shows the performance of the increased speed by more than one order while consuming less energy by about an order.
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Field-effect transistor-based biosensors have gained increasing interest due to their reactive surface to external stimuli and the adaptive feedback required for advanced sensing platforms in biohybrid neural interfaces. However, complex probing methods for surface functionalization remain a challenge that limits the industrial implementation of such devices. Herein, a simple, label-free biosensor based on molybdenum oxide (MoO3) with dopamine-regulated plasticity is demonstrated. Dopamine oxidation facilitated locally at the channel surface initiates a charge transfer mechanism between the molecule and the oxide, altering the channel conductance and successfully emulating the tunable synaptic weight by neurotransmitter activity. The oxygen level of the channel is shown to heavily affect the device's electrochemical properties, shifting from a nonreactive metallic characteristic to highly responsive semiconducting behavior. Controllable responsivity is achieved by optimizing the channel's dimension, which allows the devices to operate in wide ranges of dopamine concentration, from 100 nM to sub-mM levels, with excellent selectivity compared with K+, Na+, and Ca2+.
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Vertical two-terminal synaptic devices based on resistive switching have shown great potential for emulating biological signal processing and implementing artificial intelligence learning circuitries. To mimic heterosynaptic behaviors in vertical two-terminal synaptic devices, an additional terminal is required for neuromodulator activity. However, adding an extra terminal, such as a gate of the field-effect transistor, may lead to low scalability. In this study, a vertical two-terminal Pt/bilayer Sr1.8Ag0.2Nb3O10 (SANO) nanosheet/Nb:SrTiO3 (Nb:STO) device emulates heterosynaptic plasticity by controlling the number of trap sites in the SANO nanosheet via modulation of the tunneling current. Similar to biological neuromodulation, we modulated the synaptic plasticity, pulsed pair facilitation, and cutoff frequency of a simple two-terminal device. Therefore, our synaptic device can add high-level learning such as associative learning to a neuromorphic system with a simple cross-bar array structure.
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The paradigm shift of information carriers from charge to spin has long been awaited in modern electronics. The invention of the spin-information transistor is expected to be an essential building block for the future development of spintronics. Here, a proof-of-concept experiment of a magnetic skyrmion transistor working at room temperature, which has never been demonstrated experimentally, is introduced. With the spatially uniform control of magnetic anisotropy, the shape and topology of a skyrmion when passing the controlled area can be maintained. The findings will open a new route toward the design and realization of skyrmion-based spintronic devices in the near future.
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Graphene oxides with different degrees of oxidation are prepared by controlling UV irradiation on graphene, and the charge transport and the evolution of the transport gap are investigated according to the extent of oxidation. With increasing oxygenous defect density nD, a transition from ballistic to diffusive conduction occurs at nD≃1012 cm-2 and the transport gap grows in proportion to nD. Considering the potential fluctuation related to the e-h puddle, the bandgap of graphene oxide is deduced to be Eg≃30nD(1012cm-2) meV. The temperature dependence of conductivity showed metal-insulator transitions at nD≃0.3×1012 cm-2, consistent with Ioffe-Regel criterion. For graphene oxides at nD≥4.9×1012 cm-2, analysis indicated charge transport occurred via 2D variable range hopping conduction between localized sp2 domain. Our work elucidates the transport mechanism at different extents of oxidation and supports the possibility of adjusting the bandgap with oxygen content.
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In the era of "big data," the cognitive system of the human brain is being mimicked through hardware implementation of highly accurate neuromorphic computing by progressive weight update in synaptic electronics. Low-energy synaptic operation requires both low reading current and short operation time to be applicable to large-scale neuromorphic computing systems. In this study, an energy-efficient synaptic device is implemented comprising a Ni/Pb(Zr0.52 Ti0.48 )O3 (PZT)/0.5 wt.% Nb-doped SrTiO3 (Nb:STO) heterojunction with a low reading current of 10 nA and short operation time of 20-100 ns. Ultralow femtojoule operation below 9 fJ at a synaptic event, which is comparable to the energy required for synaptic events in the human brain (10 fJ), is achieved by adjusting the Schottky barrier between the top electrode and ferroelectric film. Moreover, progressive domain switching in ferroelectric PZT successfully induces both low nonlinearity/asymmetry and good stability of the weight update. The synaptic device developed here can facilitate the development of large-scale neuromorphic arrays for artificial neural networks with low energy consumption and high accuracy.
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Plasticidade Neuronal , Semicondutores , Computadores , Eletrônica , Humanos , Metais , Redes Neurais de ComputaçãoRESUMO
As the amount of data has grown exponentially with the advent of artificial intelligence and the Internet of Things, computing systems with high energy efficiency, high scalability, and high processing speed are urgently required. Unlike traditional digital computing, which suffers from the von Neumann bottleneck, brain-inspired computing can provide efficient, parallel, and low-power computation based on analog changes in synaptic connections between neurons. Synapse nodes in brain-inspired computing have been typically implemented with dozens of silicon transistors, which is an energy-intensive and non-scalable approach. Ion-movement-based synaptic devices for brain-inspired computing have attracted increasing attention for mimicking the performance of the biological synapse in the human brain due to their low area and low energy costs. This paper discusses the recent development of ion-movement-based synaptic devices for hardware implementation of brain-inspired computing and their principles of operation. From the perspective of the device-level requirements for brain-inspired computing, we address the advantages, challenges, and future prospects associated with different types of ion-movement-based synaptic devices.
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The function of a neural circuit can be determined by the following: (1) characteristics of individual neurons composing the circuit, (2) their distinct connection structure, and (3) their neural circuit activity. However, prior research on correlations between these three factors revealed many limitations. In particular, profiling and modeling of the connectivity of complex neural circuits at the cellular level are highly challenging. To reduce the burden of the analysis, we suggest a new approach with simplification of the neural connection in an array of honeycomb patterns on 2D, using a microcontact printing technique. Through a series of guided neuronal growths in defined honeycomb patterns, a simplified neuronal circuit was achieved. Our approach allowed us to obtain the whole network connectivity at cellular resolution using a combination of stochastic multicolor labeling via viral transfection. Therefore, we were able to identify several types of hub neurons with distinct connectivity features. We also compared the structural differences between different circuits using three-node motif analysis. This new model system, iCANN, is the first experimental model of neural computation at the cellular level, providing neuronal circuit structures for the study of the relationship between anatomical structure and function of the neuronal network.
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Semiconductors have long been perceived as a prerequisite for solid-state transistors. Although switching principles for nanometer-scale devices have emerged based on the deployment of two-dimensional (2D) van der Waals heterostructures, tunneling and ballistic currents through short channels are difficult to control, and semiconducting channel materials remain indispensable for practical switching. In this study, we report a semiconductor-less solid-state electronic device that exhibits an industry-applicable switching of the ballistic current. This device modulates the field emission barrier height across the graphene-hexagonal boron nitride interface with ION/IOFF of 106 obtained from the transfer curves and adjustable intrinsic gain up to 4, and exhibits unprecedented current stability in temperature range of 15-400 K. The vertical device operation can be optimized with the capacitive coupling in the device geometry. The semiconductor-less switching resolves the long-standing issue of temperature-dependent device performance, thereby extending the potential of 2D van der Waals devices to applications in extreme environments.
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Temperature-independent magnetoresistance (TIMR) has been studied for applications in magnetic field sensors operating in wide temperature ranges. Graphene is considered as one of the best candidates for achieving nonsaturating and large TIMR through engineering disorders. Nevertheless, large TIMR has not been achieved in disordered graphene with intrinsic defects, such as chemical doping and atomic dislocations. In this work, by introducing extrinsic defects, we realize nonsaturating and large TIMR in monolayer graphene transferred on a BiFeO3 nanoisland array (G/BFO-NIA). Furthermore, the G/BFO-NIA device exhibits a significantly larger MR (â¼250% under 9 T) than other materials without gating operation, demonstrating its application feasibility. It is shown that the large MR is a result of the coexistence of electrons and holes with almost the same density, and the observed TIMR originates from the temperature dependence of carrier transport in graphene and of the dielectric property of BFO-NIA.
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Mammalian embryos exhibit a transition from head morphogenesis to trunk elongation to meet the demand of axial elongation. The caudal neural tube (NT) is formed with neural progenitors (NPCs) derived from neuromesodermal progenitors localized at the tail tip. However, the molecular and cellular basis of elongating NT morphogenesis is yet elusive. Here, we provide evidence that caudal NPCs exhibit strong adhesion affinity that is gradually decreased along the anteroposterior (AP) axis in mouse embryonic spinal cord and human cellular models. Strong cell-cell adhesion causes collective migration, allowing AP alignment of NPCs depending on their birthdate. We further validated that this axial adhesion gradient is associated with the extracellular matrix and is under the control of graded Wnt signaling emanating from tail buds and antagonistic retinoic acid (RA) signaling. These results suggest that progressive reduction of NPC adhesion along the AP axis is under the control of Wnt-RA molecular networks, which is essential for a proper elongation of the spinal cord.
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Padronização Corporal , Movimento Celular , Células-Tronco Neurais/citologia , Medula Espinal/citologia , Medula Espinal/embriologia , Tretinoína/metabolismo , Proteínas Wnt/metabolismo , Animais , Padronização Corporal/genética , Adesão Celular/genética , Movimento Celular/genética , Matriz Extracelular/genética , Perfilação da Expressão Gênica , Regulação da Expressão Gênica no Desenvolvimento , Camundongos Transgênicos , Modelos Biológicos , Células-Tronco Neurais/metabolismo , Tubo Neural/citologia , Tubo Neural/embriologia , Transdução de Sinais/genéticaRESUMO
Two-dimensional (2D)-layered semiconducting materials with considerable band gaps are emerging as a new class of materials applicable to next-generation devices. Particularly, black phosphorus (BP) is considered to be very promising for next-generation 2D electrical and optical devices because of its high carrier mobility of 200-1000 cm2 V-1 s-1 and large on/off ratio of 104 to 105 in field-effect transistors (FETs). However, its environmental instability in air requires fabrication processes in a glovebox filled with nitrogen or argon gas followed by encapsulation, passivation, and chemical functionalization of BP. Here, we report a new method for reduction of BP-channel devices fabricated without the use of a glovebox by galvanic corrosion of an Al overlayer. The reduction of BP induced by an anodic oxidation of Al overlayer is demonstrated through surface characterization of BP using atomic force microscopy, Raman spectroscopy, and X-ray photoemission spectroscopy along with electrical measurement of a BP-channel FET. After the deposition of an Al overlayer, the FET device shows a significantly enhanced performance, including restoration of ambipolar transport, high carrier mobility of 220 cm2 V-1 s-1, low subthreshold swing of 0.73 V/decade, and low interface trap density of 7.8 × 1011 cm-2 eV-1. These improvements are attributed to both the reduction of the BP channel and the formation of an Al2O3 interfacial layer resulting in a high- k screening effect. Moreover, ambipolar behavior of our BP-channel FET device combined with charge-trap behavior can be utilized for implementing reconfigurable memory and neuromorphic computing applications. Our study offers a simple device fabrication process for BP-channel FETs with high performance using galvanic oxidation of Al overlayers.
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The manipulation of local ionic behavior via external stimuli in oxide systems is of great interest because it can help in directly tuning material properties. Among external stimuli, mechanical force has attracted intriguing attention as novel stimulus for ionic modulation. Even though effectiveness of mechanical force on local ionic modulation has been validated in terms of static effect, its real-time i.e., dynamic, behavior under an application of the force is barely investigated in spite of its crucial impact on device performance such as force or pressure sensors. In this study, we explore dynamic ionic behavior modulated by mechanical force in NiO thin films using electrochemical strain microscopy (ESM). Ionically mediated ESM hysteresis loops were significantly varied under an application of mechanical force. Based on these results, we were able to investigate relative relationship between the force and voltage effects on ionic motion and, further, control effectively ionic behavior through combination of mechanical and electrical stimuli. Our results can provide comprehensive information on the effect of mechanical forces on ionic dynamics in ionic systems.
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Vanadium dioxide (VO2) is a strong-correlated metal-oxide with a sharp metal-insulator transition (MIT) for a range of applications. However, synthesizing epitaxial VO2 films with desired properties has been a challenge because of the difficulty in controlling the oxygen stoichiometry of VO x, where x can be in the range of 1 < x < 2.5 and V has multiple valence states. Herein, a unique moisture-assisted chemical solution approach has been developed to successfully manipulate the oxygen stoichiometry, to significantly broaden the growth window, and to significantly enhance the MIT performance of VO2 films. The obvious broadening of the growth window of stoichiometric VO2 thin films, from 4 to 36 °C, is ascribed to a self-adjusted process for oxygen partial pressure at different temperatures by introducing moisture. A resistance change as large as 4 orders of magnitude has been achieved in VO2 thin films with a sharp transition width of less than 1 °C. The much enhanced MIT properties can be attributed to the higher and more uniform oxygen stoichiometry. This technique is not only scientifically interesting but also technologically important for fabricating wafer-scaled VO2 films with uniform properties for practical device applications.
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An oxide-based resistance memory is a leading candidate to replace Si-based flash memory as it meets the emerging specifications for future memory devices. The non-uniformity in the key switching parameters and low endurance in conventional resistance memory devices are preventing its practical application. Here, a novel strategy to overcome the aforementioned challenges has been unveiled by tuning the growth direction of epitaxial brownmillerite SrFeO2.5 thin films along the SrTiO3 [111] direction so that the oxygen vacancy channels can connect both the top and bottom electrodes rather directly. The controlled oxygen vacancy channels help reduce the randomness of the conducting filament (CF). The resulting device displayed high endurance over 106 cycles, and a short switching time of â¼10 ns. In addition, the device showed very high uniformity in the key switching parameters for device-to-device and within a device. This work demonstrates a feasible example for improving the nanoscale device performance by controlling the atomic structure of a functional oxide layer.
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Selectively activated inorganic synaptic devices, showing a high on/off ratio, ultrasmall dimensions, low power consumption, and short programming time, are required to emulate the functions of high-capacity and energy-efficient reconfigurable human neural systems combining information storage and processing ( Li et al. Sci. Rep. 2014 , 4 , 4096 ). Here, we demonstrate that such a synaptic device is realized using a Ag/PbZr0.52Ti0.48O3 (PZT)/La0.8Sr0.2MnO3 (LSMO) ferroelectric tunnel junction (FTJ) with ultrathin PZT (thickness of â¼4 nm). Ag ion migration through the very thin FTJ enables a large on/off ratio (107) and low energy consumption (potentiation energy consumption = â¼22 aJ and depression energy consumption = â¼2.5 pJ). In addition, the simple alignment of the downward polarization in PZT selectively activates the synaptic plasticity of the FTJ and the transition from short-term plasticity to long-term potentiation.
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Accurate and precise determination of mechanical properties of nanoscale materials is mandatory since device performances of nanoelectromechanical systems (NEMS) are closely related to the flexural properties of the materials. In this study, the intrinsic mechanical properties of highly stressed silicon nitride (SiN) beams of varying lengths are investigated using two different techniques: Dynamic flexural measurement using optical interferometry and quasi-static flexural measurement using atomic force microscopy. The resonance frequencies of the doubly clamped, highly stressed beams are found to be inversely proportional to their length, which is not usually observed from a beam but is expected from a string-like structure. The mass density of the SiN beams can be precisely determined from the dynamic flexural measurements by using the values for internal stress and Young's modulus determined from the quasi-static measurements. As a result, the mass resolution of the SiN beam resonators was predicted to be a few attograms, which was found to be in excellent agreement with the experimental results. This work suggests that accurate and precise determination of mechanical properties can be achieved through combined flexural measurement techniques, which is a crucial key for designing practical NEMS applications such as biomolecular sensors and gas detectors.
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The room-temperature resistive switching characteristics of ferroelectric, ferroelastic, and multiferroic materials are promising for application in nonvolatile memory devices. These resistive switching characteristics can be accompanied by a change in the ferroic order parameters via applied external electric and magnetic excitations. However, the dynamic evolution of the order parameters between two electrodes, which is synchronized with resistive switching, has rarely been investigated. In this study, for the first time, we directly monitor the ferroelectric/ferroelastic domain switching dynamics between two electrodes in multiferroic BiFeO3 (BFO) planar devices, which cause resistive switching, using piezoresponse force microscopy. It is demonstrated that the geometrical relationship between the ferroelectric domain and electrode in BFO planar capacitors with only 71° domain walls significantly affects both the ferroelectric domain dynamics and the resistive switching. The direct observation of domain dynamics relevant to resistive switching in planar devices may pave the way to a controllable combination of ferroelectric characteristics and resistive switching in multiferroic materials.
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Interaction between electrons has long been a focused topic in condensed-matter physics since it has led to the discoveries of astonishing phenomena, for example, high-Tc superconductivity and colossal magnetoresistance (CMR) in strongly-correlated materials. In the study of strongly-correlated perovskite oxides, Nb-doped SrTiO3 (Nb:SrTiO3) has been a workhorse not only as a conducting substrate, but also as a host possessing high carrier mobility. In this work, we report the observations of large linear magnetoresistance (LMR) and the metal-to-insulator transition (MIT) induced by magnetic field in heavily-doped Nb:STO (SrNb0.2Ti0.8O3) epitaxial thin films. These phenomena are associated with the interplay between the large classical MR due to high carrier mobility and the electronic localization effect due to strong spin-orbit coupling, implying that heavily Nb-doped Sr(Nb0.2Ti0.8)O3 is promising for the application in spintronic devices.