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To address the extended development cycle, high costs, and maintenance difficulties associated with existing microgravity simulation methods, this study has developed a semi-physical simulation platform for robotic arms tailored to different gravity environments and loading conditions. The platform represents difficult-to-model joints as physical objects, while the easily modeled components are simulated based on principles of similarity. In response to the strong coupling, nonlinearity, and excess force disturbance issues in the electric variable load loading system, a fractional-order linear active disturbance rejection control algorithm was employed. The controller parameters were tuned using an improved particle swarm algorithm with modified weight coefficients, and experimental results demonstrate that a fractional-order linear active disturbance rejection control improves response speed and disturbance rejection performance compared to linear sliding mode control. The study investigated the differences in the drive force of joint motors in space robotic arms under varying gravity environments and loading conditions. Experimental results indicate that load torque is the primary influencing factor on joint motor drive force, while radial force serves as a secondary influencing factor. Additionally, when the axis of the joint motor is perpendicular to the ground, it can, to some extent, simulate microgravity conditions on the ground.
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Reservoir computing (RC) has attracted considerable attention for its efficient handling of temporal signals and lower training costs. As a nonlinear dynamic system, RC can map low-dimensional inputs into high-dimensional spaces and implement classification using a simple linear readout layer. The memristor exhibits complex dynamic characteristics due to its internal physical processes, which renders them an ideal choice for the implementation of physical reservoir computing (PRC) systems. This review focuses on PRC systems based on memristors, explaining the resistive switching mechanism at the device level and emphasizing the tunability of their dynamic behavior. The development of memristor-based reservoir computing systems is highlighted, along with discussions on the challenges faced by this field and potential future research directions.
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Ferroelectric materials have switchable electrical polarization that is appealing for high-density nonvolatile memories. However, inevitable fatigue hinders practical applications of these materials. Fatigue-free ferroelectric switching could dramatically improve the endurance of such devices. We report a fatigue-free ferroelectric system based on the sliding ferroelectricity of bilayer 3R molybdenum disulfide (3R-MoS2). The memory performance of this ferroelectric device does not show the wake-up effect at low cycles or a substantial fatigue effect after 106 switching cycles under different pulse widths. The total stress time of the device under an electric field is up to 105 s, which is long relative to other devices. Our theoretical calculations reveal that the fatigue-free feature of sliding ferroelectricity is due to the immobile charge defects in sliding ferroelectricity.
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This work explores the polynomial fuzzy stabilization for positive systems. The traditional quadratic Lyapunov function and basic stability analysis may not be favourable for stability investigation due to the absence of the positivity property and membership functions. Therefore, a fuzzy co-positive polynomial Lyapunov-Krasovskii (FCPL) function which considers the positivity is proposed firstly through an imperfect premise matching (IPM) approach. Secondly, the symbol transfer technique which takes into account fuzzy membership knowledge relaxes the stability conditions. The number of symbols is reduced by two constraints: (1) the last and next moments of the membership functions of the FCPL function; (2) membership functions of the fuzzy model and the controller. Finally, the polynomial fuzzy controller with symbols is obtained. Two examples are implemented to verify the proposed methods.
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The development of new near-infrared-responsive photocatalysts is a fascinating and challenging approach to acquire high photocatalytic hydrogen evolution (PHE) performance. Herein, near-infrared-responsive black CuVP2S6 and CuCrP2S6 flakes, as well as CuInP2S6 flakes, are designed and constructed for PHE. Atom-resolved scanning transmission electron microscopy images and X-ray absorption fine structure evidence the formation of ultrathin single-crystalline sheet-like structure of CuVP2S6 and CuCrP2S6. The synthetic CuVP2S6 and CuCrP2S6, with a narrow bandgap of ≈1.0 eV, shows the high light-absorption edge exceeding 1100 nm. Moreover, through the femtosecond-resolved transient absorption spectroscopy, CuCrP2S6 displays the efficient charge transfer and long charge lifetime (18318.1 ps), which is nearly 3 and 29 times longer than that of CuVP2S6 and CuInP2S6, respectively. In addition, CuCrP2S6, with the appropriate d-band and p-band, is thermodynamically favorable for the H+ adsorption and H2 desorption by contrast with CuVP2S6 and CuInP2S6. As a result, CuCrP2S6 exhibits high PHE rates of 9.12 and 0.66 mmol h-1 g-1 under simulated sunlight and near-infrared light irradiation, respectively, far exceeding other layered metal phospho-sulfides. This work offers a distinctive perspective for the development of new near-infrared-responsive photocatalysts.
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Topological materials with boundary (surface/edge/hinge) states have attracted tremendous research interest. Additionally, unconventional (obstructed atomic) materials have recently drawn lots of attention owing to their obstructed boundary states. Experimentally, Josephson junctions (JJs) constructed on materials with boundary states produce the peculiar boundary supercurrent, which was utilized as a powerful diagnostic approach. Here, we report the observations of boundary supercurrent in NiTe2-based JJs. Particularly, applying an in-plane magnetic field along the Josephson current can rapidly suppress the bulk supercurrent and retain the nearly pure boundary supercurrent, namely the magnetic field filtering of supercurrent. Further systematic comparative analysis and theoretical calculations demonstrate the existence of unconventional nature and obstructed hinge states in NiTe2, which could produce hinge supercurrent that accounts for the observation. Our results reveal the probable hinge states in unconventional metal NiTe2, and demonstrate in-plane magnetic field as an efficient method to filter out the bulk contributions and thereby to highlight the hinge states hidden in topological/unconventional materials.
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Memristors offer a promising solution to address the performance and energy challenges faced by conventional von Neumann computer systems. Yet, stochastic ion migration in conductive filament often leads to an undesired performance tradeoff between memory window, retention, and endurance. Herein, a robust memristor based on oxygen-rich SnO2 nanoflowers switching medium, enabled by seed-mediated wet chemistry, to overcome the ion migration issue for enhanced analog in-memory computing is reported. Notably, the interplay between the oxygen vacancy (Vo) and Ag ions (Ag+) in the Ag/SnO2/p++-Si memristor can efficiently modulate the formation and abruption of conductive filaments, thereby resulting in a high on/off ratio (>106), long memory retention (10-year extrapolation), and low switching variability (SV = 6.85%). Multiple synaptic functions, such as paired-pulse facilitation, long-term potentiation/depression, and spike-time dependent plasticity, are demonstrated. Finally, facilitated by the symmetric analog weight updating and multiple conductance states, a high image recognition accuracy of ≥ 91.39% is achieved, substantiating its feasibility for analog in-memory computing. This study highlights the significance of synergistically modulating conductive filaments in optimizing performance trade-offs, balancing memory window, retention, and endurance, which demonstrates techniques for regulating ion migration, rendering them a promising approach for enabling cutting-edge neuromorphic applications.
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The control of robot manipulator pose is significantly complicated by the uncertainties arising from flexible joints, presenting substantial challenges in incorporating practical operational constraints. These challenges are further exacerbated in teleoperation scenarios, where factors such as synchronization and external disturbances further amplify the difficulties. At the core of this research is the introduction of a pioneering teleoperation controller, ingeniously integrating a nonlinear extended state observer (ESO) with the barrier Lyapunov function (BLF) while effectively accommodating a steady time delay. The controller in our study demonstrates exceptional proficiency in accurately estimating uncertainties arising from both flexible joints and external disturbances using the nonlinear ESO. Refined estimates, in conjunction with operational constraints of the system, are integrated into our BLF-based controller. Consequently, a synchronized control mechanism for teleoperation is achieved, exhibiting promising performance. Importantly, our experimental findings provide substantial evidence that our proposed approach effectively reduces the tracking error of the teleoperation system to within 0.02 rad. This advancement highlights the potential of our controller in significantly enhancing the precision and reliability of teleoperated robot manipulators.
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In recent years, there has been growing interest in functional devices based on two-dimensional (2D) materials, which possess exotic physical properties. With an ultrathin thickness, the optoelectrical and electrical properties of 2D materials can be effectively tuned by an external field, which has stimulated considerable scientific activities. Ferroelectric fields with a nonvolatile and electrically switchable feature have exhibited enormous potential in controlling the electronic and optoelectronic properties of 2D materials, leading to an extremely fertile area of research. Here, we review the 2D materials and relevant devices integrated with ferroelectricity. This review starts to introduce the background about the concerned themes, namely 2D materials and ferroelectrics, and then presents the fundamental mechanisms, tuning strategies, as well as recent progress of the ferroelectric effect on the optical and electrical properties of 2D materials. Subsequently, the latest developments of 2D material-based electronic and optoelectronic devices integrated with ferroelectricity are summarized. Finally, the future outlook and challenges of this exciting field are suggested.
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Optoelectronic memristors (OMs) have emerged as a promising optoelectronic Neuromorphic computing paradigm, opening up new opportunities for neurosynaptic devices and optoelectronic systems. These OMs possess a range of desirable features including minimal crosstalk, high bandwidth, low power consumption, zero latency, and the ability to replicate crucial neurological functions such as vision and optical memory. By incorporating large-scale parallel synaptic structures, OMs are anticipated to greatly enhance high-performance and low-power in-memory computing, effectively overcoming the limitations of the von Neumann bottleneck. However, progress in this field necessitates a comprehensive understanding of suitable structures and techniques for integrating low-dimensional materials into optoelectronic integrated circuit platforms. This review aims to offer a comprehensive overview of the fundamental performance, mechanisms, design of structures, applications, and integration roadmap of optoelectronic synaptic memristors. By establishing connections between materials, multilayer optoelectronic memristor units, and monolithic optoelectronic integrated circuits, this review seeks to provide insights into emerging technologies and future prospects that are expected to drive innovation and widespread adoption in the near future.
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The 2D ternary transition metal phosphorous chalcogenides (TMPCs) have attracted extensive research interest due to their widely tunable band gap, rich electronic properties, inherent magnetic and ferroelectric properties. However, the synthesis of TMPCs via chemical vapor deposition (CVD) is still challenging since it is difficult to control reactions among multi-precursors. Here, a subtractive element growth mechanism is proposed to controllably synthesize the TMPCs. Based on the growth mechanism, the TMPCs including FePS3 , FePSe3 , MnPS3 , MnPSe3 , CdPS3 , CdPSe3 , In2 P3 S9 , and SnPS3 are achieved successfully and further confirmed by Raman, second-harmonic generation (SHG), and scanning transmission electron microscopy (STEM). The typical TMPCs-SnPS3 shows a strong SHG signal at 1064 nm, with an effective nonlinear susceptibility χ(2) of 8.41 × 10-11 m V-1 , which is about 8 times of that in MoS2 . And the photodetector based on CdPSe3 exhibits superior detection performances with responsivity of 582 mA W-1 , high detectivity of 3.19 × 1011 Jones, and fast rise time of 611 µs, which is better than most previously reported TMPCs-based photodetectors. These results demonstrate the high quality of TMPCs and promote the exploration of the optical properties of 2D TMPCs for their applications in optoelectronics.
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To enhance the efficiency of catalysis, it is crucial to comprehend the behavior of individual nanowires/nanosheets. A developed on-chip microcell facilitates this study by creating a reaction window that exposes the catalyst region of interest. However, this technology's potential application is limited due to frequently-observed variations in data between different cells. In this study, we identify a conductance problem in the reaction windows of non-metallic catalysts as the cause of this issue. We investigate this problem using in-situ electronic/electrochemical measurements and atom-thin nanosheets as model catalysts. Our findings show that a full-open window, which exposes the entire catalyst channel, allows for efficient modulation of conductance, which is ten times higher than a half-open window. This often-overlooked factor has the potential to significantly improve the conductivity of non-metallic catalysts during the reaction process. After examining tens of cells, we develop a vertical microcell strategy to eliminate the conductance issue and enhance measurement reproducibility. Our study offers guidelines for conducting reliable microcell measurements on non-metallic single nanowire/nanosheet catalysts.
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Due to its inversion-broken triple helix structure and the nature of Weyl semiconductor, 2D Tellurene (2D Te) is promising to possess a strong nonlinear optical response in the infrared region, which is rarely reported in 2D materials. Here, a giant nonlinear infrared response induced by large Berry curvature dipole (BCD) is demonstrated in the Weyl semiconductor 2D Te. Ultrahigh second-harmonic generation response is acquired from 2D Te with a large second-order nonlinear optical susceptibility (χ(2) ), which is up to 23.3 times higher than that of monolayer MoS2 in the range of 700-1500 nm. Notably, distinct from other 2D nonlinear semiconductors, χ(2) of 2D Te increases extraordinarily with increasing wavelength and reaches up to 5.58 nm V-1 at ≈2300 nm, which is the best infrared performance among the reported 2D nonlinear materials. Large χ(2) of 2D Te also enables the high-intensity sum-frequency generation with an ultralow continuous-wave (CW) pump power. Theoretical calculations reveal that the exceptional performance is attributed to the presence of large BCD located at the Weyl points of 2D Te. These results unravel a new linkage between Weyl semiconductor and strong optical nonlinear responses, rendering 2D Te a competitive candidate for highly efficient nonlinear 2D semiconductors in the infrared region.
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Flat bands (FBs) can appear in two-dimensional (2D) geometrically frustrated systems caused by quantum destructive interference (QDI). However, the scarcity of pure 2D frustrated crystal structures in natural materials makes FBs hard to be identified, let alone modulate FBs relating to electronic properties. Here, the experimental evidence of the complete electronic QDI induced FB contributed by the 2D breathing-kagome layers of Nb atoms in Nb3 TeCl7 (NTC) is reported. An identical chemical state and 2D localization characteristics of the Nb breathing-kagome layers are experimentally confirmed, based on which NTC is demonstrated to be a superior concrete candidate for the breathing-kagome tight-binding model. Furthermore, it theoretically establishes the tunable roles of the on-site energy over Nb sites on bandwidth, energy position, and topology of FBs in NTC. This work opens an aveanue to manipulate FB characteristics in these 4d transition-metal-based breathing-kagome materials.
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Two-dimensional (2D) magnetic systems possess versatile magnetic order and can host tunable magnons carrying spin angular momenta. Recent advances show angular momentum can also be carried by lattice vibrations in the form of chiral phonons. However, the interplay between magnons and chiral phonons as well as the details of chiral phonon formation in a magnetic system are yet to be explored. Here, we report the observation of magnon-induced chiral phonons and chirality selective magnon-phonon hybridization in a layered zigzag antiferromagnet (AFM) FePSe3. With a combination of magneto-infrared and magneto-Raman spectroscopy, we observe chiral magnon polarons (chiMP), the new hybridized quasiparticles, at zero magnetic field. The hybridization gap reaches 0.25 meV and survives down to the quadrilayer limit. Via first principle calculations, we uncover a coherent coupling between AFM magnons and chiral phonons with parallel angular momenta, which arises from the underlying phonon and space group symmetries. This coupling lifts the chiral phonon degeneracy and gives rise to an unusual Raman circular polarization of the chiMP branches. The observation of coherent chiral spin-lattice excitations at zero magnetic field paves the way for angular momentum-based hybrid phononic and magnonic devices.
Assuntos
Hibridização Genética , Fônons , Hibridização de Ácido Nucleico , Campos Magnéticos , Movimento (Física)RESUMO
Sliding ferroelectricity associated with interlayer translation is an excellent candidate for ferroelectric device miniaturization. However, the weak polarization gives rise to the poor performance of sliding ferroelectric transistors with a low on/off ratio and a narrow memory window, which restricts its practical application. To address the issue, we propose a facile strategy by regulating the Schottky barrier in sliding ferroelectric semiconductor transistors based on γ-InSe, in which a high performance with a large on/off ratio (106) and a wide memory window (4.5 V) was ultimately acquired. Additionally, the memory window of the device can be further modulated by electrostatic doping or light excitation. These results open up new ways for designing novel ferroelectric devices based on emerging sliding ferroelectricity.
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Underwater target detection techniques have been extensively applied to underwater vehicles for marine surveillance, aquaculture, and rescue applications. However, due to complex underwater environments and insufficient training samples, the existing underwater target recognition algorithm accuracy is still unsatisfactory. A long-term effort is essential to improving underwater target detection accuracy. To achieve this goal, in this work, we propose a modified YOLOv5s network, called YOLOv5s-CA network, by embedding a Coordinate Attention (CA) module and a Squeeze-and-Excitation (SE) module, aiming to concentrate more computing power on the target to improve detection accuracy. Based on the existing YOLOv5s network, the number of bottlenecks in the first C3 module was increased from one to three to improve the performance of shallow feature extraction. The CA module was embedded into the C3 modules to improve the attention power focused on the target. The SE layer was added to the output of the C3 modules to strengthen model attention. Experiments on the data of the 2019 China Underwater Robot Competition were conducted, and the results demonstrate that the mean Average Precision (mAP) of the modified YOLOv5s network was increased by 2.4%.
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In this study, an observer-based model predictive control (MPC) algorithm is addressed for an uncertain discrete-time nonlinear networked control system (NCS) subject to hybrid malicious attacks by using interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy theory. Hybrid malicious attacks, including two typical attacks, i.e., denial-of-service (DoS) attacks and false data injection (FDI) attacks, are considered in the communication networks. Under DoS attacks, the control signals will be interfered, which cause the degradation of signal-to-interference-plus-noise ratio, then lead to packets loss. Under FDI attacks, the false signals are injected and output signals are modified so that the system performance is deteriorated. For the NCS subject to hybrid attacks, a secure observer that can resist FDI attacks is devised and a fuzzy MPC algorithm that can solve the controller gains is proposed. Besides, by updating the bound of augmented estimation error, the recursive feasibility can be guaranteed. Finally, illustrative examples are given to show the effectiveness of proposed scheme.
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Logic-in-memory devices are a promising and powerful approach to realize data processing and storage driven by electrical bias. Here, an innovative strategy is reported to achieve the multistage photomodulation of 2D logic-in-memory devices, which is realized by controlling the photoisomerization of donor-acceptor Stenhouse adducts (DASAs) on the surface of graphene. Alkyl chains with various carbon spacer lengths (n = 1, 5, 11, and 17) are introduced onto DASAs to optimize the organic-inorganic interfaces: 1) Prolonging the carbon spacers weakens the intermolecular aggregation and promotes isomerization in the solid state. 2) Too long alkyl chains induce crystallization on the surface and hinder the photoisomerization. Density functional theory calculation indicates that the photoisomerization of DASAs on the graphene surface is thermodynamically promoted by increasing the carbon spacer lengths. The 2D logic-in-memory devices are fabricated by assembling DASAs onto the surface. Green light irradiation increases the drain-source current (Ids ) of the devices, while heat triggers a reversed transfer. The multistage photomodulation is achieved by well-controlling the irradiation time and intensity. The strategy based on the dynamic control of 2D electronics by light integrates molecular programmability into the next generation of nanoelectronics.
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Two-dimensional (2D) materials with multiphase, multielement crystals such as transition metal chalcogenides (TMCs) (based on V, Cr, Mn, Fe, Cd, Pt and Pd) and transition metal phosphorous chalcogenides (TMPCs) offer a unique platform to explore novel physical phenomena. However, the synthesis of a single-phase/single-composition crystal of these 2D materials via chemical vapour deposition is still challenging. Here we unravel a competitive-chemical-reaction-based growth mechanism to manipulate the nucleation and growth rate. Based on the growth mechanism, 67 types of TMCs and TMPCs with a defined phase, controllable structure and tunable component can be realized. The ferromagnetism and superconductivity in FeXy can be tuned by the y value, such as superconductivity observed in FeX and ferromagnetism in FeS2 monolayers, demonstrating the high quality of as-grown 2D materials. This work paves the way for the multidisciplinary exploration of 2D TMPCs and TMCs with unique properties.