Flexible Switching Research Articles

Terahertz perfect absorber based on flexible active switching of ultra-broadband and ultra-narrowband

Metamaterial perfect absorbers in the terahertz band are attracting more and more attention. Pure narrowband absorbers as well as broadband absorbers have been proposed one after another in recent years. However, absorbers that can achieve both narrow-band absorption and broadband absorption have hardly been reported. To meet more practical needs, we propose a terahertz metamaterial perfect absorber that combines ultra-broadband and narrowband based on the phase transition properties of vanadium dioxide (VO2). Its main structure consists of a metal ring and four VO2 discs, and the absorber can be flexibly switched between ultra-broadband and narrowband absorption by adjusting the ambient temperature. The resonator consisting of metal rings and VO2 discs are mainly responsible for the formation of absorption peaks. A detailed explanation is given by means of magnetic resonance theory and the impedance matching principle. Compared to recent reports, our design offers a significant improvement in absorption rate and bandwidth and is also flexible in terms of tuning. Moreover, as the phase transition temperature of VO2 is only slightly higher than room temperature, there are almost no limitations for experimental and practical applications. Therefore, our design will have significant applications in modulation, sensing, energy harvesting, switching devices, etc.

The hippocampus as the switchboard between perception and memory

Adaptive memory recall requires a rapid and flexible switch from external perceptual reminders to internal mnemonic representations. However, owing to the limited temporal or spatial resolution of brain imaging modalities used in isolation, the hippocampal-cortical dynamics supporting this process remain unknown. We thus employed an object-scene cued recall paradigm across two studies, including intracranial electroencephalography (iEEG) and high-density scalp EEG. First, a sustained increase in hippocampal high gamma power (55 to 110 Hz) emerged 500 ms after cue onset and distinguished successful vs. unsuccessful recall. This increase in gamma power for successful recall was followed by a decrease in hippocampal alpha power (8 to 12 Hz). Intriguingly, the hippocampal gamma power increase marked the moment at which extrahippocampal activation patterns shifted from perceptual cue toward mnemonic target representations. In parallel, source-localized EEG alpha power revealed that the recall signal progresses from hippocampus to posterior parietal cortex and then to medial prefrontal cortex. Together, these results identify the hippocampus as the switchboard between perception and memory and elucidate the ensuing hippocampal-cortical dynamics supporting the recall process.

Leaky-Wave Antenna Arrays for Flexible Dual-Beam Switching

Two novel types of dual-beam switching leaky-wave antenna (LWA) arrays based on substrate-integrated waveguides (SIWs) are proposed. The two antenna arrays consist of five SIW LWAs that work on the fundamental wave and −1st spatial harmonic wave simultaneously, so the arrays can realize fixed-frequency or frequency controlled dual-beam switching properties. The LWAs in one of the arrays have the same equivalent waveguide width and different slot periods, defined as the asymmetric dual-beam switching (ADBS) array. The LWAs in the other array have the same slot period and different equivalent waveguide widths, which is defined as the hybrid dual-beam switching (HDBS) array. The open stopbands of the arrays are suppressed by a simple structure. Using voltage-driven radio frequency chip switches (CSW-RFs) to change the excitation port, the arrays can realize the function of dual-beam switching at a fixed frequency. The measured results show that the forward beam of the ADBS array can switch from 13° to 80° while its backward beam switches from −75° to −10°, and the forward beam of the HDBS array is fixed at 45° while its backward beam switches from −10° to −80° when working at 28 GHz. Furthermore, the LWAs themselves can realize frequency-controlled ADBS in each excitation state. Therefore, the proposed arrays exhibit excellent performance in flexible dual-beam switching, which can be used in millimeter-wave applications where fixed-frequency beam switching or frequency-controlled beam switching is required.

Selectivity Determinants of RHO GTPase Binding to IQGAPs.

IQ motif-containing GTPase-activating proteins (IQGAPs) modulate a wide range of cellular processes by acting as scaffolds and driving protein components into distinct signaling networks. Their functional states have been proposed to be controlled by members of the RHO family of GTPases, among other regulators. In this study, we show that IQGAP1 and IQGAP2 can associate with CDC42 and RAC1-like proteins but not with RIF, RHOD, or RHO-like proteins, including RHOA. This seems to be based on the distribution of charged surface residues, which varies significantly among RHO GTPases despite their high sequence homology. Although effector proteins bind first to the highly flexible switch regions of RHO GTPases, additional contacts outside are required for effector activation. Sequence alignment and structural, mutational, and competitive biochemical analyses revealed that RHO GTPases possess paralog-specific residues outside the two highly conserved switch regions that essentially determine the selectivity of RHO GTPase binding to IQGAPs. Amino acid substitution of these specific residues in RHOA to the corresponding residues in RAC1 resulted in RHOA association with IQGAP1. Thus, electrostatics most likely plays a decisive role in these interactions.

Dynamic Transitions between Neural States Are Associated with Flexible Task Switching during a Memory Task.

Flexible behavior requires switching between different task conditions. It is known that such task switching is associated with costs in terms of slowed RT, reduced accuracy, or both. The neural correlates of task switching have usually been studied by requiring participants to switch between distinct task conditions that recruit different brain networks. Here, we investigated the transition of neural states underlying switching between two opposite memory-related processes (i.e., memory retrieval and memory suppression) in a memory task. We investigated 26 healthy participants who performed a think/no-think task while being in the fMRI scanner. Behaviorally, we show that it was more difficult for participants to suppress unwanted memories when a no-think was preceded by a think trial instead of another no-think trial. Neurally, we demonstrate that think-no-think switches were associated with an increase in control-related and a decrease in memory-related brain activity. Neural representations of task condition, assessed by decoding accuracy, were lower immediately after task switching compared with the nonswitch transitions, suggesting a switch-induced delay in the neural transition toward the required task condition. This suggestion is corroborated by an association between condition-specific representational strength and condition-specific performance in switch trials. Taken together, we provided neural evidence from the time-resolved decoding approach to support the notion that carryover of the previous task set activation is associated with the switching cost, leading to less successful memory suppression.

Compartmentalized dynamics within a common multi-area mesoscale manifold represent a repertoire of human hand movements

The human hand is unique in the animal kingdom for unparalleled dexterity, ranging from complex prehension to fine finger individuation. How does the brain represent such a diverse repertoire of movements? We evaluated mesoscale neural dynamics across the human "grasp network," using electrocorticography and dimensionality reduction methods, for a repertoire of hand movements. Strikingly, we found that the grasp network represented both finger and grasping movements alike. Specifically, the manifold characterizing the multi-areal neural covariance structure was preserved during all movements across this distributed network. In contrast, latent neural dynamics within this manifold were surprisingly specific to movement type. Aligning latent activity to kinematics further uncovered distinct submanifolds despite similarities in synergistic coupling of joints between movements. We thus find that despite preserved neural covariance at the distributed network level, mesoscale dynamics are compartmentalized into movement-specific submanifolds; this mesoscale organization may allow flexible switching between a repertoire of hand movements.

Analysis of Interface Phenomena for High-Performance Dual-Stacked Oxide Thin-Film Transistors via Equivalent Circuit Modeling.

Oxide thin-film transistors (TFTs) have attracted much attention because they can be applied to flexible and large-scaled switching devices. Especially, oxide semiconductors (OSs) have been developed as active layers of TFTs. Among them, indium-gallium-zinc oxide (IGZO) is actively used in the organic light-emitting diode display field. However, despite their superior off-state properties, IGZO TFTs are limited by low field-effect mobility, which critically affects display resolution and power consumption. Herein, we determine new working mechanisms in dual-stacked OS, and based on this, we develop a dual-stacked OS-based TFT with improved performance: high field-effect mobility (∼80 cm2/V·s), ideal threshold voltage near 0 V, high on-off current ratio (>109), and good stability at bias stress. Induced areas are formed at the interface by the band offset: band offset-induced area (BOIA) and BOIA-induced area (BIA). They connect the gate bias-induced area (GBIA) and electrode bias-induced area (EBIA), resulting in high current flow. Equivalent circuit modeling and the transmission line method are also introduced for more precise verification. By verifying current change with gate voltage in the single OS layer, the current flowing direction in the dual-stacked OS is calculated and estimated. This is powerful evidence to understand the conduction mechanism in a dual-stacked OS-based TFT, and it will provide new design rules for high-performance OS-based TFTs.

Decentralized and Multi-Objective Coordinated Optimization of Hybrid AC/DC Flexible Distribution Networks

The increasing penetration of distributed energy resources and flexible electrical loads makes hybrid AC/DC distribution networks become a crucial trend for future modern distribution networks. To increase the flexibility and energy efficiency of hybrid AC/DC distribution networks, a decentralized and multi-objective coordinated optimization method by considering different control means is proposed. The salient feature of this method is that it comprehensively and properly models the full variety of possible control means (i.e., active/reactive power of distributed generation, on load tap changers, flexible distribution switch, voltage source converter). The abundant means are utilized to optimize operational cost, voltage deviation and network losses simultaneously. Then, a fully decentralized optimization method based on alternating direction multiplier method (ADMM) is proposed. The hybrid AC/DC distribution networks are divided into several sub-networks. Flexible interconnected electronic devices are utilized to transfer energy between different sub-networks to achieve the efficient and flexible utilization of controllable resources in hybrid AC/DC distribution networks. Finally, the proposed coordinated optimization method is tested on a modified dual IEEE 33-node network to demonstrate its effectiveness and advantages, and the performance of the centralized method and our proposed method is compared.

Thalamostriatal System Controls the Acquisition, Performance, and Flexibility of Learning Behavior.

The dorsal striatum (DS) is a key structure of the basal ganglia circuitry, which regulates various types of learning processes and flexible switching of behavior. Intralaminar thalamic nuclei (ILNs) provide the main source of thalamostriatal inputs to the DS and constitute multiple nuclear groups, each of which innervates specific subdivisions of the striatum. Although the anatomical and electrophysiological properties of thalamostriatal neurons have been previously characterized, the behavioral and physiological functions of these neurons remain unclarified. Two representative thalamostriatal cell groups in the parafascicular nucleus (PF) and the central lateral nucleus (CL) are located in the caudal and rostral regions of the ILNs in rodents. Recently, the behavioral roles of these thalamostriatal cell groups have been investigated by the use of genetic and pharmacological manipulation techniques. In the current review, we summarize behavioral studies on thalamostriatal neurons, showing the key roles of these neurons in different learning processes, such as the acquisition, performance, and flexibility of behavior.

Magnetically Activated Flexible Thermoelectric Switches Based on Interconnected Nanowire Networks

AbstractThe use of the spin degree of freedom in thermoelectric conversion offers new functionalities for electronic devices powered by waste heat and a promising solution for sustainable technologies. Here, thermocouples formed from two dissimilar arrays of interconnected magnetic nanowires embedded in a polymer film are used to realize flexible thermoelectric switches providing optimal magnetic‐field‐induced control of the sign and magnitude of the thermopower. By finetuning the composition of the homogeneous and multilayered nanowires forming the thermocouple legs, an ideal on/off ratio in the switching of the thermoelectric output voltage, or a simple sign reversal can be achieved in the presence of a magnetic field. This work paves the way for flexible spin‐caloritronics devices exploiting residual thermal energy for the development of thermally activated sensors and logic devices.

P041 The Impact of Simulated Night Shifts on Executive Functioning

Abstract Nightwork is associated with fatigue, decreased sleep quality, and impairments in cognitive function. While attentional tasks have been widely investigated, there are limited data on more complex tasks, such as executive functioning during nightwork. Workers often need to rapidly shift between tasks, adapting to new and complex situations. The aim of this study was to investigate the impact of nightwork on executive functioning. Healthy, non-shift working individuals (N=8; 5F, 24.8±5.0y) participated in a 7-day live-in laboratory study. Participants underwent an 8h TIB baseline sleep, followed by 4 consecutive simulated nightshifts with 7h TIB sleep during the day and an 8h TIB recovery sleep. Participants were assessed for executive function at 2000h, 2200h, 0100h and 0400h. Executive functioning was assessed with a mental flexibility switching task where a 3D rotation and math task were displayed simultaneously with an arrow indicating which task to complete in a random order. Resulting throughput data were analysed using linear mixed models. There was a main effect of time of night (F(3,77)=4.81,p=.004) on throughput such that there was a speed accuracy trade off over the night shift with slower switching ability later in the shift. There was also a main effect of nightshift (F(2,77)=54.33,p<.001) where participants’ performance improved on the task with each nightshift. This study suggests executive functioning is impaired on nightshift with worse performance at 0400h. Task improvements over consecutive nightshifts may have been due to learning or acclimation to nightwork. Understanding complex task performance on nightshift is important for tailoring countermeasures.

Facile fabrication of durable mesh with reversible photo-responsive wettability for smart oil/water separation

Oil/water separation is becoming a global obstacle since the oil-water mixture is hard to on-demand separate the desired component (water or oil) in practical application. To overcome this dilemma, herein, we report a spray-coating method to fabricate flexible surfaces reversible switch between hydrophobic and hydrophilic states with UV/vis illumination. Decorated with novel tetrapod-ZnO (T-ZnO), polydimethylsiloxane (PDMS) hydrophobic coating and 4-Aminoazobenzene (AAB) moieties, the modified nylon (Polyamide, PA) mesh possesses a porcupinefish-like structure surface with reversible photo-responsive wettability and multimechanical damage-resistant ability. The dominant advantage from reversible photo-responsive wettability composite lies in that they can take advantage of the AAB photoisomerization, the wettability of this smart material surface dynamically converted between hydrophilic and hydrophobic character in nature with UV and vis light irradiation. In consequence the intelligent material can be transformed reversibly between “oil-removing” and “water-removing” state by alternate lighting mode. More importantly, owing to the porcupinefish-like surface of the modified PA, the photo-responsive material showed prominent anti-multimechanical deformation and damages ability, which could withstand repeated mechanical deformation as well as multiple practical applications.

On-Demand Regulation of Photoreversible Color Switching for Rewritable Paper and Transient Information Encryption.

The achievement of photoreversible color switching systems (PCSS) has offered great opportunities for fundamental studies and practical applications. However, the development of PCSS that possessing highly reversible cyclability and on-demand regulation of recoloration process remains a grand challenge. Herein, we report a hydrazine-mediated self-doping strategy for the synthesis of alkaline Ti3+ self-doped TiO2-x nanoparticles, enabling the TiO2-x nanoparticles/methylene blue based PCSS with long photoreversible cyclability and rapid color switching rate. The Ti3+ species as internal sacrificial electron donors significantly improve the photoreductive activity of TiO2-x nanoparticles, which results in fast decoloration rate and long cycling number of the PCSS. Simultaneously, the alkaline property of TiO2-x nanoparticles enhances the oxidation kinetics of the PCSS to dramatically accelerate the recoloration rate. Moreover, the PCSS can be integrated elaborately with biodegradable agarose to form flexible color switching films, which exhibit long-waited on-demand regulation of recoloration rate in a wide range. By taking advantage of photoreversible color switching and time-resolved color changing process, we demonstrate their potential application in self-erasing rewritable paper and transient optical information encryption. This work represents a new strategy for the future development of PCSS and their advanced applications.

Hierarchical Power Allocation Control for Star-Connected Hybrid Energy Storage System Using Cascaded Multilevel Converters

Hybrid energy storage system (HESS) using cascaded multilevel converters (CMC) has received increasing attention due to its merits on smoothing power fluctuations for renewable energy systems (RESs). However, CMC-based HESS still faces tough challenges due to asymmetrical ac power distribution. In this paper, hierarchical power allocation control strategy is utilized in CMC-based star-connected HESS to coordinate power between batteries and supercapacitors (SCs). Using the proposed power allocation mechanism, energy management strategy (EMS) with two operation modes can be achieved, which includes SC voltage regulation mode and power compensation mode. In SC voltage regulation mode, SC voltages are regulated to achieve long-term stable operation. Power compensation mode aims to allocate the active power fluctuation and employs SCs to mitigate it. Meanwhile, the principle of the hierarchical power allocation strategy is analyzed to facilitate the accurate control and flexible switching of different operation modes. A series of simulation and experiment tests are executed to demonstrate the performance of the proposed control strategy.

Tuning Mechanical and Electrical Properties of Elastomer Composites with Hybrid Filler Network Containing Graphene for Stretchable Strain Sensors

Conductive elastomer composites (CECs) with segregated filler networks display a combination of good mechanical properties and electrical conductivity, enabling potential applications in flexible and stretchable electronics. However, it is challenging to achieve high strain sensitivity and to retain good elasticity. Here, hybrid fillers of carbon nanostructures (CNS, also known as branched carbon nanotubes) and graphene are used to achieve high strain sensitivity of thermoplastic polyurethane (TPU)‐based CECs without decreasing elasticity and electrical conductivity. By changing the graphene type, namely, single layer graphene nanosheet (GNS) and graphene nanoplatelets (GNP), mechanical properties and strain–sensing performances of the CECs can be modulated effectively at proper hybrid filler compositions. Due to the effect of graphene morphology, the TPU/CNS–GNP system has higher strain sensitivity by comparison with the TPU/CNS–GNS system. These CECs demonstrate potential applications as flexible/wearable electronics in body joint bending and flexible switches and resistors for current regulation.

A TFC-based homotopy continuation algorithm with application to dynamics and control problems

A method for solving zero-finding problems is developed by tracking homotopy paths, which define connecting channels between an auxiliary problem and the objective problem. Current algorithms’ success highly relies on empirical knowledge, due to manually, inherently selected homotopy paths. This work introduces a homotopy method based on the Theory of Functional Connections (TFC). The TFC-based method implicitly defines infinite homotopy paths, from which the most promising ones are selected. A two-layer continuation algorithm is devised, where the first layer tracks the homotopy path by monotonously varying the continuation parameter, while the second layer recovers possible failures resorting to a TFC representation of the homotopy function. Compared to pseudo-arclength methods, the proposed TFC-based method retains the simplicity of direct continuation while allowing a flexible path switching. Numerical simulations illustrate the effectiveness of the presented method.

Divergent projections of the paraventricular nucleus of the thalamus mediate the selection of passive and active defensive behaviors.

The appropriate selection of passive and active defensive behaviors in threatening situations is essential for survival. Previous studies have shown that passive defensive responses depend on activity of the central nucleus of the amygdala (CeA), whereas active ones primarily rely on the nucleus accumbens (NAc). However, the mechanisms underlying flexible switching between these two types of responses remain unknown. Here, we show in mice that the paraventricular thalamus (PVT) mediates the selection of defensive behaviors through its interaction with the CeA and the NAc. We show that the PVT–CeA pathway drives conditioned freezing responses, whereas the PVT–NAc pathway is inhibited during freezing and instead signals active avoidance events. Optogenetic manipulations revealed that activity in the PVT–CeA or PVT–NAc pathway biases behavior toward the selection of passive or active defensive responses, respectively. These findings provide evidence that the PVT mediates flexible switching between opposing defensive behaviors.

FEA-based tracking control of flexible body switching dynamic structure

AbstractIn dynamically switched systems with unknown switching signal, the control system is conventionally designed based on the worst switching scenario to ensure system stability. Such conservative design demands excessive control effort in less critical switching configurations. In the case of continuum mechanics systems, such excessive control inputs result in increased structural deformations and resultant modeling uncertainties. These deformations alter differential equations of motion which cripple the task of control. In this paper, a new approach for tracking control of uncertain continuum mechanics multivariable systems undergoing switching dynamics and unknown time delay has been proposed. Control algorithm is constructed based on the mathematical rigid model of the plant and a Common Lyapunov Function (CLF) is proposed upon sliding hyperplane regarding all switching configurations. Considering the model-based nature of sliding mode control (SMC) and inevitable uncertainties induced from modeling simplifications of continuum system or parameter evaluation errors, Finite Element Analysis (FEA) is utilized to approximate total model uncertainties. To obtain robust stability, instead of conventional switching functions in the construction of control law, the control inputs are selected such that system dynamics reside within stability bounds which are calculated based on the Lyapunov asymptotic stability criterion. Therefore, the unwanted chattering issue caused by continuous switching is not observed in control input signals. Eventually, the accuracy of the proposed method has been verified through the student version of ANSYS® mechanical APDL-based simulations and its effectiveness has been demonstrated in multiple operating conditions.

Light Controllable Electronic Phase Transition in Ionic Liquid Gated Monolayer Transition Metal Dichalcogenides.

Ionic liquid gating has proved to be effective in inducing emergent quantum phenomena such as superconductivity, ferromagnetism, and topological states. The electrostatic doping at two-dimensional interfaces relies on ionic motion, which thus is operated at sufficiently high temperature. Here, we report the in situ tuning of quantum phases by shining light on an ionic liquid-gated interface at cryogenic temperatures. The light illumination enables flexible switching of the quantum transition in monolayer WS2 from an insulator to a superconductor. In contrast to the prevailing picture of photoinduced carriers, we find that in the presence of a strong interfacial electric field conducting electrons could escape from the surface confinement by absorbing photons, mimicking the field emission. Such an optical tuning tool in conjunction with ionic liquid gating greatly facilitates continuous modulation of carrier densities and hence electronic phases, which would help to unveil novel quantum phenomena and device functionality in various materials.

Incorporating microgrids coupling with utilization of flexible switching to enhance self-healing ability of electric distribution systems

Electric distribution networks have to deal with issues caused by natural disasters. These problems possess unique characteristics, and their severity can make load restoration methods impotent. One solution that can help in alleviating the aftermath is the use of microgrids (MGs). Employing the cumulative capacity of the generation resources through MG coupling facilitates the self-healing capability and leads to better-coordinated energy management during the restoration period, while the switching capability of the system should also be considered. In this paper, to form and schedule dynamic MGs in distribution systems, a novel model based on mixed-integer linear programming (MILP) is proposed. This approach employs graph-related theories to formulate the optimal formation of the networked MGs and management of their proper participation in the load recovery process. In addition, the Benders decomposition technique is applied to alleviate computability issues of the optimization problem. The validity and applicability of the proposed model are evaluated by several simulation studies.