Flexible Channel Research Articles

Double-diffusive peristaltic MHD Sisko nanofluid flow through a porous medium in presence of non-linear thermal radiation, heat generation/absorption, and Joule heating

This article studied a numerical estimation of the double-diffusive peristaltic flow of a non-Newtonian Sisko nanofluid through a porous medium inside a horizontal symmetric flexible channel under the impact of Joule heating, nonlinear thermal radiation, viscous dissipation, and heat generation/absorption in presence of heat and mass convection, considering effects of the Brownian motion and the thermophoresis coefficients. On the other hand, the long wave approximation was used to transform the nonlinear system of partial differential equations into a nonlinear system of ordinary differential equations which were later solved numerically using the fourth-order Runge–Kutta method with shooting technique using MATLAB package program code. The effects of all physical parameters resulting from this study on the distributions of velocity, temperature, solutal concentration, and nanoparticles volume fraction inside the fluid were studied in addition to a study of the pressure gradients using the 2D and 3D graphs that were made for studying the impact of some parameters on the behavior of the streamlines graphically within the channel with a mention of their physical meaning. Finally, some of the results of this study showed that the effect of Darcy number Da and the magnetic field parameter M is opposite to the effect of the rotation parameter Omega on the velocity distribution whereas, the two parameters nonlinear thermal radiation R and the ratio temperature {theta }_{w} works on a decrease in the temperature distribution and an increase in both the solutal concentration distribution, and the nanoparticle's volume fraction. Finally, the impact of the rotation parameter Omega on the distribution of pressure gradients was positive, but the effect of both Darcy number Da and the magnetic field parameter M on the same distribution was negative. The results obtained have been compared with the previous results obtained that agreement if the new parameters were neglected and indicate the phenomenon's importance in diverse fields.

Photosensitive ion channels in layered MXene membranes modified with plasmonic gold nanostars and cellulose nanofibers

Ion channels transduce external stimuli into ion-transport-mediated signaling, which has received considerable attention in diverse fields such as sensors, energy harvesting devices, and desalination membrane. In this work, we present a photosensitive ion channel based on plasmonic gold nanostars (AuNSs) and cellulose nanofibers (CNFs) embedded in layered MXene nanosheets. The MXene/AuNS/CNF (MAC) membrane provides subnanometer-sized ionic pathways for light-sensitive cationic flow. When the MAC nanochannel is exposed to NIR light, a photothermal gradient is formed, which induces directional photothermo-osmotic flow of nanoconfined electrolyte against the thermal gradient and produces a net ionic current. MAC membrane exhibits enhanced photothermal current compared with pristine MXene, which is attributed to the combined photothermal effects of plasmonic AuNSs and MXene and the widened interspacing of the MAC composite via the hydrophilic nanofibrils. The MAC composite membranes are envisioned to be applied in flexible ionic channels with ionogels and light-controlled ionic circuits.

Motion Error Estimation and Compensation of Airborne Array Flexible SAR Based on Multi-Channel Interferometric Phase

Airborne array synthetic aperture radar (SAR) has made a significant breakthrough in the three-dimensional resolution of traditional SAR. In the airborne array SAR 3D imaging technology, the baseline length is the main factor restricting the resolution. Airborne array flexible SAR can increase the baseline length to improve the resolution and interference performance by mounting antennae on the wing. The existing research lacks results obtained using flexible actual data processing and specific motion compensation methods. Thus, this paper proposes a motion error estimation and compensation method for an airborne array flexible SAR based on a multi-channel interferometric phase. Firstly, a flexible channel motion compensation model is established based on the multi-channel interference phase of airborne array flexible SAR. Then, based on the rigid multi-channel data, combined with the ground control points, the least square method, and the global optimal search algorithm, the accurate rigid baseline length and the central incidence angle are obtained. Finally, according to the multi-channel interference phase inversion of the flexible motion error and combined with the motion compensation model, the flexible data are compensated in the time domain. The actual results indicate that, compared with traditional motion compensation methods, our method can obtain accurate flexible compensation data. This study improves the interference performance of multi-channel data of airborne array flexible SAR and lays a solid foundation for the high-precision 3D reconstruction of airborne array flexible SAR.

Dynamic gas‐diffusion electrodes for oxygen electroreduction to hydrogen peroxide

AbstractFlow‐type electrolytic cell is a viable system for many electrochemical processes, in which gas‐diffusion electrode (GDE) plays a vital role in providing optimal reacting interfaces for improved performances. Different from traditional GDEs with fixed porosity, here we propose a new type of GDE that features flexible diffusion channels. Particularly, the GDE has been assembled by pairing PTFE substrate with Ag‐TCNQ/graphene hydrogels that can be further manipulated through capillary compression. With dynamic adjustment, the average pore size inside GDE ranges from 1750 to 125 nm, and the packing density varies from 56.81 to 446.07 mg cm−3. As a consequence, the as‐assembled flow‐type electrolytic cell can display excellent performances, with a yield rate of 5572 mmol gcat−1 h−1 and Faradic efficiency of 86.4% at 0.267 V (vs. RHE). In addition, a photovoltaic (PV)‐driven flow‐electrolytic system has been assembled that achieves a record solar‐to‐hydrogen peroxide efficiency of 14.8%.

Bendocapillary instability of liquid in a flexible-walled channel

We study the bendocapillary instability of a liquid droplet that part fills a flexible walled channel. Inspired by experiments in which a periodic pattern emerges as droplets of liquid are condensed slowly into deformable microchannels, we develop a mathematical model of this instability. We describe equilibria of the system, and use a combination of numerical methods and asymptotic analysis in the limit of small channel wall deflections, to elucidate the key features of this instability. We find that configurations are unstable to perturbations of sufficiently small wavenumber regardless of parameter values, that the growth rate of the instability is highly sensitive to the volume of liquid in the channel, and that both wetting and non-wetting configurations are susceptible to the instability in the same channel. Insight into novel interfacial instabilities opens the possibility for their control and thus exploitation in processes such as microfabrication.

ZIF-8-derived N-doped hierarchical porous carbon coated with imprinted polymer as magnetic absorbent for phenol selective removal from wastewater.

Producing a desirable adsorbent with strong affinity adsorption sites, excellent selectivity properties, and the ability to easily separate solid from liquid for the removal of phenol to a permissible level remains a great challenge in wastewater treatment. Herein, an N-doped magnetic carbon skeleton is presented as a porous adsorbent matrix. Importantly, the pore volume and specific surface area of the adsorbent matrix can be meticulously tuned by adjusting the thermal treatment condition, while dispersing and immobilizing the N fraction. This would ultimately result in an N-rich matrix structure with flexible mass transfer channel. The imprinted modification generates a large number of phenol-shaped geometrical cavities on the matrix. This helps to activate the phenol recognition "awareness" of N-active sites and greatly endows the adsorbent with selective adsorption property. Due to the advantageous balance between the hierarchical porous adsorbent matrix with uniformly distributed N-active sites and the imprinted polymer, the adsorbent has a superior adsorption capacity of 995.2mgg-1 and selective recognition (Kd=3.92, 3.78; HQ, PTBP) towards phenol. It outperforms previously reported adsorbents. In addition, its easy magnetic separation property makes the adsorbent to have excellent reusability. The adsorbent presents a promising potential for separating pollutants from wastewater and it sheds light on the design of an efficient comprehensive adsorbent.

Flexible 3GPP MIMO Channel Modeling and Calibration With Spatial Consistency

Flexible 3GPP MIMO Channel Modeling and Calibration With Spatial Consistency

Architecture engineering toward highly active Rh integrated porous carbon with diverse flexible channels for hydrogen evolution

An architecture engineering strategy is developed to construct h-NCNWs which enable the uniform deposition of ultrafine Rh NPs. The resultant Rh/h-NCNWs exhibit excellent H2 production performance with a TOF of 1234 min−1 for AB hydrolysis.

The Peristaltic Flow of Jeffrey Fluid through a Flexible Channel

The purpose of this study is to calculate the effect of the elastic wall of a hollow channel of Jeffrey's fluid by peristaltic flow through two concentric cylinders. The inside tube is cylindrical and the outside is a regular elastic wall in the shape of a sine wave. Using the cylindrical coordinates and assuming a very short wavelength relative to the width of the channel to its length and using governing equations for Jeffrey’s fluid in Navier-Stokes equations, the results of the problem are obtained. Through the Mathematica program these results are analysed.

Predicting consecutive spectrum opportunities with hidden Markov models

SummaryThe increasing demands for wireless channels to accommodate the surge of internet of things devices and the associated services exacerbated the need for flexible channel allocation strategies. Opportunistic spectrum sharing is expected to provide a more reasonable use of the limited radio frequencies by allowing the coexistence of licensed users and unlicensed users in the same frequency. This arrangement is called opportunistic channel allocation, where unlicensed users explore the channel when the licensed user is not transmitting. The challenge in opportunistic spectrum allocation is to find transmission opportunities. Statistical and machine learning techniques have been used to forecast spectrum opportunities on time slotted channels based on acquired transmission data from licensed users. However, opportunity forecast is usually limited to one slot ahead of time. This work explores the use of Hidden Markov Model (HMM) training and predicting procedures to forecast a consecutive sequence of idle slots that can be explored for opportunistic transmission. To improve prediction accuracy and speedup the training process, the proposed training procedures reduce the classification alphabet, which is achieved by balancing the number of training sequences to limit the influence of outliers and provide opportunity forecast even when the training process is executed over a limited number of observed sequences. While an aggressive predictor may explore more opportunities as compared to a conservative predictor, the former may incur in higher collision rates while the latter may explore fewer opportunities. Hence, this work proposes a metric to assist in the process of selecting the best predictor's parameters to balance collision and opportunity rates. The proposed HMM predictors are evaluated on both synthetic and real traffic traces. The results on synthetic traffic shows that, for channel load from up to , the proposed predictors identified over of channel opportunities with the collision rates below . On real traffic traces, where the licensed users' transmissions have deterministic inter‐packet delays, the HMM predictors identified over of the channel opportunities with collision rates below .

Active cooling of twisted coiled actuators via fabric air channels.

Twisted coiled actuators (TCAs) are promising artificial muscles for wearable soft robotic devices due to their biomimetic properties, inherent compliance, and slim profile. These artificial muscles are created by super-coiling nylon thread and are thermally actuated. Unfortunately, their slow natural cooling rate limits their feasibility when used in wearable devices for upper limb rehabilitation. Thus, a novel cooling apparatus for TCAs was specifically designed for implementation in soft robotic devices. The cooling apparatus consists of a flexible fabric channel made from nylon pack cloth. The fabric channel is lightweight and could be sewn onto other garments for assembly into a soft robotic device. The TCA is placed in the channel, and a miniature air pump is used to blow air through it to enable active cooling. The impact of channel size on TCA performance was assessed by testing nine fabric channel sizes-combinations of three widths (6, 8, and 10 mm) and three heights (4, 6, and 8 mm). Overall, the performance of the TCA improved as the channel dimensions increased, with the combination of a 10 mm width and an 8 mm height resulting in the best balance between cooling time, heating time, and stroke. This channel was utilized in a follow-up experiment to determine the impact of the cooling apparatus on TCA performance. In comparison to passive cooling without a channel, the channel and miniature air pump reduced the TCA cooling time by 42% ( s to s, ). Unfortunately, there was also a 9% increase in the heating time ( s to s, ) and a 28% decrease in the stroke ( mm to mm, ). This work demonstrates that fabric cooling channels are a viable option for cooling thermally actuated artificial muscles within a soft wearable device. Future work can continue to improve the channel design by experimenting with other configurations and materials.

Alcohol flush does not aid in endoscope channel drying but may serve as an adjunctive microbiocidal measure: A new take on an old assumption

Alcohol is perceived to aid flexible endoscope channel drying, however we previously showed alcohol increased the time required to dry some channels with forced air versus water alone. Yet, alcohol may prevent microorganism outgrowth during storage. Drying endoscope channels has been shown to prevent outgrowth, but it is unknown if incomplete drying (<10 µL remaining) provides similar protection. Endoscope channel test articles were used to determine the efficacy of 70%-30% alcohol flush for prevention of Pseudomonas aeruginosa outgrowth and drying efficiency. For non-alcohol flushed channels, the impact of forced air drying on outgrowth of P. aeruginosa was determined. Alcohol flush (70%-30%) prevented outgrowth with little to no recovery of P. aeruginosa during ambient storage. 70% alcohol increased channel drying time by 1.5 or 3-fold compared to 50% alcohol or water, respectively. Forced air drying of non-alcohol flushed channels greatly reduced the initial contamination level and prevented outgrowth. Incomplete drying of contaminated channels was akin to no application of forced air. Applying forced air for more time than necessary to remove residual liquid did not completely eliminate the low level recovery of P. aeruginosa. Flushing with reduced concentrations of alcohol may provide a strategy to prevent microbial outgrowth while reducing drying time.

Intelligent Reflecting Surface-Aided Wireless Networks: From Single-Reflection to Multireflection Design and Optimization

Intelligent reflecting surface (IRS) has emerged as a promising technique for wireless communication networks. By dynamically tuning the reflection amplitudes/phase shifts of a large number of passive elements, IRS enables flexible wireless channel control and configuration and thereby enhances the wireless signal transmission rate and reliability significantly. Despite the vast literature on designing and optimizing assorted IRS-aided wireless systems, prior works have mainly focused on enhancing wireless links with single signal reflection only by one or multiple IRSs, which may be insufficient to boost the wireless link capacity under some harsh propagation conditions (e.g., indoor environment with dense blockages/obstructions). This issue can be tackled by employing two or more IRSs to assist each wireless link and jointly exploiting their single as well as multiple signal reflections over them. However, the resultant double-/multi-IRS-aided wireless systems face more complex design issues as well as new practical challenges for implementation compared to the conventional single-IRS counterpart, in terms of IRS reflection optimization, channel acquisition, as well as IRS deployment and association/selection. As such, a new paradigm for designing multi-IRS cooperative passive beamforming and joint active/passive beam routing arises, which calls for innovative design approaches and optimization methods. In this article, we give a tutorial overview of multi-IRS-aided wireless networks, with an emphasis on addressing the new challenges due to multi-IRS signal reflection and routing. Moreover, we point out important directions worthy of research and investigation in the future.

SCRNet: an efficient spatial channel attention residual network for spatiotemporal fusion

Spatiotemporal fusion is a simple, feasible, and economical method for balancing the temporal and spatial resolutions of satellite images. However, the current spatiotemporal fusion methods have some disadvantages, such as their insufficient feature extraction abilities and unsatisfactory fusion image effects. To obtain higher-quality spatiotemporal fusion images, a spatiotemporal data fusion method based on deep learning is proposed. This method combines an attention mechanism and a residual learning strategy to design an asymmetric spatial channel attention residual network (SCRNet). For different input images, the SCRNet extracts rich feature information to fuse high-quality images in a more emphatic and scientific manner than other approaches. Specifically, we design an efficient and flexible spatial channel attention mechanism that not only focuses on spatial information but also takes channel information into account. The optimized residual network can further enhance the ability of the network to extract feature information. In addition, we design a compound loss function and propose an edge loss to further enrich the extracted feature information and improve the resulting image quality. Experimental results on two datasets show that the proposed method outperforms existing fusion methods in subjective and objective evaluations.

Segment frame replication and elimination for redundant routing provision in the FlexE-over-WDM networks

Flexible Ethernet (FlexE)-over-WDM is one of the promising technologies of 5G transport networks that aims to provide a variety of Ethernet MAC rates over large capacity wavelength channels. Ultra-reliable communication is a key scenario of 5G, which poses a big challenge to the transport networks. To achieve ultra-reliability, frame replication and elimination for reliability (FRER) was proposed by IEEE. 802.1CB to provide redundant transmission in layer 2. However, previous studies of FRER considered to replicate MAC frames at source node and eliminate them at the destination, which may cause a waste of network resources, especially for the services that require different reliabilities in a condition of network with different packet loss rates of link and node. To this end, we propose a novel redundant routing scheme, called segment FRER (S-FRER), to balance the reliability and network efficiency. And a FlexE group allocation scheme is coming with S-FRER to assign the Flexible Ethernet channels along the path. Two heuristic algorithms, which are end-to-end FRER (E-FRER) and ordinal FRER (O-FRER), are compared with S-FRER. Simulation results show that S-FRER can satisfy diverse reliability requirements of services, and the resource redundancy and equipment cost are condensed.We further take the resource utilization efficiency as the optimization goal, and propose a FlexE Group allocation strategy based on segmented frame repetition and elimination to realize the resource redistribution of service flows on redundant routes. The experimental results verify the effectiveness of the scheme in terms of resource utilization efficiency.

Mathematical modeling for peristalsis of couple stress nanofluid

The current article investigates the magnetohydrodynamic (MHD) radiative peristaltic flow of a couple stress nanoliquid in a symmetric channel. Thermally convective and zero mass flux conditions are imposed on flexible channel walls. Impacts of Joule heating and viscous dissipation are considered. Nanofluid model consists of important features Brownian motion and thermophoresis. First‐order chemical reaction is present in mass transportation. The resulting system of differential equations is numerically tackled after adopting large wavelength and low Reynolds number assumptions. Influences of pertinent variables of interest on concentration, temperature, coefficient of heat transfer, streamlines, skin friction coefficient, and Nusselt and Sherwood numbers are examined graphically. The findings of this study reveal that temperature enhances against Brownian motion and thermophoresis parameters, whereas it decays for radiation variable. Concentration of the fluid declines for a couple stress fluid variable. Further, the heat transfer coefficient shows increasing behavior for Eckert number.

Cooling of hot cylinder placed in a flexible backward-facing step channel

This paper copes with the mixed convection heat transfer and fluid–structure interaction (FSI) of a hot cylinder placed in a backward-step channel. The step is set to be flexible and deforms according to the force imparted by fluid. To attain the best cooling, different configurations of the flexible step were assessed. Equations governing the problem are solved using the finite element technique with the Arbitrary Lagrangian–Eulerian (ALE) approach to go along the moving domain. The influential parameters of such a problem are the Reynolds number Re, Richardson number Ri and the configuration of the flexible back step. Results demonstrated an improvement in the Nusselt number where at Ri = 100, a step of horizontal flexible wall augments the Nusselt number by 7.3% and 1.4% when Re = 100 and 500, respectively. Including the pressure drop in a performance criterion, it is shown that making the vertical wall of the step flexible (VFW) improves the aspects of heat transfer and the hydrodynamic of low Reynolds number, while at high Reynolds number, all suggested configurations of flexible step do not improve the performance criterion. It is found also that Reynolds number greatly improves the performance criterion while Richardson number does not.

Bending stiffness variability between a deployable robotic laser osteotome and its insertion device

Abstract Varying device stiffness on purpose can provide safety and performance improvements in interventions involving flexible minimal-invasive surgical robotic devices. For example, when flexible robotic devices are used for inserting minimal-invasive tools along curved paths into the knee joint for arthroscopy, a high device stiffness can allow precise path following where desirable. In contrast, when the minimalinvasive flexible device has reached its desired location inside the patient’s body, decoupling the surgical tool (end-effector) from the flexible robotic insertion device can be beneficial in avoiding transferring disturbances such as vibrations to the robot-patient interaction. In this paper, we investigate bending stiffness variability in dependence on the length of a flexible supply channel. Our experiments have shown that bending stiffness in fact decreases with the length of the supply channel but the highest stiffness connection is not sufficiently rigid and we plan to implement a more rigid connection to allow precise path following during insertion.

An antifatigue and self-healable ionic polyurethane/ionic liquid composite as the channel layer for a low energy cost synaptic transistor

The developing trends of the traditional transistor include being synaptic and flexible, which could down low the energy cost and realize the daily application of flexible electronics, respectively. However, only bendable synaptic transistor has been developed, which is mainly restricted by the rigid components. Among which, the channel layer has not been replaced by any stretchable material yet. In this work, we synthesized an ionic polyurethane (iPU), and blend it with ionic liquid (IL) to construct a flexible channel layer with high transparency, stability, antifatigue and stretchability. The self-healing process can be completed at ambient and operating temperatures, and the self-healing speed was accelerated by the elevated temperature. The recovery ratio of the iPU/IL film was 95% after cyclic stretch to 50% strain for 100 cycles, which proved good antifatigue property. The stable combination between iPU and IL was verified by the two-dimensional Raman spectra, and the interconnected paths of IL around hard domains were discovered, which was probably due to the strong interaction between ions and hard segments. Spin coating technology was applied to construct the iPU/IL channel layer on a Si matrix, and an ionic conductive transistor was manufactured subsequently, in which the conductive mechanism is similar with a true synapse. The resulted transistor showed an on-off ratio of 2.1 × 102, and its energy dissipation was only 64 nJ when simulating the signal transmission of a nerve synapse, which was close to the power cost in other synaptic transistors.

Ionic liquid multistate resistive switching characteristics in two terminal soft and flexible discrete channels for neuromorphic computing

By exploiting ion transport phenomena in a soft and flexible discrete channel, liquid material conductance can be controlled by using an electrical input signal, which results in analog neuromorphic behavior. This paper proposes an ionic liquid (IL) multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL4 and H2O into the two ends of a discrete polydimethylsiloxane (PDMS) channel. The spike rate-dependent plasticity (SRDP) and spike-timing-dependent plasticity (STDP) behavior are highly stable by modulating the input signal. Furthermore, the discrete channel device presents highly durable performance under mechanical bending and stretching. Using the obtained parameters from the proposed ionic liquid-based synaptic device, convolutional neural network simulation runs to an image recognition task, reaching an accuracy of 84%. The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.