Microscale Devices Research Articles

Exploring Vacuum-Assisted Thin Films toward Supercapacitor Applications: Present Status and Future Prospects.

Demand for high-performance energy storage devices is growing tremendously. Supercapacitors possess an excellent candidature to fulfill the energy storage requisites such as high energy density when compared to conventional capacitors, high power density, and cycling stability as compared to batteries, though not only for large-scale devices for higher energy/power density applications but also for macro- to microdevices for miniaturized electrical components. With the aid of various routes, many materials have been explored with well-tuned properties with controlled surface architecture through various preparative parameters to find those best suited for supercapacitive electrodes. Growth of a thin film can be accomplished through chemical or physical (vacuum-assisted) routes. Vacuum-assisted (physical) growth yields high purity, precise dimensions with a line-of-sight deposition, along with high adhesion between the film and the substrates, and hence, these techniques are necessary to manufacture many macro- to microscale supercapacitor devices. Still, much effort has not been put forth to explore vacuum-assisted techniques to fabricate supercapacitive electrodes and energy storage applications. The present review explores the first comprehensive report on the growth of widespread materials through vacuum-assisted physical deposition techniques inclusive of thermal evaporation, e-beam evaporation, sputtering, and laser beam ablation toward supercapacitive energy storage applications on one platform. The theoretical background of nucleation and growth through physical deposition, optimization of process parameters, and characterization to supercapacitor applications from macro- to microscale devices has been well explored to a provide critical analysis with literature-reviewed materials. The review ends with future challenges to bring out upcoming prospects to further enhance supercapacitive performance, as much work and materials need to be explored through these routes.

Water flow rate quantification through an experimental CNT membrane: A molecular dynamics simulation approach

The comprehension of water flow rate within carbon nanostructures holds great importance in both theoretical understanding and engineering design of microscale and nanoscale devices. This study presents a comprehensive numerical model for analyzing the water flow rate in Carbon Nanotube (CNT) membranes. The outcomes of this model have particular relevance in predicting the performance and designing CNT membranes for water desalination, which offer the potential for remarkably rapid transport. By investigating the characteristics of the CNT membrane, various geometric properties that influence the overall flow rate are quantified. Apart from the diameter and length, attention is also given to non-ideal factors associated with the deformation of CNTs from their original structures. Specifically, the impact of eccentricity and bending on the flow rate through CNTs is examined, revealing limited but noteworthy effects. Additionally, a simplified model is developed to characterize the membrane using statistical data pertaining to CNT synthesis. The results of the total water flow rate demonstrate that the existing numerical model closely aligns with the reported experimental values.

Modeling a sample size-dependency of martensitic phase transformation using a mesoscale framework

Predicting a sample size-dependency of the constitutive response of any material system when it is being used in nano- and micro-scale devices, such as NEMS and MEMS, is very crucial for their design process. This also includes the shape memory alloys (SMAs), where predicting a sample size-dependency of the phase transformation process is the key aspect. Many experimental studies with micropillar compression tests showed an increase in critical stress to transformation and an increase in transformation hardening as the sample size decreases below a critical size. In this work, we have employed and extended a recently developed mesoscale framework to model such size effects in SMAs. A plane strain tensile SMA strip of finite width is analyzed within a small deformation framework. The martensitic transformation regions are modeled as Eshelby inclusions in an austenite phase matrix. Circular potential nucleation sites are considered with a square packing for their spatial locations and with nucleation stress assigned to each site from a Gaussian distribution. The combination of the Gaussian distribution of nucleation stress and the size of the nucleation site represents the underlying SMA material microstructure. Our numerical analysis, with varying values of the aspect ratio between the strip width and the nucleation site size, provides a critical value of the aspect ratio characterizing a transitioning length scale between a bulk vs. a sample size-dependent phase transformation behavior. At the transition, the critical stress to phase transformation and the transformation hardening increase drastically as the aspect ratio decreases below its critical value. The limitations of these predictions are discussed with existing literature on experimental observations, and some perspectives to improve the model are stated.

Luminescence-Based Infrared Thermal Sensors: Comprehensive Insights.

Recent chronological breakthroughs in materials innovation, their fabrication, and structural designs for disparate applications have paved transformational ways to subversively digitalize infrared (IR) thermal imaging sensors from traditional to smart. The noninvasive IR thermal imaging sensors are at the cutting edge of developments, exploiting the abilities of nanomaterials to acquire arbitrary, targeted, and tunable responses suitable for integration with host materials and devices, intimately disintegrate variegated signals from the target onto depiction without any discomfort, eliminating motional artifacts and collects precise physiological and physiochemical information in natural contexts. Highlighting several typical examples from recent literature, this review article summarizes an accessible, critical, and authoritative summary of an emerging class of advancement in the modalities of nano and micro-scale materials and devices, their fabrication designs and applications in infrared thermal sensors. Introduction is begun covering the importance of IR sensors, followed by a survey on sensing capabilities of various nano and micro structural materials, their design architects, and then culminating an overview of their diverse application swaths. The review concludes with a stimulating frontier debate on the opportunities, difficulties, and future approaches in the vibrant sector of infrared thermal imaging sensors.

Independent microscale sensing of phase interface and surface temperature during droplet evaporation

Despite the important and pervasive nature of evaporative heat transfer phenomena, fundamental questions still remain about the microscopic processes that occur in and around individual droplets on a surface. In order to understand the underlying physics behind evaporative heat transfer, it is critical to have information at the individual droplet level regarding the surface temperature distribution with time as well as the location and speed of the moving multiphase contact line (MCL). In this work, a multifunctional microscale device comprised of a resistance heater, an array of spatially distributed thin-film resistance temperature detectors, and a phase interface sensing capacitance micro-sensor array has been utilized to measure the local heat transfer characteristics and MCL behavior simultaneously for the evaporation of individual sessile water droplets on a horizontal heated surface. The resistance- and capacitance-based operating principles of the micro-device means that it is capable of detecting temperature changes and tracking MCL at the microscale in real time even for applications with limited or no visibility such as within thermal management hardware or processing equipment. Importantly, having knowledge of the MCL’s location and speed with microscale precision allows for its influence on surface temperature and heat transfer to be directly studied rather than inferred. Results show that the MCL passage precedes the change in local surface temperature and the duration of the time difference between these events depends on the MCL’s speed. In addition, the passage of the MCL accounts for more than 70% of the overall temperature change during the evaporation process.

Fabrication of µFFE Devices in COC via Hot Embossing with a 3D-Printed Master Mold.

The fabrication of high-performance microscale devices in substrates with optimal material properties while keeping costs low and maintaining the flexibility to rapidly prototype new designs remains an ongoing challenge in the microfluidics field. To this end, we have fabricated a micro free-flow electrophoresis (µFFE) device in cyclic olefin copolymer (COC) via hot embossing using a PolyJet 3D-printed master mold. A room-temperature cyclohexane vapor bath was used to clarify the device and facilitate solvent-assisted thermal bonding to fully enclose the channels. Device profiling showed 55 µm deep channels with no detectable feature degradation due to solvent exposure. Baseline separation of fluorescein, rhodamine 110, and rhodamine 123, was achieved at 150 V. Limits of detection for these fluorophores were 2 nM, 1 nM, and 10 nM, respectively, and were comparable to previously reported values for glass and 3D-printed devices. Using PolyJet 3D printing in conjunction with hot embossing, the full design cycle, from initial design to production of fully functional COC µFFE devices, could be completed in as little as 6 days without the need for specialized clean room facilities. Replicate COC µFFE devices could be produced from an existing embossing mold in as little as two hours.

Inkjet printing on hydrophobic surfaces: Controlled pattern formation using sequential drying.

Inkjet-printed micro-patterns on hydrophobic surfaces have promising applications in the fabrication of microscale devices such as organic thin-film transistors. The low wettability of the surface prevents the inkjet-printed droplets from spreading, connecting to each other, and forming a pattern. Consequently, it is challenging to form micro-patterns on surfaces with low wettability. Here, we propose a sequential printing and drying method to form micro-patterns and control their shape. The first set of droplets is inkjet-printed at a certain spacing and dried. The second set of droplets is printed between these dry anchors on the surface with low wettability. As a result, a stable bridge on the surface with low wettability forms. This printing method is extended to more complicated shapes such as triangles. By implementing an energy minimization technique, a simple model was devised to predict the shape of the inkjet-printed micro-patterns while confirming that their equilibrium shape is mainly governed by surface tension forces. The gradient descent method was utilized with parametric boundaries to emulate droplet pinning and wettability of the anchors and to prevent convergence issues from occurring in the simulations. Finally, the energy minimization based simulations were used to predict the required ink to produce dry lines and triangles with smooth edges.

A Highly Sensitive Sensing Technique via Surface Plasmons With Tunable Prism Refractive Index

A new perspective using Kretschmann configuration is presented to excite surface plasmon polaritons (SPP) at liquid crystal (LC)/metal interface. The excitation of SPP takes place through the electrical tuning of the prism refractive index instead of the commonly used angular interrogation. The results show that the proposed methodology is 30% superior to the traditional angular interrogation. The 5CB (4-pentyl-4’-cyanobiphenyl) is one of the best suited nematic LC material for the proposed detection framework. Its refractive index is linearly tunable in the range 1.55 ~ 1.78 (at wavelength 1.55 μm) via an external applied electric field. In that range of refractive index variation, the SPP modes are efficiently excited; and hence any minute variation in the analyte refractive index can be detected reliably and accurately through a simple tuning of the refractive index of the prism LC material. The fundamental characteristics of the sensor are assessed through the evaluation of the linearity, sensitivity (S), the full width at half maximum (FWHM) of the reflectivity curve and the figure of merit (FOM). The variation of these characteristics over a whole range of analyte refractive index (1.3–1.4) are presented as well. The electrical tuning provides a well-matched design with micro-scale devices.

Microneedle‐Integrated Device for Transdermal Sampling and Analyses of Targeted Biomarkers

Currently available point‐of‐care systems for body fluid collection exhibit poor integration with sensors. Herein, the design of a disposable device for interstitial fluid (ISF) extraction as well as glucose, lactate, and potassium ion (K+) monitoring is reported on. It is minimally invasive and appropriate for single use, minimizing the risk of infection to the user. This microscale device contains a 3D‐printed cap‐like structure with a four‐by‐four microneedle (MN) array, bioreceptor‐modified carbon fiber (CF)‐sensing surface, and negative pressure convection technology. These features are incorporated within a compact, self‐contained, and manually operated microscale device, which is capable of withdrawing ≈3.0 μL of ISF from the skin. MN arrays applied with an upward driving force may increase the ISF flow rate. Moreover, functionalized CF working electrodes (WE1, WE2, WE3) are shown to selectively detect lactate, glucose, and K+ with high sensitivities of 0.258, 0.549, and 0.657 μA μm−1 cm−2 and low detection limits of 0.01, 0.080, 0.05 μm, respectively. Ex vivo testing on porcine skin is used to detect the ISF levels of the biomarkers. The microscale device can be a replacement for current point‐of‐care diagnostic approaches.

Theoretical study of entropy-induced friction in graphene

The exceptional properties of graphene and other two-dimensional (2D) materials have endowed them with enormous potentials as fundamental elements in future microscale devices. With the dimension reduction in 2D materials, new friction behavior emerges: the friction is dominated by the contact edges rather than the contact areas. This edge-dominated behavior has an essentially entropic origin. Herein we develop an analytical model to describe this entropy-originated friction in graphene based on lattice dynamics theory. This edge-dominated friction is attributed to a translation effect of the surface interaction on the local vibration modes. By considering the potential stiffness on the vibration modes, the analytical model enables us to investigate the dependence of friction on sliding speed, normal load, and stiffness of the supporting surface. The analytical model is found to give accurate prediction close to those given by molecular dynamics simulations. These findings confirm that the analytical model can capture the underlying physics of graphene interlayer friction effectively. Though graphene is investigated herein, the analytical model will have general applications in characterizing the tribological behavior of other single-atom-thick 2D materials since they possess similar phononic properties as graphene.

Single‐Crystal Nanowire Cesium Tin Triiodide Perovskite Solar Cell

This work reports for the first time a highly efficient single-crystal cesium tin triiodide (CsSnI3 ) perovskite nanowire solar cell. With a perfect lattice structure, low carrier trap density (≈5×1010 cm-3 ), long carrier lifetime (46.7ns), and excellent carrier mobility (>600 cm2 V-1 s-1 ), single-crystal CsSnI3 perovskite nanowires enable a very attractive feature for flexible perovskite photovoltaics to power active micro-scale electronic devices. Using CsSnI3 single-crystal nanowire in conjunction with highly conductive wide bandgap semiconductors as front-surface-field layers, an unprecedented efficiency of 11.7% under AM 1.5G illumination is achieved. This work demonstrates the feasibility of all-inorganic tin-based perovskite solar cells via crystallinity and device-structure improvement for the high-performance, and thus paves the way for the energy supply to flexible wearable devices in the future.

Strong room-temperature bulk nonlinear Hall effect in a spin-valley locked Dirac material

Nonlinear Hall effect (NLHE) is a new type of Hall effect with wide application prospects. Practical device applications require strong NLHE at room temperature (RT). However, previously reported NLHEs are all low-temperature phenomena except for the surface NLHE of TaIrTe4. Bulk RT NLHE is highly desired due to its ability to generate large photocurrent. Here, we show the spin-valley locked Dirac state in BaMnSb2 can generate a strong bulk NLHE at RT. In the microscale devices, we observe the typical signature of an intrinsic NLHE, i.e. the transverse Hall voltage quadratically scales with the longitudinal current as the current is applied to the Berry curvature dipole direction. Furthermore, we also demonstrate our nonlinear Hall device’s functionality in wireless microwave detection and frequency doubling. These findings broaden the coupled spin and valley physics from 2D systems into a 3D system and lay a foundation for exploring bulk NLHE’s applications.

A Review of Cooperative Actuator and Sensor Systems Based on Dielectric Elastomer Transducers

This paper presents an overview of cooperative actuator and sensor systems based on dielectric elastomer (DE) transducers. A DE consists of a flexible capacitor made of a thin layer of soft dielectric material (e.g., acrylic, silicone) surrounded with a compliant electrode, which is able to work as an actuator or as a sensor. Features such as large deformation, high compliance, flexibility, energy efficiency, lightweight, self-sensing, and low cost make DE technology particularly attractive for the realization of mechatronic systems that are capable of performance not achievable with alternative technologies. If several DEs are arranged in an array-like configuration, new concepts of cooperative actuator/sensor systems can be enabled, in which novel applications and features are made possible by the synergistic operations among nearby elements. The goal of this paper is to review recent advances in the area of cooperative DE systems technology. After summarizing the basic operating principle of DE transducers, several applications of cooperative DE actuators and sensors from the recent literature are discussed, ranging from haptic interfaces and bio-inspired robots to micro-scale devices and tactile sensors. Finally, challenges and perspectives for the future development of cooperative DE systems are discussed.

Design and performance analysis of a novel displacement-based temperature sensor

Abstract In this paper, we present a proof-of-concept for a novel temperature sensing approach that combines the thermal expansion and a compliant mechanism. The objective is first to demonstrate its feasibility at the macroscale, develop and validate an FEM model at the macroscale and then scale down the FEM model to verify the possible implementation of the mechanism at the microscale. The sensing approach relies on a mechanical compliant mechanism that amplifies the thermal expansion of a structure. A testing platform equipped with an IR thermometer, thermocouple, a power supply, and laser distance sensors, is implemented to demonstrate the operability of the proposed sensing mechanism. A numerical model of the sensor is developed using the FE software Ansys. The numerical results show a good agreement with their experimental counterparts at the macro scale. The model is then used to numerically investigate several configurations, namely single, double, triple and quadruple compliant mechanisms. The amplification factor is found the highest when using the double compliant mechanism. A temperature sensitivity of 28.5 μm/°C is achieved for this compliant mechanism. The numerical analysis also demonstrated that the performance obtained at the macro scale, can be conserved for microscale devices. However, buckling of some elements is observed for the microscale system which degrades the performance of the sensor when subjected to relatively large displacements. The microscale FEM model shows the possible prevention of buckling issues by slightly modifying the geometry of the compliant mechanisms. The present study is expected to provide baseline and guidance for the implementation of the sensing approach for MEMS devices.

Anisotropic property of turbulent flow control through multiple stenosed microtubes

Rapid development in micro-scale systems and devices for drug delivery and biotechnical analysis has been scurrying. Microtube or microchannel roughness is another challenging factor in microfabrication technology. Moreover, the irregular roughness occurs due to the multiple depositions of cholesterol and other substances in the endothelium of the arterial wall. To investigate those issues, the effect of the irregular roughness of the wall on the anisotropy of the turbulent blood flow through an atherosclerotic artery has been analyzed. The flow through a stenosed microtube has been numerically simulated to understand the blood flow phenomenon through arterial stenosis and different turbulent states. The Reynolds stress components are estimated and plotted an invariant map and Eigen map to examine the turbulent states. The comparison results have been studied to show the nature of turbulent flow in low Reynolds numbers due to irregular roughness. The turbulent kinetic energy and turbulent viscous dissipation rate are also examined. Due to wall shear stress, the flow deserves the turbulence flow characteristic downstream of the abnormally narrowed regions of the microtube. The nature of the wall shear rate and the high viscosity of blood impact the disturbance in the flow velocity in microtubes.

Numerical and Experimental Analysis of a Prototypical Thermoelectric Generator Dedicated to Wood-Fired Heating Stove.

The typical operating range of domestic heating devices includes only heat generation. However, the availability of combined heat and power generation in microscale devices is currently becoming a more and more interesting option. This paper shows the experimental and numerical analysis of the possibility of developing a micro-cogeneration system equipped with a wood-fired heating stove and a prototype of the thermoelectric generator equipped with low-price thermoelectric modules. In the first step, mathematical modeling made it possible to analyze different configurations of the hot side of the thermoelectric generator (computational fluid dynamics was used). Next, experiments have been conducted on the prototypical test rig. The maximum power obtained during the discussed combustion process was 15.9 We when the flue gas temperature was approximately 623 K. Assuming a case, when such value of generated power occurred during the whole main phase, the energy generated would be at a level of approximately 33.1 Whe, while the heat transferred to the water would be approximately 1 078.0 Whth. In addition to the technical aspects, the economic premises of the proposed solution were analyzed. As was shown, an installation of TEG to the existing stove is economically not viable: the Simply Payback Time will be approximately 28.9-66.1 years depending on the analyzed scenario. On the other hand, the SPBT would be significantly shorter, when the installation of the stove with an integrated thermoelectric generator was considered (approximately 5.4 years). However, it should be noted that the introduction of the power generating system to a heat source can provide fully or partially network-independent operation of the hot water and heating systems.

Threshold switching stabilization of NbO2 films via nanoscale devices

The stabilization of the threshold switching characteristics of memristive NbOx is examined as a function of sample growth and device characteristics. Sub-stoichiometric Nb2O5 was deposited via magnetron sputtering and patterned in nanoscale (50×50–170×170nm2) W/Ir/NbOx/TiN devices and microscale (2×2–15×15μm2) crossbar Au/Ru/NbOx/Pt devices. Annealing the nanoscale devices at 700 °C removed the need for electroforming the devices. The smallest nanoscale devices showed a large asymmetry in the IV curves for positive and negative bias that switched to symmetric behavior for the larger and microscale devices. Electroforming the microscale crossbar devices created conducting NbO2 filaments with symmetric IV curves whose behavior did not change as the device area increased. The smallest devices showed the largest threshold voltages and most stable threshold switching. As the nanoscale device area increased, the resistance of the devices scaled with the area as R∝A−1, indicating a crystallized bulk NbO2 device. When the nanoscale device size was comparable to the size of the filaments, the annealed nanoscale devices showed similar electrical responses as the electroformed microscale crossbar devices, indicating filament-like behavior in even annealed devices without electroforming. Finally, the addition of up to 1.8% Ti dopant into the films did not improve or stabilize the threshold switching in the microscale crossbar devices.

Response Surface Methodology and Artificial Neural Network modellings on hydraulic and thermal performances of a disk-shaped heat sink with tree-like microchannels

To cope with the increasing heat generation resulting from increased power in micro-scale devices, an optimum design of a tree-like microchannel heat sink is suggested utilizing Artificial Neural Networks (ANN) and Response Surface Methodology (RSM). Based on the numerical finite volume model, both ANN and RSM models were trained, and their performances were assessed using four distinct performance criteria. The results showed that both of the models are reliable for the purpose of this study, showing a significantly high adjusted R2 for both performance control variables pressure drop (ΔP) and Nusselt number (Nu). The adjusted R2 values observed for the RSM were 0.987 and 0.997, respectively, for the Nu and ΔP. These values were calculated as high as 0.997 for Nu prediction and 0.997 for ΔP prediction using the ANN. Finally, utilizing the calibrated RSM and ANN models, three optimum design configurations for three different purposes given the priority requirements of the heat sink implementations were suggested. The minimum ΔP configuration is suitable for the longevity of the heat sink, and the maximum Nu configuration is suitable for applications where heat transfer performance is more critical. For a balanced optimum design, the efficiency index was maximized.

Organs-on-Chips Platforms Are Everywhere: A Zoom on Biomedical Investigation.

Over the decades, conventional in vitro culture systems and animal models have been used to study physiology, nutrient or drug metabolisms including mechanical and physiopathological aspects. However, there is an urgent need for Integrated Testing Strategies (ITS) and more sophisticated platforms and devices to approach the real complexity of human physiology and provide reliable extrapolations for clinical investigations and personalized medicine. Organ-on-a-chip (OOC), also known as a microphysiological system, is a state-of-the-art microfluidic cell culture technology that sums up cells or tissue-to-tissue interfaces, fluid flows, mechanical cues, and organ-level physiology, and it has been developed to fill the gap between in vitro experimental models and human pathophysiology. The wide range of OOC platforms involves the miniaturization of cell culture systems and enables a variety of novel experimental techniques. These range from modeling the independent effects of biophysical forces on cells to screening novel drugs in multi-organ microphysiological systems, all within microscale devices. As in living biosystems, the development of vascular structure is the salient feature common to almost all organ-on-a-chip platforms. Herein, we provide a snapshot of this fast-evolving sophisticated technology. We will review cutting-edge developments and advances in the OOC realm, discussing current applications in the biomedical field with a detailed description of how this technology has enabled the reconstruction of complex multi-scale and multifunctional matrices and platforms (at the cellular and tissular levels) leading to an acute understanding of the physiopathological features of human ailments and infections in vitro.

Near-Infrared Spectroscopy Coupled with Chemometrics and Artificial Neural Network Modeling for Prediction of Emulsion Droplet Diameters.

There is increased interest in the food industry for emulsions as delivery systems to preserve the stability of sensitive biocompounds with the aim of improving their bioavailability, solubility, and stability; maintaining their texture; and controlling their release. Emulsification in continuously operated microscale devices enables the production of emulsions of controllable droplet sizes and reduces the amount of emulsifier and time consumption, while NIR, as a nondestructive, noninvasive, fast, and efficient technique, represents an interesting aspect for emulsion investigation. The aim of this work was to predict the average Feret droplet diameter of oil-in-water and oil-in-aqueous mint extract emulsions prepared in a continuously operated microfluidic device with different emulsifiers (PEG 1500, PEG 6000, and PEG 20,000) based on the combination of near-infrared (NIR) spectra with chemometrics (principal component analysis (PCA) and partial least-squares (PLS) regression) and artificial neural network (ANN) modeling. PCA score plots for average preprocessed NIR spectra show the specific grouping of the samples into three groups according to the emulsifier used, while the PCA analysis of the emulsion samples with different emulsifiers showed the specific grouping of the samples based on the amount of emulsifier used. The developed PLS models had higher R2 values for oil-in-water emulsions, ranging from 0.6863 to 0.9692 for calibration, 0.5617 to 0.8740 for validation, and 0.4618 to 0.8692 for prediction, than oil-in-aqueous mint extract emulsions, with R2 values that were in range of 0.8109-0.8934 for calibration, 0.5017-0.6620, for validation and 0.5587-0.7234 for prediction. Better results were obtained for the developed nonlinear ANN models, which showed R2 values in the range of 0.9428-0.9917 for training, 0.8515-0.9294 for testing, and 0.7377-0.8533 for the validation of oil-in-water emulsions, while for oil-in-aqueous mint extract emulsions R2 values were higher, in the range of 0.9516-0.9996 for training, 0.9311-0.9994 for testing, and 0.8113-0.9995 for validation.