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This study aims to provide a microfluidic blood glucose sensing platform based on integrated interdigitated electrode arrays (IDEAs) on a flexible quartz glass substrate, adhering closely to pertinent electrochemical characterizations.

Sensors are the key elements of the modern electronics era through which all the possible physical quantities can be detected and converted into their equivalent electrical form and processed further. But to make the sensing environment better, various types of innovative architectures are being developed nowadays and among them interdigitated electrodes are quite remarkable in terms of their sensing capability. They are a well-qualified candidate in the field of gas sensing and biosensing, but even their sensitivities are getting saturated due to their physical dimensions. Most of the thin film IDEAs fabricated by conventional optical lithographic techniques do not possess a high surface-to-volume ratio to detect the target specified and that reduces their sensitivity factor. In this context, a classic conductive carbon-based highly sensitive three dimensional (3D) IDEA-enabled biosensing system has been conceived on a transparent and flexible substrate to measure the amount of glucose concentration present in human blood. 3D IDEA possesses a way better capacitive sensing behavior compared to conventional thin film microcapacitive electrodes. To transmit the target biological analyte sample property for the detection purpose to the interdigitated array-based sensing platform, the design of a microfluidic channel is initiated on the same substrate. The complex 3D Inter Digital array structure improves the overall capacitance of the entire sensing platform and the reactive surface area as well. The manufactured integrated device displays a decent value of sensitivity in the order of 5.6 µA mM⁻¹ cm⁻².

Development of a low-cost array-based integrated and highly flexible microfluidic biochip to extract the quantity of glucose present in human blood.

Potential future research opportunities in the realm of integrated miniaturized, low-cost smart biosensing systems may arise from this study.

This study aims to minimize the pressure drop across wavy microchannels using secondary branches without compromising its capacity to transfer the heat. The impact of secondary flows on the pressure drop and heat transfer capabilities at different Reynolds numbers are investigated numerically for different wavy microchannels. Finally, different channels are evaluated using performance evaluation criteria to determine their effectiveness.

To investigate the flow and heat transfer capabilities in wavy microchannels having secondary branches, a 3D conjugate heat transfer model based on finite volume method is used. In conventional wavy microchannel, secondary branches are introduced at crest and trough locations. For the numerical simulation, a single symmetrical channel is used to minimize computational time and resources and the flow within the channels remains single-phase and laminar.

The findings indicate that the suggested secondary channels notably improve heat transfer and decrease pressure drop within the channels. At lower flow rates, the secondary channels demonstrate superior performance in terms of heat transfer. However, the performance declines as the flow rate increased. With the same amplitude and wavelength, the introduction of secondary channels reduces the pressure drop compared with conventional wavy channels. Due to the presence of secondary channels, the flow splits from the main channel, and part of the core flow gets diverted into the secondary channel as the flow takes the path of minimum resistance. Due to this flow split, the core velocity is reduced. An increase in flow area helps in reducing pressure drop.

Many complex and intricate microchannels are proposed by the researchers to augment heat dissipation. There are challenges in the fabrication of microchannels, such as surface finish and achieving the required dimensions. However, due to the recent developments in metal additive manufacturing and microfabrication techniques, the complex shapes proposed in this paper are feasible to fabricate.

Wavy channels are widely used in heat transfer and micro-fluidics applications. The proposed wavy microchannels with secondary channels are different when compared to conventional wavy channels and can be used practically to solve thermal challenges. They help achieve a lower pressure drop in wavy microchannels without compromising heat transfer performance.

Selective jet electrodeposition (SJED) is an emerging additive manufacturing (AM) technology for realizing metallic components of nano and micro sizes. The deposited parts on the substrate form metallurgical bonding, so separating them from the substrate is an unsolved issue. Therefore, this paper aims to propose a method for separating the deposited micro parts from a sacrificial substrate. Furthermore, single and multi-bead optimization is performed to fabricate microparts with varying density.

A typical SJED process consists of a nozzle (to establish a column of electrolytes) retrofitted on a machine tool (to provide relative motion between substrate and nozzle) that deposits material atom-by-atom on a conductive substrate.

A comprehensive study of process parameters affecting the layer height, layer width and morphology of the deposited micro-parts has been provided. The uniformity in the deposited parts can be achieved with the help of low applied voltage and high scanning speed. Multi-bead analysis for the flat surface condition is experimentally performed, and the flat surface condition is achieved when the centre distance between two adjacent beads is kept at half of the width of a single bead.

Although several literatures have demonstrated that the SJED process can be used for the fabrication of parts; however, part fabrication through multi-bead optimization is limited. Moreover, the removal of the fabricated part from the substrate is the novelty of the current work.

This study aims to introduce a vision-based model to generate droplets with auto-tuned parameters. The model can auto-adjust the inherent uncertainties and errors involved with the fabrication and operating parameters in microfluidic platform, attaining precise size and frequency of droplet generation.

The photolithography method is utilized to prepare the microfluidic devices used in this study, and various experiments are conducted at various flow-rate and viscosity ratios. Data for droplet shape is collected to train the artificial intelligence (AI) models.

Growth phase of droplets demonstrated a unique spring back effect in droplet size. The fully developed droplet sizes in the microchannel were modeled using least absolute shrinkage and selection operators (LASSO) regression model, Gaussian support vector machine (SVM), long short term memory (LSTM) and deep neural network models. Mean absolute percentage error (MAPE) of 0.05 and R² = 0.93 were obtained with a deep neural network model on untrained flow data. The shape parameters of the droplets are affected by several uncontrolled parameters. These parameters are instinctively captured in the model.

Experimental data set is generated for varying viscosity values and flow rates. The variation of flow rate of continuous phase is observed here instead of dispersed phase. An automated computation routine is developed to read the droplet shape parameters considering the transient growth phase of droplets. The droplet size data is used to build and compare various AI models for predicting droplet sizes. A predictive model is developed, which is ready for automated closed loop control of the droplet generation.

The purpose of this paper is to provide details of biomimetic and neuromorphic sensor research and developments and discuss their applications in robotics.

Following a short introduction, this first provides examples of recent biomimetic gripping and sensing skin research and developments. It then considers neuromorphic vision sensing technology and its potential robotic applications. Finally, brief conclusions are drawn.

Biomimetics aims to exploit mechanisms, structures and signal processing techniques which occur in the natural world. Biomimetic sensors and control techniques can impart robots with a range of enhanced capabilities such as learning, gripping and multidimensional tactile sensing. Neuromorphic vision sensors offer several key operation benefits over conventional frame-based imaging techniques. Robotic applications are still largely at the research stage but uses are anticipated in enhanced safety systems in autonomous vehicles and in robotic gripping.

This illustrates how tactile and imaging sensors based on biological principles can contribute to imparting robots with enhanced capabilities.

The purpose of this research is to study the performance of piezoresistive pressure sensors using polysilicon as the piezoresistive material, which is typically used to measure pressure in high-temperature environments.

The performance of this sensor is enhanced by studying the influence of multi-turn configuration at which the piezoresistors are arranged. Different configurations are studied and compared by laying down their analytical solution.

The validation of analytical results is accomplished through finite element analysis using the software COMSOL Multiphysics. The best configuration, which uses a partial triple-turn configuration, was able to achieve a sensitivity of 116.00 mV/V/MPa over a simulated pressure range of 0 to 500 KPa.

The literature shows the study of single-turn and double-turn meander-shaped configuration of micro-electromechanical systems piezoresistive pressure sensor but multi-turn meander-shaped configuration using a square silicon diaphragm has not been reported. Its study has reflected promising results than its counterparts based on key performance parameters such as sensitivity and linearity and are more effective to be used for automotive, aviation, biomedical and consumer electronics applications.

Recently, powerful instruments for biomedical engineering research studies, including disease modeling, drug designing and nano-drug delivering, have been extremely investigated by researchers. Particularly, investigation in various microfluidics techniques and novel biomedical approaches for microfluidic-based substrate have progressed in recent years, and therefore, various cell culture platforms have been manufactured for these types of approaches. These microinstruments, known as tissue chip platforms, mimic in vivo living tissue and exhibit more physiologically similar vitro models of human tissues. Using lab-on-a-chip technologies in vitro cell culturing quickly caused in optimized systems of tissues compared to static culture. These chipsets prepare cell culture media to mimic physiological reactions and behaviors.

The authors used the application of lab chip instruments as a versatile tool for point of health-care (PHC) applications, and the authors applied a current progress in various platforms toward biochip DNA sensors as an alternative to the general bio electrochemical sensors. Basically, optical sensing is related to the intercalation between glass surfaces containing biomolecules with fluorescence and, subsequently, its reflected light that arises from the characteristics of the chemical agents. Recently, various techniques using optical fiber have progressed significantly, and researchers apply highlighted remarks and future perspectives of these kinds of platforms for PHC applications.

The authors assembled several microfluidic chips through cell culture and immune-fluorescent, as well as using microscopy measurement and image analysis for RNA sequencing. By this work, several chip assemblies were fabricated, and the application of the fluidic routing mechanism enables us to provide chip-to-chip communication with a variety of tissue-on-a-chip. By lab-on-a-chip techniques, the authors exhibited that coating the cell membrane via poly-dopamine and collagen was the best cell membrane coating due to the monolayer growth and differentiation of the cell types during the differentiation period. The authors found the artificial membrane, through coating with Collagen-A, has improved the growth of mouse podocytes cells-5 compared with the fibronectin-coated membrane.

The authors could distinguish the differences across the patient cohort when they used a collagen-coated microfluidic chip. For instance, von Willebrand factor, a blood glycoprotein that promotes hemostasis, can be identified and measured through these type-coated microfluidic chips.

Additive lamination manufacturing (ALM), as a novel additive manufacturing technology, builds up the geometry via the lamination of fiber-reinforced polymer (FRP) fabric laterally, rendering it suitable for fabricating large-scale Stay-in-Place concrete formwork. This paper aims to investigate the control parameters and structure performance of ALM and assess its application for the fabrication of large-scale concrete formwork.

Based on previous feasibility studies, this research systematically investigates the control and material parameters that influence horizontal and vertical extrusion speeds, as well as the overall quality of ALM. Once the system parameters are established, a series of prototypes are fabricated and tested to validate the tensile strength of the formwork and its reinforcement capabilities. In addition, this study assesses the potential geometric freedom and implementation constraints of ALM.

This research identifies the essential control parameters for path planning in ALM and examines their impact on fabrication. In addition, this paper evaluates ALM’s strengths and limitations in producing concrete formwork for large-scale concrete structures, comparing these to industry benchmarks.

A critical challenge in additive manufacturing lies in its scalability and compatibility with existing construction processes. In comparison to concrete, FRP offers advantages such as being lighter, easier to handle and providing surface protection and reinforcement. These qualities make FRP superior for formwork and compatible with existing building standards. Despite its advantages and potential, the current path planning and control model in 3D printing do not apply to ALM due to its novel build-up process. Also, the performance of fabricated parts as part of integrated large-scale structures is yet to be studied.

Some studies have been reported in the past on diaphragmatic hernia (DH) surgery techniques using additive manufacturing (AM) technologies, symptoms of a hernia and post-surgery complications. But hitherto little has been reported on bibliographic analysis (BA) for health monitoring of bovine post-DH surgery for long-term management. Based on BA, this study aims to explore the sensor fabrication integrated with innovative AM technologies for health monitoring assistance of bovines post-DH surgery.

A BA based on the data extracted through the Web of Science database was performed using bibliometric tools (R-Studio and Biblioshiny).

After going through the BA and a case study, this review provides information on various 3D-printed meshes used over the sutured site and available Internet of Things-based solutions to prevent the recurrence of DH.

Research gaps exist for 3D-printed conformal sensors for health monitoring of bovine post-DH surgery.

Based on previous results of the existence, uniqueness, and regularity conditions for a continuous dynamic model for a parallel-plate electrostatic micro-electron-mechanical-systems with the fringing field, the purpose of this paper concerns a Galerkin-FEM procedure for deformable element deflection recovery. The deflection profiles are reconstructed by assigning the dielectric properties of the moving element. Furthermore, the device’s use conditions and the deformable element’s mechanical stresses are presented and discussed.

The Galerkin-FEM approach is based on weighted residuals, where the integrals appearing in the solution equation have been solved using the Crank–Nicolson algorithm.

Based on the connection between the fringing field and the electrostatic force, the proposed approach reconstructs the deflection of the deformable element, satisfying the conditions of existence, uniqueness and regularity. The influence of the electromechanical properties of the deformable plate on the method has also been considered and evaluated.

The developed analytical model focused on a rectangular geometry.

The device studied is suitable for industrial and biomedical applications.

This paper proposed numerical approach characterized by low CPU time enables the creation of virtual prototypes that can be analyzed with significant cost reduction and increased productivity.