Misalignment-Tolerant Planar Spiral Coil Pair Design for 13.56 MHz Inductive Coupling of Wireless Resistive Analog Passive Sensors.

Long-term daily-life body signal monitoring offers numerous advantages, such as timely response to health alerts, diseases monitoring, and reducing time and expenses related to clinical trials. Access to physiological data can be achieved with low-cost and comfortable wireless wearable sensors. In our previous publication, we reported a low-cost, easy to implement, and unobtrusive wireless resistive analog passive (WRAP) sensor to provide a feasible bio-signal monitoring technique by using a pair of printed spiral coils (PSC) in a near field connection. Sensitivity, defined as the response to the transducer, is a critical feature in the establishment of a reliable system. In the previous publication, we presented the utilization of a Genetic Algorithm to design a pair of coils and related components to maximize sensitivity. Although the coils' misalignment can significantly affect the optimized sensitivity, it was not incorporated into the optimization process. This paper focuses on optimizing the coils and components in order to maximize both their sensitivity and their resilience against movements of the PSC pair. In a square-shaped pair comprising a primary coil of 60 mm and a secondary coil of 20 mm dimensions, we found that the sensitivity is maximized at 1.3 mƱ for a 16 mm axial distance. Additionally, it remains above 0.65 mƱ within ±11.25 mm lateral and +14 mm axial displacements.

Rice straw agri-waste for water pollutant adsorption: Relevant mesoporous super hydrophobic cellulose aerogel.

A simplistic synthesis approach for fabrication of ultra-light density (2.2 to 24 mg. cm-3), highly porous (98.4%-99.8%), and cross-linked natural cellulose aerogel from rice straw was developed via a freeze-drying process. The obtained natural cellulose aerogels exhibited porous network structure with specific areas of 178.8 m2. g-1 and mesopore volumes of 0.8 cm3. g-1. The cellulose aerogel with 1.3 wt% displayed the highest Young's modulus and compressive strength. Subsequent hydrophobic coating with methyltrimethoxysilane, the super-hydrophobic and oleophilic cellulose aerogel (water contact angle as high as 151 ± 7°) were capable of adsorbing a wide range of organic solvents and oils with adsorption capacities up to 170 g. g-1 based on the density of the liquids. Furthermore, the adsorbed organic solvent could be desorbed by means of simple mechanical squeezing. These results suggested that the super-hydrophobic natural cellulose aerogel can be used as a precious sorbents for adsorption of oil and organic solvents.

Immunomagnetic Capture and Multiplexed Surface Marker Detection of Circulating Tumor Cells with Magnetic Multicolor Surface-Enhanced Raman Scattering Nanotags.

Circulating tumor cells (CTCs) have substantial clinical implications in cancer diagnosis and monitoring. Although significant progress has been made in developing technologies for CTC detection and counting, the ability to quantitatively detect multiple surface protein markers on individual tumor cells remains very limited. In this work, we report a multiplexed method that uses magnetic multicolor surface-enhanced Raman scattering (SERS) nanotags in conjunction with a chip-based immunomagnetic separation to quantitatively and simultaneously detect four surface protein markers on individual tumor cells in whole blood. Four-color SERS nanotags were prepared using magnetic-optical iron oxide-gold core-shell nanoparticles with different Raman reporters to recognize four different cancer markers with respective antibodies. A microfluidic device was fabricated to magnetically capture the nanoparticle-bound tumor cells and to perform online negative staining and single-cell optical detection. The level of each targeted protein was obtained by signal deconvolution of the mixed SERS signals from individual tumor cells using the classic least squares regression method. The method was tested with spiked tumor cells in human whole blood with three different breast cancer cell lines and compared with the results of purified cancer cells suspended in a phosphate buffer solution. The method, with either spiked cancer cells in blood or purified cancer cells, showed a strong correlation with purified cancer cells by enzyme-linked immunosorbent assay, suggesting the potential of our method for the reliable detection of multiple surface markers on CTCs. Combining immunomagnetic enrichment with high specificity, multiplexed targeting for the capture of CTC subpopulations, multicolor SERS detection with high sensitivity and specificity, microfluidics for handling rare cells and magnetic-plasmonic nanoparticles for dual enrichment and detection, our method provides an integrated, yet a simple and an efficient platform that has the potential to more sensitively detect and monitor cancer metastasis.

Sensitivity optimization of Printed Spiral Coil for Wireless Resistive Analog Passive (WRAP) Sensors using Genetic Algorithm.

Body-worn battery-less Wireless Resistive Analog Passive (WRAP) sensor can be unobtrusive while collecting physiological data continuously. Inductive connection between a pair of Printed Spiral Coils (PSC) eliminates the intrusive wires. Inductive connection of primary and secondary PSC enabled us to probe the body signals using the inductive link. The primary side voltage is modulated by the sensed body signal at the secondary PSC. The coil physical characteristics influence the sensitivity which is defined as observed voltage changes over the sensor variation. We have previously reported an iterative method to optimize the coil specifications for maximum sensitivity with constrained coil prof ile size by maximizing the power transfer efficiency from primary to secondary. In this study sensitivity is maximized by first, driving an analytical multivariable equation of circuit components and physical characteristics, and then using Genetic Algorithm (GA) to maximize it with considering the size and fabrication constraints. The results are compared to the other methods that shows a higher result in the range of 102 comparing to the best alternate methods (sqp). It helps us to detect smaller physiological signals in the noisy environment.

Applicable models for multi-component adsorption of dyes: a review.

Adsorption is one of the several techniques that has been successfully used for dyes removal. Since most industrial colored effluents contain several components including dyes, having a strong knowledge about the scope of competitive adsorption process is a powerful key to design an appropriate system. This is mainly because of the complexity brought about by the increasing number of parameters needed for process description which complicates not only the process modeling but also the experimental data collection. A multicomponent adsorption model should be based on fundamental soundness, speed, and simplicity of calculation. For such systems, competition will change the adsorbent-adsorbate attractions. Thus, there is major concern to develop an accurate and reliable method to predict dye adsorption behavior in multi-component systems. This article covers topics such as the theory of dyes adsorption in multi-component systems along with applicable models according to the consistent theories presented by researchers.