Microwave Sensor for the Determination of DMSO Concentration in Water-DMSO Binary Mixture.

This research aims to develop a microwave sensor to accurately measure the concentration of dimethyl sulfoxide (DMSO) in water-DMSO binary mixtures. The proposed sensor will utilize microwave frequency measurements to determine the DMSO concentration, providing a non-invasive and efficient method for analyzing DMSO solutions. The research will involve the design, fabrication, and testing of the sensor, as well as the development of an appropriate calibration model. The outcomes of this study will contribute to improved monitoring and quality control in various fields, including pharmaceuticals, chemical synthesis, and biomedical research. The binary mixtures of dimethyl sulfoxide (DMSO) and water with varying concentrations were investigated in the frequency range of 1 GHz to 5 GHz at room temperature using a microwave sensor. The proposed microwave sensor design was based on an interdigital capacitor (IDC) microstrip antenna loaded with a hexagonal complementary ring resonator (HCRR). The performance of the sensor, fabricated using the print circuit board (PCB) technique, was validated through simulations and experiments. The reflection coefficient (S11) and resonance frequency (Fr) of binary mixtures of DMSO and water solutions were recorded and analyzed for DMSO concentrations ranging from 0% v/v to 75% v/v. Mathematical models were developed to analyze the data, and laboratory tests showed that the sensor can detect levels of DMSO/water binary mixtures. The sensor is capable of detecting DMSO concentrations ranging from 0% v/v to 75% v/v, with a maximum sensitivity of 0.138 dB/% for S11 and ΔS11 and 0.2 MHz/% for Fr and ΔFr at a concentration of 50% v/v. The developed microwave sensor can serve as an alternative for detecting DMSO concentrations in water using a simple and cost-effective technique. This method can effectively analyze a wide range of concentrations, including highly concentrated solutions, quickly and easily.

Sensing High 17ß-Estradiol Concentrations Using a Planar Microwave Sensor Integrated with a Microfluidic Channel.

The global issue of pollution caused by endocrine-disrupting chemicals (EDCs) has been gaining increasing attention. Among the EDCs of environmental concern, 17ß-estradiol (E2) can produce the strongest estrogenic effects when it enters the organism exogenously through various routes and has the potential to cause harm, including malfunctions of the endocrine system and development of growth and reproductive disorders in humans and animals. Additionally, in humans, supraphysiological levels of E2 have been associated with a range of E2-dependent disorders and cancers. To ensure environmental safety and prevent potential risks of E2 to human and animal health, it is crucial to develop rapid, sensitive, low cost and simple approaches for detecting E2 contamination in the environment. A planar microwave sensor for E2 sensing is presented based on the integration of a microstrip transmission line (TL) loaded with a Peano fractal geometry with a narrow slot complementary split-ring resonator (PF-NSCSRR) and a microfluidic channel. The proposed technique offers a wide linear range for detecting E2, ranging from 0.001 to 10 mM, and can achieve high sensitivity with small sample volumes and simple operation methods. The proposed microwave sensor was validated through simulations and empirical measurements within a frequency range of 0.5-3.5 GHz. The E2 solution was delivered to the sensitive area of the sensor device via a microfluidic polydimethylsiloxane (PDMS) channel with an area of 2.7 mm2 and sample value of 1.37 µL and measured by a proposed sensor. The injection of E2 into the channel resulted in changes in the transmission coefficient (S21) and resonance frequency (Fr), which can be used as an indicator of E2 levels in solution. The maximum quality factor of 114.89 and the maximum sensitivity based on S21 and Fr at a concentration of 0.01 mM were 1746.98 dB/mM and 40 GHz/mM, respectively. Upon comparing the proposed sensor with the original Peano fractal geometry with complementary split-ring (PF-CSRR) sensors without a narrow slot, several parameters were evaluated, including sensitivity, quality factor, operating frequency, active area, and sample volume. The results showed that the proposed sensor exhibited an increased sensitivity of 6.08% and had a 40.72% higher quality factor, while the operating frequency, active area, and sample volume showed decreases of 1.71%, 25%, and 28.27%, respectively. The materials under tests (MUTs) were analyzed and categorized into groups using principal component analysis (PCA) with a K-mean clustering algorithm. The proposed E2 sensor has a compact size and simple structure that can be easily fabricated with low-cost materials. With the small sample volume requirement, fast measurement with a wide dynamic range, and a simple protocol, this proposed sensor can also be applied to measure high E2 levels in environmental, human, and animal samples.

Narrow-Band Light-Emitting Diodes (LEDs) Effects on Sunflower (Helianthus annuus) Sprouts with Remote Monitoring and Recording by Internet of Things Device.

Previous studies have demonstrated that light quality critically affects plant development and growth; however, the response depends upon the plant species. This research aims to examine the effects of different light wavelengths on sunflower (Helianthus annuus) sprouts that were stimulated during the night. Natural light and narrow-band light-emitting diodes (LEDs) were used for an analysis of sunflower sprouts grown under full light and specific light wavelengths. Sunflower seeds were germinated under different light spectra including red, blue, white, and natural light. Luminosity, temperature, and humidity sensors were installed in the plant nursery and remotely monitored and recorded by an Internet of Things (IoT) device. The experiment examined seed germination for seven days. The results showed that the red light had the most influence on sunflower seed germination, while the natural light had the most influence on the increase in the root and hypocotyl lengths.

Microwave Microfluidic Sensor for Detection of High Equol Concentrations in Aqueous Solution.

This paper presents a Peano fractal geometry complementary split ring resonator (PFCSRR) loaded microstrip transmission line with a microfluidic channel for equol (EQ) sensing in a high and wide range of concentrations in aqueous solution. The proposed sensor was designed based on a CSRR loaded microstrip line with a Peano fractal in the center of a CSRR and validated through simulation and experiment. The microfluidic channel was fabricated using polydimethylsiloxane (PDMS) and installed to cover the sensing area. The free space, empty microfluidic channels, deionized (DI) water, dimethyl sulfoxide (DMSO), and various concentrations of EQ were measured by a microwave sensor through sample-filled microfluidic channels. Detection of high levels of EQ was in the concentration range of 0.01 mM - 100 mM. The materials under test (MUTs) were measured in the frequency range of 1.0 GHz-3.5 GHz based on the magnitude of the transmission coefficient (S21) and resonance frequency (Fr) at room temperature. The S21 and Fr were recorded and analyzed by logarithmic concentrations of EQ for the determinant of the correlations between EQ concentration and S21 and Fr. Principal component analysis (PCA) and K-means clustering were used to analyze and classify groups of MUTs.

The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor.

The water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real-time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

Real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentration by electromagnetic sensing.

Magnetic sensing at microwave frequencies for real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentrations is reported. The sensing element was designed based on a coplanar waveguide (CPW) loaded with a split ring resonator (SRR), which was fabricated on a DiClad 880 substrate with a thickness of 1.6mm and relative permittivity (εr) of 2.2. The magnetic sensor was connected to a Vector Network Analyzer (VNA) and the electromagnetic interaction between the samples and sensor was analyzed. The magnitude of the transmission coefficient (S21) was used as an indicator to detect the solution sample concentrations ranging from 0.04 to 0.20g/ml. The experimental results confirmed that the developed system using microwaves for the real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentrations gave unique results for each solution type and concentration. Moreover, the proposed sensor has a wide dynamic range, high linearity, fast operation and low-cost.