• Journal of the Microelectronics and Packaging Society
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• v.29 no.1
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• pp.17-33
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• 2022

Ti₃C₂T_X MXene, first reported by Naguib et al. in 2011, has attracted tremendous attention due to its excellent hydrophilicity, electrical conductivity, and mechanical/chemical stability. Since MXene is a two-dimensional material with a thickness of few nanometers, which ensure its flexibility. In last few years, due to these properties many researchers used Ti₃C₂T_X MXene into various fields such as flexible smart sensors, energy harvesting/storage devices, supercapacitors and electromagnetic interference shielding systems. In this review article, we have briefly discussed the various synthesis processes and characteristics of Ti₃C₂T_X MXene. Moreover, we reviewed the latest development of Ti₃C₂T_X MXene as flexible electrode material to be used into different applications.

• Journal of Sensor Science and Technology
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• v.31 no.4
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• pp.249-254
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• 2022

To achieve high-performance colloidal quantum dot light-emitting diodes (QD-LEDs), the use of a densely packed QD film is crucial to prevent the formation of leakage current pathways and increase in interface resistance. Spin coating is the most common method to deposit QDs; however, this method often produces pinholes that can act as short-circuit paths within devices. Since state-of-the-art QD-LEDs typically employ mono- or bi-layer QDs as an emissive layer because of their low conductivities, the use of a densely packed and pinhole-free QD film is essential. Herein, we introduce the Langmuir-Blodgett (LB) technique as a deposition method for the fabricate densely packed QD films in QD-LEDs. The LB technique successfully transfers a highly dense monolayer of QDs onto the substrate, and multilayer deposition is performed by repeating the transfer process. To validate the comparability of the LB technique with the standard QD-LED fabrication process, we fabricate and compare the performance of LB-based QD-LEDs to that of the spin-coating-based device. Owing to the non-destructiveness of the LB technique, the electroluminescence efficiency of the LB-based QD-LEDs is similar to that of the standard spin coating-based device. Thus, the LB technique is promising for use in optoelectronic applications.

• Journal of Sensor Science and Technology
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• v.31 no.2
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• pp.102-106
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• 2022

Currently, the demand for real-time monitoring of water quality has increased dramatically. Total organic carbon (TOC) analysis is a suitable method for real-time analysis compared with conventional biochemical oxygen demand (BOD) and chemical oxygen demand (COD) methods in terms of analysis time. However, this method is expensive because of the complicated internal processes involved. The photocatalytic titanium dioxide (TiO2)-based TOC method is simpler as it omits more than three preprocessing steps. This is because it reacts only with organic carbon (OC) without extra processes. We optimized the rate between the TiO2 photocatalyst and binder solution and the TiO2 concentration. The efficiency was investigated under 365 nm UV exposure onto a TiO2 coated substrate. The optimized conditions were sufficient to apply a real-time monitoring system for water quality with a short reaction time (within 10 min). We expect that it can be applied in a wide range of water quality monitoring industries.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.140-146
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• 2023

Water quality is crucial for human health and the environment. Accurate measurement of the quantity of organic carbon in water is essential for water quality evaluation, identification of water pollution sources, and appropriate implementation of water treatment measures. Total organic carbon (TOC) analysis is an important tool for this purpose. Although other methods, such as chemical oxygen demand (COD) and biochemical oxygen demand (BOD) are also used to measure organic carbon in water, they have limitations that make TOC analysis a more favorable option in certain situations. For example, COD requires the use of toxic chemicals, and BOD is time-consuming and can produce inconsistent and unreliable results. In contrast, TOC analysis is rapid and reliable, providing accurate measurements of organic carbon content in water. However, common methods for TOC analysis can be complex and energy-intensive because of the use of high-temperature heaters for liquid-to-gas phase transitions and the use of acid, which present safety risks. This study focuses on a TOC analysis method using TiO₂ photocatalysis, which has several advantages over conventional TOC analysis methods, including its low cost and easy maintenance. For TiO₂, rutile and anatase powders are mixed with an inorganic binder and spray-coated onto a glass fiber substrate. The TiO₂ powder and inorganic binder solutions are adjusted to optimize the photocatalytic reaction performance. The TiO₂ photocatalysis method is a simple and low-power approach to TOC analysis, making it a promising alternative to commonly used TOC analysis methods. This study aims to contribute to the development of more efficient and cost-effective approaches for water quality analysis and management by exploring the effectiveness and reliability of the developed equipment.

• Journal of Sensor Science and Technology
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• v.32 no.3
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• pp.131-139
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• 2023

Ascorbic acid plays a crucial role in the regulation of neurotransmitters and enzymes in the central nervous system. Maintaining an optimal level of ascorbic acid, which is between 0.6-2 mg/dL, is vital for preventing oxidative stress and associated health conditions, such as cancer, diabetes, and liver disease. Therefore, the detection of ascorbic acid is of the utmost importance. Electrochemical sensing has gained significant attention among the various detection methods, owing to its simplicity, speed, affordability, high selectivity, and real-time analysis capabilities. However, conventional electrodes have poor signal response, which has led to the development of modified electrodes with better signal response and selectivity. Carbon nanotubes (CNTs) and their composites have emerged as promising materials for the electrochemical detection of ascorbic acid. CNTs possess unique mechanical, electrical, and chemical properties that depend on their structure, and their large surface area and excellent electron transport properties make them ideal candidates for electrochemical sensing. Recently, various CNT composites with different materials and nanoparticles have been studied to enhance the electrochemical detection of ascorbic acid. Therefore, this review aims to highlight the significance of CNTs and their composites for improving the sensitivity and selectivity of ascorbic acid detection. Specifically, it focuses on the use of CNTs and their composites in electrochemical sensing to revolutionize the detection of ascorbic acid and contribute to the prevention of oxidative stress-related health conditions. The potential benefits of this technology make it a promising area for future research and development.

• Composites Research
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• v.20 no.3
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• pp.50-54
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• 2007

The Ionic Polymer Metal Composite (IPMC), an electro-active polymer, has many advantages including bending actuation, low weight, low power consumption, and flexibility. These advantages coincide with the requirements of a bio-related application. Thus, IPMC is promising materials for bio-mimetic actuator and sensor applications. Before applying IPMC to actual application, basic mechanical properties of IPMC should be studied in order to utilize IPMC for practical uses. Therefore, IPMCs are fabricated to investigate the mechanical characteristics. Nafion is used as a base ionic polymer. Mason samples cast with various thicknesses are used to test the thickness effects of IPMC. Subsequently, IPMC is fabricated using the chemical reduction method. The deformation, blocking force and frequency response of the IPMC actuator are important properties. In this present study, the performances of the IPMC actuators, including the deformation, blocking force and natural frequency, are then obtained according to only the input voltage and IPMC dimensions. Finally, the empirical performance model and the equivalent stiffness model of the IPMC actuator are established using experiments results.

• Composites Research
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• v.36 no.5
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• pp.342-348
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• 2023

There has been increasing demand for real-time monitoring of body and ambient temperatures using wearable devices. Graphene-based thermistors have been developed for high-performance flexible temperature sensors. In this study, the temperature coefficient of resistance (TCR) of monolayer graphene was controlled by coating polyethylenimine (PEI) on graphene surfaces to enhance its temperature-sensing performances. Monolayer graphene grown by chemical vapor deposition (CVD) was wet-transferred onto a target substrate. To facilitate the interfacial doping by PEI, the hydrophobic graphene surface was altered to be hydrophilic by oxygen plasma treatments while minimizing defect generation. The effect of PEI doping on graphene was confirmed using a back-gated field-effect transistor (FET). The CVD-grown monolayer graphene coated with PEI exhibited an improved TCR of -0.49(±0.03) %/K in a temperature range of 30~50℃.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.328-333
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• 2023

This study experimentally verified the etch rate of the SiO₂ sacrificial layer etching process with a single etch hole using vapor-phase hydrogen fluoride (VHF) etching. To fabricate small-sized polysilicon etch holes, both circular and triangular pattern masks were employed. Etch holes were fabricated in the polysilicon thin film on the SiO₂ sacrificial layer, and VHF etching was performed to release the polysilicon thin film. The lateral etch rate was measured for varying etch hole sizes and sacrificial layer thicknesses. Based on the measured results, we obtained an approximate equation for the etch rate as a function of the etch hole size and sacrificial layer thickness. The etch rates obtained in this study can be utilized to minimize structural damage caused by incomplete or excessive etching in sacrificial layer processes. In addition, the results of this study provide insights for optimizing sacrificial layer etching and properly designing the size and spacing of the etch holes. In the future, further research will be conducted to explore the formation of structures using chemical vapor deposition (CVD) processes to simultaneously seal etch hole and prevent adhesion owing to polysilicon film vibration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.

• Smart Media Journal
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• v.13 no.4
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• pp.23-32
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• 2024

Large-scale fires and their consequential damages are becoming increasingly common, but confidence in fire detection systems is waning. Recently, widely-used chemical fire detectors frequently generate lots of false alarms, while video-based deep learning fire detection is hampered by its time-consuming and expensive nature. To tackle these issues, this study proposes a fire detection model utilizing an autoencoder approach. The objective is to minimize false alarms while achieving swift and precise fire detection. The proposed model, employing an autoencoder methodology, can exclusively learn from normal data without the need for fire-related data, thus enhancing its adaptability to diverse environments. By amalgamating data from five distinct sensors, it facilitates rapid and accurate fire detection. Through experiments with various hyperparameter combinations, the proposed model demonstrated that out of 14 scenarios, only one encountered false alarm issues. Experimental results underscore its potential to curtail fire-related losses and bolster the reliability of fire detection systems.