Volumetric expansion and shrinkage due to different densities of solid and liquid phases are common phenomena during solidification process. Simple analytical models addressing effect of volumetric expansion/shrinkage during solidification are rarely found. The few existing 1-D solidification models are valid only for semi-infinite domain with limitations of their application for finite domain size. The focus of the present work is to develop a 1-D semi-analytical solidification model addressing effects of volumetric expansion/shrinkage in a finite domain. The proposed semi-analytical scheme involves finding simultaneous solution of transient 1-D heat diffusion equations at solid and liquid domain coupled at the interface by Stefan condition. The change of the total domain length during solidification due to volumetric expansion/shrinkage is addressed by using mass conservation. For validation of the proposed model, solidification of water in a finite domain is studied without considering volumetric expansion/shrinkage effect and results are compared with those obtained from existing enthalpy updating based numerical model. After validation, case studies pertaining to volumetric expansion and shrinkage are performed considering solidification of water and paraffin respectively and physically consistent results are obtained. The study is relevant for understanding unidirectional crystal growth under the effect of controlled boundary condition.

A high-resolution analog-to-digital converter (ADC) is presented in this paper for application in sensor signal conditioning circuits. Based on the requirements of low complexity, low speed of operation, and moderate resolution, successive approximation register (SAR) ADC is most suitable. All the sub-circuits, i.e. comparator, sample and hold (with bootstrapped switching technique), SAR logic, and differential charge scaling digital-to-analog converter (DAC) circuits are designed, simulated, and verified using Cadence Virtuoso with SCL 180 nm PDK. The proposed design achieved 1.1 MS/s for 12-bit resolution with SDNR and ENOB of 73.54 dB and 11.92 bits, respectively.

We report significantly enhanced sensitivity of AlGaN/GaN-based high electron mobility transistor (HEMT) sensor by the targeted synthesis of IT and 2H coexisting phase MoS2 and applying the gate bias voltage. The HEMT structures on Si (111) substrates were used for the detection of Hg2+ ions. The optimum sensitive regime in terms of V GS and V DS of the sensor was investigated by keeping the drain source voltage V DS constant at 2 V and by only varying the gate bias voltage V GS from 0 to 3 V. The strongest sensing response obtained from the device was around 0.547 mA ppb-1 at V GS = 3 V, which is 63.7% higher in comparison to the response achieved at 0 V which shows a sensing response of around 0.334 mA ppb-1. The current response depicts that the fabricated device is very sensitive and selective towards Hg2+ ions. Moreover, the detection limit of our sensor at 3 V was calculated around 6.21 ppt, which attributes to the strong field created between the gate electrode and the HEMT channel due to the presence of 1T metallic phase in synthesized MoS2, indicating that the lower detection limits are achievable in adequate strong fields.

The development of new nanomaterials is immensely important for real-world sensing applications to improve the sensitivity, selectivity, and stability of the sensors devices. Herein, we explore the gas sensing properties of two-dimensional quasicrystal (2D QC) nanosheets and WS2 nanoflakes. The decoration of chemically exfoliated QC nanosheets on WS2 nanoflakes significantly enhances their NO2 sensing performance. This approach allows for detecting target gas molecules with exceptionally high sensitivity. For 20 ppm NO2 at 125 °C the ΔR/Ra% value for optimal amount of 2D QC nanosheets decorated WS2 nanoflakes based sensors reaches 52%, which is a 233% higher response than that of bare WS2 nanoflakes sensors. The increased sensitivity of the 2D QC decorated device is due to the increased carrier concentration in WS2 caused by the Fermi level alignment and the high affinity of the QC towards NO2. Furthermore, the density functional theory (DFT) study revealed atomic insight into increasing the gas sensing response due to the presence of transition metals in 2D QCs, drastically enhancing the active sites for NO2 adsorption; therefore, adsorption energy is boosted manifold compared to the WS2 monolayer. This experimental and DFT study of NO2 gas sensors provides detailed insight into gas sensors, and it would be very useful for the design of highly efficient NO2 gas sensors.

A chemiresistive, 1T-TiS2 nanosheet (TNS) based gas sensor has been developed, and its ultrahigh sensitivity toward hydrogen sulfide (H2S) and oxygen (O2) gas at room temperature has been experimentally demonstrated. The sensor displayed room-temperature detection with a maximum response of 395% to 4 ppm H2S (reducing gas) in dry air and a response of 234% to 100% oxygen (oxidizing gas) in ambient conditions. The H2S and O2 sensing in humid environment (40% and 80%) has also been demonstrated so as to ensure the reliable operation of sensor in real-time applications. The ultrasensitive nature and linear behavior of the sensor enable it to operate reliably in the wide range of 300 ppb to 4 ppm H2S and 1% to 100% oxygen. Density functional theory (DFT) simulations were carried out to study the structural and electronic properties of TNS. Adsorption behavior of these gas molecules on TNS nanosheets was also studied theoretically. A plausible sensing mechanism based on the theoretical model has been detailed, and interestingly, it suggests physisorption phenomena between the adsorbate and adsorbent which enables fast recovery of the sensor without any external stimulation. The rather low lower limit of detection (LLoD) for H2S and O2 reported here, specifically at room temperature, is unique and competes favorably with reported studies. This outstanding sensor performance can be attributed to small adsorption energy and van der Waals interaction between analyte and the receptor.

Recent patents show that ultrahigh Magnetic field, Nuclear Magnetic Resonance (NMR) microscopy is emerging as bioimaging tool to study metabolic events and protein structure-functional characterization in the small animals and pure proteins in solutions. 900 MHz NMR magnet design characteristics were reviewed and imaging was done for high resolution rat skin, heart, mice kidney using NMR microscopy technique. Superparamagnetic iron-oxide bound avidin-polystyrene coated with anti-troponin (SPIOT) nanoparticles as imaging contrast agent was used to enhance contrast. 900 MHz NMR microscopy provides structural microscopic details and can detect the nanoparticle targeted heart muscle fiber orientation by deposits of nanoparticles. 900 MHz microscopy was done for imaging phantom, heart, skin, kidneys. Anti-troponin was bound with polymer coated avidin-iron oxide complex to inject in rat to image the excised heart. Fast spin echo and fast gradient echo imaging techniques were used for T2-weighted rat heart. After imaging, rat hearts were processed for histology. First time available 900 MHz NMR system was more suitable for longer data acquisition at room temperature with enhanced SNR, MR signal intensity, and high resolution in less time. The imager generated skin, kidney, and heart images with visible muscle fiber orientation and comparable with histology details. The present paper is an overview with available patents on 900 MHz NMR spectrometer to convert into microscopic imager to generate high MR signal intensity and high resolution images with possibility on 1000 MHz field. The imager was a suitable research tool for microscopy, protein structural characterization and drug therapeutic monitoring. © 2011 Bentham Science Publishers.

In this work, a facile and cost-effective approach to assemble metallic wires into two-dimensional (2D) and three-dimensional (3D) freestanding geometries by room-temperature welding is demonstrated. The low melting point of gallium (29.8 °C) enables the welding at room temperature without the aid of high-energy sources required for high-melting-point metals and alloys. The welding enables assembly of solid gallium wires into 2D and 3D geometries that could create freestanding architectures with multiple junctions along any inclined direction. These 2D and 3D freestanding metallic structures are freeze-cast in soft elastomers to obtain stretchable and soft devices: a 2D stretchable resistive and capacitive sensor patterned with parallel metal lines, a 2D stretchable capacitive sensor patterned with an interdigitated metal structure with capacitive changes on stretching in both x- and y-axes, and a 3D compressive sensor by assembly of liquid metal helices, which could sense foot pressure compression. We also developed a facile method to interconnect between soft circuits and external electronics, suppressing stress during mechanical deformation.

We fabricated non-aqueous rechargeable iron ion batteries under ambient conditions (without an inert atmosphere or glovebox) using two-dimensional (2D) graphitic-carbon nitride (g-C3N4) as the low-cost active cathode material, synthesized using the one-step simple polymerization route. Mild Steel (MS) is an anode with a non-aqueous solvent-based tetra-ethylene glycol dimethyl ether electrolyte. Galvanostatic charging-discharging (GCD) characteristics are measured at various current densities. A specific capacity of 130 mAh g−1 is observed at 40 mA g−1 current density, and more than 50% of capacity retention is recorded over 100 cycles. RIIBs are also evaluated at a higher current density of 400 mA g−1 (3C rate- 20 min for one cycle), showing 60 mAh g−1 with an excellent rate capability for more than 240 cycles. The impedance is carried out to analyze the onset of interface layer resistance during cycling. Using the stack of the seven rechargeable coin cells, we demonstrated the lightening of the “IITJ” pattern based on white light emitting diodes (LEDs). Thus, 2D-graphitic C3N4 can be used as an efficient cathode material for safer and more reliable rechargeability with non-aqueous electrolytes-based RIIBs, exhibiting potential for next-generation energy storage devices for various small/large-scale applications.

Since the breakthrough of graphene, two-dimensional (2D) materials have attracted immense research interest due to their unique electronic, optical, and mechanical properties, holding great potential for harnessing their applications in next-generation electronics, optoelectronics, and biomedical fields. The most striking feature of 2D materials is their atomic thickness, which makes them feasible to adhere to any kind of surface without losing much of their inherent properties. With this advantage, 2D materials can be integrated into various flexible and stretchable electronic devices in a conventional and scalable fashion. Here in this chapter the synthesis of 2D materials using different top-down and bottom-up methods followed by various efficient transfer methods has been discussed thoroughly. After that, state-of-the-art flexible device applications of 2D materials in electronics, sensors, and energy storage devices, along with their future possibilities, are discussed.

Water polluted by toxic chemicals due to waste from chemical/pharmaceuticals and harmful microbes such as E. Coli bacteria causes several fatal diseases; and therefore, water filtration is crucial for accessing clean and safe water necessary for good health. Conventional water filtration technologies include activated carbon filters, reverse osmosis, and ultrafiltration. However, they face several challenges, including high energy consumption, fouling, limited selectivity, inefficiencies in removing certain contaminants, dimensional control of pores, and structural/chemical changes at higher thermal conditions and upon prolonged usage of water filter. Recently, the advent of 2D materials such as graphene, BN, MoS2, MXenes, and so on opens new avenues for advanced water filtration systems. This review delves into the nanoarchitectonics of 2D materials for water filtration applications. The current state of water filtration technologies is explored, the inherent challenges they face are outlines, and the unique properties and advantages of 2D materials are highlighted. Furthermore, the scope of this review is discussed, which encompasses the synthesis, characterization, and application of various 2D materials in water filtration, providing insights into future research directions and potential industrial applications. © 2024 The Author(s). Small published by Wiley-VCH GmbH.

Two-dimensional (2D) semiconductors, such as MXenes, transition metal dichalcogenides, black phosphorus, and emerging van der Waals heterostructures, have revolutionized the field of optoelectronics by offering exceptional electrical, optical, and mechanical properties at atomic-scale thickness. Their unique features, including tunable bandgaps, high absorption coefficients, and strong excitonic effects, enable a wide range of light detection and light emission applications, making them key materials for next-generation functional optoelectronic devices. This review explores recent breakthroughs in light detection technologies using 2D materials. As photodetectors, they offer ultrafast response rates and high sensitivity across a broad spectral range. In solar cell applications, 2D materials contribute to the development of lightweight, flexible, and efficient photovoltaic devices with enhanced charge transport. Image sensors based on 2D materials exhibit superior spatial resolution and spectral selectivity, while their integration into biomedical imaging platforms enables non-invasive diagnostics due to their biocompatibility. Furthermore, novel morphable light-tracking devices leverage the mechanical flexibility and photoresponsivity of 2D materials for adaptive photonic systems in wearable and robotic applications. On the emission front, 2D semiconductors are emerging as active light-emitting materials in LEDs, lasers, and quantum emitters, benefiting from direct bandgaps in monolayers and strong quantum confinement effects. Additionally, their application as backplane driving circuits in flexible displays is gaining momentum due to their high mobility, mechanical robustness, and transparency, enabling foldable and stretchable display technologies. Despite these advancements, practical implementation faces persistent intrinsic challenges such as high contact resistance, environmental instability, difficulties in controlled doping, and a lack of scalable, reproducible synthesis methods. These issues hinder device reliability and integration. This review also outlines the perspective toward commercialization, emphasizing the need for advancements in heterostructure engineering, and interface optimization. Through interdisciplinary collaboration and innovative material processing, 2D semiconductors are poised to reshape the landscape of optoelectronics, bridging the gap between fundamental science and practical technologies. © 2025 Elsevier B.V., All rights reserved.

Quantum flatland i.e., the family of two dimensional (2D) quantum materials has become increscent and has already encompassed elemental atomic sheets (Xenes), 2D transition metal dichalcogenides (TMDCs), 2D metal nitrides/carbides/carbonitrides (MXenes), 2D metal oxides, 2D metal phosphides, 2D metal halides, 2D mixed oxides, etc. and still new members are being explored. Owing to the occurrence of various structural phases of each 2D material and each exhibiting a unique electronic structure; bestows distinct physical and chemical properties. In the early years, world record electronic mobility and fractional quantum Hall effect of graphene attracted attention. Thanks to excellent electronic mobility, and extreme sensitivity of their electronic structures towards the adjacent environment, 2D materials have been employed as various ultrafast precision sensors such as gas/fire/light/strain sensors and in trace-level molecular detectors and disease diagnosis. 2D materials, their doped versions, and their hetero layers and hybrids have been successfully employed in electronic/photonic/optoelectronic/spintronic and straintronic chips. In recent times, quantum behavior such as the existence of a superconducting phase in moiré hetero layers, the feasibility of hyperbolic photonic metamaterials, mechanical metamaterials with negative Poisson ratio, and potential usage in second/third harmonic generation and electromagnetic shields, etc. have raised the expectations further. High surface area, excellent young’s moduli, and anchoring/coupling capability bolster hopes for their usage as nanofillers in polymers, glass, and soft metals. Even though lab-scale demonstrations have been showcased, large-scale applications such as solar cells, LEDs, flat panel displays, hybrid energy storage, catalysis (including water splitting and CO2 reduction), etc. will catch up. While new members of the flatland family will be invented, new methods of large-scale synthesis of defect-free crystals will be explored and novel applications will emerge, it is expected. Achieving a high level of in-plane doping in 2D materials without adding defects is a challenge to work on. Development of understanding of inter-layer coupling and its effects on electron injection/excited state electron transfer at the 2D-2D interfaces will lead to future generation heterolayer devices and sensors.

We propose a design for an MMI based all fiber 1310/1550 nm wavelength demultiplexer using square core multimode fiber. The fabrication tolerance of the device with respect to the fiber length is also investigated.

Gas sensors are extensively employed for monitoring and detection of hazardous gases and vapors. Many of them are produced on rigid substrates, but flexible and wearable gas sensors are needed for intriguing usage including the internet of things (IoT) and medical devices. The materials with the greatest potential for the fabrication of flexible and wearable gas sensing devices are two-dimensional (2D) semiconducting nanomaterials, which consist of graphene and its substitutes, transition metal dichalcogenides, and MXenes. These types of materials have good mechanical flexibility, high charge carrier mobility, a large area of surface, an abundance of defects and dangling bonds, and, in certain instances adequate transparency and ease of synthesis. In this review, we have addressed the different 2D nonmaterial properties for gas sensing in the context of fabrication of flexible/wearable gas sensors. We have discussed the sensing performance of flexible/wearable gas sensors in various forms such as pristine, composite and noble metal decorated. We believe that content of this review paper is greatly useful for the researchers working in the research area of fabrication of flexible/wearable gas sensors.

Among many two-dimensional (2D) materials, MXenes have been demonstrated both by density functional theory (DFT) and experimental research as potential electrocatalysts due to their inherent properties, such as surface termination that can positively influence the properties of MXene and its hybrids, super hydrophilicity, and excellent electrical conductivity. Here, MXene synthesis from its MAX phase, modifications in MXenes such as MXene hybrids, variations in MXenes, doping with heteroatom, etc., have been discussed. The optimization effect as a result of these modifications has reflected on the performance of these MXenes as electrocatalysts during applications in oxygen evolution/reduction reaction (OER and ORR), hydrogen evolution reaction (HER), nitrogen reduction reaction (NRR), CO 2reduction reaction (CRR), and methanol oxidation reaction (MOR), which has also been discussed comprehensively. This chapter focuses on the material design and various methods of enhancements of MXene-based materials for electrochemical solutions to find a practical strategy for clean energy conversion.

The biosensing industry has seen exponential growth in the past decade. Impact of biosensors in the current scenario cannot be overlooked. Cardiovascular diseases (CvDs) have been recognized as one of the major causes for millions of deaths globally. This mortality can be minimized by early and accurate detection/diagnosis of CvDs with the help of biosensing devices. This also presents a global market opportunity for the development of biosensors for CvDs. A vast variety of biosensing methods and devices have been developed for this problem. Most of commercially available platforms for CvD detection rely on optical (fluorometric and colorimetric analysis) techniques using serum biomarkers since optical testing is the gold standard in medical diagnosis. Field effect transistors-based biosensors, termed as Bio-FETs, are the upcoming devices for blood or serum analyte detection due to excellent sensitivity, low operational voltage, handheld device structure and simple chip-based operation. Further, the discovery of two dimensional (2D) materials and their integration with conventional FETs has improved the overvoltage problem, sensitivity and strict operating conditions as compared to conventional FETs. Graphene-FETs based biosensing devices have been proven as promising candidates due to their attractive properties. Despite the severe threat of CvDs which has further increased in post-covid era, the Bio-FET sensor studies in literature are still rare. In this review, we aim to provide a comprehensive view of all the multidisciplinary concepts related to 2D-BioFETs for CvDs. A critical review of the different platforms has been covered with detailed discussions of related studies to provide a clear concept and present status of 2D-BioFETs based CvD biosensors.

Automatic modulation classification (AMC) has a wide range of applications in the military and civilian areas. In the military, it is used for the extraction of information from unknown intercepted signals and the generation of jamming signals. Civil applications include interference management and spectrum underutilization. To overcome the limitations of traditional methods like maximum likelihood (ML) and feature- based (FB), deep learning (DL) networks have been developed and are being evolved. Following this direction, a convolution neural network (CNN) based AMC method is proposed. The two dimensional Fast Fourier Transform (2D-FFT) is used as a classification feature and a less complex and efficient deep CNN model is designed to classify the modulation schemes of different orders of PSK and QAM. The developed method achieves adequate classification performance for considered five modulation schemes in the AWGN channel.

In the electrodialysis process, the concentration polarization phenomenon determines the value of the limiting current density and, consequently, significantly affects energy consumption. Commercial spacers are commonly used to mix the solution and enhance ion delivery to ion-exchange membranes, and its shape has a crucial impact on the electrodialysis optimization. The target features of spacers development are better mixing and lower shadow effect. In a binary NaCl electrolyte solution with different diffusion coefficients of ions (DNa≈1.5 DCl) the limiting current is determined by the cation-exchange membrane, according to Peers' equation, because its counterion has the minimal value of D in the solution. Recently using 2D simulation and corresponding experiment it was found that the limiting current of an electrodialysis channel with NaCl solution may be increased by displacing the spacer filaments towards the anion-exchange membrane. This arrangement increases the flow velocity of the solution near the surface of the cation-exchange membrane, thus, thereby reducing the boundary layer thickness near it. In this work, using 3D simulation, we investigated several types of spacers. For the first time, an unobvious result was found: displacing the filaments toward the cation-exchange membrane in NaCl solution leads to an increase in the total limiting current and the effect is more pronounced then in the case of displacement toward the anion-exchange membrane. It is theoretically shown that in 3D systems, better solution mixing and ion delivery may be achieved in nonintuitive ways and the comprehensive analysis should be done to predict the system behavior. © 2025

Radiologists routinely perform the tedious task of lesion localization, classification, and size measurement in computed tomography (CT) studies. Universal lesion detection and tagging (ULDT) can simultaneously help alleviate the cumbersome nature of lesion measurement and enable tumor burden assessment. Previous ULDT approaches utilize the publicly available DeepLesion dataset, however it does not provide the full volumetric (3D) extent of lesions and also displays a severe class imbalance. In this work, we propose a self-training pipeline to detect 3D lesions and tag them according to the body part they occur in. We used a significantly limited 30% subset of DeepLesion to train a VFNet model for 2D lesion detection and tagging. Next, the 2D lesion context was expanded into 3D, and the mined 3D lesion proposals were integrated back into the baseline training data in order to retrain the model over multiple rounds. Through the self-training procedure, our VFNet model learned from its own predictions, detected lesions in 3D, and tagged them. Our results indicated that our VFNet model achieved an average sensitivity of 46.9% at [0.125:8] false positives (FP) with a limited 30% data subset in comparison to the 46.8% of an existing approach that used the entire DeepLesion dataset. To our knowledge, we are the first to jointly detect lesions in 3D and tag them according to the body part label.