Progress and Perspective in harnessing MXene-carbon-based composites (0-3D): Synthesis, performance, and applications.

MXene is recognized as a promising catalyst for versatile applications due to its abundant metal sites, physicochemical properties, and structural formation. This comprehensive review offers an in-depth analysis of the incorporation of carbon into MXene, resulting in the formation of MXene-carbon-based composites (MCCs). Pristine MXene exhibits numerous outstanding characteristics, such as its atomically thin 2D structure, hydrophilic surface nature, metallic electrical conductivity, and substantial specific surface area. The introduction of carbon guides the assembly of MCCs through electrostatic self-assembly, pairing positively charged carbon with negatively charged MXene. These interactions result in increased interlayer spacing, reduced ion/electron transport distances, and enhanced surface hydrophilicity. Subsequent sections delve into the synthesis methods for MCCs, focusing on MXene integrated with various carbon structures, including 0D, 1D, 2D, and 3D carbon. Comprehensive discussions explore the distinctive properties of MCCs and the unique advantages they offer in each application domain, emphasizing the contributions and advancements they bring to specific fields. Furthermore, this comprehensive review addresses the challenges encountered by MCCs across different applications. Through these analyses, the review promotes a deeper understanding of exceptional characteristics and potential applications of MCCs. Insights derived from this review can serve as guidance for future research and development efforts, promoting the widespread utilization of MCCs across a broad spectrum of disciplines and spurring future innovations.

Silt erosion and cavitation impact on hydraulic turbines performance: An in-depth analysis and preventative strategies.

The primary issues in the Himalayan Rivers are sediment and cavitation degradation of the hydroelectric power turbine components. During the monsoon season, heavy material is transported by streams in hilly areas like the Himalayas through regular rainfalls, glacial and sub-glacial hydrological activity, and other factors. The severe erosion of hydraulic turbines caused by silt abrasion in these areas requires hydropower facilities to be regularly shut down for maintenance, affecting the plant's overall efficiency. This article provides an in-depth examination of the challenges that can lead to cavitation, silt erosion, and a decrease in the efficiency of various hydroelectric turbines, and it demands attention on the design, manufacture, operation, and maintenance of the turbines. This study's main objective is to critically evaluate earlier theoretical, experimental, and numerical evaluation-based studies (on cavitation and silt erosion) that are provided and addressed throughout the study. As a part of this study, various strategies for mitigating the effects of these problems and elongating the time that turbine may be utilized before they must be replaced have been provided.

An overview of techniques for monitoring and compensating tool wear in micro-electrical discharge machining.

Micro-electrical discharge machining (µEDM) is severely affected by tool wear and its process variants, which can lead to compromised precision and dimensional disruptions in micro-part production. Several attempts have been made to address this problem by suggesting offline and online (real-time) tool wear compensation strategies. Research efforts in this area have intensified over the last 20 years. However, most methods proposed were applicable only for a few work-tool combinations and in limited input process parametric settings. Instead of tool wear compensation, several research articles have focused on strategies to reduce the negative impact of tool wear on the quality of fabricated parts. The present study systematically reviews various investigations conducted in this area and aims to add cutting-edge compensation for tool wear to future inquiries. The articles reviewed here are explored in detail. Critical findings/innovations are classified into four categories: tool wear in µEDM, tool wear compensation techniques, and offline and online compensation methods.

Performance analysis and modelling of circular jets aeration in an open channel using soft computing techniques.

Dissolved oxygen (DO) is an important parameter in assessing water quality. The reduction in DO concentration is the result of eutrophication, which degrades the quality of water. Aeration is the best way to enhance the DO concentration. In the current study, the aeration efficiency (E20) of various numbers of circular jets in an open channel was experimentally investigated for different channel angle of inclination (θ), discharge (Q), number of jets (Jn), Froude number (Fr), and hydraulic radius of each jet (HRJn). The statistical results show that jets from 8 to 64 significantly provide aeration in the open channel. The aeration efficiency and input parameters are modelled into a linear relationship. Additionally, utilizing WEKA software, three soft computing models for predicting aeration efficiency were created with Artificial Neural Network (ANN), M5P, and Random Forest (RF). Performance evaluation results and box plot have shown that ANN is the outperforming model with correlation coefficient (CC) = 0.9823, mean absolute error (MAE) = 0.0098, and root mean square error (RMSE) = 0.0123 during the testing stage. In order to assess the influence of different input factors on the E20 of jets, a sensitivity analysis was conducted using the most effective model, i.e., ANN. The sensitivity analysis results indicate that the angle of inclination is the most influential input variable in predicting E20, followed by discharge and the number of jets.

355 nm Nanosecond Ultraviolet Pulsed Laser Annealing Effects on Amorphous In-Ga-ZnO Thin Film Transistors.

Bottom-gate thin-film transistors (TFTs) with n-type amorphous indium-gallium-zinc oxide (a-IGZO) active channels and indium-tin oxide (ITO) source/drain electrodes were fabricated. Then, an ultraviolet (UV) nanosecond pulsed laser with a wavelength of 355 nm was scanned to locally anneal the active channel at various laser powers. After laser annealing, negative shifts in the threshold voltages and enhanced on-currents were observed at laser powers ranging from 54 to 120 mW. The energy band gap and work function of a-IGZO extracted from the transmittance and ultraviolet photoelectron spectroscopy (UPS) measurement data confirm that different energy band structures for the ITO electrode/a-IGZO channel were established depending on the laser annealing conditions. Based on these observations, the electron injection mechanism from ITO electrodes to a-IGZO channels was analyzed. The results show that the selective laser annealing process can improve the electrical performance of the a-IGZO TFTs without any thermal damage to the substrate.

Highly Reliable 3D Channel Memory and Its Application in a Neuromorphic Sensory System for Hand Gesture Recognition.

Brain-inspired neuromorphic computing systems, based on a crossbar array of two-terminal multilevel resistive random-access memory (RRAM), have attracted attention as promising technologies for processing large amounts of unstructured data. However, the low reliability and inferior conductance tunability of RRAM, caused by uncontrollable metal filament formation in the uneven switching medium, result in lower accuracy compared to the software neural network (SW-NN). In this work, we present a highly reliable CoOx-based multilevel RRAM with an optimized crystal size and density in the switching medium, providing a three-dimensional (3D) grain boundary (GB) network. This design enhances the reliability of the RRAM by improving the cycle-to-cycle endurance and device-to-device stability of the I-V characteristics with minimal variation. Furthermore, the designed 3D GB-channel RRAM (3D GB-RRAM) exhibits excellent conductance tunability, demonstrating high symmetricity (624), low nonlinearity (ßLTP/ßLTD ∼ 0.20/0.39), and a large dynamic range (Gmax/Gmin ∼ 31.1). The cyclic stability of long-term potentiation and depression also exceeds 100 cycles (105 voltage pulses), and the relative standard deviation of Gmax/Gmin is only 2.9%. Leveraging these superior reliability and performance attributes, we propose a neuromorphic sensory system for finger motion tracking and hand gesture recognition as a potential elemental technology for the metaverse. This system consists of a stretchable double-layered photoacoustic strain sensor and a crossbar array neural network. We perform training and recognition tasks on ultrasonic patterns associated with finger motion and hand gestures, attaining a recognition accuracy of 97.9% and 97.4%, comparable to that of SW-NN (99.8% and 98.7%).

Sense and Shoot: Unveiling the Electro-/Photocatalytic Potential of 2D White Graphene-Supported Perovskite Strontium Cobaltite from Detection to Remediation of Oxidative Stress Herbicide (Mesotrione).

In this research, we employed a strategy akin to "Feeding Two Birds with One Stone" aiming for the dual objectives of highly selective electrochemical detection and photocatalytic degradation of the environmentally hazardous herbicide mesotrione (MTN). We achieved this by utilizing hexagonal boron nitride (BN)-supported strontium cobaltite perovskite nanocomposites (SrCoO3/BN). The fabrication of the innovative bifunctional SrCoO3/BN nanocomposites involved a straightforward process of precipitation, followed by an annealing treatment and ultrasonication. The successful formation of these nanocomposites was corroborated through the application of diverse spectroscopic tools. Notably, as-prepared SrCoO3/BN nanocomposites exhibited a remarkable sensing platform for MTN, characterized by a notably low detection limit (11 nm), considerable sensitivity (3.782 µA µM-1 cm-2), and outstanding selectivity, alongside remarkable stability. Concurrently, these SrCoO3/BN nanocomposites demonstrated exceptional visible-light-driven photocatalytic efficacy for MTN degradation (99%) and complete mineralization. Our investigation systematically delved into the influence of operational parameters, including catalyst loading and the involvement of reactive oxidative species, in both the electrocatalytic and photocatalytic reactions. Drawing from these comprehensive studies, we have proposed plausible mechanisms for detecting and degrading MTN. Our findings pave the way for catalyst development, offering a unified solution for detecting and eliminating toxic organic compounds from the environment.

Photothermal Lithography for Realizing a Stretchable Multilayer Electronic Circuit Using a Laser.

Photolithography is a well-established fabrication method for realizing multilayer electronic circuits. However, it is challenging to adopt photolithography to fabricate intrinsically stretchable multilayer electronic circuits fully composed of an elastomeric matrix, due to the opacity of thick stretchable nanocomposite conductors. Here, we present photothermal lithography that can pattern elastomeric conductors and via holes using pulsed lasers. The photothermal-patterned stretchable nanocomposite conductor exhibits 3 times higher conductivity (5940 S cm-1) and 5 orders of magnitude lower resistance change (R/R0 = 40) under a 30% strained 5000th cyclic stretch, compared to those of a screen-printed conductor, based on the percolation network formed by spatial heating of the laser. In addition, a 50 µm sized stretchable via holes can be patterned on the passivation without material ablation and electrical degradation of the bottom conductor. By repeatedly patterning the conductor and via holes, highly conductive and durable multilayer circuits can be stacked with layer-by-layer material integration. Finally, a stretchable wireless pressure sensor and passive matrix LED array are demonstrated, thus showing the potential for a stretchable multilayer electronic circuit with durability, high density, and multifunctionality.

Decision Tree-Based Modeling of the Aeration Effectiveness of Circular Plunging Jets.

Since soft computing has gained a lot of attention in hydrological studies, this study focuses on predicting aeration efficiency (E20) using circular plunging jets employing soft computing techniques such as reduced error pruning tree (REPTree), random forest (RF), and M5P. The study undertaken required the development and validation of models, which were achieved using 63 experimental data values with input variables, such as angle of inclination of tilt channel (α), number of plunging jets (JN), discharge of each jet (Q), hydraulic radius of each jet (HR), and Froude number (Fr. No), to evaluate the aeration efficiency (E20), which served as the output variable. To evaluate the effectiveness of the developed models, three different statistical indices were used such as the coefficient of correlation (CC), root-mean-square error (RMSE), and mean absolute error (MAE), and it was found that all of the applied techniques possessed good forecasting ability since their correlation coefficient values were greater than 0.8. Upon testing, it was discovered that the M5P model outperformed other soft computing-based models in its ability to predict E20, as demonstrated by its correlation coefficient value of 0.9564 and notably low values of MAE (0.0143) and RMSE (0.0193).

Laser-Based Selective Material Processing for Next-Generation Additive Manufacturing.

The connection between laser-based material processing and additive manufacturing is quite deeply rooted. In fact, the spark that started the field of additive manufacturing is the idea that two intersecting laser beams can selectively solidify a vat of resin. Ever since, laser has been accompanying the field of additive manufacturing, with its repertoire expanded from processing only photopolymer resin to virtually any material, allowing liberating customizability. As a result, additive manufacturing is expected to take an even more prominent role in the global supply chain in years to come. Herein, an overview of laser-based selective material processing is presented from various aspects: the physics of laser-material interactions, the materials currently used in additive manufacturing processes, the system configurations that enable laser-based additive manufacturing, and various functional applications of next-generation additive manufacturing. Additionally, current challenges and prospects of laser-based additive manufacturing are discussed.

Analytical Investigation of the Impact of Jet Geometry on Aeration Effectiveness Using Soft Computing Techniques.

Jet aeration is a commonly used technique for introducing air into water during wastewater treatment. In this investigation, the efficacy of different soft computing models, namely, Random Forest, Reduced Error Pruning Tree, Artificial Neural Network (ANN), Gaussian Process, and Support Vector Machine, was examined in predicting the aeration efficiency (E20) of circular and square jet configurations in an open channel flow. A total of 126 experimental data points were utilized to develop and validate these models. To assess the models' performance, three goodness-of-fit parameters were employed: correlation coefficient (CC), root-mean-square error (RMSE), and mean absolute error (MAE). The analysis revealed that all of the developed models exhibited predictive capabilities, with CC values surpassing 0.8. Nonetheless, when it comes to predicting E20, the ANN model outperformed other soft computing models, achieving a CC of 0.9748, MAE of 0.0164, and RMSE of 0.0211. A sensitivity analysis emphasized that the angle of inclination exerted the most significant influence on the aeration in an open channel. Furthermore, the results demonstrated that square jets delivered superior aeration compared to that of circular jets under identical operating conditions.

Advancement in COVID-19 detection using nanomaterial-based biosensors.

Coronavirus disease 2019 (COVID-19) pandemic has exemplified how viral growth and transmission are a significant threat to global biosecurity. The early detection and treatment of viral infections is the top priority to prevent fresh waves and control the pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified through several conventional molecular methodologies that are time-consuming and require high-skill labor, apparatus, and biochemical reagents but have a low detection accuracy. These bottlenecks hamper conventional methods from resolving the COVID-19 emergency. However, interdisciplinary advances in nanomaterials and biotechnology, such as nanomaterials-based biosensors, have opened new avenues for rapid and ultrasensitive detection of pathogens in the field of healthcare. Many updated nanomaterials-based biosensors, namely electrochemical, field-effect transistor, plasmonic, and colorimetric biosensors, employ nucleic acid and antigen-antibody interactions for SARS-CoV-2 detection in a highly efficient, reliable, sensitive, and rapid manner. This systematic review summarizes the mechanisms and characteristics of nanomaterials-based biosensors for SARS-CoV-2 detection. Moreover, continuing challenges and emerging trends in biosensor development are also discussed.

A comprehensive review of techniques for increasing the efficiency of evacuated tube solar collectors.

With the growing energy needs, a conscious effort has been made to use non-conventional energy sources to generate clean energy efficiently. Solar energy has always been popular among humanity. Using solar energy in heating applications is one of the most prominent ways to extract solar power. Various developments have been made to augment solar water heating system (SWHS) performance. Each modified design of SWHS has its advantages and disadvantages. Broadly, solar water heaters are categorized into two types: Flat plate solar collectors (FPSCs) and evacuated tube solar collectors (ETSCs). Earlier studies show that evacuated tube SWHS are more efficient than flat plate SWHS. Extensive research is going on the design modification of evacuated tube SWHS to enhance their efficiency. Firstly, the present review article briefly introduced the numerous types of solar collectors and their range of operation. The current work reviews various techniques used for heat transfer enhancement in SWHS, their advantages, and the region of applications. The article concentrates on research involving the usage of energy storage medium, nanomaterials, reflecting surfaces, and hybrid techniques for performance augmentation of ETSCs.

Design and Fabrication of Ultrathin Nanoporous Donor-Acceptor Copolymer-Based Organic Field-Effect Transistors for Enhanced VOC Sensing Performance.

The development of organic field-effect transistor (OFET) chemical sensors with high sensing performance and good air stability has remained a persistent challenge, thereby hindering their practical application. Herein, an OFET sensor based on a donor-acceptor copolymer is shown to provide high responsivity, sensitivity, and selectivity toward polar volatile organic compounds, as well as good air stability. In detail, a polymer blend of N-alkyl-diketopyrrolo-pyrrole-dithienylthieno[3,2-b]thiophene (DPP-DTT) and polystyrene is coated onto an FET substrate via shearing-assisted phase separation (SAPS) combined with selective solvent etching to fabricate the DPP-DTT-based OFET device having an ultrathin nanoporous structure suitable for gas sensing applications. This is achieved via optimization of the film morphology by varying the shear rate to adjust the dynamic balance between the shear and capillary forces to obtain an ultrathin thickness (∼8 nm) and nanopore size (80 nm) that are favorable for the efficient diffusion and interaction of analytes with the active layer. In particular, the sensor presents high responsivities toward methanol (∼70%), acetone (∼51.3%), ethanol (∼39%), and isopropyl alcohol (IPA) (∼29.8%), along with fast response and recovery times of ∼80 and 234 s, respectively. Moreover, the average sensitivity was determined to be 5.75%/ppm from the linear plot of the responsivity against the methanol concentration in the range of 1-100 ppm. Importantly, the device also exhibits excellent long-term (30-day) air and thermal storage stability, thereby demonstrating its high potential for practical applications.

Recent Developments and Implementations of Conductive Polymer-Based Flexible Devices in Sensing Applications.

Flexible sensing devices have attracted significant attention for various applications, such as medical devices, environmental monitoring, and healthcare. Numerous materials have been used to fabricate flexible sensing devices and improve their sensing performance in terms of their electrical and mechanical properties. Among the studied materials, conductive polymers are promising candidates for next-generation flexible, stretchable, and wearable electronic devices because of their outstanding characteristics, such as flexibility, light weight, and non-toxicity. Understanding the interesting properties of conductive polymers and the solution-based deposition processes and patterning technologies used for conductive polymer device fabrication is necessary to develop appropriate and highly effective flexible sensors. The present review provides scientific evidence for promising strategies for fabricating conductive polymer-based flexible sensors. Specifically, the outstanding nature of the structures, conductivity, and synthesis methods of some of the main conductive polymers are discussed. Furthermore, conventional and innovative technologies for preparing conductive polymer thin films in flexible sensors are identified and evaluated, as are the potential applications of these sensors in environmental and human health monitoring.

Microgels based on 0D-3D carbon materials: Synthetic techniques, properties, applications, and challenges.

Microgels are three-dimensional (3D) colloidal hydrogel particles with outstanding features such as biocompatibility, good mechanical properties, tunable sizes from submicrometer to tens of nanometers, and large surface areas. Because of these unique qualities, microgels have been widely used in various applications. Carbon-based materials (CMs) with various dimensions (0-3D) have recently been investigated as promising candidates for the design and fabrication of microgels because of their large surface area, excellent conductivity, unique chemical stability, and low cost. Here, we provide a critical review of the specific characteristics of CMs that are being incorporated into microgels, as well as the state-of-the art applications of CM-microgels in pollutant adsorption and photodegradation, H2 evoluation, CO2 capture, soil conditioners, water retention, drug delivery, cell encapsulation, and tissue engineering. Advanced preparation techniques for CM-microgel systems are also summarized and discussed. Finally, challenges related to the low colloidal stability of CM-microgels and development strategies are examined. This review shows that CM-microgels have the potential to be widely used in various practical applications.

Non-Alcoholic Fatty Liver Disease and the Risk of Diabetes Mellitus by Menopausal Status: A Nationwide Cohort Study.

Background: Non-alcoholic fatty liver disease (NAFLD) is regarded as a risk factor for type 2 diabetes mellitus (DM). Menopausal status also influences T2DM risk, where estrogen is presumed to play a protective role by decreasing insulin resistance. As such, we investigated the association between NAFLD and DM risk according to menopausal status. Objectives: We sought to examine the association between NAFLD and DM incidence in pre- and post-menopausal women. Methods: A total of 842,772 pre-menopausal and 1,074,767 post-menopausal women who underwent health examinations between 2009 and 2014 were included from the Korean National Health Insurance Service database. Multivariate Cox proportional hazard analyses were performed to evaluate the association between the risk of DM according to menopausal status and NAFLD, defined by a fatty liver index >60. Results: During the mean follow-up period (7.8 years), DM was diagnosed in 33,461 (4.0%) of pre-menopausal women and 121,102 (9.4%) post-menopausal women. A stronger association between NAFLD and the risk of DM was found in pre-menopausal women (multivariable-adjusted hazard ratio [aHR], 3.60; 95% confidence interval [CI], 3.48−3.71) than in post-menopausal women (aHR, 2.24; 95% CI, 2.21−2.28) (P-interaction < 0.01). Subgroup analyses among women aged 45 to 55 years also showed a stronger association in pre-menopausal (aHR, 3.35; 95% CI, 3.21−3.49) than in post-menopausal women (aHR, 2.83; 95% CI, 2.68−2.98) (P-interaction < 0.01). Conclusions: The association between NAFLD and DM was stronger in pre-menopausal women than in post-menopausal women. This might be due to the protective effect of estrogen, which is possibly in higher production in the peripheral fat tissue of post-menopausal women with NAFLD.

Can Robots Help Working Parents with Childcare? Optimizing Childcare Functions for Different Parenting Characteristics.

Is it true that parents always prioritize educational effectiveness when selecting childcare services? The current study identified the potential requirements of dual-income parents toward social robots' diverse childcare functions (e.g., socialization, education, entertainment, and consultation). The results revealed that parental attitudes toward robots were made more positive by all the childcare functions of robots except for their educational features. Furthermore, parents' expectations of childcare functions varied based on their parenting characteristics. Spectral clustering analysis identified distinctive parenting styles (e.g., family-oriented, work-oriented, noninterventional, and dominant), and multigroup structural equation modeling suggested that the impact of robots' socialization function was significant in all parent groups, while other childcare functions exerted limited influence according to specific parenting styles. In addition, children's characteristics were found to alter parents' preferences for each childcare function. These results offer practical implications for the early adoption of childcare robots through predetermining parents' acceptability based on their specific parenting characteristics.

Recent Advances and Progress of Conducting Polymer-Based Hydrogels in Strain Sensor Applications.

Conducting polymer-based hydrogels (CPHs) are novel materials that take advantage of both conducting polymers and three-dimensional hydrogels, which endow them with great electrical properties and excellent mechanical features. Therefore, CPHs are considered as one of the most promising platforms for employing wearable and stretchable strain sensors in practical applications. Herein, we provide a critical review of distinct features and preparation technologies and the advancements in CPH-based strain sensors for human motion and health monitoring applications. The fundamentals, working mechanisms, and requirements for the design of CPH-based strain sensors with high performance are also summarized and discussed. Moreover, the recent progress and development strategies for the implementation of CPH-based strain sensors are pointed out and described. It has been surmised that electronic skin (e-skin) sensors are the upward tendency in the development of CPHs for wearable strain sensors and human health monitoring. This review will be important scientific evidence to formulate new approaches for the development of CPH-based strain sensors in the present and in the future.

Metal-Oxide Nanomaterials Synthesis and Applications in Flexible and Wearable Sensors.

Metal-oxide nanomaterials (MONs) have gained considerable interest in the construction of flexible/wearable sensors due to their tunable band gap, low cost, large specific area, and ease of manufacturing. Furthermore, MONs are in high demand for applications, such as gas leakage alarms, environmental protection, health tracking, and smart devices integrated with another system. In this Review, we introduce a comprehensive investigation of factors to boost the sensitivity of MON-based sensors in environmental indicators and health monitoring. Finally, the challenges and perspectives of MON-based flexible/wearable sensors are considered.