Effect of suspension characteristics on the performance of thermal barrier coatings deposited by suspension plasma spray

This paper investigates the influence of suspension characteristics on microstructure and performance of suspensions plasma sprayed (SPS) thermal barrier coatings (TBCs). Five suspensions were produced using various suspension characteristics, namely, type of solvent and solid load content, and the resultant suspensions were utilized to deposit five different TBCs under identical processing conditions. The produced TBCs were evaluated for their performance i.e. thermal conductivity, thermal cyclic fatigue (TCF) and thermal shock (TS) lifetime. This experimental study revealed that the differences in the microstructure of SPS TBCs produced using varied suspensions resulted in a wide-ranging overall TBC performance. All TBCs exhibited thermal conductivity lower than 1 W/(m. K) except water-ethanol mixed suspension produced TBC. The TS lifetime was also affected to a large extent where 10 wt % solid loaded ethanol and 25 wt % solid loaded water suspensions produced TBCs exhibited the highest and the lowest lifetime, respectively. On the contrary, TCF lifetime was not as significantly affected as thermal conductivity and TS lifetime, and all ethanol suspensions showed marginally better TCF lifetime than water and ethanol-water mixed suspensions deposited TBCs.     

Tissue-Engineered Vascular Grafts: Emerging Trends and Technologies

Vascular tissue engineering has made prodigious progress in recent years by converging multidisciplinary approaches. Latest technological advancements foster the development of next-generation tissue-engineered vascular grafts (TEVGs) for treating various vasculopathies. While traditional therapeutic methods rely on bypassing the severely damaged vessels with synthetic counterparts with no growth potential, contemporary perspectives focus on biodegradable conduits bestowing an inherent remodeling capability. This review highlights emerging innovative trends and technologies adopted to pragmatically fulfill current scientific needs while improving overall TEVG performance in pre-clinical and clinical settings. A comprehensive overview of various milestones achieved in the past few decades is first summarized, followed by an appraisal of the significant hurdles for clinical translation. The latest techniques to rationally address critical challenges, viz., intimal hyperplasia, thrombosis, constructive graft remodeling, and adequate neo-tissue formation are discussed. Finally, an update on ongoing clinical trials is provided and future perspectives required to persuade TEVGs to become a clinical reality are delineated.     

Recent Developments in Semipolar InGaN Laser Diodes

Semiconductors - Group III-nitride semiconductors (GaN, AlN, and InN) are attractive materials for a wide range of electronic and photonic applications. The most widely employed growth plane for...     

Electrical and magnetic properties of double perovskite: Y2CoMnO6

In this communication, the structural, micro-structural, dielectric, electrical, magnetic, and leakage-current characteristics of a double perovskite (Y₂CoMnO₆) ceramic material have been reported. The material was synthesized via a high-temperature mixed-oxide route. The compound crystallizes in a monoclinic structure which is confirmed from preliminary X-ray structural study. The morphological study by using scanning electron micrograph reveals the almost homogeneous distribution of grains throughout the surface of the sample. The nature of frequency-dependence of dielectric constant has been described by the Maxwell-Wagner model. The occurrence of a dielectric anomaly in the temperature dependence of dielectric permittivity study demonstrates the ferroelectric-paraelectric phase transition in the material. From the Nyquist plots, we found the existence of both grain and grain boundary effects. The frequency dependence of conductivity was studied by the Jonscher’s Power law, and the conduction phenomenon obeys the large overlapping polaron tunneling model. By using the Arrhenius equation, the activation energy has been calculated which is nearly equal to the energy required for the hoping of the electron. Both impedance and conductivity analysis demonstrate that the sample exhibits negative temperature coefficient of resistance (NTCR) properties indicating the semiconducting type of material at high temperatures. The anti-ferromagnetic character of the material is observed from the nature of magnetic hysteresis loop. The leakage current analysis suggests that the conduction process in the material follows the space charge limited conduction phenomenon. Such material will be helpful for modern electronic devices and spintronic applications.     

Review of electrospun hydrogel nanofiber system: Synthesis,Properties and Applications

Hydrogel-based nanofibers or vice versa are a relatively new class of nanomaterials, in which hydrogels are structured in nanofibrous form. Structure and size of the material directly governs its functionality, therefore, in hydrogel science, the nanofibrous form of hydrogels enables its usage in targeted applications. Hydrogel nanofiber system combines the desirable properties of both hydrogel and nanofiber like flexibility, soft consistency, elasticity, and biocompatibility due to high water content, large surface area to volume ratio, low density, small pore size and interconnected pores, high stiffness, tensile strength, and surface functionality. Swelling behavior is a critical property of hydrogels that is significantly increased in hydrogel nanofibers due to their small size. Electrospinning is the most popular method to fabricate “hydrogel nanofibers,” while other processes like self-assembly, solution blowing and template synthesis also exist. Merging the characteristics of both hydrogels and nanofibers in one system allows applications in drug delivery, tissue engineering, actuation, wound dressing, photoluminescence, light-addressable potentiometric sensor (LAPS), waterproof breathable membranes, and enzymatic immobilization. Treatment of wastewater, detection, and adsorption of metal ions are also emerging applications. In this review paper, we intend to summarize in detail about electrospun “hydrogel nanofiber” in relation to its synthesis, properties, and applications.     

A Comprehensive Review on the Application of Internet of Thing (IoT) in Smart Agriculture

Wireless Personal Communications - IoT-based smart farming techniques have come up as one of the solutions to tackle the effect of climate change, water scarcity, etc. which are the prime reason...     

A privacy-preserving model based on differential approach for sensitive data in cloud environment

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully trust this environment. However, it has become a challenge to ensure privacy preservation when sharing data effectively among different parties. This paper proposes a novel model that partitions data into sensitive and non-sensitive parts, injects the noise into sensitive data, and performs classification tasks using k-anonymization, differential privacy, and machine learning approaches. It allows multiple owners to share their data in the cloud environment for various purposes. The model specifies communication protocol among involved multiple untrusted parties to process owners’ data. The proposed model preserves actual data by providing a robust mechanism. The experiments are performed over Heart Disease, Arrhythmia, Hepatitis, Indian-liver-patient, and Framingham datasets for Support Vector Machine, K-Nearest Neighbor, Random Forest, Naive Bayes, and Artificial Neural Network classifiers to compute the efficiency in terms of accuracy, precision, recall, and F1-score of the proposed model. The achieved results provide high accuracy, precision, recall, and F1-score up to 93.75%, 94.11%, 100%, and 87.99% and improvement up to 16%, 29%, 12%, and 11%, respectively, compared to previous works.

     

Deep transfer modeling for classification of Maize Plant Leaf Disease

Multimedia Tools and Applications - Currently, Deep Learning is playing an influential role for Image analysis and object classification. Maize’s diseases reduce production that subsequently...