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Synthesis, Properties and Applications of Polymer Nanocomposites-A Review
Polymer nanocomposites have been a rapidly expanding research topic for producing materials over the last few decades. In the previous two decades, there has been a significant scientific interest in nanoscience and nanotechnology. Nanomaterials' distinct features are related to quantum phenomena, greater surface area, and self-assembly. Quantum effects can begin to dominate matter's behaviour in the nanoscale, particularly at the lower end, affecting optical, electrical, and magnetic properties. Nanomaterials have evolved into nanocomposites with numerous applications. Its applications catapulted them to prominence in the field of material research. Because of their unique property combinations and design practicality, polymer nanocomposites are employed in sports equipment, wastewater treatment, the automobile industry, and biomedical applications. Even though they have numerous advantages, producing them in sufficient quantities and high quality is still one of the biggest challenges. During the last few decades, polymer nanocomposites have been a fast-developing research topic for material production. There has been a surge in scientific interest in nanoscience and nanotechnology during the last two decades. Nanomaterials have developed into nanocomposites, which have a wide range of uses. Its uses propelled them to the forefront of material research. Nanocomposites physical, mechanical, barrier, flame retardancy, optical, dielectric, rheological, and thermal characteristics have been thoroughly researched. Their uses have also been discussed. 2024, Informatics Publishing Limited. All rights reserved. -
Synthesis, properties, and state-of-the-art advances in surface tuning of borophene for emerging applications
Being composed of boron atoms that can be maneuvered to orchestrate low planar hexagonal structures, this two-dimensional material carefully exhibits versatility and has conventional covalent bonds between each atom. Borophene has recently proliferated the scientific research community by storm, trailblazing industries from fine chemicals, electrical equipment manufacturing, and biomedical innovation up to sustainable energy. Here, we provide streamlined information and particulars about the recent advances in the evolution of borophene since its inception and the essence of its electrocatalytic applications. We first introduce the sophisticatedly cultivated progress in borophene's structural, mechanical, optical, and electrical properties and further discuss its variegated polymorphism. Subsequently, we also delve into several capable synthesis techniques and recently concocted surface tuning and doping methods. Finally, we analyze the advancing state-of-the-art applications of this two-dimensional nanomaterial under investigation, ranging from bioimaging, energy storage, electrode reduction, and electrochemical sensing. Further, we have broadly discussed the future insights and challenges that borophene brings. 2024 -
Synthesis, spectral and DNA/Protein binding evaluation of novel Cu(II) chelates of an NNO donor tridentate aroylhydrazone: Halogen bonding directed close packing
An NNO donor aroylhydrazone monohydrate, HFPBH2O (3-fluoropyridine-2-carbaldehyde benzoylhydrazone monohydrate) was synthesized from 3-fluoropyridine-2-carbaldehyde and benzhydrazide and physicochemically characterised. The coordination behaviour of the aroylhydrazone with the metal ion is investigated through various physicochemical techniques and it is concluded that it binds to the metal ion predominantly in the enolate resonance form, while few complexes exhibit keto form of the ligand. The structure of [Cu(FPB)(OAc)(H2O)]H2O (4a) established by single-crystal X-ray diffraction method unveiled that the metal ion has a distorted square-pyramidal geometry in this complex. The coordination sites of Cu(II) ion are occupied by azomethine N, pyridyl N and iminolate O from a monodeprotonated hydrazone moiety and the remaining two positions are occupied by two oxygen atoms, one each from acetate ion and the water molecule. Potential applications of the complexes were studied by subjecting them to DNA/protein (BSA) binding studies using electronic and fluorescence spectroscopy. The complexes were found to bind with DNA/protein (BSA) with binding constants in the order of 104 M?1 to 105 M?1. The intercalative mode of binding of the complexes with DNA was proved using spectral studies and molecular docking. Furthermore, the complex [Cu(FPB)(N3)(H2O)2] (5) was found to cleave the DNA from form I to form II during gel electrophoresis studies. 2020 Elsevier B.V. -
Synthesis, spectral characterization and antimicrobial studies of novel acyl hydrazones of pacetoxybenzaidehyde
Novel acyl hydrazones derived from p-acetoxybenzaldehyde and various acid hydrazides have been synthesized. Synthetic procedure is simple and convenient and affords good yield. Elemental analysis and spectral results of the products arc also reported. 2015 Scientific Publishers. All Rights Reserved. -
Synthesis, structural characterization, electrochemical and photocatalytic properties of vanadium complex anchored on reduced graphene oxide
In this work, vanadium complex anchored reduced graphene oxide (rGO-VO) was successfully synthesized by coordination interaction with phenyl azo salicylaldehyde (PAS) coupled trimethoxy silyl propanamine (TMSPA). The physicochemical and microscopic properties of rGO-VO were studied with different analytical techniques such as Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, Scanning electron microscopy (SEM), and Transmission electron microscopy (TEM) which confirmed the synthesis of rGO-VO. The electrochemical studies of rGO-VO in glassy carbon electrode demonstrated high current density because of the amazing electrochemical properties of rGO. The photocatalytic studies of anchored rGO-VO and VO(acac)2 toward MB dye indicated that anchored rGO-VO with visible light irradiated MB was degraded fast as compared to VO(acac)2. 2021 Taylor & Francis Group, LLC. -
Synthesis, Structure, and Physical Properties of Bulk MoS2
With the discovery of graphene by Novoselov and Geim in 2004, two-dimensional (2D) materials have been extensively researched due to their bizarre promise in the fields of electronics, optics, medical, mechanics, energy conversion, and storage. Especially, 2D-layered materials consisting of atomic sheets stacked together by weak van der Waal forces have received intriguing research interest in recent years. Cutting-edge 2D materials being investigated by researchers include 2D oxides (V2O5, MoO3, LixCoO2), topological insulators (Bi2Se3, Bi2Te3, HfBr), nitrides (h-BN, MoN, Ti4N3Tx, W2N, V2N), carbides (Ti3C2, Ta4AlC3), and transition-metal dichalcogenides (MoS2, WS2). Research has proved that these materials could counterpart graphene in a variety of fields and applications. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Synthetic Applications of Prins Cyclization in Natural Product Syntheses
The natural products having tetrahydropyran unit with multiple chiral centers serve as magnificent building blocks for various active pharmaceutical ingredients (APIs). Prins cyclization is one of the wonderful strategies to construct tetrahydropyran unit stereoselectively in asymmetric synthesis. In this account, we discuss our research efforts toward the synthesis of various natural products from the past two decades (20052020) by using Prins cyclization as a key step. Further, the synthetic utility of this reaction was investigated and well demonstrated on various molecules successfully. 2022 The Chemical Society of Japan & Wiley-VCH GmbH. -
Synthetic Approaches of Prelactone and Its Analogues: A Review
In this review we have discussed the synthetic approaches of prelactones and their epimers from 1997 to date. The presence of unique molecular architecture and its high biological importance enhanced the research activity over the last two decades. Most of the syntheses involve either a chiral auxiliary, chiral pool or catalytic enantioselective approaches as a key step. Overall this review highlights the contribution from different research groups in the total synthesis of various prelactones. 2021 Wiley-VCH GmbH -
Synthetic Approaches to Diospongins: A Two Decade Journey
Tetrahydropyran units having multiple stereogenic centers serve as excellent building blocks for various active pharmaceutical ingredients (APIs). In particular, the presence of the unique molecular architecture of the trisubstituted tetrahydropyran (THP) unit in diospongins enhances their biological activity due to multiple stereogenic centers and has attracted attention from the synthetic community over the last two decades. In this review, we discuss synthetic approaches to chiral and racemic forms of diospongins during the period 2006 2020 in chronological order. 2022 by the authors. -
Synthetic approaches toward butenolide-containing natural products
The butenolide scaffold is ubiquitous in many natural products and pharmaceutical active ingredients. These candidates appeal to organic chemists for the synthesis of products with various biological activities. This review delineates the efforts made in the total synthesis of natural products based on the butenolide core unit such as umbelactones, akolactones, ansepcinolide, lissoclinolide, fugomycin, and muricadienin. Many of the reported syntheses involve chiral pool, enzyme resolution, and chiral auxiliary, or enantioselective approaches as a key step. Overall, this review highlights the synthetic methods involved in the preparation of butenolide-containing molecules and aims to increase the profile of such scaffolds to the synthetic community. 2022 Wiley Periodicals LLC. -
Synthetic biology for sustainable food ingredients production: recent trends
Problems with food security result from increased population, global warming, and decrease in cultivable land. With the advancements in synthetic biology, microbial synthesis of food is considered to be an efficient alternate approach that could permit quick food biosynthesis in an eco-friendly method. Furthermore, synthetic biology can be assumed to the synthesis of healthy or specially designed food components like proteins, lipids, amino acids and vitamins and widen the consumption of feedstocks, thus offering possible resolutions to high-quality food synthesis. This review describes the impact of synthetic biology for the microbial synthesis of various food ingredients production. 2022, Jiangnan University. -
Synthetic Biology Tools for Genome and Transcriptome Engineering of Solventogenic Clostridium
Strains of Clostridium genus are used for production of various value-added products including fuels and chemicals. Development of any commercially viable production process requires a combination of both strain and fermentation process development strategies. The strain development in Clostridium sp. could be achieved by random mutagenesis, and targeted gene alteration methods. However, strain improvement in Clostridium sp. by targeted gene alteration method was challenging due to the lack of efficient tools for genome and transcriptome engineering in this organism. Recently, various synthetic biology tools have been developed to facilitate the strain engineering of solventogenic Clostridium. In this review, we consolidated the recent advancements in toolbox development for genome and transcriptome engineering in solventogenic Clostridium. Here we reviewed the genome-engineering tools employing mobile group II intron, pyrE alleles exchange, and CRISPR/Cas9 with their application for strain development of Clostridium sp. Next, transcriptome engineering tools such as untranslated region (UTR) engineering and synthetic sRNA techniques were also discussed in context of Clostridium strain engineering. Application of any of these discussed techniques will facilitate the metabolic engineering of clostridia for development of improved strains with respect to requisite functional attributes. This might lead to the development of an economically viable butanol production process with improved titer, yield and productivity. Copyright 2020 Kwon, Paari, Malaviya and Jang. -
Synthetic Data Augmentation for Robust Solar Flare Classification: A Comparative Analysis of Conditional DCGAN, VAE, and Diffusion Models
Solar flares are extremely dangerous to the ground and space-based resources. Solar flares have to be classified properly and in good time to offer protection to assets in both the environments. Deep Learning-based flares have been divided into 3 classes (C, M and X). The main problems with this kind of classification are that high impact M- or X-class solar flares are extremely rare, and cannot be well sampled, thus leading to a very unbalanced sample. This paper exemplifies a comparative analysis of three models of Conditional Generative Models (cDCGAN models, cVAE models and cDDPM) to produce realistic images of solar flares considering each of the low frequency and high-impact solar flare types. The research question will be how such models can be evaluated in terms of their capacity to create realistic, class-specific images (magnetograms, and EUV) and time-series data which could be used to create class-balanced training samples. The initial experiments make use of the cDCGAN, cVAE, cDDPM architecture and considering the generation of class-conditional solar flare images portray high levels of stability (convergence was stated in less than 600 epochs in the case of the cDCGAN, cVAE models and cDDPM) and the generation of images which could be considered as practically indistinguishable to real life images. The results indicate that cDDPM may be a possible solution to a high-fidelity production of solar features. We measured the efficiency of these models in quantitative terms (popular metrics, like the Frhet Inception Distance, Structural Similarity Index) in a manner that we could determine the best manner of training model based solar flare classification systems using realistic data. This research is aligned with Sustainability Development Goals 9- Industry, Innovation and Infrastructure with focus on verticals 9.1 and 9.5. 2026 IEEE. -
Synthetic Image Generation for Crop Disease Classification Using Generative Adversarial Networks
Due to biological diversity and unstructured surroundings, agricultural image analysis strives for optimal model performance to better accomplish visual identification objectives. Large-scale, balanced, and ground-truthed image datasets are very helpful, but they are frequently hard to come by, which restricts the creation of very effective models. The identification of plant diseases has benefited enormously from the continuous advancement of deep learning (DL) techniques, which provide a robust tool with incredibly accurate results. However, the efficiency of deep learning models is dependent on the quantity and caliber of labeled data used for training. Precise classification of crop diseases is important for precision agriculture. These models suffer from limited and imbalance datasets especially for rare diseases. The study suggests a framework using Generative Adversarial Network (GAN) for image generation to enhance the classification of diseases. The study employs conditional GAN trained on a PlantVillage and New plant diseases datasets to generate synthetic images of diseased leaves. The images are evaluated using Structural similarity index (SSIM). Then the augmented images are integrated with the CNN classifier to measure the accuracy of disease prediction using synthetic dataset to validate the efficiency of image generation. The Author(s) 2026. -
Synthetic polymer hydrogels as potential tissue phantoms in radiation therapy and dosimetry
The efficacy of synthetic polymers as hydrogel phantoms for radiation therapy and dosimetry has been investigated for photon and charged particle (electron, proton and alpha particle) interactions. Tissue equivalence has been studied in terms of photon mass energy-absorption coefficients, KERMA (kinetic energy released per unit mass), equivalent atomic number and energy absorption build-up factors, relative to human tissues (skin, soft tissue, cortical bone and skeletal muscle), in the energy range 0.015-15 MeV. For charged particle interactions, ratio of effective atomic number is examined for tissue-equivalence in the energy region of 10 keV-1 GeV. Well established theoretical formulations are used for computation of photon mass-energy absorption effective atomic number, electron density and KERMA. Five-parameter geometric progression (G-P) fitting approximation is used to compute the values of energy absorption build-up factors. Effective atomic number for charged particle interaction is determined using logarithmic interpolation method. Using the analytical methodology, it has been revealed that all the selected synthetic polymers have good tissue-equivalence relative to all tissue except cortical bone. In particular, polyglycolic acid (PGA) and poly-lactic-co-glycolic acid (PLGA) prove to be best substitute material for photon interactions. On the other hand, % difference between effective atomic number for charged particle relative to human tissues is found least for polyethylene glycol (PEG) demonstrating adequate tissue-equivalence. Therefore, the present study is expected to be useful to choose most appropriate phantom material for radiation therapy. 2020 IOP Publishing Ltd. -
System Design for Financial and Economic Monitoring Using Big Data Clustering
Economic data executives are becoming increasingly important for the longevity and improvement of ventures due to the constant expansion in the influence of data innovation. This study lays out an undertaking economic data the executive's structure for the intricate internal undertaking economic data the board business. It also includes the application of web-based big data technology to understand the fairness, reliability, and security of system database calculations, mainly to improve office capabilities and solve daily project management problems. used in the project. The aim is to evaluate the suitability of transfer clustering computation (DCA) for managing large amounts of data in energy systems and the suitability of data economics dispatch methods for harnessing new energies. Then, combine day-ahead shipping plans with continuous shipping plans to create a multi-period, data-economic shipping model. Consider how the calculations are performed using a case study on the use of new energies. This will enable new energy in multi-period data economics shipping models while meeting his DR requirements on the customer side. 2023 IEEE. -
Systematic Contemplate Paradigm on Diabetes Mellitus using different Machine Learning Predictive Techniques
As the foodies love fast food, from micro to combined families across the world the ratio of family members 1:4 is affected with silent killer named as diabetes. A very high blood glucose levels, metabolism, improper carbohydrate, damaged hormone insulin alleviating a human body disability leading to the silent killer of the body parts is the diabetes. An estimated 425 million of people around the globe suffering with diabetes up to 108 million to 1.7 trillion will be affected with diabetes. Therefore millennium, the universe ubiquity suffering with diabetes has next to quadrupled, growing from 9 percent and above among the people. As the eating habits of people in this trendy 21st century is dramatically devastating to the risk of overweight or obese. The silent killer diabetes consequences include kidney failure, Diabetic retinopathy, Heart attack, Stiffness of body muscles, Nerves stroke and lower limb amputation leads to type I and type II diabetes. As the researchers across the globe are using the machine learning algorithms as the reliable problem solver, The complications still continue. The purpose of this percu is to help with the apt selection of features garnishing with machine learning paradigm techniques in selecting the accurate attributes for each person to be properly diagnosed. In this archetype survey paper, we have done a systematic review chronologically a decade research which will help the researchers to explore and get the contemplate on various tangible and intangible data sets they can adopt in diagnosing the mellitus diabetes. Grenze Scientific Society, 2023. -
Systematic investigation on unsymmetrical mesogenic cyanobiphenyl dimers towards optical storage devices: synthesis, mesomorphic, photo switching and DFT studies
This research presents the synthesis and analysis of a novel series of mesogenic dimers comprising cyanobiphenyl and azonaphthyl units. Structural validation was performed using FT-IR, 1H-NMR, 13C-NMR, elemental analysis, mass spectrometry, etc. The dimers thermotropic behaviours were studied through POM and DSC, revealing enantiotropic nematic phases in all cases, with some also showing monotropic smectic C phases. The study explores the relationship between the chemical structure of the dimers and the length of the flexible spacer, the odd-even effect, and their phase transition temperatures. Longer chains tended to form smectic phases, while shorter chains primarily exhibited nematic phases. Computational analysis using B3LYP/6-31g(d,p) and evaluations of electrostatic potential (ESP) and optical properties provided further insight into the electronic structures. Photoisomerization studies demonstrated consistent photochromic responses, with all dimers showing high conversion efficiency (88-95%) under UV light along with similar back relaxation times (?10-12 hours). Optical storage devices prepared by these materials showed excellent contrast between dark and bright states elucidating the importance of such materials for the future. 2025 The Royal Society of Chemistry.