Electrospun nanoyarns: A comprehensive review of manufacturing methods and applications

The global smart textile industry is estimated to reach 5.9 billion by 2026. However current textiles are limited due to the number of materials that can be incorporated into textiles that provide functionality and due to the use of bulky and rigid electronics. Nanofibers provide an avenue to address these limitations. Additionally, by incorporating nanofibers into textiles, functionality, and properties can be controlled from the nanoscale to the macroscale. A new method of incorporating nanofibers into textiles is by transforming nanofibers into nanoyarns. Nanoyarns would expand the applications of smart textiles to include bioactive scaffolds, tissue engineering, sensors, solar cells, and batteries. This review paper provides a comprehensive overview of different manufacturing methods for producing nanoyarns and their applications in tissue engineering and energy.     

Isolated word language identification system with hybrid features from a deep belief network

The representation of good audio features is the first and foremost requirement for improving the identification performance of any system. Most of the representation learning approaches are based on connectionist systems to learn and extract latent features from the speech data. This research work presents a hybrid feature extraction approach to integrate Mel-Frequency Cepstral Coefficients (MFCC) features with Shifted Delta Cepstral (SDC) coefficients features, which are further stacked to Deep Belief Network (DBN), for yielding new feature representations of the speech signals. DBN is utilized for unsupervised feature learning on the extracted MFCC-SDC acoustic features. A 3-layer Back Propagation Neural Network (BPNN) classifier is initialized in terms of the learning outcomes of hidden layers of DBN for identifying language from the uttered speech. The efficiency of the proposed approach is evaluated by simulating several experimental algorithms on the user-defined database of isolated words in four languages, namely, Tamil, Malayalam, Hindi, and English, in the working platform of MATLAB. The obtained results for the proposed hybrid approach MFCC-SDC-DBN are promising. The proposed approach is also compared with the baseline feature extraction approach MFCC-SDC by utilizing traditional acoustic features and BPNN classifier. The accuracy obtained with our proposed approach is 98.1% whereas that of the baseline approach is 82%, thereby providing an overall improvement of 16.1%.     

A Review on Biogenic Synthesis of Selenium Nanoparticles and Its Biological Applications

In recent decades, aquaculture and environment plays a noteworthy role in rewarding the massive stipulate in all industries. Environmental damage and disease domination are seen as essential issues in the region. In addition to these, nanotechnology as a fresh and imaginative instruments were extremely feasible in aquaculture and environmental applications. Next-generation biological applications of these nanomaterials might lead to an explosion in the bio industries. In order to utilizing the nanoparticles of biogenic expansion, selenium has plays major role in the biological progresses. Selenium (Se) is a multifunctional trace element. The present review analytically intends to the potential biological applications of biosynthesized selenium nanoparticles (SeNPs). Synthesis of SeNPs physical, chemical and biological methods has been used. Physical and chemical methods of SeNPs have high cost, non ecofriendly, highly time consuming. Therefore, there is a growing concern to develop eco friendly and sustainable methods for biosynthesis. Biosynthesis method has ecofriendly, low cost, nontoxic and zero contamination. Biosynthesis of selenium nanoparticles by plant extracts, bacteria, protein, biopolymers, seaweed extracts, fungi and yeasts have used for capping or stabilizing agents. Therefore this review represented original evidence for antibacterial, antifungal, antibiofilm, antioxidant, anticancer, antidiabetic, antimosquito larvicidal and aquaculture applications of prospective biogenic SeNPs were provided in turn in this regard of literatures. Bio synthesis of SeNPs and it is used for many applications like medical, environmental and aquaculture applications. In this review study, the importance of selenium nanoparticles as a competitive element for sustainable aquaculture and environmental applications is also examined in detail.

     

Probing the Mysterious Behavior of Tungsten as a Dopant Inside Pristine Cobalt-Free Nickel-Rich Cathode Materials

Nickel-rich cathode materials with small amounts of tungsten (W) dopants have attracted extensive attention in recent years. However, the chemical state, crystalline form, compound chemistry, and location of W in these layered cathodes are still not well-understood. In this study, these missing structural properties are determined through a combination of macro-, to atomic-sensitive characterization techniques and density functional theory (DFT). W-doped LiNiO₂ (LNO) particles, prepared with mechanofusion and coprecipitation methods, are used to probe changes in the structure and location of W-species. The results indicate that W is mainly distributed on the surfaces and inside grain boundaries of the secondary particles, regardless of the doping method. Electron energy loss spectroscopy (EELS) mapping confirms the simultaneous presence of W, O, with and without Ni in the grain boundaries as well as W- and O-rich regions on the very surface. The W-rich areas inside the grain boundaries are found to be in two forms, crystalline and amorphous. This paper suggests the presence of kinetically stabilized-Li_4+xNi_1-xWO₆ (x = 0, 0.1) with the possibility of Li_xW_yO_z phases in LNO which are consistent with the electron microscopy, X-ray absorption and diffraction data. The multiple roles of W in this complex microstructure are discussed considering the W distribution.