MXene Composite and Coaxial Fibers with High Stretchability and Conductivity for Wearable Strain Sensing Textiles

The integration of nanomaterials with high conductivity into stretchable polymer fibers can achieve novel functionalities such as sensing physical deformations. With a metallic conductivity that exceeds other solution‐processed nanomaterials, 2D titanium carbide MXene is an attractive material to produce conducting and stretchable fibers. Here, a scalable wet‐spinning technique is used to produce Ti₃C₂T_x MXene/polyurethane (PU) composite fibers that show both conductivity and high stretchability. The conductivity at a very low percolation threshold of ≈1 wt% is demonstrated, which is lower than the previously reported values for MXene‐based polymer composites. When used as a strain sensor, the MXene/PU composite fibers show a high gauge factor of ≈12900 (≈238 at 50% strain) and a large sensing strain of ≈152%. The cyclic strain sensing performance is further improved by producing fibers with MXene/PU sheath and pure PU core using a coaxial wet‐spinning process. Using a commercial‐scale knitting machine, MXene/PU fibers are knitted into a one‐piece elbow sleeve, which can track various movements of the wearer's elbow. This study establishes fundamental insights into the behavior of MXene in elastomeric composites and presents strategies to achieve MXene‐based fibers and textiles with strain sensing properties suitable for applications in health, sports, and entertainment.     

Optimization of Run-of-River Hydropower Plant Design under Climate Change Conditions

The assessment of climate change and its impacts on hydropower generation is a complex issue. This paper evaluates the application of representative concentration pathways (RCPs, 2.6, 4.5, and 8.5) with the change factor (CF) method and the statistical downscaling method (SDSM) to generate six climatic scenarios of monthly temperature and rainfall over the period 2020–2049 in the Karkheh basin, Iran. The identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) model was employed to simulate runoff for the purpose of designing a run-of-river hydropower plant in the Karkheh basin. The non-dominated sorting genetic algorithm (NSGA)-II was employed to maximize yearly energy generation and the plant factor, simultaneously. Results indicate the runoff scenarios associated with the SDSM lead to higher run-of-river hydropower generation in 2020–2049 compared to the CF results.     

Preparation of Au nanoparticles by Q switched laser ablation and their application in 4-nitrophenol reduction

Clean Technologies and Environmental Policy - This work reports the fabrication of Au nanoparticles (NPs) by laser ablation of a gold metal plate immersed in water in the absence of stabilizing...     

Photocatalytic decomposition of VOCs by AC–TiO2 and EG–TiO2 nanocomposites

Clean Technologies and Environmental Policy - In this study, TiO2 nanoparticles (NPs)-based catalysts were prepared for the photocatalytic removal of toluene as a model VOC from air under UV light....     

Nanoethosomal formulation of gammaoryzanol for skin-aging protection and wrinkle improvement: a histopathological study

Background: Free radical scavengers and antioxidants, with the main focus on enhanced targeting to the skin layers, can provide protection against skin ageing.

Objective: The aim of the present study was to prepare nanoethosomal formulation of gammaoryzanol (GO), a water insoluble antioxidant, for its dermal delivery to prevent skin aging.

Methods: Nanoethosomal formulation was prepared by a modified ethanol injection method and characterized by using laser light scattering, scanning electronic microscope (SEM) and X-ray diffraction (XRD) techniques. The effects of formulation parameters on nanoparticle size, encapsulation efficiency percent (EE%) and loading capacity percent (LC%) were investigated. Antioxidant activity of GO-loaded formulation was investigated in vitro using normal African green monkey kidney fibroblast cells (Vero). The effect of control and GO-loaded nanoethosomal formulation on superoxide dismutase (SOD) and malondialdehyde (MDA) content of rat skin was also probed. Furthermore, the effect of GO-loaded nanoethosomes on skin wrinkle improvement was studied by dermoscopic and histological examination on healthy humans and UV-irradiated rats, respectively.

Results: The optimized nanoethosomal formulation showed promising characteristics including narrow size distribution 0.17?±?0.02, mean diameter of 98.9?±?0.05?nm, EE% of 97.12?±?3.62%, LC% of 13.87?±?1.36% and zeta potential value of –15.1?±?0.9?mV. The XRD results confirmed uniform drug dispersion in the nanoethosomes structure. In vitro and in vivo antioxidant studies confirmed the superior antioxidant effect of GO-loaded nanoethosomal formulation compared with control groups (blank nanoethosomes and GO suspension).

Conclusions: Nanoethosomes was a promising carrier for dermal delivery of GO and consequently had superior anti-aging effect.     

Deep learning and optimization algorithms for automatic breast cancer detection

Breast cancer is caused by the abnormal and rapid growth of breast cells. An early diagnosis can ensure an easier and effective treatment. A mass in the breast is a significant early sign of breast cancer, even though differentiating the cancerous mass's tissue from normal tissue for diagnosis is a difficult task for radiologists. The development of computer-aided detection systems in recent years has led to nondestructive and efficient cancer diagnostic techniques. This paper proposes a comprehensive method to locate the cancerous region in the mammogram image. This method employs image noise reduction, optimal image segmentation based on the convolutional neural network, a grasshopper optimization algorithm, and optimized feature extraction and feature selection based on the grasshopper optimization algorithm, thereby improving precision and decreasing the computational cost. This method was applied to the Mammographic Image Analysis Society Digital Mammogram Database and Digital Database for Screening Mammography breast cancer databases and the simulation results were compared with 10 different state-of-the-art methods to analyze the proposed system's efficiency. Final results showed that the proposed method had 96% Sensitivity, 93% Specificity, 85% PPV, 97% NPV, 92% accuracy, and better efficiency than other traditional methods in terms of Sensitivity, Specificity, PPV, NPV, and Accuracy.     

Laser-assisted preparation of C3N4/Fe2O3/Au nanocomposite: a magnetic reusable catalyst for pollutant degradation

Clean Technologies and Environmental Policy - Assorted common contaminants namely organic dyes and nitro compounds are generated by various industries and have caused alarming problems for the...     

MXenes Antibacterial Properties and Applications: A Review and Perspective

The mutations of bacteria due to the excessive use of antibiotics, and generation of antibiotic-resistant bacteria have made the development of new antibacterial compounds a necessity. MXenes have emerged as biocompatible transition metal carbide structures with extensive biomedical applications. This is related to the MXenes’ unique combination of properties, including multifarious elemental compositions, 2D-layered structure, large surface area, abundant surface terminations, and excellent photothermal and photoelectronic properties. The focus of this review is the antibacterial application of MXenes, which has attracted the attention of researchers since 2016. A quick overview of the synthesis strategies of MXenes is provided and then summarizes the effect of various factors (including structural properties, optical properties, surface charges, flake size, and dispersibility) on the biocidal activity of MXenes. The main mechanisms for deactivating bacteria by MXenes are discussed in detail including rupturing of the bacterial membrane by sharp edges of MXenes nanoflakes, generating the reactive oxygen species (ROS), and photothermal deactivating of bacteria. Hybridization of MXenes with other organic and inorganic materials can result in materials with improved biocidal activities for different applications such as wound dressings and water purification. Finally, the challenges and perspectives of MXene nanomaterials as biocidal agents are presented.     

The cost-effective fault detection and fault location approach for communication channels in NoC

In the current paper, we propose a new online search, fault detection, and fault location approach for short faults in network on chip communication channels. The approach proposed consists of a built-in self-test as well as a packet/flit comparings module embedded in the network adapter and a router, respectively. The approach is mainly characterized by the fact that, firstly, the diagnosis and location processes are simultaneously carried out after which the test time is minimized. Secondly, the approach updates the NoC routing tables far less costly in a parallel fashion. Thirdly, insignificant hardware is added to the system. The high scalability in the approach, in addition, leads to 100% test coverage, 71.4% capability of detecting faulty channels, and 100% detected faults location in one round (two phases). The simulation results show that the approach hardware is optimized compared with the previous methodologies.