4D Printing of Shape Memory Materials for Textiles: Mechanism,Mathematical Modeling,and Challenges

Shape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.     

Tuning of shear thickening behavior and elastic strength of polyvinylidene fluoride via doping of ZnO-graphene

ZnO rice like nonarchitects are grafted on the graphene carbon core via a rapid microwave synthesis route. The prepared grafted systems are characterized via XRD, SEM, RAMAN, and XPS to examined the structural and morphological parameters. Zinc oxide grafted graphene sheets (ZnO-G) are further doped in β-phase of polyvinylidene fluoride (PVDF) to prepare the polymer nanocomposites (PNCs) via mixed solvent approach (THF/DMF). β-phase confirmation of PVDF PNCs is done by FTIR studies. It is observed that ZnO-G filler enhances the β-phase content in the PNCs. Non-doped PVDF and PNCs are further studied for rheological behavior under the shear rate of 1–100 s⁻¹. Doping of ZnO-G dopant to the PVDF matrix changes its discontinuous shear thickening (DST) behavior to continues shear thickening behavior (CST). Hydrocluster formation and their interaction with the dopant could be the reason for this striking DST to CST behavioral change. Strain amplitude sweep (10⁻³% -10%) oscillatory test reveals that the PNCs shows extended linear viscoelastic region with high elastic modulus and lower viscous modulus. Effective shear thickening behavior and strong elastic strength of these PNCs present their candidature for various fields including mechanical and soft body armor applications.     

Photon and vibration synergism on planar defects induced 2D-graphitic carbon nitride for ultrafast remediation of dyes and antibiotic ampicillin

Journal of Materials Science - Hybrid oxidation methodologies (HOMs) and active site enrichment of 2D nanocatalyst through defects induction are ubiquitously used for generating adequate reactive...     

Fabrication of Wear-Resistant Ti3AlC2/Al3Ti Hybrid Aluminum Composites by Friction Stir Processing

Metallurgical and Materials Transactions A - Hybrid nanocomposites have potential as wear-resistant materials. However, synthesizing these nanocomposites by conventional molten state methods result...     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Design and performance study of phase‐locked loop using fractional‐order loop filter

The present work reports the realization of an analog fractional‐order phase‐locked loop (FPLL) using a fractional capacitor. The expressions for bandwidth, capture range, and lock range of the FPLL have been derived analytically and then compared with the experimental observations using LM565 IC. It has been observed that bandwidth and capture range can be extended by using FPLL. It has also been found that FPLL can provide faster response and lower phase error at the time of switching compared to its integer‐order counterpart. Copyright © 2014 John Wiley & Sons, Ltd.     

Large Area Self-Assembled Ultrathin Polyimine Nanofilms Formed at the Liquid–Liquid Interface Used for Molecular Separation

Separation membranes with higher molecular weight cut-offs are needed to separate ions and small molecules from a mixed feed. The molecular sieving phenomenon can be utilized to separate smaller species with well-defined dimensions from a mixture. Here, the formation of freestanding polyimine nanofilms with thicknesses down to ≈14 nm synthesized via self-assembly of pre-synthesized imine oligomers is reported. Nanofilms are fabricated at the water–xylene interface followed by reversible condensation of polymerization according to the Pieranski theory. Polyimine nanofilm composite membranes are made via transferring the freestanding nanofilm onto ultrafiltration supports. High water permeance of 49.5 L m^-2 h⁻¹ bar⁻¹ is achieved with a complete rejection of brilliant blue-R (BBR; molecular weight = 825 g mol⁻¹) and no more than 10% rejection of monovalent and divalent salts. However, for a mixed feed of BBR dye and monovalent salt, the salt rejection is increased to ≈18%. Membranes are also capable of separating small dyes (e.g., methyl orange; MO; molecular weight = 327 g mol⁻¹) from a mixed feed of BBR and MO. Considering a thickness of ≈14 nm and its separation efficiency, the present membrane has significance in separation processes.     

Estimation of power density in IMPATT using different materials

ABSTRACT

The RF output power dissipated per unit area is calculated using Runge-Kutta method for the high-moderate-moderate-high (n⁺-n-p-p⁺) doping profile of double drift region (DDR)-based impact avalanche transit time (IMPATT) diode by taking different substrate at Ka band. Those substrates are silicon, gallium arsenide, germanium, wurtzite gallium nitride, indium phosphide and 4H-silicon carbide. A comparative study regarding power dissipation ability by the IMPATT using different material is being presented thereby modelling the DDR IMPATT diode in a one-dimensional structure. The IMPATT based on 4H-SiC element has highest power density in the order of 10¹⁰ Wm^?2 and the Si-based counterpart has lowest power density of order 10⁶ Wm^?2 throughout the Ka band. So, 4H-SiC-based IMPATT should be preferable over others for the power density preference based application. This result will be helpful to estimate the power density of the IMPATT for any doping profile and to select the proper element for the optimum design of the IMPATT as far as power density is concerned in the Ka band. Also, we have focused on variation of power density with different junction temperatures and modelled the heat sink with analysis of thermal resistances.