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. 相似文献
An ecofriendly and biodegradable porous structure was prepared from drying aqueous foams based on nano fibrillated cellulose (NFC), extracted from softwood pulp by subcritical water/CO2 treatment (SC-NFC). The primary aim of this work was to use the modified SC-NFC as stabilizer for a water-based Pickering emulsion which upon drying, yielded porous cellulosic materials, a good dye adsorbent. In order to exploit the carboxymethylated SC-NFC (CMSC-NFC, with a degree of substitution of 0.35 and a charge density of 649 μeqv/g) as a stabilizer for water-based Pickering emulsion in subsequent step, an optimized quantity of octyl amine (30 mg/g of SC-NFC) was added to make them partially hydrophobic. A series of dry foam structures were prepared by varying the concentrations of treated CMSC-NFCs and 4 wt% was found to be the optimum concentration to yield foam with high porosity (99%) and low density (0.038 g/cc) along with high compression strength (0.24 MPa), superior to the conventionally extracted NFC. The foams were applied to capture as high as 98% of methylene blue dyes, making them a potential green candidate for treating industrial effluent. In addition, the dye adsorption kinetics and isotherms were found to be well suited with second order kinetics and Langmuir isotherm models. 相似文献
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... 相似文献
The influence of cementite spheroidization on the impact toughness and electrochemical properties of a high-carbon steel has been thoroughly investigated in this study. Heavy warm rolling, followed by 2 h of annealing, has resulted in near-complete spheroidization, leading to a microstructure consisting of nano-cementite globules dispersed in the ultrafine-grained ferritic matrix. The Charpy impact test exhibited superior impact toughness with increased spheroidization. It is validated by the presence of abundant dimples in the fractographs of spheroidized specimens, in contrast to the as-received one that experienced a brittle failure due to its lamellar pearlitic structure. Potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) carried out in a 3.5% NaCl solution revealed that the corrosion resistance of the alloy gets improved with the increase in the degree of spheroidization. This is attributed to the lower susceptibility of the spheroidized specimen to microgalvanic corrosion owing to the minimum area of contact between nano-spheroidized cementite and ferrite, as elucidated with the help of EIS results aided by equivalent electrical circuit model. 相似文献
Metallurgical and Materials Transactions A - Hybrid nanocomposites have potential as wear-resistant materials. However, synthesizing these nanocomposites by conventional molten state methods result... 相似文献
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.
In the recent sub-20 nm technology node, the process variability issues have become a major problem for scaling of MOS devices. We present a design for a strained Si/SiGe FinFET on an insulator using a 3D TCAD simulator. The impact of metal gate work function variability (WFV) on electrical parameters is studied. Such impact of WFV for different mole fractions (x) of the SiGe layer in a strained SOI-FinFET with varying grain size is presented. The results show that as the mole fraction is increased, the variability in threshold voltage (σVT) and off current (σIoff) is decreased; while, the variability of on-current (σIon) is increased. A notable observation is the distribution of electrical parameters approaches a normal distribution for smaller grain sizes. 相似文献