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.     

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.

     

Tetrahydroindoles as Multipurpose Screening Compounds and Novel Sirtuin Inhibitors

Indoles are privileged structures in medicinal and bioorganic chemistry that are particularly well suited to serve as platforms for diversity. Among many other therapeutic areas, the indole scaffold has been used to design aromatic compounds useful to interfere with enzymes engaged in the regulation of substrate acylation status, such as sirtuins. However, the planarity of the indole ring is not necessarily optimal for all target enzymes, especially when functionalization with aromatic side chains is required. Replacement of flat scaffolds by nonplanar molecular cores dominated by sp³ hybridization is a common strategy to avoid the disadvantages associated with poor solubility and high promiscuity, while covering less-well-explored areas of chemical space. Thus, we synthesized fragment-like tetrahydroindoles suitable for fragment-based drug discovery as well as a well-characterized small library intended as multipurpose screening compounds. For proof of principle, these compounds were screened against sirtuins 1–3, enzymes known to be addressable by indoles. We found that 2,6,6-trimethyl-4-oxo-4,5,6,7-tetrahydro-1H-indole-3-carboxamides are potent and selective SIRT2 inhibitors. Compound 16 t displayed an IC₅₀ value of 0.98 μm and could serve as exquisite starting point for hit-to-lead profiling.     

Experimental and numerical analysis of the influence of cable tray arrangements on the resulting mass loss rate and fire spreading

In the context of industrial buildings and power plants, electrical installations and cable trays represent a main fuel load and a potential initial fire source due to possible short circuits or comparable malfunction. Furthermore, a fire can spread from one tray to additional trays mounted above and/or horizontally on one tray. Because of the high significance of cable fires, several research projects have been carried out, investigating the fire behaviour of cables from small‐scale tests, eg, the cone calorimeter, up to large‐scale tests, analysing complete cable tray constructions. The goal of the work presented in this paper is the extension of the knowledge regarding the influence of geometrical parameters like the packing density and tray distance on the burning behaviour and fire spread of cable tray installations. The results are considered, together with test results from the literature, to quantify the main physical parameters describing the burning behaviour. In a next step, the general applicability of these parameters as input data for the parametrization of the source term of numerical simulations is shown. The test results show that the burning behaviour and the fire spreading highly depend on the cable arrangement of the cables on the cable tray, in combination with other boundary conditions. By applying the results as input for a fire simulation, the mass loss rate is considered appropriately.     

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.     

Beneficial effects of wettability altering surfactants in oil-wet fractured reservoirs

In fractured reservoirs, an effective matrix-fracture mass transfer is required for oil recovery. Surfactants have long been considered for oil recovery enhancement, mainly in terms of their ability to reduce oil–water interfacial tension. These surfactants are effective when the fractured formations are water-wet, where capillary imbibition of surfactants from the fracture into the matrix contributes to oil recovery. However, another beneficial aspect of surfactants, namely their ability to alter wettability, remains to be explored and exploited. Surfactants capable of altering wettability can be especially beneficial in oil-wet fractured formations, where the surfactant in the fracture diffuses into the matrix and alters the wettability, enabling imbibition of even more surfactant into the matrix. This sequential process of initial diffusion followed by imbibition continues well into the matrix yielding significant enhancements in oil recovery.In order to test this hypothesis of sequential diffusion–imbibition phenomenon, Dual-Drop Dual-Crystal (DDDC) contact angle experiments have been conducted using fractured Yates dolomite reservoir fluids, two types of surfactants (nonionic and anionic) and dolomite rock substrates. A new experimental procedure was developed in which crude oil equilibrated with reservoir brine has been exposed to surfactant to simulate the matrix-fracture interactions in fractured reservoirs. This procedure enables the measurements of dynamic contact angles and oil–water interfacial tensions, in addition to providing the visual observations of the dynamic behavior of crude oil trapped in the rock matrix as it encounters the diffusing surfactant from the fractures. Both the measurements and visual observations indicate wettability alterations of the matrix surface from oil-wet to less oil-wet or intermediate wet by the surfactants. Thus this study is of practical importance to oil-wet fractured formations where surfactant-induced wettability alterations can result in significant oil recovery enhancements. In addition, this study has also identified the need to include contact angle term in the dimensionless Bond number formulations for better quantitative interpretation of rock–fluids interactions.