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.     

An automated patient monitoring using discrete‐time wireless sensor networks

In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature.     

Cubic–Quartic Optical Solitons with Differential Group Delay for Kudryashov’s Model by Extended Trial Function

Journal of Communications Technology and Electronics - This paper implements mathematically rigorous extended trial function algorithm to address cubic–quartic optical solitons in...     

Effect of 100 KeV Ar+ ion beam irradiation on ZnO thin films – Influence of morphology vis-a-vis electrode/electrolyte interface and its impact on photoelectrochemical water splitting

The present study attempts quantitative determination of changes in the morphological surface features viz. fractal dimension, lower and upper cut off length scale through Power Spectral Density analysis prior to and after irradiation of 100 KeV Ar⁺ ion beam at incidence angles of 0°, 40° and 60° on ZnO thin films. All the unirradiated and irradiated samples are subjected to photoelectrochemical characterization and a correlation between photoelectrochemical performance and morphological parameters is established. Sample irradiated at 40° angle at the fluence of 5 × 10¹⁶ ions/cm² is found to possess maximum fractal dimension of 2.72, lower and upper cut off length scale of 3.16 nm and 63.00 nm respectively. This sample exhibits maximum photocurrent density of 3.19 mA/cm² and applied bias photon-to-current efficiency of 1.12% at 1.23 V/RHE. Hydrogen gas collected for duration of 1 h for the same sample was ~4.83 mLcm^?2.     

Synthesis and characterization of a novel Ca-alginate-biochar composite as efficient zinc (Zn2+) adsorbent: Thermodynamics,process design,mass transfer and isotherm modeling

In this present work, Ca-alginate-biochar adsorbent has been synthesized, characterized and tested its effectiveness in the removal of aqueous phase Zn²⁺ metal. The removal efficiency was studied under various physicochemical process parameters. External mass transfer model, intraparticle diffusion model and pseudo-first-order and pseudo-second-order models were used to fit the experimental Zn²⁺ adoption kinetic results and to identify the mechanism of adsorption. The desorption studies indicate the possibilities of ion-exchange and physical–chemical adsorption of Zn^2+. The adsorption was best described by Langmuir isotherm model. Thermodynamic parameters suggested that the adsorption process becomes spontaneous, endothermic and irreversible in nature.     

Nitrogen transformations and fate of other parameters in columnar denitrification

Soil columns were used as denitrifying reactors in the laboratory where the feed solutions were composed of nitrified solution and kitchen waste. Five different carbon (expressed as methanol) to nitrogen ratios ranging from 2:1 to 6:1 were applied to twenty soil columns. Transformation of nitrogen compounds and fate of associated parameters during denitrification were investigated. A high degree of denitrification was obtained for C:N ratios of 4:1 or higher. Rate of application was not a significant factor in this study. Most of the TKN present in the feed solutions escaped the denitrification reactors. Production of total alkalinity during denitrification was found to be somewhat lower than the values reported in the literature. In some cases the column effluents contained higher solids concentrations than in the influent.     

A comparative thermodynamic study of sorption systems: second law analysis

As a consequence of the phasing out of CFCs, sorption systems appear to be potential candidates to replace vapour compression systems. Amongst sorption systems there exists a choice between several systems, such as liquid absorption, solid adsorption and chemical reaction heat pumps. Nevertheless, few comparative studies between these systems have been undertaken so far. It is the aim of this paper to present such a study based on combined first and second law thermodynamical analysis of the different cycles. Simple entropy generation processes explain why the basic cycles for these systems yield performances much lower than the Carnot efficiency. The possibility of operating regenerative cycles with internal heat recovery and higher efficiencies has also been considered for typical common base conditions. Different entropy generation considerations have been visualised, such as thermal coupling (external/internal), non-uniform temperature component entropy production and other irreversible processes for the COP degradation in these systems. It is found that thermal coupling irreversibilities in solid sorption systems and other internal irreversibilities in liquid sorption systems with solution heat exchanger are dominant in the actual COP degradation with respect to the reversible Carnot COP.     

A 4-MB on-chip L2 cache for a 90-nm 1.6-GHz 64-bit microprocessor

A 4-MB L2 data cache was implemented for a 64-bit 1.6-GHz SPARC(r) RISC microprocessor. Static sense amplifiers were used in the SRAM arrays and for global data repeaters, resulting in robust and flexible timing operation. Elimination of the global clock grid over the SRAM array saves power, enabled by combining the clock information with array select signals. Redundancy was implemented flexibly, with shift circuits outside the main data array for area efficiency. The chip integrates 315 million transistors and uses an 8-metal-layer 90-nm CMOS process.     

Relationships between multiaxial stress states and internal fracture patterns in sphere-impacted silicon carbide

Internal fracture patterns developed in silicon carbide cylindrical targets as a result of dynamic indentation (63–500 m/s) by tungsten carbide spheres are defined. Microscopy of recovered and sectioned targets delineate into three regions, each associated with distinct cracking modes, i.e., shallow cone macrocracking at and near the impact surface, steep interior cone macrocracks that radiate into the target from the impact region and local grain-scale microcracking directly underneath the impact region. The observed fracture patterns are found to maintain a noticeable degree of self-similarity upto the impact velocity of 500 m/s. Linear elastic analysis of the full (surface and interior) stress field developed under static (Hertz) contact loading delineate the target into four regions, based on the number of principal stresses that are tensile (none, 1, 2 or all 3). A strong correlation is found between the principal stress conditions within each region and the forms of cracking, their locations and orientations present therein. This correlation has a number of implications, including non-interaction of crack systems, which are discussed. Illustrative linear elastic fracture mechanics analyses are performed for three regions, and calculated and observed macrocrack lengths are found to be in reasonable agreement.