Flexible,Mechanically Stable,Porous Self-Standing Microfiber Network Membranes of Covalent Organic Frameworks: Preparation Method and Characterization

Covalent organic frameworks (COFs) show advantageous characteristics, such as an ordered pore structure and a large surface area for gas storage and separation, energy storage, catalysis, and molecular separation. However, COFs usually exist as difficult-to-process powders, and preparing continuous, robust, flexible, foldable, and rollable COF membranes is still a challenge. Herein, such COF membranes with fiber morphology for the first time prepared via a newly introduced template-assisted framework process are reported. This method uses electrospun porous polymer membranes as a sacrificial large dimension template for making self-standing COF membranes. The porous COF fiber membranes, besides having high crystallinity, also show a large surface area (1153 m² g⁻¹), good mechanical stability, excellent thermal stability, and flexibility. This study opens up the possibility of preparation of large dimension COF membranes and their derivatives in a simple way and hence shows promise in technical applications in separation, catalysis, and energy in the future.     

Microbial susceptibility of various polymers and evaluation of thermoplastic elastomers with antimicrobial additives

The incursion of microbial growth on polymeric products can deteriorate their performance and lead to the development of undesirable staining and odors. A growing trend in the industry has aimed to reduce microbial populations on high-touch surfaces via the use of antimicrobials to protect material aesthetics and durability or to prevent the spread of pathogenic microorganisms. In this study, a variety of plastic substrates (30 unique polymer compounds), including poly(acrylonitrile-co-butadiene-co-styrene), poly(butylene terephthalate), poly(etherimide), various thermoplastic elastomers (TPEs), poly(carbonates), and poly(amides), were screened for susceptibility to microbial attack using American Society for Testing and Materials (ASTM) G21 (fungi susceptibility), Japanese Industrial Standard (JIS) Z2801, and modified ASTM E1428-15a (bacterial susceptibility) test standards. TPEs were determined to be most susceptible to microbial attack under the appropriate environmental conditions. Subsequent studies assessed the use of an antimicrobial additive, zinc pyrithione (ZPT), for potential efficacy in a variety of TPE blends for diverse target market applications. ZPT proved to be very effective in protecting TPEs, reducing Staphylococcus aureus and Escherichia coli populations by 99.9% or more in JIS Z2801 testing and inhibiting fungal growth (rating = 0) according to the ASTM G21 standard.     

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.     

Deep autoencoders for feature learning with embeddings for recommendations: a novel recommender system solution

Neural Computing and Applications - We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from...     

Face verification across age progression.

Human faces undergo considerable amounts of varialions with aging. While face recognition systems have been proven to be sensitive to factors such as illumination and pose, their sensitivity to facial aging effects is yet to be studied. How does age progression affect the similarity between a pair of face images of an individual? What is the confidence associated with establishing the identity between a pair of age separated face images? In this paper, we develop a Bayesian age difference classifier that classifies face images of individuals based on age differences and performs face verification across age progression. Further, we study the similarity of faces across age progression. Since age separated face images invariably differ in illumination and pose, we propose preprocessing methods for minimizing such variations. Experimental results using a database comprising of pairs of face images that were retrieved from the passports of 465 individuals are presented. The verification system for faces separated by as many as nine years, attains an equal error rate of 8.5%.     

Surface effects in nanocrystalline silicon

Exposure to ammonia (NH₃) increases the dark current (DC) in nanocrystalline silicon. Light soaking (LS) for short periods also enhances the dark current, which remains at a high value for a long time. Pumping alone is unable to restore the initial annealed state, but annealing brings it back. The final state obtained by LS and NH₃ exposure depends on the order in which they are performed. Evaporated selenium (Se) deposited on nanocrystalline silicon decreases the DC. These effects cannot be explained entirely by the presence of a-Si : H alone, in our sample. DC and photoluminescence (PL) measurements indicate the presence of two types of center in our sample, which behave differently when exposed to NH₃.     

Static energy reduction techniques for microprocessor caches

Microprocessor performance has been improved by increasing the capacity of on-chip caches. However, the performance gain comes at the price of static energy consumption due to subthreshold leakage current in cache memory arrays. This paper compares three techniques for reducing static energy consumption in on-chip level-1 and level-2 caches. One technique employs low-leakage transistors in the memory cell. Another technique, power supply switching, can be used to turn off memory cells and discard their contents. A third alternative is dynamic threshold modulation, which places memory cells in a standby state that preserves cell contents. In our experiments, we explore the energy and performance tradeoffs of these techniques. We also investigate the sensitivity of microprocessor performance and energy consumption to additional cache latency caused by leakage-reduction techniques.     

Estimating and reducing the memory requirements of signal processing codes for embedded systems

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented.