An Insight into molecular structure and properties of flexible amorphous polymers: A molecular dynamics simulation approach

Visualization of polymer molecules by molecular dynamics simulation remains a challenging area in molecular modeling, as it involves a number of factors like type of force field, simulation time, simulation steps, and so forth. In our present study, we have used the condensed-phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field, which is specific for polymers and organic molecules, in order to visualize the macromolecular chains of various flexible amorphous polymers: natural rubber, polybutadiene rubber, styrene–butadiene rubber, nitrile rubber, polychloroprene rubber, and fluoroelastomer. The study covered a wide range from nonpolar rubbers to polar rubbers, and the COMPASS force field was promising to understand the local structure and the packing of the chains inside the simulation box. The distance between different adjacent pairs of carbon atoms within the polymer chains was discussed in detail from intramolecular radial distribution function and represented pictorially in the polymer chains. Various bond angles were also examined for further details. In addition, interchain contacts, glass-transition temperature, and solubility parameter were predicted and compared with the experimental values. The diffusive characteristic of the chains was assessed by mean square displacement which in turn described the polymer chain mobility. In essence, the present study is expected to aid in the vivid conceptualization of molecular orientation of various polymers and would help in predicting various physical properties. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47457     

Synthesis and characterization of chemically stable sulfonated copoly(triazole imide)s with high proton conductivity

The synthesis and characterization of a series of new sulfonated copoly(triazole imide)s (PTPQSH‐XX) are reported in this work. The PTPQSH‐XX with different degree of sulfonation (DS) were prepared by click polymerization of equimolar amounts of a diimide‐based dialkyne monomer, namely bis‐N,N′‐(prop‐2‐ynyl)pyromellitic diimide (TP) and a mixture of two different diazide monomers (one sulfonated, 4,4‐bis[3′‐trifluoromethyl‐4′{4‐azidobenzoxy} benzyl] biphenyl, and another nonsulfonated, 4,4′‐diazido‐2,2′‐stilbene disulfonic acid disodium salt [SAZ]), in different molar ratios. The copolymers showed high inherent viscosity (1.12–1.28 dL/g) in n‐methyl pyrrolidone (NMP) indicating the formation of high molar masses. Freestanding membranes were prepared from these copolymers by solution casting method. DS of the copolymers was determined from ¹H NMR signal intensities, and the values were in good agreement with the quantity of SAZ monomer used in polymer feed, indicating the successful incorporation of the sulfonated monomer. The copolymers exhibited high thermal and mechanical stabilities. The PTPQSH‐80 membrane showed proton conductivity as high as 178 mS/cm at 90°C with good oxidative and hydrolytic stability. Cross‐sectional transmission electron microscope micrographs of the membranes indicated phase segregated morphology along with interconnected hydrophilic domains with dimension in the range 15–150 nm. POLYM. ENG. SCI., 59:2279–2289, 2019. © 2019 Society of Plastics Engineers     

Excimer laser ablation processed ferroelectric and antiferroelectric thin films

Abstract

The dielectric and electrical properties of excimer laser ablated processed paraelectric (Ba_0.5, Sr_0.5)TiO₃, ferroelectric Bi-layered SrBi₂(Ta_0.5Nb_0.5)₂O₉, and antiferroelectric (PbZrO₃) thin films have been investigated. The effect of processing parameters on the microstructure of the films and the functional properties has been presented in detail. Some of the recent studies of stress induced effects, dielectric, hysteresis and ac and dc electrical properties have been highlighted in conjunction with microstructures of the films.     

A dynamic model for short-term prediction of stream attributes

Multiple data streams coming out of a complex system form the observable state of the system. The streams may correspond to various sensors attached with the system or outcome of internal processes. Such stream data may consist of multiple attributes and may differ in terms of their frequency of generation and observation. The streams may have dependency among themselves. One will have to rely on such data streams for monitoring the health of the system or to take any corrective measure. Predicting the value of certain stream data is an important task that can help one to take decision and act accordingly. In this work, a simple but generic visualization of a complex system is presented and thereafter a linear regression-based dynamic model for short-term prediction is proposed. The model is based on the past history of the attributes of multiple streams as suggested by the domain experts. But, it automatically determines the meaningful attributes and reformulates the model. The model is also re-computed if the prediction error exceeds the allowable tolerance. All these make the model dynamic. Experiment is carried out with stock market data streams to predict the close value well in advance. It is observed that in terms of quality of prediction and performance metric, the proposed model is quite effective.     

A novel methodology for vessel extraction from retinal fundus image and detection of neovascularization

Multimedia Tools and Applications - Vessel extraction from the retinal fundus images plays a significant role in ophthalmologic disease diagnosis. Proliferative Diabetic Retinopathy (PDR) is the...     

Pervasive computing: a paradigm for the 21st century

Pervasive computing promises to make life simpler via digital environments that sense, adapt, and respond to human needs. Yet we still view computers as machines that run programs in a virtual environment. Pervasive computing presumes a different vision. A device can be a portal into an application-data space, not just a repository of custom software a user must manage. An application is a means by which a user performs a task, not software written to exploit a device's capabilities. And a computing environment is an information-enhanced physical space, not a virtual environment that exists to store and run software. Pervasive computing is close to technical and economic viability.     

Spectral entropy and spectral shape based pre-quantization for real time speaker identification system

Pre-processing is one of the vital steps for developing robust and efficient recognition system. Better pre-processing not only aid in better data selection but also in significant reduction of computational complexity. Further an efficient frame selection technique can improve the overall performance of the system. Pre-quantization (PQ) is the technique of selecting less number of frames in the pre-processing stage to reduce the computational burden in the post processing stages of speaker identification (SI). In this paper, we develop PQ techniques based on spectral entropy and spectral shape to pick suitable frames containing speaker specific information that varies from frame to frame depending on spoken text and environmental conditions. The attempt is to exploit the statistical properties of distributions of speech frames at the pre-processing stage of speaker recognition. Our aim is not only to reduce the frame rate but also to maintain identification accuracy reasonably high. Further we have also analyzed the robustness of our proposed techniques on noisy utterances. To establish the efficacy of our proposed methods, we used two different databases, POLYCOST (telephone speech) and YOHO (microphone speech).     

A cohesive modeling technique for theoretical and experimental estimation of damping in serial robots with rigid and flexible links

Dynamic model incorporating damping characteristics, namely joint damping and structural damping in flexible links, of the serial robots with rigid and flexible links is presented. A novel procedure, based on the unified approach of theoretical formulation and analysis of experimental data, is proposed for the estimation of damping coefficients. First, the dynamic model of a robotic system with rigid and flexible links is presented. Next, the modifications in the dynamic model due to the considerations of damping characteristics of joints and structural damping characteristics of the flexible links are presented. A systematic methodology based on analysis of data obtained from experiments is presented for estimation and determination of damping coefficients of rigid-flexible links. The determination of joint damping coefficients, is based on the logarithmic decay of the amplitude of the oscillations of robotic links, while the structural damping coefficients are estimated mainly using the modal analysis and the method of evolving spectra. The method of evolving spectra, based on the Fast Fourier Transform of the decay of the amplitude in structural vibrations of the robot links in progressive windows is used to estimate the structural damping ratios while the critical structural coefficients are determined using the modal analysis. The methodology is illustrated through a series of simple experiments on simple robotic systems. The experimental results are then compared with the simulation results incorporating the damping coefficients determined using the proposed procedure. The comparisons leads to the validation of the proposed dynamic modeling technique, modeling of the damping characteristics, and the method proposed for estimation of damping coefficients for rigid-flexible link robotic systems.     

Vectorial scale-based fuzzy-connected image segmentation

This paper presents an extension of previously published theory and algorithms for fuzzy-connected image segmentation. In this approach, a strength of connectedness is assigned to every pair of image elements. This is done by finding the strongest among all possible connecting paths between the two elements in each pair. The strength assigned to a particular path is defined as the weakest affinity between successive pairs of elements along the path. Affinity specifies the degree to which elements hang together locally in the image. A scale is determined at every element in the image that indicates the size of the largest homogeneous hyperball region centered at the element. In determining affinity between any two elements, all elements within their scale regions are considered. This method has been effectively utilized in several medical applications. In this paper, we generalize this method from scalar images to vectorial images. In a vectorial image, scale is defined as the radius of the largest hyperball contained in the same homogeneous region under a predefined condition of homogeneity of the image vector field. Two different components of affinity, namely homogeneity-based affinity and object-feature-based affinity, are devised in a fully vectorial manner. The original relative fuzzy connectedness algorithm is utilized to delineate a specified object via a competing strategy among multiple objects. We have presented several studies to evaluate the performance of this method based on simulated MR images, 20 clinical MR images, and 250 mathematical phantom images. These studies indicate that the fully vectorial fuzzy connectedness formulation has generally overall better accuracy than the method using some intermediate ad hoc steps to fit the vectorial image to a scalar fuzzy connectedness formulation, and precision and efficiency are similar for these two methods.