Novel isocyanate-free self-curable cathodically depositable epoxy coatings: Influence of epoxy groups on coating properties

Novel self-curable cathodically depositable coatings were developed from glycidyl functional epoxy ester-acrylic graft co-polymer (EEAG) without using any external crosslinking agents. The EEAG-amine adducts (EEAGAs) were prepared by reacting EEAG with varying amount of diethanolamine (DEoA) which are neutralized with acid and dispersed in deionised water to give stable dispersion for cathodic electrodeposition (CED) coatings. The dispersions were cathodically electrodeposited on phosphated steel panels and thermally cured to give uniform coating. The coatings were evaluated for different mechanical, chemical and corrosion resistance properties. The coatings were evaluated for their thermal properties using thermo gravimetric analysis (TGA). The final properties of the coatings were found to be affected by the amount of amine reacted with epoxy. The coating films showed good overall performance properties for their use in coating industry.     

Glycated proteome: From reaction to intervention

Glycation, a nonenzymatic reaction between reducing sugars and proteins, is a proteome wide phenomenon, predominantly observed in diabetes due to hyperglycemia. Glycated proteome of plasma, kidney, lens, and brain are implicated in the pathogenesis of various diseases, including diabetic complications, neurodegenerative diseases, cancer, and aging. This review discusses the strategies to characterize protein glycation, its functional implications in different diseases, and intervention strategies to protect the deleterious effects of protein glycation.     

Spatio-temporal polygonal clustering with space and time as first-class citizens

Detecting spatio-temporal clusters, i.e. clusters of objects similar to each other occurring together across space and time, has important real-world applications such as climate change, drought analysis, detection of outbreak of epidemics (e.g. bird flu), bioterrorist attacks (e.g. anthrax release), and detection of increased military activity. Research in spatio-temporal clustering has focused on grouping individual objects with similar trajectories, detecting moving clusters, or discovering convoys of objects. However, most of these solutions are based on using a piece-meal approach where snapshot clusters are formed at each time stamp and then the series of snapshot clusters are analyzed to discover moving clusters. This approach has two fundamental limitations. First, it is point-based and is not readily applicable to polygonal datasets. Second, its static analysis approach at each time slice is susceptible to inaccurate tracking of dynamic cluster especially when clusters change over both time and space. In this paper we present a spatio-temporal polygonal clustering algorithm known as the Spatio-Temporal Polygonal Clustering (STPC) algorithm. STPC clusters spatial polygons taking into account their spatial and topological properties, treating time as a first-class citizen, and integrating density-based clustering with moving cluster analysis. Our experiments on the drought analysis application, flu spread analysis and crime cluster detection show the validity and robustness of our algorithm in an important geospatial application.     

Assessing Decentralised Water Solutions: Towards a Framework for Adaptive Learning

This paper reports on the use of qualitative analysis to inform a risk analysis framework for decentralised water systems. To realise the benefits from these technologies, a methodology is applied to learn from previous difficulties in implementing and managing them. A workshop process was used to capture stories from industry professionals on difficulties they have encountered in planning and implementation. Qualitative analysis of story narratives revealed stages where there was some type of development process failure; as well as failure modes and factors influencing the difficulties encountered. The analysis also generated insights: difficulties in one part of the development process tends to propagate to subsequent stages; system difficulties most often occurred in the policy stage of development due to institutional inertia and lack of adaptive governance; and the best indicator of problems with a decentralised system was complaints of poor water quality. Furthermore, this paper also provides a method to learn from past difficulties by identifying what data needs to be collected in order to populate a risk model which can be used for improving risk assessment of the development process for decentralised systems. This can provide a basis for better decision making, policy and guidelines; an important factor in mainstream acceptance.     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Novel Lyapunov-based rapid and ripple-free MPPT using a robust model reference adaptive controller for solar PV system

The technological, economic, and environmental benefits of photovoltaic (PV) systems have led to their widespread adoption in recent years as a source of electricity generation. However, precisely identifying a PV system''s maximum power point (MPP) under normal and shaded weather conditions is crucial to conserving the maximum generated power. One of the biggest concerns with a PV system is the existence of partial shading, which produces multiple peaks in the P–V characteristic curve. In these circumstances, classical maximum power point tracking (MPPT) approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point (GMPP). To overcome such obstacles, a new Lyapunov-based Robust Model Reference Adaptive Controller (LRMRAC) is designed and implemented to reach GMPP rapidly and ripple-free. The proposed controller also achieves MPP accurately under slow, abrupt and rapid changes in radiation, temperature and load profile. Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods, i.e., ANFIS, INC, VSPO, and P&O. MPP and GMPP are accomplished in less than 3.8 ms and 10 ms, respectively. Based on the results presented, the LRMRAC controller appears to be a promising technique for MPPT in a PV system.     

Organometallic L-Alanine Cadmium Iodide Crystals for Optical Device Fabrication

Single crystals of L-alanine cadmium iodide (LACI) were grown by the slow evaporation technique at room temperature. A single-crystal X-ray diffraction (SXRD) model was used to evaluate the crystal structure of the as-grown LACI crystal. The energy dispersive X-ray (EDX) analysis and ultraviolet-visible-near infrared (UV-vis-NIR) transmittance studies were carried out, and the results reveal the presence of elements in the title compound. From the transmittance data, the optical bandgap as a function of photon energy was estimated, and the different optical constants were calculated. A fluorescence study was performed for the LACI crystal. Thermogravimetric and differential thermal analyses have also been studied to investigate the thermal property of the LACI crystal. The efficiency of the second harmonic generation (SHG) of the title crystal was investigated. The magnetic and electrical properties were estimated by the vibrating sample magnetometer (VSM) analysis and impedance study, respectively.     

Polyelectrolyte multilayers for bio‐applications: recent advancements

The synergistic relationship between structure and the bulk properties of polyelectrolyte multilayer (PEM) films has generated tremendous interest in their application for loading and release of bioactive species. Layer‐by‐layer assembly is the simplest, cost effective process for fabrication of such PEMs films, leading to one of the most widely accepted platforms for incorporating biological molecules with nanometre precision. The bulk reservoir properties of PEM films render them a potential candidate for applications such as biosensing, drug delivery and tissue engineering. Various biomolecules such as proteins, DNA, RNA or other desired molecules can be incorporated into the PEM stack via electrostatic interactions and various other secondary interactions such as hydrophobic interactions. The location and availability of the biological molecules within the PEM stack mediates its applicability in various fields of biomedical engineering such as programmed drug delivery. The development of advanced technologies for biomedical applications using PEM films has seen rapid progress recently. This review briefly summarises the recent successes of PEM being utilised for diverse bio‐applications.Inspec keywords: polymer electrolytes, multilayers, polymer films, molecular biophysics, biomedical materials, biochemistryOther keywords: bioapplications, polyelectrolyte multilayer films, bioactive species, layer‐by‐layer assembly, biological molecules, biosensing, drug delivery, tissue engineering, biomolecules, proteins, DNA, RNA, electrostatic interactions, secondary interactions, hydrophobic interactions, biomedical engineering, programmed drug delivery, biomedical applications, PEM films     

CFD study of forced convective heat transfer enhancement in a 90° bend duct of square cross section using nanofluid

In this paper, the forced convective heat transfer enhancement with nanofluids in a 90° pipe bend has been presented. Numerical investigation is carried out for the turbulent flow through the pipe employing finite volume method. The governing differential equations are discretized using hexahedral cells, and the resulting algebraic equations are solved using Commercial solver Fluent 6.3. In order to close the time averaged Navier–Stokes equations, the two-equation k–? turbulence model with a standard wall function have been used. The duct Reynolds number is varied in the range of 2,500–6,000. It is observed that the heat transfer is enhanced significantly by varying the volume fraction of the nanofluid. It is also found that the heat transfer is increased with Reynolds number. A strong secondary flow is observed due to the presence of the wall. Turbulent kinetic energy near outer wall is found to be higher than the inner wall of the bend. A comparative assessment for the heat transfer enhancement with different types of nanofluids is also presented. The computed results of area weighted average Nusselt numbers are validated with some of the existing literature.     

A multisource energy harvesting utilizing highly efficient ferroelectric PMN-PT single crystal

This paper demonstrates a multi-source energy harvester that is able to utilize simultaneously both piezoelectric and pyroelectric effects in lead magnesium niobate-lead titanate (PMN-PT) single crystal. The paper presents a study of PMN-PT single crystal with a (67:33) composition grown in our laboratory via a vertical gradient freeze method without any flux. The performance of the piezoelectric and pyroelectric energy harvester using unimorph device structure was evaluated via modeling and experiment. The theoretical study was implemented based on a distributed parameter electromechanical model and the modelling procedure was approximated using finite element analysis to predict the electromechanical behavior of the harvester. The maximum power density at a resonance frequency of 50 Hz and optimum resistance of 2 MΩ was 16.7 nW/(g² cm³) under a 1 g acceleration of vibration. The measured values of electrical output parameters were in good agreement with theoretical and modelling results using MATLAB and COMSOL Multiphysics, respectively. By using the pyroelectric effect along with the piezoelectric effect, the output voltage of the energy harvester was found to be enhanced at the optimum resistance and specific frequency values. It was noticed that the output voltage was increased monotonically with temperature-difference (ΔT) and reaches up to 180 % of its original value under temperature difference of 1.7 °C at a frequency value of 49 Hz.