Influence of melt treatments on sliding wear behavior of Al–7Si and Al–7Si–2.5Cu cast alloys

The microstructures and dry sliding wear behavior of Al–7Si and Al–7Si–2.5Cu cast alloys were studied after various melt treatments like grain refinement and modification. Results indicate that combined grain refined and modified Al–7Si–2.5Cu cast alloys have microstructures consisting of uniformly distributed α-Al grains, eutectic Al– silicon and fine CuAl₂ particles in the interdendritic region. These alloys exhibited better wear resistance in the cast condition compared with the same alloy subjected to only grain refinement or modification. The improved wear resistances of Al–7Si–2.5Cu cast alloys are related to the refinement of the aluminum grain size, uniform distribution of eutectic Al-silicon and fine CuAl₂ particles in the interdendritic region resulting from combined refinement and modification. This paper attempts to investigate the influence of the microstructural changes in the Al–7Si and Al–7Si–2.5Cu cast alloys by grain refinement, modification and combined action of both on the sliding wear behavior.     

An intermediate-layer lithography method for generating multiple microstructures made of different conducting polymers

An intermediate-layer lithography (ILL) method has been developed in this work to generate multiple microstructures of different conducting polymers on the same substrate. Previous and current efforts in developing conducting polymer microsystems mainly focus on generating a device of a single function. When multiple micropatterns of different conducting polymers are produced on the same substrate, many microsystems of multiple functions can be envisioned. However, existing techniques present significant technical challenges of degradation, low throughput, low resolution, depth of field, and/or residual layer in producing conducting polymer microstructures. To circumvent these challenges, the ILL method has been explored to generate multiple micropatterns of different conducting polymers in a parallel manner. In this method, conducting polymer materials and a non-conducting polymer intermediate layer are first coated on a substrate, and are then patterned through a mold insertion at a raised temperature. In this work, the ILL has been used to successfully pattern three types of commonly used conducting polymers on the same substrate under a single mold insertion, and simulation has been conducted to gain a good understanding of the molding process. Due to distinctive advantages of simplicity, low cost and high throughput, the ILL has promising applications in fabricating micropatterns for polymer-based microsystems.     

QFD-based expert system for non-traditional machining processes selection

Selection of an optimal non-traditional machining (NTM) process for generating a desired feature on a given material requires the consideration of several factors among which the type of the workpiece material and shape to be machined are the most significant ones. This paper presents a quality function deployment (QFD) based methodology to ease out the optimal NTM process selection procedure. It includes the design of a QFD-based expert system that can automate the decision making process with the help of graphical user interfaces and visual aids. The developed expert system employs the use of a house of quality (HOQ) matrix for comparison of the relevant product and process characteristics. The weights obtained for various process characteristics are utilized to estimate an overall score for each of the NTM processes. Finally, if some of the NTM processes satisfy certain critical criteria, they are again compared with each other on the basis of their overall scores and the process having the maximum score is selected as the optimal choice.     

Mixing characteristics in microchannels with biomimetic superhydrophobic (Lotus leaf replica) walls

We demonstrate here the mixing characteristics in microchannels with a biomimetic superhydrophobic (lotus leaf replica) wall. The lotus leaf replica is fabricated using a frugal, yet efficient, double-step soft lithography method. In microchannels with a lotus leaf replica wall, the unidirectional laminar flow pertaining to the low hydrodynamics regime changes into an erratic flow field beyond a critical flow rate. We show here that such lotus leaf replica-induced erratic flow, even for low Reynolds number, can be used for enhanced mixing at the microscale. The enhancement in the mixing is quantified by the reduction in the mixing length in the microchannels with the biomimetic lotus leaf replica wall as compared to identical microchannels with flat walls. We believe that the simple cost-effective methodology for enhancing mixing in microchannels, as demonstrated here, can be integrated into lab-on-a-chip devices, which may be beneficial for applications requiring microscale mixing like DNA sequencing, enzyme reaction, and medical diagnostics.     

A Critical Assessment of Kriging Model Variants for High-Fidelity Uncertainty Quantification in Dynamics of composite Shells

This paper presents a critical comparative assessment of Kriging model variants for surrogate based uncertainty propagation considering stochastic natural frequencies of composite doubly curved shells. The five Kriging model variants studied here are: Ordinary Kriging, Universal Kriging based on pseudo-likelihood estimator, Blind Kriging, Co-Kriging and Universal Kriging based on marginal likelihood estimator. First three stochastic natural frequencies of the composite shell are analysed by using a finite element model that includes the effects of transverse shear deformation based on Mindlin’s theory in conjunction with a layer-wise random variable approach. The comparative assessment is carried out to address the accuracy and computational efficiency of five Kriging model variants. Comparative performance of different covariance functions is also studied. Subsequently the effect of noise in uncertainty propagation is addressed by using the Stochastic Kriging. Representative results are presented for both individual and combined stochasticity in layer-wise input parameters to address performance of various Kriging variants for low dimensional and relatively higher dimensional input parameter spaces. The error estimation and convergence studies are conducted with respect to original Monte Carlo Simulation to justify merit of the present investigation. The study reveals that Universal Kriging coupled with marginal likelihood estimate yields the most accurate results, followed by Co-Kriging and Blind Kriging. As far as computational efficiency of the Kriging models is concerned, it is observed that for high-dimensional problems, CPU time required for building the Co-Kriging model is significantly less as compared to other Kriging variants.     

Selecting useful groups of features in a connectionist framework.

Suppose for a given classification or function approximation (FA) problem data are collected using l sensors. From the output of the ith sensor, ni features are extracted, thereby generating p = sigma li = 1 ni features, so for the task we have X subset Rp as input data along with their corresponding outputs or class labels Y subset Rc. Here, we propose two connectionist schemes that can simultaneously select the useful sensors and learn the relation between X and Y. One scheme is based on the radial basis function (RBF) network and the other uses the multilayered perceptron (MLP) network. Both schemes are shown to possess the universal approximation property. Simulations show that the methods can detect the bad/derogatory groups of features online and can eliminate the effect of these bad features while doing the FA or classification task.     

Imaging of Small Animal Peripheral Artery Disease Models: Recent Advancements and Translational Potential

Peripheral artery disease (PAD) is a broad disorder encompassing multiple forms of arterial disease outside of the heart. As such, PAD development is a multifactorial process with a variety of manifestations. For example, aneurysms are pathological expansions of an artery that can lead to rupture, while ischemic atherosclerosis reduces blood flow, increasing the risk of claudication, poor wound healing, limb amputation, and stroke. Current PAD treatment is often ineffective or associated with serious risks, largely because these disorders are commonly undiagnosed or misdiagnosed. Active areas of research are focused on detecting and characterizing deleterious arterial changes at early stages using non-invasive imaging strategies, such as ultrasound, as well as emerging technologies like photoacoustic imaging. Earlier disease detection and characterization could improve interventional strategies, leading to better prognosis in PAD patients. While rodents are being used to investigate PAD pathophysiology, imaging of these animal models has been underutilized. This review focuses on structural and molecular information and disease progression revealed by recent imaging efforts of aortic, cerebral, and peripheral vascular disease models in mice, rats, and rabbits. Effective translation to humans involves better understanding of underlying PAD pathophysiology to develop novel therapeutics and apply non-invasive imaging techniques in the clinic.     

Fine particles sampled at an urban background site and an industrialized coastal site in Northern France—Part 2: Comparison of offline and online analyses for carbonaceous aerosols

Particulate matter was sampled in Northern France during two summer and winter periods at both an urban background site (Douai, DO) and an industrialized coastal site (Grande-Synthe, GS). Ambient levels of particulate carbonaceous species and Polycyclic Aromatic Hydrocarbons (PAH) were measured by real-time measurements and via collection and analysis of offline filters (F). The comparison between online organic matter (OM) measured by an Aerosol Mass Spectrometer (AMS) and organic carbon (OC) determined by an offline thermal-optical method showed good linear trends in wintertime GS (r² = 0.82 while only 0.50 in summer), and DO (r² = 0.86 in summer and 0.92 in winter). However, significant differences were observed between analytical methods and sites with OC_AMS/OC_F ratios decreasing from 0.80 in DO during winter to ≈0.20 for GS in summer, suggesting that a large part of OM could be in the PM₁–PM_2.5 fraction. The simultaneous measurements of Black Carbon (BC) and Elemental Carbon (EC) concentrations in PM_2.5 were also well correlated at both sites with r² = 0.61–0.97 and slopes between 0.6 and 0.8. PAHs were analyzed in PM_2.5 and also measured online by AMS in PM₁. Their wintertime concentrations were highly correlated in DO (r² = 0.98) and to a lesser degree in GS (r² = 0.67). r² values determined for comparison between online and offline parameters (OC and PAHs) in GS were lower than in DO, probably due to a more complex aerosol composition and a higher variability of the physical and chemical properties resulting from the coastal situation and diversity of emission sources in the vicinity of GS.

Copyright © 2018 American Association for Aerosol Research     

Large third-order optical nonlinearity of silver colloids in silica glasses synthesized by ion implantation

Silver ion implantations in fused silica glasses have been made to synthesize silver nanocluster-glass composites and a combination of ‘Anti-Resonant Interferometric Nonlinear Spectroscopy (ARINS)’ and ‘Z-scan’ techniques has been employed for the measurement of the third-order optical susceptibility of these nanocomposites. The ARINS technique utilizes the dressing of two unequal-intensity counter-propagating pulsed optical beams with differential nonlinear phases, which occurs upon traversing the sample. This difference in phase manifests itself in the intensity-dependent transmission, measurement of which enables us to extract the values of nonlinear refractive index (η₂) and nonlinear absorption coefficient (β), finally yielding the real and imaginary parts of the third-order dielectric susceptibility (χ⁽³⁾). The real and imaginary parts of χ⁽³⁾ are obtained in the orders of 10⁻¹⁰ e.s.u for silver nanocluster-glass composites. The present value of χ⁽³⁾, to our knowledge, is extremely accurate and much more reliable compared to the values previously obtained by other workers for similar silver-glass nanocomposites using only Z-scan technique. Optical nonlinearity has been explained to be due to two-photon absorption in the present nanocomposite glasses and is essentially of electronic origin.