Synthesis of tin oxide-coated gold nanostars and evaluation of their surface-enhanced Raman scattering activities

Tin oxide-coated gold nanostar hybrid nanostructures are prepared by first synthesizing gold nanostars (ca. 400 nm), then introducing Na₂SnO₃ precursor followed by its hydrolysis and formation of a tin oxide layer on nanoparticle surface. The synthesized hybrid structures have been characterized by combination of UV–Vis spectroscopy, transmission electron microscope (TEM), energy-dispersive X-ray studies, scanning electron microscope (SEM), X-Ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy. The TEM and SEM analyses showed that gold nanostars have a coating with an approximate thickness of 15 nm. The tin (IV) oxide coating on the gold nanostars was identified by XRD and XPS analyses and confirmed by FTIR spectroscopy. Surface-enhanced Raman scattering (SERS) spectroscopy was performed on tin oxide-coated and uncoated gold nanostars with crystal violet as a probe molecule. The SERS studies revealed field enhancement properties of Au nanostars, thus their strong SERS activity remained after tin oxide coating.     

A generic method for estimating system reliability using Bayesian networks

This study presents a holistic method for constructing a Bayesian network (BN) model for estimating system reliability. BN is a probabilistic approach that is used to model and predict the behavior of a system based on observed stochastic events. The BN model is a directed acyclic graph (DAG) where the nodes represent system components and arcs represent relationships among them. Although recent studies on using BN for estimating system reliability have been proposed, they are based on the assumption that a pre-built BN has been designed to represent the system. In these studies, the task of building the BN is typically left to a group of specialists who are BN and domain experts. The BN experts should learn about the domain before building the BN, which is generally very time consuming and may lead to incorrect deductions. As there are no existing studies to eliminate the need for a human expert in the process of system reliability estimation, this paper introduces a method that uses historical data about the system to be modeled as a BN and provides efficient techniques for automated construction of the BN model, and hence estimation of the system reliability. In this respect K2, a data mining algorithm, is used for finding associations between system components, and thus building the BN model. This algorithm uses a heuristic to provide efficient and accurate results while searching for associations. Moreover, no human intervention is necessary during the process of BN construction and reliability estimation. The paper provides a step-by-step illustration of the method and evaluation of the approach with literature case examples.     

Functional properties of microwave-treated wheat gluten

In this study, the effects of microwave treatments on solubility, foaming and emulsifying properties of gluten were investigated. The solubility of microwave-heated gluten proteins gradually decreased as the treatment time increased, at all power levels applied. The highest solubility values were obtained for gluten samples microwave treated at 50% power level. The lowest emulsifying capacity values were obtained with the samples heated at 100% power level at all treatment times. The emulsifying stability values of microwave-heated gluten samples were found to be slightly higher than those of the control sample. However, there were no significant differences among the microwave power levels at all treatment times in terms of the emulsifying stability values. The foam volumes of the samples treated at 80 and 100% energy levels were slightly higher than those of the control gluten. The foam stability values of microwave-heated gluten samples gradually increased with treatment time at all power levels, which were more pronounced at 100% power level. Generally, microwave treatment did not cause major changes on the protein electrophoretic patterns of gluten samples at the power levels used.     

Hierarchical Organization of Structurally Colored Cholesteric Phases of Cellulose via 3D Printing

Structural color—a widespread phenomenon observed throughout nature is caused by light interference from ordered phases of matter. While state-of-the-art nanofabrication techniques can produce structural organization in small areas, cost-effective and scalable techniques are still lacking to generate tunable color at sub-micron length scales. In this work, structurally colored hydroxypropyl cellulose filaments are produced with a suppressed angular color response by 3D printing. The systematic study of the morphology of the filaments reveals the key stages in the induction of a two-degree hierarchical order through 3D printing. The first degree of order originated from the changing of the cholesteric pitch at a few hundred nm scale via chemical modification and tuning of the solid content of the lyotropic phase. Upon 3D printing, the secondary hierarchical order of periodic wrinkling is introduced through the Helfrich–Hurault deformation of the shear-aligned cholesteric phases. In single-layered filaments, four morphological zones with varying orders of wrinkles are identified. Detailed morphological characterization is carried out using SEM to shed light on the mechanism of the wrinkling behavior. Through this work, the possibility of modifying the wrinkling behavior is demonstrated and thus the angle dependence of the color response by changing the printing conditions.     

The Use of Digital Image Processing Method to Estimate the Foam Characteristics of Polyurethane

Four air-bubbled polyurethane (PU) foams with different polyol:PMDI wt.% are produced, respectively. The chemical reaction mechanisms of polyurethane and bubble formation are proposed by performing standard Gibbs free energy calculations using the DFT M06-2X/6-31+G(d,p) method. The local minima, transition states, and intermediates in reaction mechanisms are detected. It is concluded that both reactions are exothermic. Then, raw images of the produced PU foams are taken with a 13 MP mobile phone camera, which can be considered inexpensive, and the mean radii of the pores are calculated by an image processing based method (IPBM) on a standard desktop computer with an i5 processor. It is determined that there is a close relationship between the calculated mean radius and instrumentally measured thermal conductivity coefficient of the foams. However, the thermal conductivity coefficients are independent of the calculated number and percentage of the pores. The mean radii of the samples calculated by the proposed IPBM are close to that of the SEM, with acceptable relative errors of less than 10%. Finally, it is concluded that IPBM, which is a more cost-effective, cleaner, and faster method than SEM, might replace SEM in the air bubble analysis of PU foams.