Thermal diffusion in nanostructured porous InP

Nanostructured porous InP samples were prepared by electrochemical anodic dissolution of InP for various current densities and etching periods. The samples were characterized by SEM and photoluminescence (PL) where a blue shift was observed in PL. Thermal properties studied by photoacoustic (PA) spectroscopy revealed one order decrease in thermal conductivity of porous InP compared to the bulk. Further it is shown that the thermal conductivity of porous InP decreases with decrease in size of the particles.     

江苏德邦化工集团有限公司，江苏连云港 222023

1 简介 印度第一个纯碱厂始建于1932年，位于印度西部古吉拉特邦的Dhrangadhra，装置能力为50t/d。 作为基础无机化工产品，因为整个印度无天然碱矿，全部产品--包括轻灰和重灰只能以合成法生产。     

Sample size and error in the determination of mode shapes by principal components analysis

Principal components analysis (PCA) is a multivariate statistical technique that transforms a data set having a large number of inter-related variables to a new set of uncorrelated variables called the principal components, determined to allow the dimensionality of the data set to be reduced while retaining as much of the variation present as possible. PCA can be applied to dynamic structural response data to identify the predominant modes of vibration of the structure. Because PCA is a statistical technique, there are errors in the computed modes due to the use of a sample of finite size. The aim of this paper is to study the effect of sample size on the accuracy with which the modes of vibration can be computed. The paper focuses predominantly on elastic response data and examines the potential influence of various parameters such as the period of the structure, the input excitation, and the spatial distribution of mass over the structure. Issues relating to errors in the modes of nonlinear structures are also discussed.     

Safety in robotic installations

The rapid growth of the robotic industry has made it imperative to consider more seriously the safety aspects of robotic installations. Some work has been initiated recently in this area; a standard proposed by the Robotic Industries Association is a step in the right direction. This paper is based on an investigation of the state of the art in robotic safety, and contains an analysis of the sources of accidents, and the accident-prone operational phases of robotic installations. It forms the groundwork (literature survey) of a research project at the University of Windsor to develop a hardware/software-based safety system. It is suggested that both the robot manufacturer and the user should regard robotic safety as an important consideration.     

The coming of age of agroforestry

The success of modern agricultural and forestry production can be largely attributed to monoculture systems using a few select species. In the drive for maximizing yield and profit, the age‐old tradition of using combined farming systems was essentially avoided and in some cases this has resulted in environmental problems such as land and water degradation and increased land clearing. During the last 30 years, however, the positive benefits of agroforestry to the producer and the environment have been increasingly recognized. Combining trees and crops in spatial or temporal arrangements has been shown to improve food and nutritional security and mitigate environmental degradation, offering a sustainable alternative to monoculture production. By providing supportive and complimentary roles with a flexible approach, agroforestry can offer specific social and environmental benefits across a range of landscapes and economies. More research and effort is needed to explore the full potential of agroforestry applications and to fuel awareness. As the plethora of benefits of agroforestry are realized, modern land‐use systems are evolving towards a more sustainable and holistic approach to land management. Copyright © 2007 Society of Chemical Industry     

An energy‐efficient asynchronous wake‐up scheme for underwater acoustic sensor networks

In addition to the requirements of the terrestrial sensor network where performance metrics such as throughput and packet delivery delay are often emphasized, energy efficiency becomes an even more significant and challenging issue in underwater acoustic sensor networks, especially when long‐term deployment is required. In this paper, we tackle the problem of energy conservation in underwater acoustic sensor networks for long‐term marine monitoring applications. We propose an asynchronous wake‐up scheme based on combinatorial designs to minimize the working duty cycle of sensor nodes. We prove that network connectivity can be properly maintained using such a design even with a reduced duty cycle. We study the utilization ratio of the sink node and the scalability of the network using multiple sink nodes. Simulation results show that the proposed asynchronous wake‐up scheme can effectively reduce the energy consumption for idle listening and can outperform other cyclic difference set‐based wake‐up schemes. More significantly, high performance is achieved without sacrificing network connectivity. Copyright © 2015 John Wiley & Sons, Ltd.     

Tapered element oscillating microbalance (TEOM) studies of isobutane,n‐butane and propane sorption in β‐ and Y‐zeolites

A TEOM is used to elucidate the adsorption/desorption characteristics of alkylation reactants on USY‐ and β‐zeolites. Equilibrium adsorption isotherms were obtained on USY‐ and β‐zeolites using n‐butane, isobutane and propane as proxy reactant molecules (T = 303–398 K, adsorbate partial pressure 0–1.2 bar). Analysis of the transient adsorption/desorption profiles of these molecules from either a bed of the zeolite or pelletized particles of the crystals (with mean size < 1 μm) demonstrate that diffusion in the secondary meso‐/macroporous structure formed in the packing or the pellets controls the overall sorption rates. The experimental adsorption/desorption profiles from the pelletized zeolites were regressed with available mathematical models to obtain effective meso‐/macropore diffusivities for reactant molecules, and nearly perfect fits of the experimental and the modeled profiles. Taking into account the dead volume in the system, a criterion for reliable measurements of either micropore or mesopore diffusivities by the TEOM technique is derived. © 2009 American Institute of Chemical Engineers AIChE J, 2010     

Modeling of key reaction pathways: Zeolite catalyzed alkylation processes

A six lump kinetic model that considers the key reactions for the zeolite catalyzed alkylation process is presented. The influence of different reactions and rate limiting steps on reactor performance is examined by coupling an appropriate reactor model that accounts for different back-mixing on reactor scale, with a zeolite particle model which accounts for the diffusion inside the zeolite pore, the alkylation reaction, and zeolite deactivation. Model predictions are compared with experimental results and lead to conclusions that hydride transfer and oligomerization reactions are the key kinetic steps affecting the overall performance of zeolite catalyzed alkylation processes. It is suggested that higher alkylate yield and longer zeolite activity are achieved by increasing the intrinsic hydride transfer rate and the ratio of feed isobutane to n-butene (P/O) concentration. For a given P/O feed ratio, achieving close to plug flow for isobutane and high back-mixing for n-butene further enhances local P/O ratio and yield. Furthermore, optimal zeolite catalyst design should consider the egg shell type of Brønsted acid site distribution and a lower silicon to alumina (Si/Al) ratio.     

Effective parameter estimation within a multi-dimensional population balance model framework

This study considers optimization problems with multi-dimensional population balance models embedded. The objective function is formulated as a least-squares problem, minimizing the difference between target data and simulated model output and the goal is to find model parameter values that best fit the data. Results show that derivative-free methods, such as the Nelder–Mead simplex method, fail to converge to an optimal solution. A similar result was obtained with gradient-based methods such as BFGS, quasi-Newton, Newton, Gauss–Newton, Levenberg–Marquardt and SQP, and with a stochastic genetic algorithm. It was hypothesized that three main issues could contribute to these convergence failures: (1) gradients were calculated based on finite differences, and as a result of improper step size determination, the numerical error could be prohibitive resulting in inaccurate derivative information, (2) the parameters may not be identifiable and (3) numerical instability could occur during the course of optimization. To circumvent these issues, this work addresses the calculation of derivative information based on automatic differentiation and sensitivity analysis to ensure increased accuracy. Issues such as parameter identifiability are also dealt with by analyzing an accurate Fisher information matrix. Given the computational burden in calculating accurate Jacobians and Hessians, compounded by the potential nonsmoothness introduced into the objective function as a result of granule nucleation, other optimization strategies may be warranted and this work addresses those accordingly. Overall, by systematically assessing the problem formulation and mechanisms, the results show that substantial improvements in convergence can be achieved by utilizing appropriate optimization techniques, thus leading to more successful and optimal parameter estimation.