Single-step synthesis of N-doped TiO2 by flame aerosol method and the effect of synthesis parameters

We have established a novel route for the synthesis of N-doped TiO₂ by adopting flame aerosol (FSP) technique and investigated the effect of water content on the physico-chemical properties of the as-synthesized nanoparticles. The key characteristics of the developed method are to modify the precursor solution in order to incorporate nitrogen atoms into the TiO₂ lattice without altering the FSP set-up. The reduction of the flame enthalpy resulting in N-incorporation into the TiO₂ and the N-doping can be greatly enhanced further by the addition of secondary N-source (urea). Our XRD results reveal a shift of the (101) plane anatase diffraction peak to lower angles in our N-doped TiO₂ compared to undoped TiO_2, which suggest the distortion and strain in the crystal lattice prompted by the incorporation of the nitrogen atoms. The growth or expansion of crystal lattice can be attributed to the larger atomic radius of respective nitrogen atoms (r?=?1.7 Å) compared to oxygen (r?=?1.40 Å). Our XPS and EDX spectroscopy results elucidate that the nitrogen was effectively doped into the crystal lattice of TiO₂ in our as-synthesized N-TiO₂ catalysts predominantly in the form of interstitial nitrogen (Ti?O?N). The nitrogen atoms incorporation into the crystal lattice of titania modifies the electronic band structure of TiO₂, resulting in a new mid-gap energy state N 2p band formed above O 2p valence band. This occurrence narrows the band gap of TiO₂ (from 3.12 to ～2.51?eV) in our N-doped TiO₂ and shifts the optical absorption to the visible region.

Copyright © 2018 American Association for Aerosol Research     

Multilayer thermal object identification in frequency domain using IR thermography and vector fitting

This paper deals with the identification of the thermal parameters of multilayer objects using the concept of thermal impedance. In order to perform such identification, temperature evolution in time is obtained by an infrared camera after power excitation is applied in the investigated structure. Infrared thermography offers the advantage of being a noncontact temperature detection and measurement method. In many practical cases, it is impossible to use contact temperature measurements. Typically, the power in the form of a step function is applied. In order to calculate the thermal impedance of an object, temperature and power are converted into the frequency domain using the Laplace transform for s = jω. Then, the poles of the thermal impedance are identified using vector fitting, which allows calculating the thermal impedance as a sum of partial fractions. This corresponds directly to the Foster network of a thermal object. In addition, the vector fitting method offers much better convergence in comparison with other methods using the polynomial rational approximation of thermal impedance. A considerable improvement of the numerical Laplace transform in high frequency range is proposed. In this approach, the variable s = jω is replaced by , and then, the integration result is corrected by the Taylor series. It leads to a kind of filtering of the temperature signal.     

Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge,Deep Architectures,and Beyond

International Journal of Computer Vision - Automatic understanding of human affect using visual signals is of great importance in everyday human–machine interactions. Appraising human...     

A Semi-Parametric Non-linear Neural Network Filter: Theory and Empirical Evidence

In this work, we decompose a time series into trend and cycle by introducing a novel de-trending approach based on a family of semi-parametric artificial neural networks. Based on this powerful approach, we propose a relevant filter and show that the proposed trend specification is a global approximation to any arbitrary trend. Furthermore, we prove formally a famous claim by Kydland and Prescott (1981, 1997) that over long time periods, the average value of the cycles is zero. A simple procedure for the econometric estimation of the model is developed as a seven-step algorithm, which relies on standard techniques, where all relevant measures may be computed routinely. Next, using relevant DGPs, we compare and show by means of Monte Carlo simulations that our approach is superior to Hodrick–Prescott (HP) and Baxter and King (BK) regarding the generated distortionary effects and the ability to operate in various frequencies, including changes in volatility, amplitudes and phase. In fact, while keeping the structure of the model relatively simple, our approach is perfectly capable of addressing the case of stochastic trend, in the sense that the generated distortionary effects in the near unit root case are minimal and, by all means, considerably fewer than those generated by HP and BK. Application to EU15 business cycles clustering is presented and the empirical results are consistent with the rigorous theoretical framework developed in this work.     

A Survey of IoT Key Enabling and Future Technologies: 5G,Mobile IoT,Sematic Web and Applications

The Internet of Things (IoT) is the communications paradigm that can provide the potential of ultimate communication. The IoT paradigm describes communication not only human to human (H2H) but also machine to machine (M2M) without the need of human interference. In this paper, we examine, review and present the current IoT technologies starting from the physical layer to the application and data layer. Additionally, we focus on future IoT key enabling technologies like the new fifth generation (5G) networks and Semantic Web. Finally, we present main IoT application domains like smart cities, transportation, logistics, and healthcare.     

Gas Phase Synthesis of Multifunctional Fe‐Based Nanocubes

Magnetron‐sputtering inert‐gas condensation is an emerging technique offering single‐step, chemical‐free synthesis of nanoparticles with well‐defined morphologies optimized for specific applications. In this study, the authors report a flexible approach to produce Fe nanocubes as building blocks for high‐performance NO₂ gas sensor devices, and hybrid FeAu nanocubes with magneto‐plasmonic properties. Considering that nucleation happens within a short distance from the sputtering target, the authors utilize the high‐permeability and resultant screening effect induced by magnetic Fe targets of various thicknesses to manipulate the magnetic field configuration and plasma confinement. The authors thus readily switch from bimodal to single‐Gaussian size distributions of Fe nanocubes by modifying their primordial thermal environments, as explained by a combination of modeling methods. Simultaneously, the authors obtain a material yield increase of more than one order of magnitude compared to experiments using postgrowth mass filtration. The effectiveness of the method is demonstrated by the deposition of Fe nanocubes on microhotplate devices, leading to unprecedented NO₂ detection performance for Fe‐based chemoresistive gas sensors. The exceedingly low detection limit down to 3 ppb is attributed to a morphological change in operando from Fe/Fe‐oxide core/shell to specific hollow‐nanocube structures, as revealed by in situ environmental transmission electron microscopy.     

Cyclic scheduling in synchronous production lines

In this paper we address the scheduling problem in unpaced synchronous mixed-model production lines operated under a cyclic scheduling policy. We first discuss operations of a production line with the synchronous transfer of parts. We then present an integer programming formulation of the problem. The problem, however, is W-hard, and for its exact solution we propose an implicit enumeration scheme. We discuss a property of the scheduling problem which allows us to effectively solve large size instances of the problem. We also present an approximate solution procedure with very good avenge performance. Useful managerial insights are obtained as we search for ways to improve the performance of synchronous lines. The relaxation of one of our original assumptions in the scheduling problem formulation results in an easy problem whose solution generates the absolute best in throughput performance configuration of the production line. Implementation of this solution, however, requires increasing the number of buffers in the line. We suggest other performance improvement ways to better balance the tradeoff between throughput and average Work-In-Progress (WIP) inventory in the line.