Review on zirconate-cerate-based electrolytes for proton-conducting solid oxide fuel cell

The performance of low-to-intermediate temperature (400–800?°C) solid oxide fuel cells (SOFCs) depends on the properties of electrolyte used. SOFC performance can be enhanced by replacing electrolyte materials from conventional oxide ion (O^2-) conductors with proton (H⁺) conductors because H⁺ conductors have higher ionic conductivity and theoretical electrical efficiency than O^2- conductors within the target temperature range. Electrolytes based on cerate and/or zirconate have been proposed as potential H⁺ conductors. Cerate-based electrolytes have the highest H⁺ conductivity, but they are chemically and thermally unstable during redox cycles, whereas zirconate-based electrolytes exhibit the opposite properties. Thus, tailoring the properties of cerate and/or zirconate electrolytes by doping with rare-earth metals has become a main concern for many researchers to further improve the ionic conductivity and stability of electrolytes. This article provides an overview on the properties of four types of cerate and/or zirconate electrolytes including cerate-based, zirconate-based, single-doped cerate–zirconate and hybrid-doped cerate–zirconate. The properties of the proton electrolytes such as ionic conductivity, chemical stability and sinterability are also systematically discussed. This review further provides a summary of the performance of SOFCs operated with cerate and/or zirconate proton conductors and the actual potential of these materials as alternative electrolytes for proton-conducting SOFC application.     

Stabilization of 6H-Hexagonal SrMnO3 Polymorph by Al2O3 insertion

We demonstrate the structural evolution of polymorphic phases in Al₂O₃-inserted SrMnO₃ ceramics synthesized by solid state reaction. While the 4H-hexagonal phase is predominant in pure SrMnO₃ ceramics, a small amount of 6H-hexagonal polymorph is identified in addition to the primary 4H-hexagonal SrMnO₃ and the secondary hexagonal SrAl₂O₄ phases in the as-sintered ceramics, evidenced by x-ray diffraction and subsequent Rietveld refinement analyses. The existence of the 6H-hexagonal SrMnO₃ phase is corroborated using Raman spectroscopy. The chemical compositions and electronic structures of the Al₂O₃-inserted SrMnO₃ compounds are also examined using energy dispersive spectroscopy and x-ray photoelectron spectroscopy, respectively. The first-principles calculations reveal that there is no clear difference between the total energies of 4H- and 6H-hexagonal polymorphs regardless of the presence/absence of Sr and oxygen vacancies. Possible origins are discussed with the estimation of actual strain based on the refined lattice parameter of 6H SrMnO₃.     

Material state remapping in computational solid mechanics

A computational procedure for remapping material state information from one finite element mesh to another is described. The procedure is useful in connection with evolving meshes for inelastic problems, as for example occur in the context of fracture simulation and adaptive mesh refinement. The proposed method is based on weak enforcement of equality between corresponding fields on the two meshes, where piecewise‐constant fields on both meshes are generalized from the quadrature‐point values. The essential algorithmic problem is that of calculating the volume partition of an arbitrary convex region with respect to a covering set of disjoint convex regions. Instead of geometrically resolving the associated intersections, the problem is herein approximated by a constrained optimization problem, which may be readily and efficiently solved computationally. This formulation is a main contribution of the paper. Computational examples are given that illustrate the effectiveness of the proposed procedure. Copyright © 2002 John Wiley & Sons, Ltd.     

Smart home security: challenges,issues and solutions at different IoT layers

The Journal of Supercomputing - The Internet of Things is a rapidly evolving technology in which interconnected computing devices and sensors share data over the network to decipher different...     

Sex pheromones of male yellowfin Baikal sculpin (Cottocomephorus grewingki): Isolation and chemical studies

Three components of the male yellowfin Baikal sculpin pheromonal signal have been isolated from urine by diethyl ether extraction, thinayer chromatography (TLC), and high-performance liquid chromatography (HPLC). Using mass spectrometry, we have identified two of them as testosterone (T) and 11-hydroxytestosterone (11HT). These steroids are synthesized in testes during full spermatogenesis, and they are excreted in male urine with milt. The third component is not a steroid. It is more likely to be a polyene alcohol (farnesol). 2Z,6E-Farnesol possesses behavioral activity.     

Aggregation Operators of Interval‐Valued 2‐Tuple Linguistic Information

The group decision‐making problem with linguistic information evaluation values of decision makers are used based on 2‐tuple interval‐valued. Operational laws on interval value 2‐tuple are introduced. On the basis of these laws, new aggregation operators are introduced by using the Choquet integral. A multiple attribute decision‐making method based on these aggregation operators is proposed. An example is given to illustrate the efficiency, practicality, and feasibility of our method.     

Photoalignment dynamics of azo dyes series with different coordination metals

There are many photoaligned azo dyes that can be used for orientation of liquid crystals in various display devices. However, the structure of these compounds needs to be optimized to increase the rate of the process of molecule photoalignment, as well as to spread the application of these compounds. The main coordination metal that presents in the molecules of azo dyes is sodium derivatives. The use of other alkali metals remains an open question. We used quantum‐chemical computation methods and reversible intermolecular bonding model to determine the effect of metal coordination on the velocity of photoalignment. The theoretical predictions were experimentally verified using sodium, potassium, lithium, and cesium salts of the model azo dye synthesized by us. We conclude that potassium azo derivatives are the fastest, ceteris paribus.     

A literature survey and an experimental study of coal devolatilization at mild and severe conditions: influences of heating rate, temperature, and reactor type on products yield and composition

Coal devolatilization studies to maximize the yield of condensable products by operating at elevated temperatures and heating rates have been published. The objectives of this study were to investigate the influences of relatively mild operating conditions (e.g. relatively low temperature and pressure) on product quality, by comparing devolatilized products obtained at various temperatures and heating rates. Fixed bed, fluid bed, and entrained flow reactor units were used to obtain pyrolysis products. In addition, literature data on tar yields in various reactor units at a range of temperatures and residence times were surveyed and compared with experimental data. The liquids were characterized by a number of techniques, including field ionization mass spectroscopy (f.i.m.s.), sequential elution solvent chromatography (s.e.s.c.) and elemental analysis. The results demonstrate that the quality and yield of liquids obtained at a rapid heating rate are functions of peak pyrolysis temperature. It was shown that at a rapid heating rate, the yields of heavier polyfunctional groups (i.e. hydrocarbons with greater mean molecular weight) are greater than those obtained in the fixed bed slow heating rate reactor. The liquids generated at a slow heating rate are of lower molecular weight, viscosity, and sulphur content, and of higher H/C atomic ratios compared with the liquids obtained in a rapid heating rate unit. The effect of increasing the maximum pyrolysis temperature (at a constant slow heating rate) was to increase the yield of light gases (mainly H) at the expense of char hydrogen content and char reactivity. The tar yield is not markedly influenced when the peak devolatilization temperature is increased at a relatively slow heating rate. However, the quality (as defined by the H/C (atomic) ratio) of the liquids, and the reactivity (in air) of char, was reduced when the peak pyrolysis temperature was increased. At a rapid heating rate, the primary products, which have many structural characteristics of the parent coal, are devolatilized. The quality of the liquids obtained at a rapid heating rate is, therefore, determined by the devolatilized primary coal fragments evolved at the devolatilization temperature. In a slow heating rate fixed bed unit, however, the primary coal fragments undergo additional cracking reactions which involve stabilization of free radicals by donatable hydrogen. This leads to the formation of low molecular weight hydrocarbons of relatively higher quality. In-situ (both intraparticle or extraparticle) stabilization of reactive coal fragments by donatable hydrogen may lead to a significant improvement in the overall quality of the pyrolysis liquids in a fixed bed system in which time-temperature history is conducive for such reactions.     

MIRRE approach: nonlinear and multimodal exploration of MIR aggregated search results

Multimedia Tools and Applications - Nowadays, web users frequently explore multimedia contents to satisfy their information needs. The exploration approaches usually provide linear interaction...     

Deep learning approaches for speech emotion recognition: state of the art and research challenges

Speech emotion recognition (SER) systems identify emotions from the human voice in the areas of smart healthcare, driving a vehicle, call centers, automatic translation systems, and human-machine interaction. In the classical SER process, discriminative acoustic feature extraction is the most important and challenging step because discriminative features influence the classifier performance and decrease the computational time. Nonetheless, current handcrafted acoustic features suffer from limited capability and accuracy in constructing a SER system for real-time implementation. Therefore, to overcome the limitations of handcrafted features, in recent years, variety of deep learning techniques have been proposed and employed for automatic feature extraction in the field of emotion prediction from speech signals. However, to the best of our knowledge, there is no in-depth review study is available that critically appraises and summarizes the existing deep learning techniques with their strengths and weaknesses for SER. Hence, this study aims to present a comprehensive review of deep learning techniques, uniqueness, benefits and their limitations for SER. Moreover, this review study also presents speech processing techniques, performance measures and publicly available emotional speech databases. Furthermore, this review also discusses the significance of the findings of the primary studies. Finally, it also presents open research issues and challenges that need significant research efforts and enhancements in the field of SER systems.