Hematites Precipitated in Alkaline Precursors: Comparison of Structural and Textural Properties for Methane Oxidation

Hematite (α-Fe₂O₃) catalysts prepared using the precipitation methods was found to be highly effective, and therefore, it was studied with methane (CH₄), showing an excellent stable performance below 500 °C. This study investigates hematite nanoparticles (NPs) obtained by precipitation in water from the precursor of ferric chloride hexahydrate using precipitating agents NaOH or NH₄OH at maintained pH 11 and calcined up to 500 °C for the catalytic oxidation of low concentrations of CH₄ (5% by volume in air) at 500 °C to compare their structural state in a CH₄ reducing environment. The conversion (%) of CH₄ values decreasing with time was discussed according to the course of different transformation of goethite and hydrohematites NPs precursors to magnetite and the structural state of the calcined hydrohematites. The phase composition, the size and morphology of nanocrystallites, thermal transformation of precipitates and the specific surface area of the NPs were characterized in detail by X-ray powder diffraction, transmission electron microscopy, infrared spectroscopy, thermal TG/DTA analysis and nitrogen physisorption measurements. The results support the finding that after goethite dehydration, transformation to hydrohematite due to structurally incorporated water and vacancies is different from hydrohematite α-Fe₂O₃. The surface area SBET of Fe₂O₃_NH-70 precipitate composed of protohematite was larger by about 53 m²/g in comparison with Fe₂O₃_Na-70 precipitate composed of goethite. The oxidation of methane was positively influenced by the hydrohematites of the smaller particle size and the largest lattice volume containing structurally incorporated water and vacancies.     

UV‐Triggered Polydopamine Secondary Modification: Fast Deposition and Removal of Metal Nanoparticles

Since the first report in 2007, polydopamine (PDA) coating has shown great potential as a general and versatile method to create functional nanocoatings on arbitrary substrates. Slow kinetics and poor controllability of the coating and secondary modification processes, however, have limited the further development of this attractive method. In this work, it is demonstrated that UV irradiation at 365 nm significantly accelerates the process of secondary modification of a PDA‐coated surface. The kinetics of both thiol and amine modifications of PDA are increased 12‐fold via UV irradiation, while the kinetics of metal ion reduction at the PDA interface is increased more than 550 times. Moreover, it is demonstrated that irradiating a PDA/metal nanoparticle composite surface with UV light at 254 nm leads to dissolution of the deposited metal nanoparticles (MNPs). Finally, grayscale metallic patterns, dynamic deposition, and removal of MNPs on PDA surface are realized with the proposed method.     

Signal shaper with a distributed delay: Spectral analysis and design

Input shapers with time delays have proved useful in many applications related to controls for various oscillatory devices, for example flexible manipulators and cranes. In the paper, a novel approach for designing a zero-vibration signal shaper based on equally distributed delay is proposed. The parameter assessment of the shaper is based on the spectral approach. Various characteristics of the shaper are analyzed and compared with the classical zero-vibration shaper with a lumped delay. The analysis shows that the novel shaper is a slower, but more robust alternative to the classical shaper. Besides, the discrete implementation of the shaper is proposed and tested. It includes zero placement based parameter adjustment with the objective to preserve full compensation of the oscillatory mode by the discrete algorithm.     

A Linear Optimal Transportation Framework for Quantifying and Visualizing Variations in Sets of Images

Transportation-based metrics for comparing images have long been applied to analyze images, especially where one can interpret the pixel intensities (or derived quantities) as a distribution of ‘mass’ that can be transported without strict geometric constraints. Here we describe a new transportation-based framework for analyzing sets of images. More specifically, we describe a new transportation-related distance between pairs of images, which we denote as linear optimal transportation (LOT). The LOT can be used directly on pixel intensities, and is based on a linearized version of the Kantorovich-Wasserstein metric (an optimal transportation distance, as is the earth mover’s distance). The new framework is especially well suited for computing all pairwise distances for a large database of images efficiently, and thus it can be used for pattern recognition in sets of images. In addition, the new LOT framework also allows for an isometric linear embedding, greatly facilitating the ability to visualize discriminant information in different classes of images. We demonstrate the application of the framework to several tasks such as discriminating nuclear chromatin patterns in cancer cells, decoding differences in facial expressions, galaxy morphologies, as well as sub cellular protein distributions.     

Analyzing probabilistic pushdown automata

The paper gives a summary of the existing results about algorithmic analysis of probabilistic pushdown automata and their subclasses.     

Persistent excitation condition within the dual control framework

Model Predictive Control framework is currently used in many different fields of expertise. The inherent part and very often also the main bottleneck is the model of a process used for the computation of predictions.Due to many reasons e.g. ageing, from time to time there exists a need to adjust/re-identify (if there was already some kind of a model-based controller) or to construct a brand new model (in other cases). Frequently, the process generating the data is under some kind of control, imposing thus problems when classical open loop identification methods are considered. The need for models identified from the data gathered in a closed-loop fashion and a request for possible re-identification of the model parameters lead to the emerge of dual control where the problems of control and system identification are addressed simultaneously.In this paper, we present a new algorithm based on the persistent excitation condition when the minimal eigenvalue of the information matrix is maximized in order to have sufficiently exciting optimal control signal satisfying the control requirements.     

Discrete (n + 1)-valued states and n-perfect pseudo-effect algebras

We give sufficient and necessary conditions to guarantee that a pseudo-effect algebra admits an (n + 1)-valued discrete state. We introduce n-perfect pseudo-effect algebras as algebras which can be split into n + 1 comparable slices. We prove that the category of strong n-perfect pseudo-effect algebras is categorically equivalent to the category of torsion-free directed partially ordered groups of a special type.     

Enhancing the performance of hybrid genetic algorithms by differential improvement

A differential improvement modification to Hybrid Genetic Algorithms is proposed. The general idea is to perform more extensive improvement algorithms on higher quality solutions. Our proposed Differential Improvement (DI) approach is of rather general character. It can be implemented in many different ways. The paradigm remains invariant and can be easily applied to a wider class of optimization problems. Moreover, the DI framework can also be used within other Hybrid metaheuristics like Hybrid Scatter Search algorithms, Particle Swarm Optimization, or Bee Colony Optimization techniques.     

Phase Transitions in Liquid Crystal Doped with Magnetic Particles of Different Shapes

In this study, observations of structural transitions in ferronematics based on the thermotropic nematic 4-trans-4′-n-hexyl-cyclohexyl-isothiocyanato-benzene (6CHBT) are described. Droplets of the nematic phase in the isotropic phase were observed in solutions of nematogenic 6CHBT dissolved in phenyl isocyanate and 6CHBT dissolved in phenyl isocyanate and doped with magnetic particles of different shapes (nanorods and chain-like particles). Magneto-dielectric measurements of structural transitions in these new systems enable to estimate of the type of anchoring of the nematic molecules on the magnetic particles surface.     

New algorithm for a robust user-independent evaluation of beginning instability for the experimental FLC determination

The failure prediction in sheet metal forming is typically realized by evaluating the so called forming limit curves (FLC). The standard experimental method is the Nakajima test, where sometimes also the Marciniak test setup is used. Up to now, the FLC determination was performed with failed specimens and an one-directional intersection line method or by manually analyzing the estimated strains before cracking. Both methods determine the failure by considering the occurrence of cracking and do not consider the possibility of time continuous recording of the Nakajima test. Consequently forming limit curves which have been evaluated in such way are often “laboratory dependent” and deviate for identical materials significantly. This paper presents an algorithm for a fully automatic and time-dependent determination of the beginning plastic instability based on physical effects. The algorithm is based on the evaluation of the strain distribution based on the displacement field which is evaluated by optical measurement and treated as a mesh of a finite element calculation. The critical deformation states are then defined by 2D-consideration of the strain distribution and their time derivates using a numerical evaluation procedure for detecting the beginning of the localization. The effectiveness of the proposed algorithm will be presented for different materials used for the Numisheet’08 Benchmark-1 with Nakajima test.