OXIDATIVE COUPLING OF METHANE ON SUPERCONDUCTOR-TYPE CATALYTIC MATERIALS

Oxidative coupling of methane to higher hydrocarbons was investigated using alkali and rare earth cuprates such as YBa₂Cu₃O_7-x, La_1.8Ba_0.2CuO and La₂CuO₄. Oxygen and methane in helium were fed to the reactor in a cofeed mode. Approximately, 5 g of catalyst in powder form was placed in a quartz flow reactor in all experiments. Oxygen partial pressure was changed as a parameter (P₀ = 0.5 to 9.1 kPa) while keeping methane partial pressure and temperature constant at 18kPa and 1023 K respectively. Investigation of catalytic activity in terms of overall methane conversion and C₂ + (C₂H₄+C₂H₆) product selectivity indicated that higher conversions and lower selectivities were obtained as O₂ partial pressure was increased at a constant methane partial pressure of 8kPa. In comparing the performance of the two catalysts, La_1.8Ba_0.2CuO and La₂CuO₄; the selectivity results indicated a positive influence of incorporation of Ba into La₂CuO₄ structure. Similarly, selectivity values substantially increased teaching 86.3% at a reaction temperature of 1023 K and at P_CH4./P_O3, = 6 when La was replaced by Y and Ba.     

Stress calculations on diamond surfaces

Calculations were carried out to evaluate stresses for atoms located in the top several layers of the (100)-(1 × 1), (100)-(2 × 1) and (111)-(1 × 1) surfaces of diamond. Only equilibrated surfaces were taken into consideration in this investigation. Stress values in the direction perpendicular to the exposed surface vanish. In lateral directions, however, stresses have non-vanishing values, in general. For the (100) surfaces calculated stress values are anisotropic. While the (2 × 1) reconstructed surface is under compression in both directions, calculations for the unreconstructed (1 × 1) plane produced a compressive stress in one direction and a slight tension in the other. On the (111) surface, isotropic and relatively low compressive stress values were found. Present calculations indicate that atoms located only in a few top layers have lateral excess stresses which vanish very quickly for the atoms of interior layers as depart form the exposed surface.     

An ant colony optimization algorithm for load balancing in parallel machines with sequence-dependent setup times

This study introduces the problem of minimizing average relative percentage of imbalance (ARPI) with sequence-dependent setup times in a parallel-machine environment. A mathematical model that minimizes ARPI is proposed. Some heuristics, and two metaheuristics, an ant colony optimization algorithm and a genetic algorithm are developed and tested on various random data. The proposed ant colony optimization method outperforms heuristics and genetic algorithm. On the other hand, heuristics using the cumulative processing time obtain better results than heuristics using setup avoidance and a hybrid rule in assignment.     

Automatic expression spotting in videos

In this paper, we propose a novel solution for the problem of segmenting macro- and micro-expression frames (or retrieving the expression intervals) in video sequences, which is a prior step for many expression recognition algorithms. The proposed method exploits the non-rigid facial motion that occurs during facial expressions by capturing the optical strain corresponding to the elastic deformation of facial skin tissue. The method is capable of spotting both macro-expressions which are typically associated with expressed emotions and rapid micro- expressions which are typically associated with semi-suppressed macro-expressions. We test our algorithm on several datasets, including a newly released hour-long video with two subjects recorded in a natural setting that includes spontaneous facial expressions. We also report results on a dataset that contains 75 feigned macro-expressions and 37 feigned micro-expressions. We achieve over a 75% true positive rate with a 1% false positive rate for macro-expressions, and a nearly 80% true positive rate for spotting micro-expressions with a .3% false positive rate.     

Oxidative coupling of methane over NbO (p-type) and Nb2O5 (n-type) semiconductor materials

Oxidative coupling of methane to higher hydrocarbons was investigated using two types of semiconductor catalysts, NbO (p-type) and Nb₂O₅ (n-type) at 1 atm pressure. The ratio of methane partial pressure to oxygen partial pressure was changed from 2 to 112 and the temperature was kept at 1023 K in the experiments conducted in a cofeed mode. The results indicated a strong correlation between C₂₊ selectivity performance and the electronic properties of the catalyst in terms of p-vs. n-type conductivity. The p-type semiconductor catalyst, NbO, had a larger selectivity (e.g. 95.92%) over the n-type Nb₂O₅ catalyst (23.08%) both at the same methane conversion of 0.64%. Catalyst characterization via X-ray diffraction, TGA and reaction studies indicated that NbO was transformed to Nb₂O₅ during the course of the reaction which limits catalyst life.     

Plasmon-enhanced solar water splitting with metal oxide nanostructures: A brief overview of recent trends

In the last decade, the surface plasmon resonance-enhanced solar water splitting (SWS) has been actively investigated for improved hydrogen production. In this mini-review, we briefly introduce the mechanisms for plasmon-enhanced SWS and then review some representative studies related to these mechanisms. In addition, we also briefly discuss how metal oxide geometry affects the SWS activity in combined metal-semiconductor nanostructures. Finally, we summarize the recent discoveries and proposed a future vision for plasmon-enhanced SWS with metal oxide nanostructures.     

Prediction of Optimal Conditions of Hydrogenation Reaction Using the Likelihood Ranking Approach

The selection of experimental conditions leading to a reasonable yield is an important and essential element for the automated development of a synthesis plan and the subsequent synthesis of the target compound. The classical QSPR approach, requiring one-to-one correspondence between chemical structure and a target property, can be used for optimal reaction conditions prediction only on a limited scale when only one condition component (e.g., catalyst or solvent) is considered. However, a particular reaction can proceed under several different conditions. In this paper, we describe the Likelihood Ranking Model representing an artificial neural network that outputs a list of different conditions ranked according to their suitability to a given chemical transformation. Benchmarking calculations demonstrated that our model outperformed some popular approaches to the theoretical assessment of reaction conditions, such as k Nearest Neighbors, and a recurrent artificial neural network performance prediction of condition components (reagents, solvents, catalysts, and temperature). The ability of the Likelihood Ranking model trained on a hydrogenation reactions dataset, (~42,000 reactions) from Reaxys^® database, to propose conditions that led to the desired product was validated experimentally on a set of three reactions with rich selectivity issues.     

Statische und dynamische Berechnung von Turbinenfundamenten aus Stahlbeton

Structural and Dynamic Analysis of Turbine Foundations in Reinforced Concrete This paper presents the state of art of layout and analysis of turbine foundations in reinforced concrete from the civil engineering point of view. Possible foundation types, loads to be taken into account, and requirements to be met are discussed in detail. Current analysis methods for the determination of eigenvalues and dynamic amplitudes as well as the treatment of special cases in earthquake zones are described. Constructional aspects and characteristic data of realized gas and steam turbine foundations complete the paper.     

Etherification rates of 2‐methyl‐2‐butene and 2‐methyl‐1‐butene with ethanol for environmentally clean gasoline production

Etherification of C₅ reactive olefins available in light fluidized catalytic cracking (FCC) gasoline is an attractive way to decrease the olefins and to increase the octane number. The reactivities of 2‐methyl‐1‐butene (2M1B) and 2‐methyl‐2‐butene (2M2B) in the etherification reaction with ethanol catalysed by a strongly acidic macroreticular resin catalyst were investigated in a temperature range of 333–360 K using a liquid phase differential flow reactor. In the presence of excess alcohol, the apparent reaction orders of etherification reactions of isoamylenes were found to be 0.93 and 0.69 with respect to 2M1B and 2M2B concentrations, respectively. 2M1B was shown to be more reactive than 2M2B and its activation energy is also lower in the etherification reaction. It was also shown that diffusion resistances, especially in the macropores of the catalyst, may play an important role on the observed rates. © 1999 Society of Chemical Industry