Characterisation of the adsorption sites of hydrogen on Pt/C fuel cell catalysts

A key component of a hydrogen fuel cell is a catalyst to dissociate dihydrogen to hydrogen atoms. In the present study, the adsorption of hydrogen on Pt/C fuel cell catalysts has been investigated by inelastic neutron scattering spectroscopy.

Monitoring a clean Pt(50%)/C catalyst with low energy neutron spectroscopy, after exposure to dihydrogen at 20 K, as it was heated to room temperature, showed three distinct temperature regimes: (i) a decrease in intensity from 10 to 60 K, (ii) a rise to a maximum between 60 and 120 K and then (iii) a slow fall-off towards room temperature. We assign the three regions as: (i) desorption of physisorbed dihydrogen, (ii) dissociation of dihydrogen to give an adsorbed layer and (iii) damping of the response by an increasing Debye–Waller factor.

The vibrational INS spectra of a series of Pt/C catalysts prepared under varying conditions were similar indicating that the same types of site are common to all the catalysts, although the relative proportions of each site are sample dependent. Features at 520, 950 and part of the intensity at 1300 cm⁻¹ are assigned to hydrogen on (1 1 1) faces, in good agreement with single crystal data. The mode at 640 cm⁻¹ is assigned as the doubly degenerate asymmetric stretch of Pt(1 0 0) faces with the symmetric stretch near 550 cm⁻¹.

We assign the bending mode of the on-top site to the feature at 470 cm⁻¹. The Pt–H stretch mode was observed at 2079 cm⁻¹. This is a significant result: this is the first time that hydrogen on the on-top sites has been observed on nanosized platinum particles supported on high surface area carbon black. The width of the INS peak is surprisingly large and may give additional information on the type and relative proportions of the crystallographic faces present on the catalyst particles.     

Cholesterol synthesis and esterification in isolated enterocytes: Regulation by cholesterol and cholestyramine feeding

The purpose of the present study was to investigate the physiological control of the main regulatory enzymes of cholesterol metabolism in isolated enterocytes obtained from chick duodenum, jejunum and ileum. Cholesterol feeding resulted in an inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase and mevalonate 5-pyrophosphate decarboxylase, while cholestyramine feeding increased reductase activity in all the regions studied and decarboxylase activity only in duodenum. Cholesterol feeding markedly increased acyl-CoA:cholesterol acyltransferase, but the effects of cholestyramine were less clear. The effects on transferase activity cannot be due to differences in the availability of acyl-CoA as exogenous substrate as no significant differences were found in acyl-CoA hydrolase activity after any of the dietary treatments. The effects of cholesterol feeding were related to changes in the cholesterol content of epithelial cells, whereas in the case of cholestyramine this relationship was less apparent.     

Combination of computational prescreening and experimental library construction can accelerate enzyme optimization by directed evolution

Chiral compounds can be produced efficiently by using biocatalysts. However, wild-type enzymes often do not meet the requirements of a production process, making optimization by rational design or directed evolution necessary. Here, we studied the lipase-catalyzed hydrolysis of the model substrate 1-(2-naphthyl)ethyl acetate both theoretically and experimentally. We found that a computational equivalent of alanine scanning mutagenesis based on QM/MM methodology can be applied to identify amino acid positions important for the activity of the enzyme. The theoretical results are consistent with concomitant experimental work using complete saturation mutagenesis and high-throughput screening of the target biocatalyst, a lipase from Bacillus subtilis. Both QM/MM-based calculations and molecular biology experiments identify histidine 76 as a residue that strongly affects the catalytic activity. The experiments demonstrate its important influence on enantioselectivity.     

Radial density distribution of fractal clusters

The radial density distributions of fractal clusters generated in both DLCA and RLCA conditions by Monte-Carlo off-lattice cluster-cluster aggregation have been investigated. It has been computed by averaging a large number of clusters of same mass to form an average cluster, which is then considered as spherically symmetric. It is found that the radial density distribution, calculated using the mass center of the cluster as the center point, does not follow the fractal scaling, as sometimes assumed in the literature. An empirical model has been proposed to describe the dependence of the radial density distribution on the number of particles in the cluster. The obtained radial density distribution is used to compute permeability profile of the fractal cluster using several literature models, which is then applied to estimate the cluster hydrodynamic radius, R_h, by considering the cluster as a porous permeable object and using the solution of Brinkman equations for the fluid flow inside the cluster. The so obtained R_h values are compared to those in the literature, computed using the Kirkwood-Riseman (KR) theory. It has been found that, among the five permeability models examined, only the model proposed by Davis (Proceedings of the Institution of Mechanical Engineers Part B 1, 185) provides results in good agreement with those obtained using the KR model. Furthermore, it has been verified that the R_h values are insensitive to the model used for the density distribution.     

Prediction of Experimental Methanol Decomposition Rates on Platinum from First Principles

A microkinetic model for methanol decomposition on platinum is presented. The model incorporates competitive decomposition pathways, beginning with both O–H and C–H bond scission in methanol, and uses results from density functional theory (DFT) calculations [Greeley and Mavrikakis, J. Am. Chem. Soc. 124 (2002) 7193, Greeley and Mavrikakis, J. Am. Chem. Soc. 126 (2004) 3910]. Results from reaction kinetics experiments show that the rate of H₂ production increases with increasing temperature and methanol concentration in the feed and is only nominally affected by the presence of CO or H₂ with methanol. The model, based on the values of binding energies, pre-exponential factors and activation energy barriers derived from first principles calculations, accurately predicts experimental reaction rates and orders. The model also gives insight into the most favorable reaction pathway, the rate-limiting step, the apparent activation energy, coverages, and the effects of pressure. It is found that the pathway beginning with the C–H bond scission (CH₃OH→H₂COH→HCOH→CO) is dominant compared with the path beginning with O–H bond scission. The cleavage of the first C–H bond in methanol is the rate-controlling step. The surface is highly poisoned by CO, whereas COH appears to be a spectator species.     

Hybrid materials based on metal oxides and poly(organophosphazenes)

In this paper the sol-gel preparation of hybrid materials made of metal oxide and polytorganophosphazenel components is described. The main problem focused on during this research was to avoid phase separation in order to get homogeneous materials. This problem was pursued looking at the formation of genuine chemical bonds between the exploited polyphosphazenes and the inorganic composite networks. Investigations on the thermal, mechanical, and electroconductive properties of the synthesized, phosphazene-containing composite materials showed that these matrices presented improved mechanical and thermal features with respect to those of the original phosphazene macromolecule, while the ionic conductivities of the prepared molecular hybrids doped with lithium or silver trillate are of the same order of magnitude as those measured for the neat, original phosphazene substrate.Presented at the Ist Italian Workshop on Cyclo- and Polytphosphazenel Materials. February 15–16, 1996. at the CNR Research Area in Padova, Italy.     

HEGM: A hierarchical elastic graph matching for hand gesture recognition

A hierarchical scheme for elastic graph matching applied to hand gesture recognition is proposed. The proposed algorithm exploits the relative discriminatory capabilities of visual features scattered on the images, assigning the corresponding weights to each feature. A boosting algorithm is used to determine the structure of the hierarchy of a given graph. The graph is expressed by annotating the nodes of interest over the target object to form a bunch graph. Three annotation techniques, manual, semi-automatic, and automatic annotation are used to determine the position of the nodes. The scheme and the annotation approaches are applied to explore the hand gesture recognition performance. A number of filter banks are applied to hand gestures images to investigate the effect of using different feature representation approaches. Experimental results show that the hierarchical elastic graph matching (HEGM) approach classified the hand posture with a gesture recognition accuracy of 99.85% when visual features were extracted by utilizing the Histogram of Oriented Gradient (HOG) representation. The results also provide the performance measures from the aspect of recognition accuracy to matching benefits, node positions correlation and consistency on three annotation approaches, showing that the semi-automatic annotation method is more efficient and accurate than the other two methods.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

Gravity optimised particle filter for hand tracking

This paper presents a gravity optimised particle filter (GOPF) where the magnitude of the gravitational force for every particle is proportional to its weight. GOPF attracts nearby particles and replicates new particles as if moving the particles towards the peak of the likelihood distribution, improving the sampling efficiency. GOPF is incorporated into a technique for hand features tracking. A fast approach to hand features detection and labelling using convexity defects is also presented. Experimental results show that GOPF outperforms the standard particle filter and its variants, as well as state-of-the-art CamShift guided particle filter using a significantly reduced number of particles.     

A GPU-based parallel method for evolutionary tree construction

Evolutionary trees are widely applied in various applications to show the inferred evolutionary relationships among species or entities. Neighbor-Joining is one solution for data-intensive and time-consuming evolutionary tree construction, with polynomial time complexity. However, its performance becomes poorer with the growth of massive datasets. Graphics Processing Units (GPUs) have brought about new opportunities for these time-consuming applications. Based on its high efficiency, a GPU-based parallel Neighbor-Joining method is proposed, and two efficient parallel mechanisms, data segmentation with asynchronous processing and the minimal chain model with bitonic sort, are put forward to speed up the processing. The experimental results show that an average speedup of 25.1 is achieved and even approximately 30 can be obtained with a sequence dataset ranging from 16,000 to 25,000. Moreover, the proposed parallel mechanisms can be effectively exploited in some other high performance applications.