Effect Of Cluster Size Research Articles

Effect of the size of Cu clusters on selectivity and activity of acetylene selective hydrogenation

In order to probe into the size effect of Cu catalyst on the selectivity and activity of ethylene formation in acetylene selective hydrogenation, different sizes of Cu catalysts including Cu13, Cu38, Cu55 clusters and the periodic Cu(111) surface have been employed to systematically investigate the selective hydrogenation of C2H2 using density functional theory calculations. The results show that the adsorption ability of C2H2 is stronger than that of C2H4 on different sizes of Cu catalysts, which is in favor of C2H2 activation and hydrogenation. On Cu13 and Cu38 clusters, C2H2 easily undergoes over-hydrogenation to form ethane via CHCH2 and CHCH3 intermediates, namely, both clusters exhibit a poor selectivity towards C2H4 formation. However, on Cu55 cluster, C2H2 is easily hydrogenated to form C2H4via CHCH2 intermediate, and C2H4 prefers desorption over its hydrogenation, suggesting that Cu55 cluster exhibits a good selectivity towards C2H4 formation. Further, the periodic Cu(111) surface regarded as the large Cu particle sizes has the same results with Cu55 cluster. Therefore, among different sizes of Cu cluster, the size of Cu cluster affects the preferred pathway of C2H2 selective hydrogenation, and alters the selectivity towards C2H4 formation; moreover, beginning with Cu55 cluster, Cu cluster is beneficial to C2H2 hydrogenation to C2H4. The activity of C2H4 formation follows the order of Cu(111) > Cu38> Cu55 >> Cu13, which corresponds to the d-band center of these catalysts. The identifications about the relationship of the intrinsic selectivity and activity with cluster size effect would provide a clue for designing highly-efficient Cu-based catalysts in C2H2 hydrogenation to C2H4.

The Vibronic Theory of Size Effects in CO Oxidation by Gold Nanocatalysts

A theoretical model, based on the vibronic theory of catalysis, has been developed for the CO oxidation reaction catalyzed by gold nanoparticles. The charge fraction transferred between the catalyst and the adsorbed CO molecule depends upon the relative positions of the size-dependent Fermi level of the cluster and the energy levels of the molecular orbitals of CO adsorbed onto the cluster. The charge transferred from the nanocluster to the adsorbed CO molecule increases the absolute values of forces deforming the molecule chemical bond and force constants defining the curvature of potential for nuclear oscillation leading to the decrease in activation energy for CO oxidation. The application of vibronic and jellium theories to CO oxidation provides an explanation of the observed cluster size effects. The relative locations of electronic energy levels of a gold cluster and a CO molecule before and after the adsorption onto the cluster surface

Direct numerical simulation of evaporation in a biporous media

Biporous media having clusters of size range 300 - 425 μm, 425 - 600 μm, > 600 μm have been sintered at 950 °C, 180 min using gas atomized spherical particles (D50 of 90 microns) of pure copper in reducing atmosphere of pure hydrogen gas. MicroCT scan of biporous samples have been performed to and then images have been reconstructed to 3D CAD models, which further have been discretised into tetrahedral mesh using image processing and reconstruction software Avizo Fire 8.0. Direct numerical simulations have been performed to obtain Evaporative heat transfer coefficient (EHTC) over the surface of these biporous clusters. The transient evaporation phenomena and effect of cluster size on evaporation has been investigated in this paper. These results have been compared with the experimental results available in literature for evaporative heat transfer coefficient for biporous media.

Investigation of solvation of iron nanoclusters in ionic liquid 1-butyl-1,1,1-trimethylammonium methane sulfonate using molecular dynamics simulations: Effect of cluster size at different temperatures

The systems composed of metal nanoclusters in ionic liquids are relevant for applications in lubrication, electrochemical devices, catalysis, and chemical processes. The mechanism of solvation and interactions of these systems are not understood at present. In this work, we have simulated iron nanoclusters with different sizes in ionic liquid 1-butyl-1,1,1-trimethylammonium methane sulfonate [N1114][C1SO3] at two temperatures (300 and 500K) and at atmospheric pressure. We have investigated the effects of cluster size and the temperature on some of the thermodynamics, structural and dynamical properties of the systems. Our results also show that the absolute value of solvation energy increases as the nanocluster size increases. Also the absolute solvation energy increases as the temperature increases. It is also shown that the effect of the cluster size is much more than the effect of the temperature. Our structural investigations indicate at least two shells (a double layer) around the nanocluster and the anions are closer to the cluster surface than the cations. The self-diffusion coefficients of cations, anions, and iron clusters have been also presented and discussed in this work.

Copper Cluster Size Effect in Methanol Synthesis from CO2

Size-selected Cun catalysts (n = 3, 4, 20) were synthesized on Al2O3 thin films using mass-selected cluster deposition. A systematic study of size and support effects was carried out for CO2 hydrogenation at atmospheric pressure using a combination of in situ grazing incidence X-ray absorption spectroscopy, catalytic activity measurement, and first-principles calculations. The catalytic activity for methanol synthesis is found to strongly vary as a function of the cluster size; the Cu4/Al2O3 catalyst shows the highest turnover rate for CH3OH production. With only one atom less than Cu4, Cu3 showed less than 50% activity. Density functional theory calculations predict that the activities of the gas-phase Cu clusters increase as the cluster size decreases; however, the stronger charge transfer interaction with Al2O3 support for Cu3 than for Cu4 leads to remarkably reduced binding strength between the adsorbed intermediates and supported Cu3, which subsequently results in a less favorable energetic pathway t...

Insight into size dependence of C2 oxygenate synthesis from syngas on Cu cluster: The effect of cluster size on the selectivity

Size dependence of C2 oxygenate formation from syngas on Cu cluster has been investigated to qualitatively probe into the effect of Cu cluster size on the selectivity of C2 oxygenates, which includes two key steps: CHx and C2 oxygenate formations; Cu13, Cu38 and Cu55 clusters have been employed to model different sizes of Cu cluster. Here, density functional theory method has been performed. Our results show that the adsorption ability of the species involving in C2 oxygenate formation decreases with the increasing of Cu cluster size; Cu cluster size significantly affects the dominant existence forms of CHx(x=1–3) species and C2 oxygenates. Among three Cu clusters, Cu13 cluster exhibits the highest selectivity toward C2 oxygenates compared to other two clusters, suggesting that Cu cluster size can affect the selectivity toward C2 oxygenates, moreover, the smaller Cu cluster size is, the higher the selectivity of C2 oxygenates is. That is probably related to the high concentration of low-coordinated defect sites on small size Cu cluster, which results in the higher activity and selectivity toward C2 oxygenates. The identification of higher intrinsic selectivity of C2 oxygenates, active sites, and stronger cluster size effect would be valuable for developing more efficient and stable Cu catalyst with higher selectivity toward C2 oxygenate in syngas conversion.

Cluster Size Effects in Ethylene Hydrogenation over Palladium

Density functional theory calculations are used to investigate ethylene hydrogenation over palladium clusters in the range from Pd13 to Pd116. A comparison is made to single crystal surfaces, which exemplifies several novel aspects of clusters. We find that the adsorption energies are always higher for the clusters, even if the comparison is made to adsorption on stepped surfaces in the low-coverage regime. Clusters are found to accommodate higher adsorbate coverages than extended surfaces. The saturation coverage for Pd13 is unity, whereas it is 0.33 on Pd(111). The activation energies for hydrogenation of C2H4 to C2H5 over Pd38 are clearly different from Pd(111) and Pd(211), which stresses the limitation of extended surfaces as models for nanoparticles.

Cluster Lifetime Analysis for Cooperative Beamforming in Wireless Sensor Networks

Cooperative multiple input multiple outputs (MIMO) or its variation cooperative multiple input single outputs (MISO) is becoming a potential technique to minimize the energy consumption and prolong lifetime in wireless sensor networks. For cluster based wireless sensor networks, cluster lifetime for cooperative beamforming (CBF) based cooperative MISO scheme is studied in this paper.We first establish the energy model of a cluster with cooperative MISO scheme based on CBF. Based on the energy consumption model, the effects of cluster size and distance between cluster and sink node on the performance of cluster lifetime are discussed, an joint optimization to maximize cluster lifetime by finding the optimal modulation parameter and number of cooperative nodes is proposed. Numerical results show that CBF based cooperative MISO scheme can achieve longer cluster lifetime compare with STBC and the joint optimization can further improve the cluster lifetime.

Electrocatalysis by Mass-Selected Ptn Clusters.

Mass-selected Ptn+ ion deposition in ultrahigh vacuum (UHV) was used to prepare a series of size-selected electrodes with Ptn (n ≤ 14) clusters supported on either glassy carbon (GC) or indium tin oxide (ITO). After characterization of the physical properties of the electrodes in UHV, an in situ method was used to study electrocatalytic activity for the oxygen reduction and ethanol oxidation reactions, without significant air exposure. For each reaction studied, there are similarities between the catalytic properties of Ptn-containing electrodes and those of nanoparticulate or bulk Pt electrodes, but there are also important differences that provide mechanistic insights. For all systems, strong cluster size effects were observed. For comparison, select experiments were done under identical conditions but with the Ptn electrodes exposed to air prior to electrochemical studies, resulting in strong modification/suppression of catalytic activity due to adventitious contaminants. For ethanol oxidation at Ptn/ITO, activity varies with size nonmonotonically, by more than an order of magnitude. The sharp size dependence persists during at least 30 to 40 cycles through the Pt redox potential, indicating that processes that would tend to broaden the size distribution are not efficient. All but the least active sizes are substantially more active per mass of Pt, than Pt nanoparticles under the same conditions. The oscillatory dependence of activity on size is anticorrelated with the binding energy of the Pt 4d core level, demonstrating that activity is controlled by the electronic structure of the supported clusters. For oxygen reduction at Ptn/ITO, the branching between water and hydrogen peroxide production is strongly dependent on cluster size, with small clusters selectively producing peroxide with high activity. The selectivity appears to be related to the size of the active site, with no obvious correlation to Pt electronic properties. The most unusual effect seen was for Ptn/GC, studied under acid conditions appropriate to oxygen reduction. Pt7 and a few other cluster sizes show "normal" oxygen reduction activity, similar to what is measured for Pt nanoparticles on GC under the same conditions. Many of the small clusters, however, are found to catalyze highly efficient oxidation, by water, of the glassy carbon support, with essentially no overpotential. The high activity for carbon oxidation for many Ptn/GC electrodes and the absence of significant carbon oxidation for a GC electrode with Pt nanoparticles raise the question of whether small Pt clusters may be responsible for much of the corrosion observed in Pt/carbon electrodes. This system provides another example where activity for oxidation catalysis is anticorrelated with the Pt core level binding energies, indicating that it is electronic, rather than geometric, structure that limits activity.

Effects of ligand species and cluster size of biomolecule-protected Au nanoclusters on eff iciency of singlet-oxygen generation

Thiolate-protected Au25 nanoclusters (NCs) have been shown to be efficient 1O2 photosensitizers. The 1O2-generation efficiency of thiolate-protected Au NCs is expected to depend on the thiolate ligand species and size of the gold clusters. In the present study, Au25(glutathione)18 nanoclusters (Au25(SG)18 NCs) and bovine-serum-albumin (BSA)-protected Au25 nanoclusters (BSA–Au25 NCs) were synthesized to investigate the effect of different thiolate ligands on the 1O2 generation. The efficiency of 1O2 generation by the Au25 NCs that were photo-excited at 532nm was evaluated with methotrexate as a chemical probe. The effect of Au NC size on the 1O2-generation efficiency of thiolate-protected Au18 and Au25 NCs was also investigated. The 1O2-generation efficiency of BSA–Au25 NCs was higher than that of Au25(SG)18 NCs. The long lifetime of the electronic excitations and the high-photo-stability were key factors facilitating the formation of 1O2 in BSA–Au25 NCs. The effect of Au NC size on the 1O2-generation efficiency of thiolate-protected Au NCs, Aun(SR)m, decreased in the following order: Au25(SR)18>Au18(SR)14.

A practical Bayesian stepped wedge design for community-based cluster-randomized clinical trials: The British Columbia Telehealth Trial.

Many clinical trial designs are impractical for community-based clinical intervention trials. Stepped wedge trial designs provide practical advantages, but few descriptions exist of their clinical implementational features, statistical design efficiencies, and limitations. Enhance efficiency of stepped wedge trial designs by evaluating the impact of design characteristics on statistical power for the British Columbia Telehealth Trial. The British Columbia Telehealth Trial is a community-based, cluster-randomized, controlled clinical trial in rural and urban British Columbia. To determine the effect of an Internet-based telehealth intervention on healthcare utilization, 1000 subjects with an existing diagnosis of congestive heart failure or type 2 diabetes will be enrolled from 50 clinical practices. Hospital utilization is measured using a composite of disease-specific hospital admissions and emergency visits. The intervention comprises online telehealth data collection and counseling provided to support a disease-specific action plan developed by the primary care provider. The planned intervention is sequentially introduced across all participating practices. We adopt a fully Bayesian, Markov chain Monte Carlo-driven statistical approach, wherein we use simulation to determine the effect of cluster size, sample size, and crossover interval choice on type I error and power to evaluate differences in hospital utilization. For our Bayesian stepped wedge trial design, simulations suggest moderate decreases in power when crossover intervals from control to intervention are reduced from every 3 to 2 weeks, and dramatic decreases in power as the numbers of clusters decrease. Power and type I error performance were not notably affected by the addition of nonzero cluster effects or a temporal trend in hospitalization intensity. Stepped wedge trial designs that intervene in small clusters across longer periods can provide enhanced power to evaluate comparative effectiveness, while offering practical implementation advantages in geographic stratification, temporal change, use of existing data, and resource distribution. Current population estimates were used; however, models may not reflect actual event rates during the trial. In addition, temporal or spatial heterogeneity can bias treatment effect estimates.

Size-, electric-field-, and frequency-dependent third-order nonlinear optical properties of hydrogenated silicon nanoclusters.

We investigated the electronic properties and second hyperpolarizabilities of hydrogenated silicon nanoclusters (H-SiNCs) by using the density functional theory method. The effects of cluster size, external electric field and incident frequency on the second hyperpolarizability were also examined, respectively. We found that small H-SiNCs exhibit large second hyperpolarizability. With the increase of the number of silicon atoms in H-SiNCs, the frontier molecular orbital energy gap decreases, attributed to the enhancement of the second hyperpolarizability. Interestingly, we also found the electric-field-induced gigantic enhancement of the second hyperpolarizability for H-SiNCs due to the change of electron density distributions. In addition, our results demonstrate a significant dependence on the frequency of incident light.

A Cluster-Size Averaging Model for Strongly Discontinuous Percolation

We propose a network percolation model, called cut-off model, which exhibits strongly discontinuous transition by an averaging effect of cluster sizes. In this model, a randomly selected bond is added if the size of the cluster formed by the bond is less than a times of the mean cluster size. It is shown that the model is strongly discontinuous when a is a finite constant.

Ab initio calculations of optical properties of silver clusters: cross-over from molecular to nanoscale behavior

Electronic and optical properties of silver clusters were calculated using two different \textit{ab initio} approaches: 1) based on all-electron full-potential linearized-augmented plane-wave method and 2) local basis function pseudopotential approach. Agreement is found between the two methods for small and intermediate sized clusters for which the former method is limited due to its all-electron formulation. The latter, due to non-periodic boundary conditions, is the more natural approach to simulate small clusters. The effect of cluster size is then explored using the local basis function approach. We find that as the cluster size increases, the electronic structure undergoes a transition from molecular behavior to nanoparticle behavior at a cluster size of 140 atoms (diameter $\sim 1.7$\,nm). Above this cluster size the step-like electronic structure, evident as several features in the imaginary part of the polarizability of all clusters smaller than Ag$_\mathrm{147}$, gives way to a dominant plasmon peak localized at wavelengths 350\,nm$\le\lambda\le$ 600\,nm. It is, thus, at this length-scale that the conduction electrons' collective oscillations that are responsible for plasmonic resonances begin to dominate the opto-electronic properties of silver nanoclusters.

Power to Detect Intervention Effects on Ensembles of Social Networks

The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention effect using the hierarchical latent space model, an important subfamily of HNMs. We derive basic convergence results and asymptotic bounds on power, showing that standard error for the treatment effect is inversely proportional to the product of the number of ties and the number of networks; a result rather different from the usual effect of cluster size in hierarchical linear models, for example. We explore these results with a simulation study and suggest a tentative approach to power for practical applications.

Modeling of Transition Metal Color Centers in Diamond

ABSTRACTDiamond stands out among single-photon sources due to an intrinsically large band gap, photo-stable emission, room-temperature operation, short excited state lifetimes, and the ability to host hundreds of different color centers. Currently, most of these centers are active in the optical spectrum, but a single-photon source in the infrared would represent a significant advancement. In pursuit of this end, a number of different transition metal atoms have been studied as dopants in the diamond lattice via the GAMESS (General Atomic Molecular and Electronic Structure System) cluster calculation package. The importance of cluster size and electron correlation effects is considered, and excitation energies have been calculated via time-dependent density functional theory.

A DFT study of arsine adsorption on palladium doped graphene: Effects of palladium cluster size

In this study, we have investigated the size effects of palladium (Pd) doped single-vacancy defective graphene (SDG) surface to the adsorption of AsH3 and its dehydrogenated products on Pd using density functional theory calculations. Here, Pd cluster binding study revealed that Pd6 nanocluster bound strongest to the SDG surface, while adsorption of AsHx (x=0–3) on the most stable Pdn doped SDG showed that dehydrogenated arsine compounds adsorbed onto the surface stronger than the pristine AsH3 molecule. Charge analysis revealed that considerable amount of charge migration from Pd to dehydrogenated arsine molecules after adsorption may constitute strong adsorption for dehydrogenated arsine. In addition, study of thermodynamic pathways of AsH3 dehydrogenation on Pdn doped SDG adsorbents indicated that Pd cluster doping on SDG adsorbent tends to be thermodynamically favorable for AsH3 decomposition than the single-Pd atom doped SDG. Hence, our study has indicated that Pd6 clusters doped SDG is more advantageous as adsorbent material for AsH3 removal.

Dynamics and Thermodynamics of Pd–PdO Phase Transitions: Effects of Pd Cluster Size and Kinetic Implications for Catalytic Methane Combustion

Methane oxidation rates uncorrupted by nonchemical effects of transport, taken together with stoichiometric oxygen uptake (oxidation cycle) and evolution (decomposition cycle) data, are used to establish for the first time a set of conditions required for true thermodynamic equilibrium during metal-to-oxide interconversions in small Pd clusters (1.8–8.8 nm). These conditions allow us to assess the intrinsic thermodynamics of small Pd clusters and their catalytic effects in CH4 oxidation. PdO decomposition in the absence of CH4 deviates from equilibrium, as this step is limited by the nucleation of an oxygen vacancy ensemble on oxide domains. The nucleation bottleneck is removed by CH4 during its catalytic sojourns, when CH4 pressure and the related rates exceed a critical value, because CH4 effectively removes the oxygen adatoms near an oxygen vacancy site via C–H bond activation on an oxygen–oxygen vacancy site pair that converts the O* adatom to a hydroxyl intermediate, which desorbs as H2O in sequentia...

Double-observer evaluation of pronghorn aerial line-transect surveys

Context Distance sampling is used to estimate abundance for several taxa, including pronghorn (Antilocapra americana). Comparisons between population estimates derived from quadrat sampling and distance sampling suggest that distance sampling underestimates pronghorn density, likely owing to violations of the critical assumption of distance sampling that all pronghorn within the innermost distance band (A band; nearest to the aircraft) are detected. Aims We sought to rigorously test the assumption that all pronghorn clusters are detected within the innermost distance band by applying a double-observer approach to an established pronghorn aerial-survey protocol. Additionally, we evaluated potential effects of cluster size, landscape composition and seat position (front seat versus rear) on the probability of detection. Methods We conducted aerial line-transect distance-sampling surveys using independent, paired observers and modelled the probability of detection with mark–recapture distance-sampling (MRDS) analysis techniques that explicitly estimate the probability of detection for pronghorn clusters in the innermost distance band. We compared density estimates produced by the MRDS analysis with those produced by multiple-covariate distance sampling (MCDS), a method that assumes complete detection for clusters on the transect line. Key results We identified violations of the assumption that all clusters within the innermost distance band were detected, which would contribute to proportional biases in density estimates for analysis techniques that assume complete detection. The frequency of missed clusters was modest from the front-seat position, with 45 of the 47 (96%) clusters in the A band detected. In contrast, the frequency of missed clusters was more substantial for the rear position, from which 37 of 47 (79%) clusters in the A band were detected. Further, our analysis showed that cluster size and landscape composition were important factors for pronghorn sightability. Conclusions When implementing standard survey methodologies, pronghorn aerial-line transect surveys underestimated population densities. A double-observer survey configuration allowed us to quantify and correct for the bias caused by the failure of observers to detect all pronghorn clusters within the innermost distance band. Implications Population monitoring programs should incorporate double-observer validation trials to quantify the extent of bias owing to undetected clusters within the innermost distance band realised under typical survey conditions. Wildlife managers can improve the precision of pronghorn aerial line-transect surveys by incorporating cluster size and measures of landscape composition and complexity into detection models without incurring additional survey costs.

Effects of Cluster Sizes on Variance Components in Two-Stage Sampling

Abstract Determining sample sizes in multistage samples requires variance components for each stage of selection. The relative sizes of the variance components in a cluster sample are dramatically affected by how much the clusters vary in size, by the type of sample design, and by the form of estimator used. Measures of the homogeneity of survey variables within clusters are related to the variance components and affect the numbers of sample units that should be selected at each stage to achieve the desired precision levels. Measures of homogeneity can be estimated using standard software for random-effects models but the model-based intracluster correlations may need to be transformed to be appropriate for use with the sample design. We illustrate these points and implications for sample size calculation for two-stage sample designs using a realistic population derived from household surveys and the decennial census in the U.S.