Effect Of Cluster Size Research Articles

Effect of the RhnNin alloy cluster size on the catalytic performance of RhnNin/TiO2 in the conversion of syngas to ethanol

The direct conversion of syngas to ethanol on the RhnNin/TiO2 (n = 1, 2, 3, 4) catalyst has been investigated by using the density functional theory (DFT) and micro-kinetic methods, in order to elucidate the regulatory mechanism of RhnNin alloy cluster size-induced metal-support interaction on the catalytic performance of RhnNin/TiO2 in the ethanol synthesis. The results indicate that Rh1Ni1/TiO2 and Rh3Ni3/TiO2 can significantly enhance the conversion of CO and the formation of C–C bond and meanwhile inhibit the generation of methane. Rh1Ni1/TiO2 exhibits the highest ethanol production activity and relative selectivity. The electronic property analysis results suggest that Ni atoms on the alloy clusters and Ti and O atoms on the supports transfer the most charge to the Rh atoms on the Rh1Ni1/TiO2 catalyst, which displays the strongest Rh-Ni interaction on the alloy clusters as well as the strongest interaction between the alloy clusters and the TiO2 support, endowing Rh1Ni1/TiO2 with the highest catalytic activity. In addition, the Ab-initio molecular dynamics (AIMD) simulations at 525 K show that the Rh1Ni1/TiO2 catalyst has high thermal stability.

Phonotactic and morphonotactic influences on the (a)synchronicity of consonant clusters in Polish

A pilot speech production experiment combined articulatory data obtained using Electromagnetic Articulography (EMA), along with acoustic measures, to investigate the effects of cluster size (CC vs. CCC) and morpheme boundaries on consonant cluster synchronicity for five speakers of Polish. We found that being placed in a larger cluster leads to less synchronous productions of two-consonant sequences. We also found, surprisingly, greater synchronicity for clusters spanning a morpheme boundary than for the same cluster within a morpheme. Our findings may be interpreted from a listener-oriented perspective in which speech production is sensitive to perceptual considerations.

Effects of cluster size on trypophobic discomfort in children aged 4–9 years

It has been reported that strong discomfort associated with clusters of circles and holes (trypophobia), including lotus pod seeds, manifests in individuals as young as 4 or 5 years old. This study investigated how the size and number of circles within clusters affected discomfort levels in adults and in children aged 4–9 years. In Experiment 1, we confirmed that the remote experimental procedure could evoke discomfort when participants were presented with cluster images. The findings reveal that children as young as 4 or 5 years old consistently experienced discomfort when rating trypophobic images, even printed images rated in real time during video calls. In Experiment 2, we explored the impact of cluster size, considering both the size and number of circles, in a remote experiment. The results indicate that discomfort tended to increase with cluster size in both children and adults, with the effect becoming more pronounced with age.

In vitro mass propagation of Dendrocalamus asper (Giant bamboo) through direct organogenesis

Dendrocalamus asper (giant bamboo) is a clumping type of bamboo belonging to the Poaceae family. Due to its economic and environmental value, demand for this species has increased tremendously. Conventional propagation methods have limitations due to low seed viability and the lack of healthy clumps. Therefore, an in vitro mass propagation protocol was developed to provide healthy plants for large-scale plantations. Seeds were used as the explant and they were surface sterilized and cultured on MS medium free of growth regulators. Nodal segments taken from in vitro germinated seedlings were used for shoot initiation. The best medium for shoot induction (MS medium supplemented with 0.0–2.5 mg/L BAP), best medium for multiple shoot induction (MS medium supplemented with 0.0–5.0 mg/L BAP), effect of shoot cluster size (shoot clusters containing 1–4 shoots) and effect of physical state of the medium (semisolid and liquid media) on multiple shoot induction were determined using shoots per node, mean shoot length and mean number of leaves per shoot after 6 weeks of incubation. Elongated shoots were transferred into a rooting medium and the best medium for root induction (MS medium supplemented with 0.0–5.0 mg/L IBA and IAA) and effect of cluster size (shoot clusters containing 1–4 shoots) on rooting were determined using the number of roots and root length after 6 weeks of incubation. All the cultures were maintained under a 16-hour photoperiod. Well-developed plantlets were transferred to coir pellets and after four weeks transferred into different potting mixtures containing different combinations of sand, compost and coir dust. Unless otherwise mentioned there were at least twenty replicates in all treatments. The highest mean number of shoots per node (16.87±0.52), mean shoot length (4.12±0.27 cm) and mean number of leaves per shoot (4.80±0.33) were observed in the MS medium supplemented with 1.0 mg/L BAP. The MS medium supplemented with 2.0 mg/L BAP was the best for multiple shoot induction, shoot cluster with 3 shoots was the best cluster size and the liquid medium had a better effect on shoot multiplication. The half-strength MS medium supplemented with 2.0 mg/L IBA was the best for in vitro root induction with the highest mean number of roots (7.15±0.77) and a mean root length of 10.79±1.11 cm. Shoot clusters with 3 shoots was the best cluster size for root induction. A sand: compost: coir dust (1:1:1) mixture was the best potting mixture giving 100% survival. These findings provide a reliable micropropagation protocol for D. asper, which holds great promise for meeting the growing demand for bamboo resources and promoting sustainable bamboo cultivation.

A molecular beam study of CO oxidation on Pd clusters supported on alumina: the effect of cluster size.

The activity in CO oxidation of regular arrays of Pd clusters, in the size range of 5-180 atoms, supported on alumina has been studied by using a molecular beam method. The Pd clusters are grown on a nanostructured ultrathin alumina film on Ni3Al(111) providing a hexagonal array of clusters with a narrow size distribution. The steady state turnover frequency (TOF) is measured as a function of the mean cluster size. On average the TOF increases with size. Below about 20 atoms, the TOF increases rapidly and for larger clusters it grows slowly and reaches a value close to those obtained on bulk single crystals at 180 atoms. The size effect is explained by the smaller activity of Pd atoms in contact with the alumina support.

Leveraging transcriptomics-based approaches to enhance genomic prediction: integrating SNPs and gene networks for cotton fibre quality improvement.

Cultivated cotton plants are the world's largest source of natural fibre, where yield and quality are key traits for this renewable and biodegradable commodity. The Gossypium hirsutum cotton genome contains ~80K protein-coding genes, making precision breeding of complex traits a challenge. This study tested approaches to improving the genomic prediction (GP) accuracy of valuable cotton fibre traits to help accelerate precision breeding. With a biology-informed basis, a novel approach was tested for improving GP for key cotton fibre traits with transcriptomics of key time points during fibre development, namely, fibre cells undergoing primary, transition, and secondary wall development. Three test approaches included weighting of SNPs in DE genes overall, in target DE gene lists informed by gene annotation, and in a novel approach of gene co-expression network (GCN) clusters created with partial correlation and information theory (PCIT) as the prior information in GP models. The GCN clusters were nucleated with known genes for fibre biomechanics, i.e., fasciclin-like arabinogalactan proteins, and cluster size effects were evaluated. The most promising improvements in GP accuracy were achieved by using GCN clusters for cotton fibre elongation by 4.6%, and strength by 4.7%, where cluster sizes of two and three neighbours proved most effective. Furthermore, the improvements in GP were due to only a small number of SNPs, in the order of 30 per trait using the GCN cluster approach. Non-trait-specific biological time points, and genes, were found to have neutral effects, or even reduced GP accuracy for certain traits. As the GCN clusters were generated based on known genes for fibre biomechanics, additional candidate genes were identified for fibre elongation and strength. These results demonstrate that GCN clusters make a specific and unique contribution in improving the GP of cotton fibre traits. The findings also indicate that there is room for incorporating biology-based GCNs into GP models of genomic selection pipelines for cotton breeding to help improve precision breeding of target traits. The PCIT-GCN cluster approach may also hold potential application in other crops and trees for enhancing breeding of complex traits.

Comparative analysis of MapReduce and Apache Tez Performance in Multinode clusters with data compression

This article conducts a thorough comparative analysis of Apache Tez and MapReduce in the context of big data processing. It focuses on key performance metrics, scalability, and ease of use. The analysis begins with an overview of the architectural distinctions between the two frameworks, emphasizing their fundamental design principles. A detailed performance evaluation follows, considering factors such as execution time, resource utilization, and throughput across diverse workloads. The study explores scalability by examining how Apache Tez and MapReduce respond to increasing data volumes and computational demands. Cluster size effects, resource allocation strategies, and adaptability to dynamic workloads are scrutinized. Additionally, the article evaluates the frameworks' ease of use for developers and administrators, incorporating aspects like programming model simplicity, debugging capabilities, and system configurability. User experiences are gathered through surveys and practical use cases. The conclusions drawn from this analysis offer valuable insights for organizations and practitioners seeking suitable distributed computing frameworks. By addressing both performance and user experience, the article aims to provide a comprehensive perspective on the strengths and weaknesses of Apache Tez and MapReduce, assisting decision-makers in making informed choices for their big data processing requirements.

Unraveling the Molecular Dynamics of Glucose Oxidase Desorption Induced by Argon Cluster Collision.

The bombardment of a protein multilayer target by an energetic argon cluster ion beam enables protein transfer onto a collector in the vacuum while preserving their bioactivity (iBEAM method). In parallel to this new soft-landing variant, protein transfer in the gas phase is a prerequisite for their characterization by mass spectrometry. The successful transfer of bioactive lysozymes (14 kDa) by cluster-induced soft landing and its mechanistic explanation by molecular dynamics (MD) simulations have sparked an important inquiry: Can heavier biomolecules be desorbed while maintaining their tridimensional structure and hence their bioactivity? To address this question, we employed MD simulations using a reactive force field (ReaxFF). Specifically, the Ar cluster-induced desorption of glucose oxidase from either a gold substrate or a lysozyme underlayer was modeled using the LAMMPS code. First, the force field parameters were trained by computing the dissociation energetics of a series of organic molecules with ReaxFF and DFT, in order to realistically describe N-S and O-S interactions in the bombarded glucose oxidase molecule. Second, bombardment simulations investigated the effects of cluster size (ranging from 1000 to 10000 Ar atoms) and kinetic energy (1.5 and 3.0 eV/atom) on the structural features and energetics of the desorbing glucose oxidase. Our results show that large argon clusters (≥7000) are needed to desorb glucose oxidase from a gold surface, yet protein fragmentation and/or pronounced denaturation occur. However, the transfer of structurally preserved glucose oxidase in the gas phase is predicted by the simulations when an organic layer is used as a substrate.

Study of the Effect of ZnO Functionalization on the Performance of a Fully Formulated Engine Oil.

The automotive sector is demanding higher specifications to achieve maximum efficiency; in this sense a new generation of lubricants with higher thermo-oxidative stability and superior tribological properties is being explored. The formulation of nanolubricants based on the nature of different nanomaterials is one of the most recent approaches, with several gaps to cover, such as dispersion stability, related to the compatibility of proposed nanomaterials with conventional additives and baseoils used in lubricant formulation. This study evaluated the effect of ZnO nanomaterial dispersed in a commercial engine oil using two different approaches; the use of surfactant and nanomaterial surface functionalization to promote higher stability and lower cluster size. Experimental evidence shows a synergetic effect between the tribological protection mechanism and the antioxidant properties in the lubricant. The effect of nanoparticle cluster size, functionalization level, and nanomaterial content are presented.

Density Functional Treatment of Photoionization of Sodium Clusters: Effects of Cluster Size and Exchange–Correlation Framework

The ground state and photoionization properties of Nax (x = 20, 40, and 92) clusters are investigated using a method based on density functional theory (DFT) in a spherical jellium frame. Two different exchange–correlation treatments with the Gunnarsson–Lundqvist parametrization are used: (i) the electron self-interaction correction (SIC) scheme and (ii) the van Leeuwen–Baerends (LB94) scheme based on the gradient of the electron density. The shapes of the mean-field potentials and bound state properties, obtained in the two schemes, qualitatively agree, but differ in the details. The effect of the schemes on the photoionization dynamics, calculated in linear response time-dependent DFT is compared, in which the broader features are found to be universal. The general similarity of the results in SIC and LB94 demonstrates the reliability of DFT treatments. The study further elucidates the evolution of the ground state and ionization description as a function of the cluster size.

Prediction of the optical properties of TiO2 suspension by coupling the classical particle agglomeration model with the discrete dipole approximation algorithm and experimental verification

Nanofluids are widely used in the field of energy and environment. However, the optical properties of such multiphase suspension are quite complex. Even for the well-studied TiO2 suspension, theoretical investigation of its optical parameters is quite rare, which remarkably restricts the extension of their application especially in the field of solar energy and optofluidics. Therefore, in this paper, the optical properties of TiO2 suspension were studied by coupling the classical particle agglomeration model and the discrete dipole approximation algorithm. The absorption and scattering coefficients of TiO2 aqueous suspension have been calculated and verified by experimental results. The effects of cluster compactness, size and other factors on the phase function were analyzed. Our work can also provide a reference for the study of optical properties of other nanofluids.

Coordination-number-determined activity of copper catalyst in water-gas shift reaction

The water–gas shift reaction (WGSR) is of great significance in industrial hydrogen production. In this paper, Cun/TiO2(n = 1,2,4,8) and Cu (111) crystal planes were studied to explore the effect of size effect on the activity of WGSR. Density functional theory (DFT) calculations showed that the adsorption energy of H2O molecule was significantly enhanced on the surface of Cu1 and Cu2 clusters compared with Cu4 and Cu8 clusters, while CO adsorption strength first increased and then decreased. Among many copper clusters of different sizes, the redox pathway cannot proceed due to the lack of active sites on Cu1 and Cu2 clusters. According to the analysis of the microkinetic model, the order of WGSR activity on the surface of copper clusters of different sizes is: Cu4 > Cu2 ≈ Cu8 > Cu1 > Cu (111). The active center structure of the copper cluster is composed of 3 copper atoms in which the Cu-Cu coordination number is ca. 2 ∼ 3, and the active center is partially oxidized copper. Essentially, the low-coordination copper atoms determined by the geometry structure promote the WGSR activity of the copper clusters. This work not only reveals the copper cluster size effect on WGSR, but also provides the guidance for the size design and control of other supported metal catalysts.

Effects of incoming particle energy and cluster size on the G-value of hydrated electrons

In hydrated electron (e−aq) dosimetry, absorbed radiation dose to water is measured by monitoring the concentration of radiation-induced e−aq. However, to obtain accurate dose, the radiation chemical yield of e−aq, G(e−aq), is needed for the radiation quality/setup under investigation. The aim of this study was to investigate the time-evolution of the G-values for the main generated reactive species during water radiolysis using GEANT4-DNA. The effects of cluster size and linear energy transfer (LET) on G(e−aq) were examined. Validity of GEANT4-DNA for calculation of G(e−aq) for clinically relevant energies was studied. Three scenarios were investigated with different phantom sizes and incoming electron energies (1 keV to 1 MeV). The time evolution of G(e−aq) was in good agreement with published data and did not change with decreasing phantom size. The time-evolution of the G-values increases with increasing LET for all radiolytic species. The particle tracks formed with high-energy electrons are separated and the resulting reactive species develop independently in time. With decreasing energy, the mean separation distance between reactive species decreases. The particle tracks might not initially overlap but will overlap shortly thereafter due to diffusion of reactive species, increasing the probability of e−aq recombination with other species. This also explains the decrease of G(e−aq) with cluster size and LET. Finally, if all factors are kept constant, as the incoming electron energy increases to clinically relevant energies, G(e−aq) remains similar to its value at 1 MeV, hence GEANT4-DNA can be used for clinically relevant energies.

Understanding the effect of Ni cluster size on methane activation and dehydrogenation

The cluster size of the active metal of the catalyst has great effect on the carbon deposits during the dry reforming of methane. In this paper, the effect of active metal cluster size on methane activation and dehydrogenation is specifically studied. Three cluster models of Ni4, Ni9, and Ni16 are applied to study and simulate the activation and dehydrogenation process of CH4 on Ni clusters of different sizes. It is found that the adsorption energy of CH4 on Ni clusters increases with the increase of cluster size, but it is fairly close. The adsorption energies of CH3, CH2, CH and C are the largest on Ni9. In this process, electrons are always transferred from Ni clusters to adsorbents, and the amount of electron transfer is proportional to the adsorption energy. In the CH4 dehydrogenation process, Ni16 showed the most excellent activity and anti-carbon performance.

Exploring the Impact of Soft Errors on the Reliability of Real-Time Embedded Operating Systems

The continuous scaling of electronic components has led to the development of high-performance microprocessors that are suitable even for safety-critical applications where radiation-induced errors such as Single Event Effects (SEEs) can have a significant impact on the performance and reliability of the system. This work is dedicated to investigating the reliability of systems based on programmable hardware and Real-time operating Systems (RTOS) in the presence of architectural faults induced by soft errors in the configuration memory of the programmable hardware. We performed a proton radiation test campaigned at PSI radiation facility to identify the fault model affecting the configuration memory of Xilinx Zynq-7020 reconfigurable AP-Soc Device. The identified fault model in terms of SEU and MBU clusters has been used to evaluate the impact of proton-induced faults on applications running within FreeRTOS on a Microblaze soft processor. A Single Event Multiple Upset fault model resulting from a proton test is presented, focusing on characteristics such as shape, size, and frequency of observed cluster of errors. We conduct two fault injection campaigns and analyze the results to assess the effect of cluster size on system reliability. Moreover, we discuss software exceptions caused by faults that can affect the hardware structure of the soft processor.

Influence of poly(vinyl alcohol)/poly(N-vinyl-2-pyrrolidone) polymer matrix composition on the bonding environment and characteristics of Ag nanoparticles produced by gamma irradiation

A series of silver nanoparticles (AgNPs)-poly(vinyl alcohol)/poly(N-vinyl-2-pyrrolidone) (PVA/PVP) hydrogel nanocomposites were synthesized by gamma irradiation to examine the matrix's impact on properties of Ag nanocrystals important for strain engineering in functional materials. SEM analysis and the swelling studies revealed nanocomposite morphology and fluid transport properties. UV–Vis absorption characterization of AgNPs has enabled an understanding of the cluster size effects. The gel content indicated inter-crosslinking of the two components of the polymer matrix, especially for equivalent (1:1) PVA/PVP ratio, affecting the investigated AgNPs structural parameters. The lattice parameters and the interface stress, analyzed using XRD, have the lowest negative magnitude from the bulk lattice constant for the PVA/PVP (2:1) and (1:1) ratio. The lowest values of the lattice strain and dislocation density, as mutually dependent parameters, are obtained in AgNPs embedded in a PVA/PVP (2:1) and (1:1) matrix. The XPS and FTIR data show a positive shift of the O1s and a redshift of the CO – Ag vibration band indicating charge transfer to the vacant orbital of Ag nanocrystals. The N atoms of the pyrrolidine ring are not directly involved in the electronic interactions, but over the p-π conjugation with carbonyl O. In addition, the tested Ag-(PVA/PVP) hydrogel nanocomposites showed significant potential as a broad-spectrum antibacterial material.

Effect of Support and Pd Cluster Size on Catalytic Methane Partial Oxidation to Dimethyl Ether Using a NO/O2Shuttle

The partial oxidation of methane to dimethyl ether (DME) was studied on palladium supported on SiO2, SiO2-ZrO2, and ZrO2 at 225–375 °C and 0.1 MPa using either O2 or a mixture of NO and O2 as the oxidants. The NO + O2 mixture was more reactive than the O2 toward methane, probably due to the formation of active surface nitrate species. The formation of DME on the catalysts was influenced by the support, with the Pd/ZrO2 catalyst producing DME and the Pd/SiO2 catalyst producing only CO2, irrespective of the oxidant used. The Pd/SiZrO2 catalyst formed DME only when O2 alone was used as the oxidant. For the reaction with NO + O2, in situ Fourier transform infrared (FTIR) measurements showed that the partial oxidation activity on Pd/ZrO2 was related to its ability to form surface-bridged nitrate species, likely due to the presence of basic sites. However, an inhibitory effect of basicity on CH4 turnover frequency (TOF) was attributed to surface nitrate-induced structural modification deduced from X-ray absorption fine structure spectroscopy measurements. For the reaction with only O2, the formation of DME over Pd/ZrO2 and Pd/SiZrO2 was attributed to the reported ability of ZrO2 to retain methoxy intermediates. Furthermore, a weak structural effect on the TOF observed with O2 was attributed to competing effects of decreasing activity for C-H activation and increasing resistance to Pd oxidation with increasing particle size.

Effects of Energetic Carbon-Cluster Ion Irradiation on Lattice Structures of EuBa2Cu3O7−x Oxide Superconductor

C-axis-oriented EuBa2Cu3O7−x oxide films that were 100 nm thick were irradiated with 0.5 MeV C monoatomic ions, 2 MeV C4 cluster ions and 4 MeV C8 cluster ions at room temperature. Before and after the irradiation, X-ray diffraction (XRD) measurement was performed using Cu-Ka X-ray. The c-axis lattice constant increased almost linearly as a function of numbers of irradiating carbon ions, but it rarely depended on the cluster size. Cluster size effects were observed in the XRD peak intensity and the XRD peak width. With increasing the cluster size, the decrease in peak intensity becomes more remarkable and the peak width increases. The experimental result implies that the cluster ions with a larger size provide a more localized energy deposition in a sample, and cause larger and more inhomogeneous lattice disordering. As such, local and large lattice disordering acts as a pinning center for quantum vortex; energetic carbon-cluster ion irradiation will be effective for the increment in the critical current of EuBa2Cu3O7−x superconductors.

Effect of Pt cluster size on CO2 adsorption and activation on (110) and (100) γ-alumina surfaces: insights from DFT using a periodic boundary approach.

We performed a structural investigation on the adsorption and activation of CO2 molecules on different sized Pt clusters to study the effect of Pt cluster size on CO2 adsorption. Several Ptx clusters (x = 1-5 and 13) were analyzed to represent metal dispersion on surfaces and nanoscale metal clusters. For (110) γ-alumina surfaces, the Pt2 cluster site was the most stable. In addition, the Pt3 cluster site was the most stable for CO2 adsorption on Pt/Al2O3. Charge transfer from Pt clusters to CO2 was critical for CO2 activation.

Atom by atom built subnanometer copper cluster catalyst for the highly selective oxidative dehydrogenation of cyclohexene.

The effect of particle size and support on the catalytic performance of supported subnanometer copper clusters was investigated in the oxidative dehydrogenation of cyclohexene. From among the investigated seven size-selected subnanometer copper particles between a single atom and clusters containing 2-7 atoms, the highest activity was observed for the titania-supported copper tetramer with 100% selectivity toward benzene production and being about an order of magnitude more active than not only all the other investigated cluster sizes on the same support but also the same tetramer on the other supports, Al2O3, SiO2, and SnO2. In addition to the profound effect of cluster size on activity and with Cu4 outstanding from the studied series, Cu4 clusters supported on SiO2 provide an example of tuning selectivity through support effects when this particular catalyst also produces cyclohexadiene with about 30% selectivity. Titania-supported Cu5 and Cu7 clusters supported on TiO2 produce a high fraction of cyclohexadiene in contrast to their neighbors, while Cu4 and Cu6 solely produce benzene without any combustion, thus representing odd-even oscillation of selectivity with the number of atoms in the cluster.