Initial Cluster Size Research Articles

Deciphering the molecular mechanism underlying morphology transition in two-component DNA-protein cophase separation.

Nucleic acid and protein co-condensates exhibit diverse morphologies crucial for fundamental cellular processes. Despite many previous studies that advanced our understanding of this topic, several interesting biophysical questions regarding the underlying molecular mechanisms remain. We investigated DNA and human transcription factor p53 co-condensates-a scenario where neither dsDNA nor the protein demonstrates phase-separation behavior individually. Through a combination of experimental assays and theoretical approaches, we elucidated: (1) the phase diagram of DNA-protein co-condensates at a certain observation time, identifying a phase transition between viscoelastic fluid and viscoelastic solid states, and a morphology transition from droplet-like to "pearl chain"-like co-condensates; (2) the growth dynamics of co-condensates. Droplet-like and "pearl chain"-like co-condensates share a common initial critical microscopic cluster size at the nanometer scale during the early stage of phase separation. These findings provide important insights into the biophysical mechanisms underlying multi-component phase separation within cellular environments.

Does Cluster Encapsulation Inhibit Sintering? Stabilization of Size-Selected Pt Clusters on Fe3O4(001) by SMSI.

The metastability of supported metal nanoparticles limits their application in heterogeneous catalysis at elevated temperatures due to their tendency to sinter. One strategy to overcome these thermodynamic limits on reducible oxide supports is encapsulation via strong metal-support interaction (SMSI). While annealing-induced encapsulation is a well-explored phenomenon for extended nanoparticles, it is as yet unknown whether the same mechanisms hold for subnanometer clusters, where concomitant sintering and alloying might play a significant role. In this article, we explore the encapsulation and stability of size-selected Pt5, Pt10, and Pt19 clusters deposited on Fe3O4(001). In a multimodal approach using temperature-programmed desorption (TPD), X-ray photoelectron spectroscopy (XPS), and scanning tunneling microscopy (STM), we demonstrate that SMSI indeed leads to the formation of a defective, FeO-like conglomerate encapsulating the clusters. By stepwise annealing up to 1023 K, we observe the succession of encapsulation, cluster coalescence, and Ostwald ripening, resulting in square-shaped crystalline Pt particles, independent of the initial cluster size. The respective sintering onset temperatures scale with the cluster footprint and thus size. Remarkably, while small encapsulated clusters can still diffuse as a whole, atom detachment and thus Ostwald ripening are successfully suppressed up to 823 K, i.e., 200 K above the Hüttig temperature that indicates the thermodynamic stability limit.

Sensitivity Analysis of the Spatial Parameters in Modelling the Evolutionary Interaction Between Autonomous Vehicles and Other Road Users

The road user network is a dynamic, ever-evolving population in which road users interact to share and compete for road space. The advent of autonomous road vehicles (ARVs) will usher in numerous opportunities and challenges in road user dynamics. One of the challenges is whether an ARV population would be able to successfully enter the existing road user space. Previous work demonstrates that successful introduction of ARVs into the road network must consider the evolutionary dynamics of the existing population. This study examines the effect of different spatial parameters as starting conditions for the introduction of a small population of ARVs into a resident population of human-driven vehicles (HDV). The model utilises the concept of evolutionary game theory and uses a square lattice grid with a novel agent mobility approach. The results show that ARV success exhibits significant sensitivity to variations in initial cluster size, position, and travel range. ARVs seem to perform best in fewer, larger clusters with a shorter travel range. This suggests that the best form of early ARV introduction may take the shape of centralised, highly co-operative fleets of local passenger or freight transport.

MarVeLScaler: A Multi-View Learning-Based Auto-Scaling System for MapReduce

To promote cloud computing from current pay-per-request model to truly pay-per-use, tenants are crying for automatic tools to auto-estimate the amount of resources for MapReduce jobs. Such tools call for accurately quantifying the relationship among workload, resources and completion time. Various prediction models have been proposed. However, none of these models takes virtual machines&#x2019; (VMs) performance variance during a job&#x0027;s execution into consideration, leading to underestimate the required resources and exceed the job&#x0027;s deadline. To address this problem, we propose a multi-view deep learning model to capture real-time performance variance and automatically scale out the cloud cluster whenever necessary. We implement <i>MarVeLScaler</i>, a prototype system including two useful modules, namely, <i>Scale Estimator</i> and <i>Scale Controller</i>. Scale Estimator preliminarily estimates the required cluster size for a MapReduce job with given a concrete workload and deadline. During the runtime, Scale Controller adjusts the scale of the cluster according to its real-time running status to guarantee the job finished on time. We evaluate the performance of MarVeLScaler based on Hadoop in Alibaba Cloud. Experiments show that MarVeLScaler can provide 98.4 percent accuracy of prediction in determining initial cluster size, and save 30.8 percent of expense while still guaranteeing similar performance compared with the state-of-the-art methods.

A model for the formation of stellar associations and clusters from giant molecular clouds

ABSTRACT We present a large suite of magnetohydrodynamic simulations of turbulent, star-forming giant molecular clouds (GMCs) with stellar feedback, extending previous work by simulating 10 different random realizations for each point in the parameter space of cloud mass and size. It is found that once the clouds disperse due to stellar feedback, both self-gravitating star clusters and unbound stars generally remain, which arise from the same underlying continuum of substructured stellar density, i.e. the hierarchical cluster formation scenario. The fraction of stars that are born within gravitationally bound star clusters is related to the overall cloud star formation efficiency set by stellar feedback, but has significant scatter due to stochastic variations in the small-scale details of the star-forming gas flow. We use our numerical results to calibrate a model for mapping the bulk properties (mass, size, and metallicity) of self-gravitating GMCs on to the star cluster populations they form, expressed statistically in terms of cloud-level distributions. Synthesizing cluster catalogues from an observed GMC catalogue in M83, we find that this model predicts initial star cluster masses and sizes that are in good agreement with observations, using only standard IMF and stellar evolution models as inputs for feedback. Within our model, the ratio of the strength of gravity to stellar feedback is the key parameter setting the masses of star clusters, and of the various feedback channels direct stellar radiation (photon momentum and photoionization) is the most important on GMC scales.

Decoherence-Induced Universality in Simple Metal Cluster Photoelectron Angular Distributions

Measured angular distributions of photoelectrons from size-selected copper and sodium cluster anions are demonstrated to exhibit a universal behavior independent of the initial electron state, cluster size, or material, which can be traced back to momentum conservation upon photoemission. Quantum simulations reproduce the universality under the assumption that multielectron dynamics localizes the emission on the cluster surface and renders the cluster opaque to photoelectrons, thereby quenching interference effects that would otherwise obscure this almost classical behavior.

Dynamical evolution of population III stellar systems and the resulting binary statistics

ABSTRACT We use N-body simulations to study the dynamical evolution of population III (Pop III) stellar systems and the resulting binary statistics. We design a physically motivated framework for the initial conditions of Pop III star clusters, based on small-scale hydrodynamic simulations and the scale-free nature of disc evolution during Pop III star formation. Our novel approach enables us to explore the dependence of binary statistics on initial conditions and arrive at more robust predictions for the signals of Pop III X-ray binaries (XRBs) and binary black hole (BBH) mergers, compared to simple extrapolations of Pop III protostar systems. We find that binary properties are highly sensitive to the initial cluster size and distribution of binary separation, while the effect of initial mass function is relatively minor. Our simulations predict less close binaries, and thus, significantly lower efficiencies (by a factor of ∼10–104) for the formation and accretion of Pop III XRBs, than found in previous studies, implying that the contribution of Pop III XRBs to the cosmic X-ray background is negligible and their feedback effects are unimportant. We estimate the efficiency of Pop III BBH mergers as $\sim 10^{-5}\!-\!10^{-4}\ \rm M_{\odot }^{-1}$, for which three-body hardening by surrounding stars in dense star clusters or close binary interactions is required to facilitate in-spirals of BBHs. All simulation data, including catalogues of Pop III binaries and multiple systems, are publicly available.

Electron ionization of bare neon clusters and neon clusters doped with CO2 molecules

In the present study we have investigated the ionization threshold behavior of neon cluster ions ${\mathrm{Ne}}^{n+}$ (with $n=2\ensuremath{-}6$) formed upon the electron ionization of small neon clusters. The clusters were formed by supersonic expansion of cold neon gas through a pinhole nozzle. The appearance energies for these cluster ions were subsequently determined using a nonlinear least-squares fitting procedure. The obtained thresholds turned out to be only slightly lower than the ionization energy of the single neon atom. The present results are compared with previous electron impact and photoionization results. In addition, we investigated the electron ionization of neon clusters doped with $\mathrm{C}{\mathrm{O}}_{2}$ molecules. The mass spectrum at the electron energy of 70 eV showed predominantly bare cluster ions of $\mathrm{C}{\mathrm{O}}_{2}$. Charged clusters with fragments of $\mathrm{C}{\mathrm{O}}_{2}$ were observed as well, though in weaker abundance than the intact cluster ions. The relative abundance of these fragment ions was different from the ratios previously reported for electron ionization of bare $\mathrm{C}{\mathrm{O}}_{2}$ clusters and indicated increased formation of ${(\mathrm{C}{\mathrm{O}}_{2})}_{4}{{\mathrm{O}}_{2}}^{+}$ due to a neon matrix effect. We further investigated the ionization mechanisms in the cluster by measuring the ion yields of ${{(\mathrm{C}{\mathrm{O}}_{2})}_{4}}^{+}$ as a function of the electron energy close to the threshold. Direct ionization by the incoming electron, Penning ionization, and charge-transfer ionization were identified as possible processes, with varying contributions for different initial mean neon cluster sizes.

Dynamics and Kinetics of Methanol-Graphite Interactions at Low Surface Coverage.

The processes of molecular clustering, condensation, nucleation, and growth of bulk materials on surfaces, represent a spectrum of vapor-surface interactions that are important to a range of physical phenomena. Here, we describe studies of the initial stages of methanol condensation on graphite, which is a simple model system where gas-surface interactions can be described in detail using combined experimental and theoretical methods. Experimental molecular beam methods and computational molecular dynamics simulations are used to investigate collision dynamics and surface accommodation of methanol molecules and clusters at temperatures from 160 K to 240 K. Both single molecules and methanol clusters efficiently trap on graphite, and even in rarified systems methanol-methanol interactions quickly become important. A kinetic model is developed to simulate the observed behavior, including the residence time of trapped molecules and the quantified Arrhenius kinetics. Trapped molecules are concluded to rapidly diffuse on the surface to find and/or form clusters already at surface coverages below 10-6 monolayers. Conversely, clusters that undergo surface collisions fragment and subsequently lose more loosely bound molecules. Thus, the surface mediates molecular collisions in a manner that minimizes the importance of initial cluster size, but highlights a strong sensitivity to surface diffusion and intermolecular interactions between the hydrogen bonded molecules.

On the presence of intermediate black holes in three globular clusters

AbstractWe investigate whether the globular clusters 47 Tuc, ω Cen and NGC 6624 contain intermediate-mass black holes (IMBHs) by fitting a large grid of N-body simulations against their surface density and velocity dispersion profiles. In our simulations we vary the initial cluster size, the initial mass function and the initial density profile of the clusters as well as the mass fraction of a central intermediate-mass black hole. We find that the surface density and velocity dispersion profiles of all three clusters can be better reproduced by models that do not contain a central IMBH than by any of our IMBH models. If ω Cen and NGC 6624 contain any IMBHs at all, they have to be significantly less massive than suggested in the past.

Understanding the Influence of Initial Cluster Size Distribution On Crystallization Dynamics in The Ge2Sb2Te5 Phase‐Change Alloy

Phase‐change materials are recognized as major contenders to develop fast, low power, and small non‐volatile memories and data processors. Crystallization remains the limiting factor in deciding the operating speeds of phase‐change devices. It has been shown experimentally that pre‐annealing amorphous phase‐change materials leads to shorter crystallization times. This was attributed to the formation of crystalline nano‐clusters embedded in the amorphous phase that reduce the incubation time and enhance crystallization speeds, which was recently confirmed using enhanced transmission microscopy. The correlation between the initial size distribution of nano‐clusters on the crystallization dynamics is still however unclear which is crucial for increasing the speed of crystallization. This theoretical investigation simulates initial cluster size distributions following pre‐annealing and melt‐quenching in as‐deposited amorphous Ge2Sb2Te5 phase‐change materials using the physically realistic Master rate equation approach, and their influence on the crystallization dynamics. This approach is also extended to systematically study assumed Gaussian initial cluster densities in the sub‐nanometer to few tens of nanometers size range on the crystallization dynamics at different annealing rates. The simulations revealed enhancement of crystallization speeds with narrow initial distributions of small cluster sizes of few nanometers (for the same initial crystalline fraction) in agreement with enhanced microscopy observations.

Asymmetry in initial cluster size favors symmetry in a network of oscillators.

Counterintuitive to the common notion of symmetry breaking, asymmetry favors synchrony in a network of oscillators. Our observations on an ensemble of identical Stuart-Landau systems under a symmetry breaking coupling support our conjecture. As usual, for a complete deterministic and the symmetric choice of initial clusters, a variety of asymptotic states, namely, multicluster oscillation death (1-OD, 3-OD, and -OD), chimera states, and traveling waves emerge. Alternatively, multiple chimera death (1-CD, 3-CD, and -CD) and completely synchronous states emerge in the network whenever some randomness is added to the symmetric initial states. However, in both the cases, an increasing asymmetry in the initial cluster size restores symmetry in the network, leading to the most favorable complete synchronization state for a broad range of coupling parameters. We are able to reduce the network model using the mean-field approximation that reproduces the dynamical features of the original network.

Experimental evidence for the significant role of initial cluster size and liquid confinement on thermo-physical properties of magnetic nanofluids under applied magnetic field

Though huge thermal conductivity enhancement was observed in some magnetic fluids under an external field, the percentage of enhancement reported were largely different in similar magnetic fluids, which was quite perplexing to the scientific community. Here, we probe the role of initial cluster size and the liquid layer confinement between nanoparticles within chains that are formed under an external magnetic field, on thermal, rheological and interfacial property enhancement in model nanofluids. Three different ferrofluids containing oleic acid capped superparamagnetic magnetic nanoparticles (Fe3O4) of average crystallite sizes 9.6, 8.3 and 10.5nm (referred as S1, S2 and S3, respectively), with different polydispersity and coating thickness, synthesized by coprecipitation technique, are used in the present study. The synthesized nanoparticles were characterized by X-ray diffraction, small angle X-ray scattering (SAXS), dynamic light scattering (DLS), vibrating sample magnetometry and thermogravimetry.Thermal conductivity enhancement in samples S1 and S2 in the presence of magnetic field when the direction of field is parallel to the direction of heat flux were 127% (at 160G) and 42% (at 70G), respectively while S3 did not show significant enhancement with field. Our results suggest that in a relatively monodisperse system, nucleation occur at longer time scales and at high field strengths. On the contrary, in significantly polydisperse system, the larger particles act as nucleation centers and hence the aggregation kinetics is much faster. Under a low magnetic field strength, the particles present in S1 interact with each other and form short nanosized chains, where the growth via tip to tip aggregation is hindered by smaller particles. However in S3, larger sized particles act as nucleation centers to initiate chain formation at low field and form thick columnar structures via zippering at higher fields that lower the heat transport efficiency. Owing to the functional group, solvent molecules are trapped between the nanoparticles and the confinement of liquid molecules reduces phonon scattering at the interface. <10% enhancement in k/kf obtained when the heat flux is perpendicular to the applied field in all three systems confirms the series mode of conduction paths. For field strength of 200G, S3 showed 800% enhancement in viscosity while S1 and S2 showed negligible viscosity enhancement. S3 showed a significantly higher yield stress than S2 indicating that the field induced structures are stronger in S3.The much larger thermal conductivity enhancement in samples with very small fraction of larger clusters (with minimum polydispersity) confirm the numerical simulation results that when liquids are confined in nanochannels, long range phonons are sustained by the base fluid that enhance heat transport by lowering the Kapitza resistance. These results provide several new insights into the mechanism of heat conduction in magnetic nanofluids and ways to achieve efficient heat transfer without increasing pumping power.

A Technique for Cloud Based Clustering and Spatial Resource Reuse and Scheduling of 3D In-Building Small Cells Using CoMP for High Capacity CRAN

In this paper, we propose a technique for cloud coordinated clustering and scheduling of small cells, i.e., femtocells, in CRAN to improve capacity and spectral efficiency in 3D in-building environments. Control-and user-plane of each cell is decoupled. The clustering technique consists of two levels of clustering such that level 1 clustering defines an initial 3D femtocell cluster size. Level 2 clustering defines a cooperating set of femtocells per floor within each level 1 cluster to explore joint transmission coordinated multipoint (CoMP) during off-states of their transmit power. Femtocells are split at the MAC layer, and a mechanism is presented to model the bandwidth and latency fronthaul constraints. We derive the system level aggregate capacity, spectral efficiency, and energy efficiency. We then develop a heuristic algorithm and discuss its scheduler implementation. With numerical and simulation results, we show with an example scenario that the proposed technique can achieve the maximum CoMP capacity gain of 44% per building and 32.15% in overall system level. Finally, we demonstrate that the proposed technique can achieve the performance requirements of 5G cellular systems and point out the significance and further research issues.

Back to the future: estimating initial globular cluster masses from their present-day stellar mass functions

We use N-body simulations to model the 12 Gyr evolution of a suite of star clusters with identical initial stellar mass functions over a range of initial cluster masses, sizes, and orbits. Our models reproduce the distribution of present-day global stellar mass functions that is observed in the Milky Way globular cluster population. We find that the slope of a star cluster's stellar mass function is strongly correlated with the fraction of mass that the cluster has lost, independent of the cluster's initial mass, and nearly independent of its orbit and initial size. Thus, the mass function - initial mass relation can be used to determine a Galactic cluster's initial total stellar mass, if the initial stellar mass function is known. We apply the mass function - initial mass relation presented here to determine the initial stellar masses of 33 Galactic globular clusters, assuming an universal Kroupa initial mass function. Our study suggests that globular clusters had initial masses that were on average a factor of 4.5 times larger than their present day mass, with three clusters showing evidence for being 10 times more massive at birth.

Synthesis of water-soluble gold clusters in nanosomes displaying robust photoluminescence with very large Stokes shift

This paper reports a novel procedure using nanosomes, made of bola-hydroxyl and mercapto-palmitic acids, for the production of gold clusters with robust luminescent emissions and very large Stokes shifts. It shows that these results cannot be explained by the currently accepted mechanism based on ligand-to-metal charge transfer absorptions involving electron-rich ligands attached to the cluster core. Exhaustive characterization of the cluster samples using Mass Spectrometry, HR-TEM/STEM, XPS, EXAFS, and steady-state and time-resolved luminescence allows to deduce that a mixture of two cluster sizes, having non-closed shell electronic configurations, are firstly generated inside the nanosome compartments due to the difference in bonding strength of the two types of terminal groups in the fatty acids. This initial bimodal cluster size distribution slowly evolves into very stable, closed-shell Au cluster complexes (Au6–Au16 and Au5–Au14) responsible for the observed luminescent properties. The very small (≈1.2nm) synthesized cluster complexes are water soluble and suitable to be used for the conjugation of biomolecules (through the terminal COO− groups) making these systems very attractive as biomarkers and offering, at the same time, a novel general strategy of fabricating stable atom-level quantum dots with large Stokes shifts of great importance in many sensor applications.

Nanoisland formation of small Ag -clusters on HOPG as determined by inner-shell photoionisation spectroscopy

Abstract XPS (3d) and Auger spectra (MNN) of deposited Ag n -clusters on a non-sputtered HOPG surface have been measured. Most of the XPS and Auger spectra appear very similar to the corresponding bulk spectrum, caused by a high mobility and agglomeration of the clusters on the inert carbon surface, independent of the initial cluster size. The metallic fingerprint of the cluster-agglomerated islands is sustained under UHV conditions for several days. Oxidised Ag-islands reveal a positive binding energy shift in distinct contrast to the negative XPS shift usually observed for silver oxide bulk compounds. The XPS binding energy shift has been used for estimation of the diameter of the cluster-assembled nanoislands (6–9 nm) using an electrostatic model.

Kinetics of Ni3Al cluster formation with decomposition of solid solution

We have proven cluster nucleation with the decomposition of nickel alloy solid solution upon quenching cooling numerically and experimentally. The initial cluster sizes, the nucleation time, and the growth time of clusters with average sizes, as well as the formation time for a fixed volume fraction of the phase during thermal exposure, have been calculated via a method adopted earlier [1, 5]. The data allow one to plot the isothermal decay diagrams (TTT diagrams) to optimize the modes of thermal exposure of alloys.

Reaction-induced cluster ripening and initial size-dependent reaction rates for CO oxidation on Pt(n)/TiO2(110)-(1×1).

We determined the CO oxidation rates for size-selected Ptn (n ∈ {3,7,10}) clusters deposited onto TiO2(110). In addition, we investigated the cluster morphologies and their mean sizes before and after the reaction. While the clusters are fairly stable upon annealing in ultrahigh vacuum up to 600 K, increasing the temperature while adsorbing either one of the two reactants leads to ripening already from 430 K on. This coarsening is even more pronounced when both reactants are dosed simultaneously, i.e., running the CO oxidation reaction. Since the ripening depends on the size initially deposited, there is nevertheless a size effect; the catalytic activity decreases monotonically with increasing initial cluster size.

Estimating atmospheric nucleation rates from size distribution measurements: Analytical equations for the case of size dependent growth rates

While laboratory and field measurements indicate that atmospheric nucleation most likely initiates with the formation clusters of ~1.0–1.5nm diameter, most atmospheric observations to date measure only particles larger than 3–10nm in size. Because of this, several analytical formulations have been developed to estimate the real nucleation rate at the initial cluster size from the “apparent” nucleation rate at the measured larger sizes. All previous analytical formulations have assumed a constant particle growth rate below the instrument detection limit; however, recent atmospheric measurements have shown that the growth rate is often strongly size dependent. This study presents new analytical equations to connect the real and “apparent” nucleation rates in two special cases, i.e. when the cluster growth rate follows a (1) linear, or (2) power-law dependence on the particle size. The accuracy of these equations is tested with an ensemble of numerical model simulations of new particle formation events. Both new formulations are capable of estimating the nucleation rate at 1.5nm fairly accurately (largest normalised mean bias −1.4% for the power-law and −23% for the linear events). We find, however, that the power law formulation gives a more accurate estimate of the nucleation rate even for a majority of the events with linear growth rate dependence. Further analysis indicates that previous studies of atmospheric nucleation events, which have assumed a constant cluster growth rate, may have clearly underestimated the real nucleation rate.