Formation and transformation of metastable LPSO building blocks clusters in Mg-Gd-Y-Zn-Zr alloys by spinodal decomposition and heterogeneous nucleation

To study the formation and transformation mechanism of long-period stacked ordered(LPSO)structures,a systematic atomic scale analysis was conducted for the structural evolution of long-period stacked ordered(LPSO)structures in the Mg-Gd-Y-Zn-Zr alloy annealed at 300℃~500℃.Various types of metastable LPSO building block clusters were found to exist in alloy structures at different temperatures,which precipitate during the solidification and homogenization process.The stability of Zn/Y clusters is explained by the first principles of density functional theory.The LPSO structure is distinguished by the arrangement of its different Zn/Y enriched LPSO structural units,which comprises local fcc stacking sequences upon a tightly packed plane.The presence of solute atoms causes local lattice distortion,thereby enabling the rearrangement of Mg atoms in the different configurations in the local lattice,and local HCP-FCC transitions occur between Mg and Zn atoms occupying the nearest neighbor positions.This finding indicates that LPSO structures can generate necessary Schockley partial dislocations on specific slip surfaces,providing direct evidence of the transition from 18R to 14H.Growth of the LPSO,devoid of any defects and non-coherent interfaces,was observed separately from other precipitated phases.As a result,the precipitation sequence of LPSO in the solidification stage was as follows:Zn/Ycluster+Mg layers→various metastable LPSO building block clusters→18R/24R LPSO;whereas the precipitation sequence of LPSO during homogenization treatment was observed to be as follows:18R LPSO→various metastable LPSO building block clusters→14H LPSO.Of these,14H LPSO was found to be the most thermodynamically stable structure.

Unsaturated bi-heterometal clusters in metal-vacancy sites of 2D MoS2 for efficient hydrogen evolution

The valence states and coordination structures of doped heterometal atoms in two-dimensional(2D)nanomaterials lack predictable regulation strategies.Hence,a robust method is proposed to form unsaturated heteroatom clusters via the metal-vacancy restraint mechanism,which can precisely regulate the bonding and valence state of heterometal atoms doped in 2D molybdenum disulfide.The unsaturated valence state of heterometal Pt and Ru cluster atoms form a spatial coordination structure with Pt–S and Ru–O–S as catalytically active sites.Among them,the strong binding energy of negatively charged suspended S and O sites for H+,as well as the weak adsorption of positively charged unsaturated heterometal atoms for H*,reduces the energy barrier of the hydrogen evolution reaction proved by theoretical calculation.Whereupon,the electrocatalytic hydrogen evolution performance is markedly improved by the ensemble effect of unsaturated heterometal atoms and highlighted with an overpotential of 84 mV and Tafel slope of 68.5 mV dec^(−1).In brief,this metal vacancy-induced valence state regulation of heterometal can manipulate the coordination structure and catalytic activity of heterometal atoms doped in the 2D atomic lattice but not limited to 2D nanomaterials.

A Shared Natural Neighbors Based-Hierarchical Clustering Algorithm for Discovering Arbitrary-Shaped Clusters

In clustering algorithms,the selection of neighbors significantly affects the quality of the final clustering results.While various neighbor relationships exist,such as K-nearest neighbors,natural neighbors,and shared neighbors,most neighbor relationships can only handle single structural relationships,and the identification accuracy is low for datasets with multiple structures.In life,people’s first instinct for complex things is to divide them into multiple parts to complete.Partitioning the dataset into more sub-graphs is a good idea approach to identifying complex structures.Taking inspiration from this,we propose a novel neighbor method:Shared Natural Neighbors(SNaN).To demonstrate the superiority of this neighbor method,we propose a shared natural neighbors-based hierarchical clustering algorithm for discovering arbitrary-shaped clusters(HC-SNaN).Our algorithm excels in identifying both spherical clusters and manifold clusters.Tested on synthetic datasets and real-world datasets,HC-SNaN demonstrates significant advantages over existing clustering algorithms,particularly when dealing with datasets containing arbitrary shapes.

Thermal stable Pt clusters anchored by K/TiO_(2)—Al_(2)O_(3)for efficient cycloalkane dehydrogenation

Catalytic dehydrogenation of cycloalkanes is considered a valuable endothermic process for alleviating the thermal barrier issue of hypersonic vehicles.However,conventional Pt-based catalysts often face the severe problem of metal sintering under high-temperature conditions.Herein,we develop an efficient K_(2)CO_(3)-modified Pt/TiO_(2)—Al_(2)O_(3)(K—Pt/TA)for cycloalkane dehydrogenation.The optimized K—Pt/TA showed a high specific activity above 27.9 mol·mol^(-1)·s^(-1)(H_(2)/Pt),with toluene selectivity above 90.0%at 600℃with a high weight hourly space velocity of 266.4 h^(-1).The introduction of alkali metal ions could generate titanate layers after high-temperature hydrogen reduction treatment,which promotes the generation of oxygen vacancy defects to anchored Pt clusters.In addition,the titanate layers could weaken the surface acidity of catalysts and inhibit side reactions,including pyrolysis,polymerization,and isomerization reactions.Thus,this work provides a modification method to develop efficient and stable dehydrogenation catalysts under high-temperature conditions.

Advances of Synergistic Electrocatalysis Between Single Atoms and Nanoparticles/Clusters

Combining single atoms with clusters or nanoparticles is an emerging tactic to design efficient electrocatalysts.Both synergy effect and high atomic utilization of active sites in the composite catalysts result in enhanced electrocatalytic performance,simultaneously provide a radical analysis of the interrelationship between structure and activity.In this review,the recent advances of single-atomic site catalysts coupled with clusters or nanoparticles are emphasized.Firstly,the synthetic strategies,characterization,dynamics and types of single atoms coupled with clusters/nanoparticles are introduced,and then the key factors controlling the structure of the composite catalysts are discussed.Next,several clean energy catalytic reactions performed over the synergistic composite catalysts are illustrated.Eventually,the encountering challenges and recommendations for the future advancement of synergistic structure in energy-transformation electrocatalysis are outlined.

Solving the Conundrum of Dark Matter and Dark Energy in Galaxy Clusters

This paper develops the Dark Matter by Quantum Gravitation theory, DMbQG theory hereafter, in clusters of galaxies in the cosmologic model ΛCDM of the Universe. Originally this theory was developed by the author for galaxies, especially using MW and M31 rotation curves. An important result got by the DMbQG theory is that the total mass associated to a galactic halo depend on the square root of radius, being its dominion unbounded. Apparently, this result would be absurd because of divergence of the total mass. As the DE is negligible at galactic scale, it is needed to extend the theory to clusters in order to study the capacity of DE to counterbalance to DM. Thanks this property, the DMbQG theory finds unexpected theoretical results. In this work, it is defined, the total mass as baryonic matter plus DM and the gravitating mass as the addition of the total mass plus the negative mass associated to dark energy. In clusters it is defined the zero gravity radius (RZG hereafter) as the radius needed by the dark energy to counterbalance the total mass. It has been found that the ratio RZG/RVIRIAL ≈ 7.3 and its Total mass associated at RZG is ≈2.7 MVIRIAL. In addition, it has been calculated that the sphere with the extended halo radius RE = 1.85 RZG has a ratio DM density versus DE density equal to 3/7 and its total mass associated at RE is ≈3.6 MVIRIAL. This works postulates that the factor 3.6 may equilibrate perfectly the strong imbalance between the Local mater density parameter (0.08) versus the current Global matter density one (0.3). Currently, this fact is a big conundrum in cosmology, see chapter 7. Also it has been found that the zero velocity radius, RZV hereafter, i.e. the cluster border because of the Hubble flow, is ≈0.6 RZG and its gravitating mass is ≈ 1.5 MVIR. By derivation of gravitating mass function, it is calculated that at 0.49 RZG, this function reaches its maximum whose value is ≈1.57 MVIR. Throughout the paper, some of these results have been validated with recent data published for the Virgo cluster. As Virgo is the nearest big cluster, it is the perfect benchmark to validate any new theory about DM and DE. These new theoretical findings offer to scientific community a wide number of tests to validate or reject the theory. The validation of DMbQG theory would mean to know the nature of DM that at the present, it is an important challenge for the astrophysics science.

Synergistic effect of heterogeneous single atoms and clusters for improved catalytic performance

Electrocatalytic water splitting provides an efficient method for the production of hydrogen.In electrocatalytic water splitting,the oxygen evolution reaction(OER)involves a kinetically sluggish four-electron transfer process,which limits the efficiency of electrocatalytic water splitting.Therefore,it is urgent to develop highly active OER catalysts to accelerate reaction kinetics.Coupling single atoms and clusters in one system is an innovative approach for developing efficient catalysts that can synergistically optimize the adsorption and configuration of intermediates and improve catalytic activity.However,research in this area is still scarce.Herein,we constructed a heterogeneous single-atom cluster system by anchoring Ir single atoms and Co clusters on the surface of Ni(OH)_(2)nanosheets.Ir single atoms and Co clusters synergistically improved the catalytic activity toward the OER.Specifically,Co_(n)Ir_(1)/Ni(OH)_(2)required an overpotential of 255 mV at a current density of 10 mA·cm^(−2),which was 60 mV and 67 mV lower than those of Co_(n)/Ni(OH)_(2)and Ir1/Ni(OH)_(2),respectively.The turnover frequency of Co_(n)Ir_(1)/Ni(OH)_(2)was 0.49 s^(−1),which was 4.9 times greater than that of Co_(n)/Ni(OH)_(2)at an overpotential of 300 mV.

A Dark Matter Theory by Quantum Gravitation for Galaxies and Clusters

This paper develops an original theory of dark matter in the current ΛCDM framework, whose main hypothesis is that DM is generated by the own gravitational field, according to an unknown quantum gravitational phenomenon. This work is the best version of the theory, which I have been developing and publishing since 2014. The hypothesis of DM by quantum gravitation, DMbQG hereafter, has two main consequences: the first one is that the law of DM generation has to be the same, in the halo region, for all the galaxies and the second one is that the haloes are unbounded, so the total DM goes up without limit as the gravitational field is unbounded as well. The first one consequence is backed by the fact that M31 and MW has a fitted function with the same power exponent for the rotation curve at the halo region and both giant galaxies are the only ones whose rotation curves at the halo region may be studied with accuracy. This paper is firstly developed all the theory with M31 rotation curve data up to Chapter 9. The most important formula of the theory is the called Direct mass, which calculates the total mass at a specific radius into the halo region. Chapter 10 is dedicated to apply the theory to Milky Way, it is calculated its total mass at different radius into the halo and such results have been validated successfully using the data of masses at different radius published by two researcher teams. In Chapter 11, it is calculated the direct mass for the Local Group, and it is shown how the DMbQG theory is able to calculate the total mass at 770 kpc, that the dynamical methods estimate to be 5×1012MΘ. In Chapter 12, it is shown a method to estimate the Direct mass formula for a cluster of galaxies, using only its virial mass and virial radius. By this method, it is estimated the parameter a2 of the Local Group, which match with the one calculated in previous chapter by a different method. Also are calculated the parameters a2 associated to Virgo and Coma clusters. In Chapter 13, it is demonstrated how the DE is able to counterbalance the DM at cluster scale, as the Direct mass grows up with the square root of radius whereas the DE grows up with the cubic power. The chapter is an introduction to the DMbQG theory for cluster of galaxies, which has been developed fully by the author in other works. This theory aims to be a powerful method to study DM in the halo region of galaxies and cluster of galaxies and conversely the measures in galaxies and clusters offer the possibility to validate the theory.

BSEC Method for Unveiling Open Clusters and its Application to Gaia DR3:83 New Clusters

Open clusters(OCs) are common in the Milky Way, but most of them remain undiscovered. There are numerous techniques, including some machine-learning algorithms, available for the exploration of OCs. However, each method has its limitations and therefore, different approaches to discovering OCs hold significant values. We develop a comprehensive approach method to automatically explore the data space and identify potential OC candidates with relatively reliable membership determination. This approach combines the techniques of Hierarchical Density-Based Spatial Clustering of Applications with Noise, Gaussian mixture model, and a novel cluster member identification technique, color excess constraint. The new method exhibits efficiency in detecting OCs while ensuring precise determination of cluster memberships. Because the main feature of this technique is to add an extra constraint(EC) for the members of cluster candidates using the homogeneity of color excess,compared to typical blind search codes, it is called Blind Search-Extra Constraint(BSEC) method. It is successfully applied to the Gaia Data Release 3, and 83 new OCs are found, whose color–magnitude diagrams(CMDs) are fitted well to the isochrones. In addition, this study reports 621 new OC candidates with discernible main sequence or red giant branch. It is shown that BSEC technique can discard some false negatives of previous works, which takes about three percentage of known clusters. It shows that as an EC, the color excess(or twocolor) constraint is useful for removing fake cluster member stars from the clusters that are identified from the positions and proper motions of stars, and getting more precise CMDs, when differential reddening of member stars of a cluster is not large(e.g., ΔE(G_(BP)-G_(RP)) < 0.5 mag). It makes the CMDs of 15% clusters clearer(in particular for the region near turnoff) and therefore is helpful for CMD and stellar population studies. Our result suggests that the color excess constraint is more appropriate for clusters with small differential reddening, such as globular clusters or older OCs, and clusters that the distances of member stars cannot be determined accurately.

Optimization of jamming formation of USV offboard active decoy clusters based on an improved PSO algorithm

Offboard active decoys(OADs)can effectively jam monopulse radars.However,for missiles approaching from a particular direction and distance,the OAD should be placed at a specific location,posing high requirements for timing and deployment.To improve the response speed and jamming effect,a cluster of OADs based on an unmanned surface vehicle(USV)is proposed.The formation of the cluster determines the effectiveness of jamming.First,based on the mechanism of OAD jamming,critical conditions are identified,and a method for assessing the jamming effect is proposed.Then,for the optimization of the cluster formation,a mathematical model is built,and a multi-tribe adaptive particle swarm optimization algorithm based on mutation strategy and Metropolis criterion(3M-APSO)is designed.Finally,the formation optimization problem is solved and analyzed using the 3M-APSO algorithm under specific scenarios.The results show that the improved algorithm has a faster convergence rate and superior performance as compared to the standard Adaptive-PSO algorithm.Compared with a single OAD,the optimal formation of USV-OAD cluster effectively fills the blind area and maximizes the use of jamming resources.

Nomogram prediction of vessels encapsulating tumor clusters in small hepatocellular carcinoma≤3 cm based on enhanced magnetic resonance imaging

BACKGROUND Vessels encapsulating tumor clusters(VETC)represent a recently discovered vascular pattern associated with novel metastasis mechanisms in hepatocellular carcinoma(HCC).However,it seems that no one have focused on predicting VETC status in small HCC(sHCC).This study aimed to develop a new nomogram for predicting VETC positivity using preoperative clinical data and image features in sHCC(≤3 cm)patients.AIM To construct a nomogram that combines preoperative clinical parameters and image features to predict patterns of VETC and evaluate the prognosis of sHCC patients.METHODS A total of 309 patients with sHCC,who underwent segmental resection and had their VETC status confirmed,were included in the study.These patients were recruited from three different hospitals:Hospital 1 contributed 177 patients for the training set,Hospital 2 provided 78 patients for the test set,and Hospital 3 provided 54 patients for the validation set.Independent predictors of VETC were identified through univariate and multivariate logistic analyses.These independent predictors were then used to construct a VETC prediction model for sHCC.The model’s performance was evaluated using the area under the curve(AUC),calibration curve,and clinical decision curve.Additionally,Kaplan-Meier survival analysis was performed to confirm whether the predicted VETC status by the model is associated with early recurrence,just as it is with the actual VETC status and early recurrence.RESULTS Alpha-fetoprotein_lg10,carbohydrate antigen 199,irregular shape,non-smooth margin,and arterial peritumoral enhancement were identified as independent predictors of VETC.The model incorporating these predictors demonstrated strong predictive performance.The AUC was 0.811 for the training set,0.800 for the test set,and 0.791 for the validation set.The calibration curve indicated that the predicted probability was consistent with the actual VETC status in all three sets.Furthermore,the decision curve analysis demonstrated the clinical benefits of our model for patients with sHCC.Finally,early recurrence was more likely to occur in the VETC-positive group compared to the VETC-negative group,regardless of whether considering the actual or predicted VETC status.CONCLUSION Our novel prediction model demonstrates strong performance in predicting VETC positivity in sHCC(≤3 cm)patients,and it holds potential for predicting early recurrence.This model equips clinicians with valuable information to make informed clinical treatment decisions.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma:Machine learning model based on contrast-enhanced computed tomography

BACKGROUND Recently,vessels encapsulating tumor clusters(VETC)was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner,and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma(HCC).AIM To develop and validate a preoperative nomogram using contrast-enhanced computed tomography(CECT)to predict the presence of VETC+in HCC.METHODS We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers.Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase.Radiomics features,essential for identifying VETC+HCC,were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set.The model’s performance was validated on two separate test sets.Receiver operating characteristic(ROC)analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets.The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features.ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features,the radiomics features and the radiomics nomogram.RESULTS The study included 190 individuals from two independent centers,with the majority being male(81%)and a median age of 57 years(interquartile range:51-66).The area under the curve(AUC)for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825,0.788,and 0.680 in the training set and the two test sets.A total of 13 features were selected to construct the Rad-score.The nomogram,combining clinicalradiological and combined radiomics features could accurately predict VETC+in all three sets,with AUC values of 0.859,0.848 and 0.757.Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models.CONCLUSION This study demonstrates the potential utility of a CECT-based radiomics nomogram,incorporating clinicalradiological features and combined radiomics features,in the identification of VETC+HCC.

Geometries and electronic structures of Zr_(n)Cu(n=2–12) clusters: A joint machine-learning potential density functional theory investigation

Zr-based amorphous alloys have attracted extensive attention because of their large glassy formation ability, wide supercooled liquid region, high elasticity, and unique mechanical strength induced by their icosahedral local structures.To determine the microstructures of Zr–Cu clusters, the stable and metastable geometry of Zr_(n)Cu(n=2–12) clusters are screened out via the CALYPSO method using machine-learning potentials, and then the electronic structures are investigated using density functional theory. The results show that the Zr_(n)Cu(n ≥ 3) clusters possess three-dimensional geometries, Zr_(n)Cu(n≥9) possess cage-like geometries, and the Zr_(12)Cu cluster has icosahedral geometry. The binding energy per atom gradually gets enlarged with the increase in the size of the clusters, and Zr_(n)Cu(n=5,7,9,12) have relatively better stability than their neighbors. The magnetic moment of most Zr_(n)Cu clusters is just 1μB, and the main components of the highest occupied molecular orbitals(HOMOs) in the Zr_(12)Cu cluster come from the Zr-d state. There are hardly any localized two-center bonds, and there are about 20 σ-type delocalized three-center bonds.

Development of Multilayer Models of Globular Star Clusters and Study of Their Evolution

Usually, models of globular star clusters are created by analyzing their luminosity and other observation parameters. The goal of this work is to create stable models of globular clusters based on the laws of mechanics. It is necessary to set the coordinates, velocities and masses of the stars so that as a result of their gravitational interaction the globular cluster is not destroyed. This is not an easy task, and it has been solved in this paper. Using an exact solution of the axisymmetric gravitational interaction of N-bodies, single-layer spherical structures were created. They are combined into multilayer models of globular clusters. An algorithm and a program for their creation is described. As a result of solving the problem of gravitational interaction of N bodies, evolution of 5-, 10-, and 15-layer structures was studied. During the inter-body interaction, there proceeds a transition from the initial specially organized structure to a structure with bodies, uniformly distributed in space. The number of inter-body collisions decreases, and the globular cluster model passes into the stable form of its existence. The collisions of bodies and the acquisition of rotational motion and thermal energy by them are considered. As a result of the passage to scaled dimensions, the results were recalculated to the conditions of globular star clusters. The periods of rotation and the temperatures of merged stars are calculated. Attention is paid to a decreased central-body mass in the analyzed models of globular star clusters.

Research of caged dynamics of clusters center atoms in Pd_(82)Si_(18) amorphous alloy

To date,there is still a lack of a comprehensive explanation for caged dynamics which is regarded as one of the intricate dynamic behaviors in amorphous alloys.This study focuses on Pd_(82)Si_(18)as the research object to further elucidate the underlying mechanism of caged dynamics from multiple perspectives,including the cage's lifetime,atomic local environment,and atomic potential energy.The results reveal that Si atoms exhibit a pronounced cage effect due to the hindrance of Pd atoms,resulting in an anomalous peak in the non-Gaussian parameters.An in-depth investigation was conducted on the caged dynamics differences between fast and slow Si atoms.In comparison to fast Si atoms,slow Si atoms were surrounded by more Pd atoms and occupied lower potential energy states,resulting in smaller diffusion displacements for the slow Si atoms.Concurrently,slow Si atoms tend to be in the centers of smaller clusters with coordination numbers of 9 and 10.During the isothermal relaxation process,clusters with coordination numbers 9 and 10 have longer lifetimes,suggesting that the escape of slow Si atoms from their cages is more challenging.The findings mentioned above hold significant implications for understanding the caged dynamics.

Optimal operation of Internet Data Center with PV and energy storage type of UPS clusters

With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.

Isochrone Fitting of Galactic Globular Clusters—Ⅵ.High-latitude Clusters NGC 5024 (M53),NGC 5053,NGC 5272 (M3),NGC 5466,and NGC7099 (M30)

We fit various color–magnitude diagrams(CMDs) of the high-latitude Galactic globular clusters NGC 5024(M53),NGC 5053,NGC 5272(M3),NGC 5466,and NGC 7099(M30) by isochrones from the Dartmouth Stellar Evolution Database and Bag of Stellar Tracks and Isochrones for α–enrichment [α/Fe] = +0.4.For the CMDs,we use data sets from Hubble Space Telescope,Gaia,and other sources utilizing,at least,25 photometric filters for each cluster.We obtain the following characteristics with their statistical uncertainties for NGC 5024,NGC 5053,NGC 5272,NGC 5466,and NGC 7099,respectively:metallicities [Fe/H] =-1.93 ± 0.02,-2.08 ± 0.03,-1.60 ± 0.02,-1.95 ± 0.02,and-2.07 ± 0.04 dex with their systematic uncertainty 0.1 dex;ages 13.00 ± 0.11,12.70 ± 0.11,11.63 ± 0.07,12.15 ± 0.11,and 12.80 ± 0.17 Gyr with their systematic uncertainty 0.8 Gyr;distances(systematic uncertainty added) 18.22 ± 0.06 ± 0.60,16.99 ± 0.06 ± 0.56,10.08 ± 0.04 ± 0.33,15.59 ±0.03 ± 0.51,and 8.29 ± 0.03 ± 0.27 kpc;reddenings E(B-V) = 0.023 ± 0.004,0.017 ± 0.004,0.023 ± 0.004,0.023 ± 0.003,and 0.045 ± 0.002 mag with their systematic uncertainty 0.01 mag;extinctions AV= 0.08 ± 0.01,0.06 ± 0.01,0.08 ± 0.01,0.08 ± 0.01,and 0.16 ± 0.01 mag with their systematic uncertainty 0.03 mag,which suggest the total Galactic extinction AV= 0.08 across the whole Galactic dust to extragalactic objects at the North Galactic Pole.The horizontal branch morphology difference of these clusters is explained by their different metallicity,age,mass-loss efficiency,and loss of low-mass members in the evolution of the core-collapse cluster NGC 7099 and loose clusters NGC 5053 and NGC 5466.

Simulating the Dynamics of Bimetallic Clusters Deposited onto a Surface Using Molecular Dynamics

This paper examines the interface development between a single crystalline Ag matrix and core-shell AgnCom nanoclusters that have been deposited with energies varying between 0.25 eV and 1.5 eV per atom using computer modeling techniques. Clusters undergo deformation as a result of the slowing down;they may also become epitaxial with the substrate and maintain their core-shell structure. A detailed analysis of the effects of the cluster-surface interaction is conducted over a realistic size and energy range, and a model is created to show how clusters accumulate. It is discovered that both the silver shells and the cobalt cluster cores exhibit limited epitaxy with the substrate, and that the contact produced is only a few atomic layers thick. The effect is higher for Ag shells than for Co cores, and it is not very energy dependent.

Study of 26 Galactic Open Clusters with Extended Main-sequence Turnoffs

Recent studies indicate that some Galactic open clusters(OCs)exhibit extended main-sequence turnoff(eMSTO)in their color–magnitude diagrams(CMDs).However,the number of Galactic OCs with eMSTO structures detected so far is limited,and the reasons for their formation are still unclear.This work identifies 26 Galactic OCs with undiscovered eMSTOs and investigates the causes of these features.Stellar population types and fundamental parameters of cluster samples are acquired using CMD fitting methods.Among them,the results of 11 OCs are reliable as the observed CMDs are well-reproduced.We propose the crucial role of stellar binarity and confirm the importance of stellar rotation in reproducing eMSTO morphologies.The results also show that the impact of age spread is important,as it can adequately explain the structure of young OCs and fit the observed CMDs of intermediate-age OCs better.

Adaptive Density-Based Spatial Clustering of Applications with Noise(ADBSCAN)for Clusters of Different Densities

Finding clusters based on density represents a significant class of clustering algorithms.These methods can discover clusters of various shapes and sizes.The most studied algorithm in this class is theDensity-Based Spatial Clustering of Applications with Noise(DBSCAN).It identifies clusters by grouping the densely connected objects into one group and discarding the noise objects.It requires two input parameters:epsilon(fixed neighborhood radius)and MinPts(the lowest number of objects in epsilon).However,it can’t handle clusters of various densities since it uses a global value for epsilon.This article proposes an adaptation of the DBSCAN method so it can discover clusters of varied densities besides reducing the required number of input parameters to only one.Only user input in the proposed method is the MinPts.Epsilon on the other hand,is computed automatically based on statistical information of the dataset.The proposed method finds the core distance for each object in the dataset,takes the average of these distances as the first value of epsilon,and finds the clusters satisfying this density level.The remaining unclustered objects will be clustered using a new value of epsilon that equals the average core distances of unclustered objects.This process continues until all objects have been clustered or the remaining unclustered objects are less than 0.006 of the dataset’s size.The proposed method requires MinPts only as an input parameter because epsilon is computed from data.Benchmark datasets were used to evaluate the effectiveness of the proposed method that produced promising results.Practical experiments demonstrate that the outstanding ability of the proposed method to detect clusters of different densities even if there is no separation between them.The accuracy of the method ranges from 92%to 100%for the experimented datasets.