Three-layer Cluster Research Articles

Cluster Self-Organization of Intermetallic Systems: New Four-Layer Clusters K339 = Tb@18@42@86@192 and Three-Layer Clusters K147 = Tb@18@42@86) and K124 = 0@8@26@90 in the Crystal Structure of Tb117Fe52Ge112-cF1124

Cluster Self-Organization of Intermetallic Systems: New Four-Layer Clusters K339 = Tb@18@42@86@192 and Three-Layer Clusters K147 = Tb@18@42@86) and K124 = 0@8@26@90 in the Crystal Structure of Tb117Fe52Ge112-cF1124

Cluster Self-Organization of Intermetallic Systems: Three-Layer Clusters K159A = 1@16@44@98 and K159B = 1@14@40@104 and Two-Layer Clusters K61 = 1@16@44 and K26 = 0@4@22 in the Crystalline Structure Ta156Al288-cF444

Cluster Self-Organization of Intermetallic Systems: Three-Layer Clusters K159A = 1@16@44@98 and K159B = 1@14@40@104 and Two-Layer Clusters K61 = 1@16@44 and K26 = 0@4@22 in the Crystalline Structure Ta156Al288-cF444

Anonymous node location based on clustering

With the rapid development of network technology, the network’s scale is increasing and becoming more complex. It is imperative to understand the structure of the network for network management and network security. Therefore, the construction of the routing topology has become a top priority. Routing topology analysis is already a relatively mature technology, but anonymous nodes’ positioning has not received enough attention. Nowadays, the primary solutions to anonymous nodes are graph analysis and tomographic tree construction. Based on these two methods, this paper proposes a rough location of anonymous nodes based on the method of three-level clustering. They are the K-means clustering of data before anonymous identification, hierarchical clustering of feature values in anonymous identification, and central point calculation based on clustering ideas during anonymous positioning. Experiments have proved that performing the first-level K-means clustering before anonymous node identification can effectively improve anonymous positioning accuracy. And the three-layer clustering idea proposed in this paper can roughly get the location of anonymous nodes based on reducing the complexity of the original method.

Cluster Self-Organization of Intermetallic Systems: K66 and K130 Clusters for the Self-Assembly of the K78In160-hP238 Crystal Structure and K17 Clusters for the Self-Assembly of the K8In11-hR114 Crystal Structure

The combinatorial topological analysis and modeling of self-assembly of the K78In160-hP238 (space group P-3m1, a = b = 17.211, c = 28.888 A, V = 7410 A3) and K8In11-hR114 (space group R-3c, a = b = 10.021 A, c = 50.891 A, V = 4426 A3) crystal structures are performed by computer methods (the ToposPro software package). Icosahedra In12 (with the -3m symmetry) are the templates on which three-layer clusters K130 = 0@12(In12)@30(In12K18)@86(K20In66) with the diameter of 17 A are formed. The two-layer cluster K66 formed on Friauf polyhedra K(K4In12) (with 3m symmetry) has a chemical composition of shells K@16(K4In12)@49(K16In33) and a diameter of 14 A. The K130 and K66 nanoclusters are framework-forming and involved in the formation of 2D layers A and B, respectively, thus forming a three-layer B–A–B package. The In12 clusters (with the -3m symmetry), In8 hexagonal bipyramids (with the 3m symmetry), and K spacer atoms are located in the voids of the layer of the K66 clusters. The three-layer package thickness corresponds to the value of the translation vector modulus c = 28.888 A. The framework structure is formed by linking the three-layer B–A–B packages in the [001] direction. The cluster precursor K17 = 0@In11K6 is installed for K8In11-hR114 in the form of a triangular In5 bipyramid on six faces of which In atoms are located with six bound potassium atoms. The microlayer is formed when the primary chains are bound in the (001) plane with a shift. The localization of the K spacer atoms takes place in the layer. The microframework of the structure is formed when the microlayers are bound with a shift.

Cluster Self-Organization of Intermetallic Systems: New Four-Layer Cluster Precursor K244 = 0@12@20@80@132 and New Three-Layer Cluster Precursor K245 = 1@14@48@206 in the Rh140Al403-cP549 and Mn18Pd138Al387-cP549 Crystal Structures

The geometric and topological analysis of the crystal structure of (i) the Rh140Al403-cP549 intermetallide with cubic cell parameters a = 19.9350 A, V = 7922.25 A3, and the Pm-3 space group and (ii) the Mn18Pd138Al387-cP549 intermetallide with cubic cell parameters a = 20.211 A and Pm-3 space group is conducted by the ToposPro program package. Two new cluster precursors with the symmetry -43m is established: the K244 = 0@12@20@80@132 four-layer cluster with an inner icosahedron Pd12 or Rh12 and the three-layer cluster K245 = 1@14@48@206 with an inner 15-atom polyhedron Al@Pd8Al6 or Al@Rh8Al6. The symmetric and topological code of self-assembly processes of 3D structures from K244 and K245 nanocluster precursors is reconstructed in the following form: primary chain → microlayer → microframework. MAl3 and M2Al2 (M = Rh or Pd) clusters bound by Al atoms were adjusted as spacers occupying voids in the 3D framework of the K242 and K245 nanoclusters.

Cluster Self-Organization of Intermetallic Systems: New Three-Layer Cluster Precursor K136 = 0@Zn12@32(Mg20Zn12)@92(Zr12Zn80) and a New Two-Layer Cluster Precursor K30 = 0@Zn6@Zn24 in the Crystal Structure of Zr6Mg20Zn128-cP154

Using computer methods (ToposPro software package), the geometrical and topological analysis of the crystal structure of the Zr6Mg20Zn128-cP154 intermetallic compound with cubic cell parameters a = 13.709 A, V = 2576.42 A3, and space group Pm-3 is carried out. Two new nanocluster precursors with the ‑43m symmetry are determined: a three-layer K136 nanocluster of the 0@Zn12@32(Mg20Zn12@92(Zr12Zn80) composition with an internal icosahedron 0@Zn12 and 12 Zr atoms and 20 Zn atoms in 60-atomic Zn-shell and a two-layer K30 nanocluster of the 0@Zn6@Zn24 composition with an internal Zn6-octahedron and 24 Zn atoms in the external shell. The symmetrical and topological codes of the self-assembly processes of 3D structures from K136 and K30 nanocluster precursors are reconstructed in the following form: primary chain → microlayer → microframework. The Zn2 dimers are determined as the spacers occupying the voids in the 3D framework from K136 and K30 nanoclusters.

Trust-based energy-efficient routing protocol for Internet of things–based sensor networks

Internet of things grew swiftly and many services, software, sensors-embedded electronic devices and related protocols were developed and still in progress with full swing. Internet of things enabling physically existing things to see, hear, think and perform a notable task by allowing them to talk to each other and share useful information while making decision and caring-on/out their important tasks. Internet of things is greatly promoted by wireless sensor network as it becomes a perpetual layer for it. Wireless sensor network works as a base-stone for most of the Internet of things applications. There are severe general and specific threats and technical challenges to Internet of things–based sensor networks which must overcome to ensure adaptation and diffusion of it. Most of the limitations of wireless sensor networks are due to its resource constraint objects nature. The specified open research challenges in Internet of things–based sensor network are power consumption, network lifespan, network throughput, routing and network security. To overcome aforementioned problems, this work aimed to prolong network lifetime, improve throughput, decrease packet latency/packet loss and further improvise in encountering malicious nodes. To further tune the network lifetime in terms of energy, wireless harvesting energy is suggested in proposed three-layer cluster-based wireless sensor network routing protocol. The proposed mechanism is a three-tier clustering technique with implanted security mechanism to encounter malicious activities of sensor nodes and to slant them into blacklist. It is a centred-based clustering protocol, where selection of cluster head and grid head is carried out by sink node based on the value of its cost function. Moreover, hardware-based link quality estimators are used to check link effectiveness and to further improve routing efficiency. At the end, excessive experiments have been carried out to check efficacy of the proposed protocol. It outperforms most of its counterpart protocols such as fuzzy logic–based unequal clustering and ant colony optimization–based routing hybrid, Artificial Bee Colony-SD, enhanced three-layer hybrid clustering mechanism and energy aware multi-hop routing in terms of network lifetime, network throughput, average energy consumption and packet latency.

Cluster Self-Organization of Intermetallic Systems: New Three-Layer Cluster K142 for the Self-Assembly of the K44In80-hR366 Crystal Structure and the Bergman Tetracluster K141 for the Self-Assembly of the K34In82-cF464 Crystal Structure

Cluster Self-Organization of Intermetallic Systems: New Three-Layer Cluster K142 for the Self-Assembly of the K44In80-hR366 Crystal Structure and the Bergman Tetracluster K141 for the Self-Assembly of the K34In82-cF464 Crystal Structure

THS-IDPC: A three-stage hierarchical sampling method based on improved density peaks clustering algorithm for encrypted malicious traffic detection

With the rapid increase in amount of network encrypted traffic and malware samples using encryption to evade identification, detecting encrypted malicious traffic presents challenges. The quality of the encrypted traffic sampling method directly affects the result of malware detection, but most existing machine learning methods for sampling flow-based encrypted traffic data are inherently inaccurate. To solve these problems, an innovative three-stage hierarchical sampling approach based on the improved density peaks clustering algorithm (THS-IDPC) is proposed to enhance the accuracy and efficiency of encrypted malicious traffic detection model. First, we propose an improved density peaks clustering algorithm based on grid screening, custom center decision value and mutual neighbor degree (DPC-GS-MND). In DPC-GS-MND, grid screening effectively reduces the computational complexity and mutual neighbor degree improves the clustering accuracy. Then, we extract and research the three categories features of encrypted traffic data related to malicious activities, and adopt a three-layer hierarchical clustering algorithm based on DPC-GS-MND. Finally, a three-stage sampling approach based on the three-layer hierarchical clustering algorithm (THS-IDPC) is proposed to sample the encrypted traffic data for further deep detection. The experimental results demonstrated that the proposed THS-IDPC is very effective to reduce normal traffic from massive network encrypted traffic simultaneously, and the encrypted malicious traffic detection model with THS-IDPC sampling method can detect multiple encrypted malicious traffic families with higher accuracy and efficiency. Meanwhile, DPC-GS-MND and THS-IDPC have good application prospects in network intrusion detection system under the big data environment.

Mobility-Aware Hierarchical Clustering in Mobile Wireless Sensor Networks

Wireless sensor networks (WSNs) are one of the chief enabling technologies for the Internet of Things. These networks are severely resource-constrained which calls for designing energy-efficient and effective routing techniques. The hierarchical- or clustering-based routing approaches have shown to improve both energy-efficiency and scalability in WSNs. However, when clustering is implemented in mobile WSNs (MWSNs), the mobility of sensor nodes results in high data loss due to possible dis-association of nodes with their cluster heads which negatively affects the data rates and energy consumption. In order to mitigate the impact of node mobility on clustering, we propose two mobility-aware hierarchical clustering algorithms for MWSN based on three-layer clustering hierarchy: mobility-aware centralized clustering algorithm (MCCA) and mobility-aware hybrid clustering algorithm (MHCA). The MCCA algorithm employs centralized gridding at both layers of clustering hierarchy, and the MHCA algorithm employs centralized gridding at the upper layer and distributed clustering at the lower layer. The simulation results show that our proposed algorithms improve network lifetime, reduce energy consumption, stabilize cluster formation, and enhance data rates in mobile sensor networks. We also observe that the centralized clustering approach is superior to the hybrid clustering approach.

Theoretical Study of Site Dependency on Charge Transfer at Au(111) Nanoclusters

Molecular clusters of gold built from Au(111) layers, namely, Au18, Au19, Au27, and Au28 have been designed and optimized using the density functional theory (DFT) approach (B3LYP) with the LANL2DZ basis. The Au27 and Au18 species are perfect three- and two-layer cluster models, respectively, while Au28 and Au19 each include an extra Au dopant atom. Charge distribution calculations on the above moieties reveal that there is an extra charge build-up at corner atoms. The same general result has been obtained when various dopant atoms such as Cu, Pd, Ag, and Pt have been utilized in the above two- and three-layer cluster models. O2 adsorption on Au27 and Au28 clusters has been investigated, and different interaction behaviors have been observed. In the former perfect cluster case, the interaction has resulted in the O2 molecule losing some electric charge and thereby having a shorter bond. On the other hand, the O2 bond distance slightly increases via interaction with the imperfect Au28 cluster species.

Graphene Signal Mixer for Sensing Applications

A multilayer graphene device performing as a chemistry-based signal mixer is shown by a theoretical–experimental approach. We find current fluctuations across a three-layer graphene cluster using a combination of density functional and Green’s function theories. We suggest that these current fluctuations are due to the effect of the external bias on plasmons created from electron delocalization in graphene plates. The bias potentials affect the intrinsic behavior of the electron density corresponding to the frontier orbitals and perhaps other energetically near orbitals. The theoretical finding suggests that if the sheets of graphene show a plasmon behavior they may be used to mix signals of different frequencies. We corroborate this suggestion performing a proof-of-concept experiment on a sample of few-layer graphene by introducing two signals of different frequencies. We find experimentally that the recovered output contains the input frequencies, their sum and differences, as well as their second- and ...

Effect of Solvation on the Oxygen Reduction Reaction on Pt Catalyst

Previous models of PEM fuel cells have not explicitly considered the effect of a bulk water layer on the mechanism of the oxygen reduction reaction. The dominant mechanism is considered to be PtO2+H++e−→PtO2H, PtO2H→PtO+PtOH, PtO+H++e−→PtOH, and PtOH+H++e−→PtOH2. Using the B3LYP functional with the LANL2DZ basis set and effective core potential on Pt and the CC-pVDZ basis set on O and H with two clusters, the first a planar Pt10 cluster and the second a three-layer Pt20 cluster, we have considered the effect of a solvation model consisting of two stacked hexagonal water structures with another water in the center above a hexagon of surface Pt atoms. We find that dissociation of O2H is much less favorable on the water covered surface as compared to the bare surface unless at least one water molecule is removed to create two adjacent surface Pt atoms. We find an H2O·O2 complex, where one H2O has been turned so as to form a hydrogen bond with the O2, and this complex can be viewed as the branch point in the mechanism. O2 can be reduced to HO2, which can dissociate to OH plus O if at least one water is removed from the surface. Alternatively, we find a new low energy pathway: H2O+O2→OH+HO2, HO2+H2O→H2O2+OH, and H2O2→OH+OH. This reaction sequence is found to be all downhill or thermoneutral. We believe both of these pathways are involved in the oxygen reduction reaction in PEM fuel cells.

Hybrid DFT and hyper-GGA DFT studies of the CO adsorption on Pt nanoclusters: Effects of the cluster size and better CO LUMO description

CO adsorptions on six model Pt nanoclusters were studied using the B3LYP, BMK and M05-2X methods. BMK and M05-2X gave a better unbound description of CO 2π ∗ LUMO. The B3LYP results show no observable preference as reported earlier in other calculations. For BMK, the CO prefers to adsorb on top site except for Pt 10-6-3 and Pt 9-9-9. For M05-2X, top-site preference exists in the two-layer Pt 10-6, Pt 19-12 and the three-layer Pt 9-9-9, but does not exist in other three-layer Pt clusters. Although BMK and M05-2X give the better LUMO of CO molecule, the poor description of the Pt band gap may cause problems in the site preference when the size increases.

A study of oxygen dissociative adsorption on close-packed metal surfaces using a hybrid analytical approach

The adiabatic and nonadiabatic formalisms developed for calculations of the X2 molecule dissociative adsorption on metal surfaces are reviewed. The adiabatic formalism is extended here to account for the tunnel effect along the reaction coordinate. This approach is applied for calculating the activation energies, and rate constants associated with oxygen dissociative adsorption on close-packed metal surfaces of Pd, Pt, Rh, Ir, Ru, and Ni. Published information and data calculated in this work from a density functional treatment of a three-layer cluster model are used to determine the geometric and spectroscopic characteristics of atomic and molecular oxygen adsorbed on these surfaces. Results of the calculations are compared with published theoretical and experimental activation energies. The tunnel effect on the preexponential factor and on the activation energy of oxygen dissociative kinetic is discussed. A relationship between the kinetic and the corresponding thermodynamic characteristics of the reactions is considered.

Multiple structural transformations in Lennard-Jones clusters: Generic versus size-specific behavior

The size-temperature "phase diagram" for Lennard-Jones clusters LJn with sizes up to n=147 is constructed based on the analysis of the heat capacities and orientational bond order parameter distributions computed by the exchange Monte Carlo method. Two distinct types of "phase transitions" accompanied by peaks in the heat capacities are proven to be generic. Clusters with Mackay atom packing in the overlayer undergo a lower-temperature melting (or Mackay-anti-Mackay) transition that occurs within the overlayer. All clusters undergo a higher-temperature transition, which for the three-layer clusters is proven to be the 55-atom-core-melting transition. For the two-layer clusters, the core/overlayer subdivision is ambiguous, so the higher-temperature transition is better characterized as the breaking of the local icosahedral coordination symmetry. A pronounced size-specific behavior can typically be observed at low temperatures and often occurs in clusters with highly symmetric global minima. An example of such behavior is LJ135, which undergoes a low-temperature solid-solid transition, besides the two generic transitions, i.e., the overlayer reconstruction and the core melting.

Dissociation of molecular oxygen on unpromoted and cesium promoted Ag(110) surfaces

We have computed the binding energies for the molecular and atomic chemisorbed states of oxygen, and barriers between them, for a three-layer model cluster representative of the (110) face of silver as a function of cesium coverage. To increase computational efficiency, a one-electron potential was developed for the third layer of the silver atoms making up the model cluster. These calculations predict a barrier of ∼17 kcal/mol to dissociate chemisorbed O 2, in good agreement with experiment. When a Cs atom is added to the cluster, the barrier for O 2 dissociation is significantly lowered. However, when two Cs atoms were added the barrier for dissociation increased relative to the barrier for the cluster with one adsorbed Cs atom. These calculations predict that the dissociation of chemisorbed molecular oxygen will have a Cs coverage dependence. This dissociation pattern is consistent with prior calculations on Ag(111) model clusters.

A Fuzzy Modelling Approach Using Hierarchical Neural Networks

A simple and effective fuzzy modelling approach is presented in this paper. A three-layer hierarchical clustering neural network is developed to build fuzzy rule-based models from numerical data. Differing from existing clustering-based methods, in this approach the structure identification of the fuzzy model is implemented on the basis of a class of subclusters created by a self-organising network instead of on raw data. By combined use of unsupervised and supervised learning, both structure identification and parameter optimisation of the fuzzy model can be carried out automatically. The simulation results show that the proposed method can provide good model structure for fuzzy modelling and has high computing efficiency.

Density-functional cluster study of K adsorption on GaAs(110) surface

Local density approximation of the density-functional theory has been used to investigate K adsorption on a GaAs(110) surface. The surface is modeled by finite hydrogen-bonded clusters and two different formalisms (Slater–Vosko–Wilk–Nusair and Becke–Lee–Yang–Paar) for the exchange-correlation energies are used. All the clusters representing the GaAs(110) surface are found to be stable at the correlated levels of theory and the binding energy, in general, increases with the number of atoms in the cluster. The most stable cluster is found to be the three-layer cluster, Ga4As5H11 followed by Ga5As4H12 which were considered for the study of chemisorption. Of the three sites considered for K adsorption on an ideal surface, sites I and II, are found to be stable, whereas site III is unstable. Site II is the most favorable site for K adsorption with a chemisorption energy of 2.09 eV, which is comparable to the second-order many-body perturbation theory (MP2) value of 2.02 A. The equilibrium distance of the adato...

Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network

In this paper, we propose a new scheme for off-line recognition of totally unconstrained handwritten numerals using a simple multilayer cluster neural network trained with the backpropagation algorithm and show that the use of genetic algorithms avoids the problem of finding local minima in training the multilayer cluster neural network with gradient descent technique, and improves the recognition rates. In the proposed scheme, Kirsch masks are adopted for extracting feature vectors and a three-layer cluster neural network with five independent subnetworks is developed for classifying similar numerals efficiently. In order to verify the performance of the proposed multilayer cluster neural network, experiments with handwritten numeral database of Concordia University of Canada, that of Electro-Technical Laboratory of Japan, and that of Electronics and Telecommunications Research Institute of Korea were performed. For the case of determining the initial weights using a genetic algorithm, 97.10%, 99.12%, and 99.40% correct recognition rates were obtained, respectively.