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Related Concept Videos

Metallic Solids02:37

Metallic Solids

Metallic solids such as crystals of copper, aluminum, and iron are formed by metal atoms. The structure of metallic crystals is often described as a uniform distribution of atomic nuclei within a “sea” of delocalized electrons. The atoms within such a metallic solid are held together by a unique force known as metallic bonding that gives rise to many useful and varied bulk properties.
All metallic solids exhibit high thermal and electrical conductivity, metallic luster, and malleability. Many...
Coordination Number and Geometry02:57

Coordination Number and Geometry

For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.
Valence Bond Theory02:42

Valence Bond Theory

Coordination compounds and complexes exhibit different colors, geometries, and magnetic behavior, depending on the metal atom/ion and ligands from which they are composed. In an attempt to explain the bonding and structure of coordination complexes, Linus Pauling proposed the valence bond theory, or VBT, using the concepts of hybridization and the overlapping of the atomic orbitals. According to VBT, the central metal atom or ion (Lewis acid) hybridizes to provide empty orbitals of suitable...
Biasing of Metal-Semiconductor Junctions01:27

Biasing of Metal-Semiconductor Junctions

Biasing metal-semiconductor junctions involves applying a voltage across the junction. Specifically, the metal is connected to a voltage source, while the semiconductor is grounded. This technique is essential for controlling the direction and magnitude of current flow in electronic devices, including diodes, transistors, and photovoltaic cells.
In Schottky junctions, where the semiconductor is n-type, applying a positive voltage to the metal relative to the semiconductor reduces its Fermi...

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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry
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Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

Published on: April 8, 2020

Geometry optimization of bimetallic clusters using an efficient heuristic method.

Xiangjing Lai1, Ruchu Xu, Wenqi Huang

  • 1School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.

The Journal of Chemical Physics
|November 4, 2011
PubMed
Summary
This summary is machine-generated.

A new heuristic algorithm efficiently optimizes bimetallic cluster structures. This method combines monotonic basin-hopping with guided perturbation (MBH-GP) and iterated local search (ILS) to find new global minima.

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Area of Science:

  • Computational Chemistry
  • Materials Science
  • Cluster Physics

Background:

  • Determining the ground-state structure of bimetallic clusters is crucial for understanding their properties.
  • Traditional methods often struggle with the complexity and vast search space of cluster geometry optimization.

Purpose of the Study:

  • To propose and validate an efficient heuristic algorithm for the geometry optimization of bimetallic clusters.
  • To identify new putative global minima structures for various bimetallic systems.

Main Methods:

  • The algorithm integrates monotonic basin-hopping with guided perturbation (MBH-GP) for structural optimization.
  • It employs a surface optimization method for refining cluster geometries.
  • Iterated local search (ILS) is utilized to explore the potential energy surface for optimal homotops.

Main Results:

  • The proposed method was successfully applied to Cu-Au and Ag-Au bimetallic clusters.
  • It demonstrated high efficiency compared to existing literature methods.
  • Several new putative global minima structures were discovered for the studied systems.

Conclusions:

  • The developed heuristic algorithm is a promising tool for theoretical determination of bimetallic cluster ground-state structures.
  • The method offers significant improvements in efficiency and accuracy for complex cluster optimization problems.