What is the coordination number of copper(ii) in metallosupramolecular chemistry?

2006 ◽  
Vol 30 (12) ◽  
pp. 1740 ◽  
Author(s):  
Val?rie Chaurin ◽  
Edwin C. Constable ◽  
Catherine E. Housecroft
Keyword(s):  
Coordination Number ◽  
Metallosupramolecular Chemistry

Bond-length distributions for ions bonded to oxygen: Results for the lanthanides and actinides and discussion of the f-block contraction

2017 ◽  
Author(s):  
Olivier Charles Gagné
Keyword(s):  
Bond Length ◽  
Coordination Number ◽  
Lanthanide Ions ◽  
Lanthanide Contraction ◽  
Trivalent Lanthanide ◽  
Actinide Ions

Bond-length distributions have been examined for eighty-four configurations of the lanthanide ions and twenty-two configurations of the actinide ions bonded to oxygen. The lanthanide contraction for the trivalent lanthanide ions bonded to O<sup>2-</sup> is shown to vary as a function of coordination number and to diminish in scale with increasing coordination number.

Elasticity of colloidal gels: structural heterogeneity, floppy modes, and rigidity

Soft Matter ◽  
2021 ◽  
Author(s):  
D. Zeb Rocklin ◽  
Lilian C Hsiao ◽  
Megan E Szakasits ◽  
Michael J Solomon ◽  
Xiaoming Mao
Keyword(s):  
Coordination Number ◽  
Volume Fraction ◽  
Structural Parameters ◽  
Structural Heterogeneity ◽  
Colloidal Gels ◽  
Shear Moduli ◽  
Rheological Measurements

Rheological measurements of model colloidal gels reveal that large variations in the shear moduli as colloidal volume-fraction changes are not reflected by simple structural parameters such as the coordination number,...

Metallosupramolecular Chemistry in Two Dimensions

2003 ◽  
Vol 15 (7-8) ◽  
pp. 549-555 ◽  
Author(s):  
Markus Schütte ◽  
Christa Stolle ◽  
Dirk G. Kurth
Keyword(s):  
Two Dimensions ◽  
Metallosupramolecular Chemistry

scholarly journals Estimating Contact Force Chains Using Artificial Neural Network

2021 ◽  
Vol 11 (14) ◽  
pp. 6278
Author(s):  
Mengmeng Wu ◽  
Jianfeng Wang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Particle Size ◽  
Granular Materials ◽  
Coordination Number ◽  
Contact Force ◽  
Force Chains ◽  
Granular System ◽  
Biaxial Test ◽  
Artificial Neural

The inhomogeneous distribution of contact force chains (CFC) in quasi-statically sheared granular materials dominates their bulk mechanical properties. Although previous micromechanical investigations have gained significant insights into the statistical and spatial distribution of CFC, they still lack the capacity to quantitatively estimate CFC evolution in a sheared granular system. In this paper, an artificial neural network (ANN) based on discrete element method (DEM) simulation data is developed and applied to predict the anisotropy of CFC in an assembly of spherical grains undergoing a biaxial test. Five particle-scale features including particle size, coordination number, x- and y-velocity (i.e., x and y-components of the particle velocity), and spin, which all contain predictive information about the CFC, are used to establish the ANN. The results of the model prediction show that the combined features of particle size and coordination number have a dominating influence on the CFC’s estimation. An excellent model performance manifested in a close match between the rose diagrams of the CFC from the ANN predictions and DEM simulations is obtained with a mean accuracy of about 0.85. This study has shown that machine learning is a promising tool for studying the complex mechanical behaviors of granular materials.

scholarly journals Atoms in Highly Symmetric Environments: H in Rhodium and Cobalt Cages, H in an Octahedral Hole in MgO, and Metal Atoms Ca-Zn in C20 Fullerenes

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1281
Author(s):  
Zikri Altun ◽  
Erdi Ata Bleda ◽  
Carl Trindle
Keyword(s):  
Density Functional Theory ◽  
Quantum Theory ◽  
Coordination Number ◽  
Electronic Structures ◽  
Density Functional ◽  
Functional Theory ◽  
Metal Atoms ◽  
Tetragonal Pyramidal ◽  
Non Covalent Interactions ◽  
Covalent Interactions

An atom trapped in a crystal vacancy, a metal cage, or a fullerene might have many immediate neighbors. Then, the familiar concept of valency or even coordination number seems inadequate to describe the environment of that atom. This difficulty in terminology is illustrated here by four systems: H atoms in tetragonal-pyramidal rhodium cages, H atom in an octahedral cobalt cage, H atom in a MgO octahedral hole, and metal atoms in C20 fullerenes. Density functional theory defines structure and energetics for the systems. Interactions of the atom with its container are characterized by the quantum theory of atoms in molecules (QTAIM) and the theory of non-covalent interactions (NCI). We establish that H atoms in H2Rh13(CO)243− trianion cannot be considered pentavalent, H atom in HCo6(CO)151− anion cannot be considered hexavalent, and H atom in MgO cannot be considered hexavalent. Instead, one should consider the H atom to be set in an environmental field defined by its 5, 6, and 6 neighbors; with interactions described by QTAIM. This point is further illustrated by the electronic structures and QTAIM parameters of M@C20, M=Ca to Zn. The analysis describes the systematic deformation and restoration of the symmetric fullerene in that series.

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