Analytical model based on cohesive energy to indicate the edge and corner effects on melting temperature of metallic nanoparticles

2010 ◽  
Vol 378 (1-3) ◽  
pp. 14-18 ◽  
Author(s):  
Reza Shidpour ◽  
H. Hamid Delavari ◽  
M. Vossoughi
Keyword(s):  
Melting Temperature ◽  
Analytical Model ◽  
Cohesive Energy ◽  
Metallic Nanoparticles ◽  
Model Based ◽  
Corner Effects

Size-dependent melting temperature of nanoparticles based on cohesive energy

2014 ◽  
Vol 28 (19) ◽  
pp. 1450157 ◽  
Author(s):  
Kai-Tuo Huo ◽  
Xiao-Ming Chen
Keyword(s):  
Melting Temperature ◽  
Cohesive Energy ◽  
Metallic Nanoparticles ◽  
Present Model ◽  
Packing Fraction ◽  
Size Dependent ◽  
Crystal Cell ◽  
K Factor ◽  
The Relationship ◽  
Crystalline Plane

Size-dependent melting temperature of metallic nanoparticles is studied theoretically based on cohesive energy. Three factors are introduced in the present model. The k factor, i.e. efficiency of space filling of crystal lattice is defined as the ratio between the volume of the atoms in a crystal cell and that of the crystal cell. The β factor is defined as the ratio between the cohesive energy of surface atom and interior atom of a crystal. The qs factor represents the packing fraction on a surface crystalline plane. Considering the β, qs and k factors, the relationship between melting temperature and nanoparticle size is discussed. The obtained model is compared with the reported experimental data and the other models.

scholarly journals Generalized analytical model based on harmonic coupling for hybrid plasmonic modes: comparison with numerical and experimental results

2015 ◽  
Vol 23 (21) ◽  
pp. 27376 ◽  
Author(s):  
Mitradeep Sarkar ◽  
Jean-François Bryche ◽  
Julien Moreau ◽  
Mondher Besbes ◽  
Grégory Barbillon ◽  
...  
Keyword(s):  
Analytical Model ◽  
Experimental Results ◽  
Model Based

scholarly journals CONSTRUCTION OF NEURAL NETWORK MODEL FOR STUDYING OF CRYSTAL STRUCTURES PROPERTIES

2021 ◽  
Author(s):  
Olga Uvarova ◽  
Sergey Uvarov
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Total Energy ◽  
Crystal Structures ◽  
Network Model ◽  
Neural Network Model ◽  
Cohesive Energy ◽  
Computational Experiment ◽  
Model Based ◽  
Artificial Neural

The paper considers a mechanism for constructing a model based on artificial neural network for obtaining the values of the cohesive energy of a system of atoms. Cohesive energy allows for calculation of total energy of system. It is one of the most important characteristics of a structure. A computational experiment is carried out for one-component crystal structures of Si, Ge and C.

scholarly journals An analytical model based on radiative heating for the determination of safety distances for wildland fires

2011 ◽  
Vol 46 (8) ◽  
pp. 520-527 ◽  
Author(s):  
J.L. Rossi ◽  
A. Simeoni ◽  
B. Moretti ◽  
V. Leroy-Cancellieri
Keyword(s):  
Analytical Model ◽  
Radiative Heating ◽  
Wildland Fires ◽  
Model Based
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