Journal Of Applied and Computational Sciences in Mechanics

Journal Of Applied and Computational Sciences in Mechanics

Analysis of fracture behavior of carbon nitride poly crystalline by genetic algorithm and molecular dynamics methods

Document Type : Original Article

Authors
Mehdi Beynaghi 1
S. Rahnama 1
Ali Dadrasi 2
1 University of Birjand
2 Department of Mechanical Engineering, Faculty of Engineering, Hakim Sabzevari University, Sabzevar Iran
10.22067/jacsm.2023.83323.1192
Abstract
Nonlinear buckling caused by grain boundaries in two-dimensional structures and geometric defects are introduced as factors affecting the fracture behavior of these structures. Since the mechanical behavior of polycrystalline nanostructures is not well known, in this article, the mechanical behavior of carbon nitride nanosheets was studied as a function of temperature and grain boundaries. The mechanical performance of polycrystalline carbon nitride was tested in the presence and absence of edge cracks and at temperatures from 100 to 900 K. Molecular dynamics simulation was used as a cost-effective method for modeling two-dimensional nanosheets by choosing the appropriate potential function and boundary conditions. The results showed that the mechanical properties of carbon nitride monocrystalline decrease with increasing temperature and the results were reported in zigzag direction higher than armchair. The same trend was observed for the polycrystalline structures. The increase in temperature caused the mechanical features to decrease. Also, increasing the crack length from 5 to 25 angstroms caused a decrease in mechanical properties. On the other hand, increasing the number of regions for carbon nitride polycrystalline decreased the failure stress. In addition, the optimization was carried out by genetic algorithm and the results showed that the optimal value of Young's modulus for carbon nitride polycrystalline with 53 regions at a temperature of 586.95 K and a crack length of 6.52 angstroms is equivalent to 338.18 GPa. The results obtained from this study can be generalized to more complex cases to predict a deeper understanding of the next generations of two-dimensional structures.
Keywords
Carbon nitride
Mechanical properties
Simulation
Polycrystalline
Genetic algorithm
Molecular dynamics
Subjects
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