Global structural optimization and growth mechanism of cobalt oxide nanoclusters by genetic algorithm with spin-polarized DFT
Multi-convergence relaxation procedures within the genetic algorithm method refined by spin-polarized density functional theory were applied to search for the global and local minima of cobalt oxide nanoclusters ConOn(n�=�3−7). The study found new global minimum structures for the Co5O5and Co6O6...
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| Main Authors: | , , |
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| Format: | Article |
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Elsevier
2017
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| Subjects: | |
| Online Access: | http://eprints.um.edu.my/18829/ http://dx.doi.org/10.1016/j.jallcom.2016.11.153 |
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| Summary: | Multi-convergence relaxation procedures within the genetic algorithm method refined by spin-polarized density functional theory were applied to search for the global and local minima of cobalt oxide nanoclusters ConOn(n�=�3−7). The study found new global minimum structures for the Co5O5and Co6O6clusters, which are more stable than the best previous models. Through comparison with previous theoretical and experimental data, the genetic algorithm accurately predicted the global minima of Co3O3, Co4O4and Co7O7, and the stability of the planar-like Co4O4from the second-order energy difference calculation. Most interestingly, a new growth mechanism of ConOnfrom the planar-like to the compact as the global minimum structure was predicted that occurs at the Co5O5cluster. |
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