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Gamot, Ritchie Mae Tonzo
Languages: English
Types: Doctoral thesis
Subjects: QA
A modified version of the Intelligent Water Drops algorithm (MIWD) was developed then used to determine the most stable configurations of Lennard-Jones (LJ), Binary Lennard-Jones (BLJ) and Morse Clusters. The algorithm is unbiased in that it uses no a priori cluster geometry information or cluster seeds. Results for LJ clusters show that the algorithm is effective and efficient in rediscovering all clusters up to size N = 104 with better success rates specially on difficult clusters compared to previous best methodologies reported in literature. Results on more difficult systems, such as the Binary Lennard Jones clusters up to size 50 (with 5 different atomic size ratios) and Morse clusters up to size 60 (with 2 interparticle range potentials), also showed the ability of MIWD to handle more complex systems.\ud \ud MIWD was then applied to predict the most stable structures of Janus clusters up to size 50 and on size 100 using a LJ potential model with a modulated angular term suited for two-patched Janus particles. Results show that MIWD is able to find well-structured geometries of Janus clusters. It is believed that this has been the first time that a nature-inspired stochastic algorithm and a variant of the IWD algorithm has been applied to the configurational optimization of Janus clusters.
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