RC
R. Calegari
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This thesis aims to enhance the understanding of quasicrystal formation by integrating global geometry optimization and atomic simulations using the Oscillating Pair Potential (OPP). Quasicrystals, with non-periodic long-range order and forbidden rotational symmetries, have captivated scientists since their discovery. This research combines the use of OPP and geometry optimization techniques to investigate the energetically stable structures of quasicrystalline materials.
The core of the thesis revolves around the implementation of the aforementioned computational methods using the HOOMD-blue Python package. Simulations explore clusters with varying numbers of atoms under different potentials, comparing the stable structures formed. The results provide valuable insights into the formation of icosahedral quasicrystals.
This study contributes to the understanding of quasicrystal formation, unlocking new possibilities for material design and technological advancements. ...
The core of the thesis revolves around the implementation of the aforementioned computational methods using the HOOMD-blue Python package. Simulations explore clusters with varying numbers of atoms under different potentials, comparing the stable structures formed. The results provide valuable insights into the formation of icosahedral quasicrystals.
This study contributes to the understanding of quasicrystal formation, unlocking new possibilities for material design and technological advancements. ...
This thesis aims to enhance the understanding of quasicrystal formation by integrating global geometry optimization and atomic simulations using the Oscillating Pair Potential (OPP). Quasicrystals, with non-periodic long-range order and forbidden rotational symmetries, have captivated scientists since their discovery. This research combines the use of OPP and geometry optimization techniques to investigate the energetically stable structures of quasicrystalline materials.
The core of the thesis revolves around the implementation of the aforementioned computational methods using the HOOMD-blue Python package. Simulations explore clusters with varying numbers of atoms under different potentials, comparing the stable structures formed. The results provide valuable insights into the formation of icosahedral quasicrystals.
This study contributes to the understanding of quasicrystal formation, unlocking new possibilities for material design and technological advancements.
The core of the thesis revolves around the implementation of the aforementioned computational methods using the HOOMD-blue Python package. Simulations explore clusters with varying numbers of atoms under different potentials, comparing the stable structures formed. The results provide valuable insights into the formation of icosahedral quasicrystals.
This study contributes to the understanding of quasicrystal formation, unlocking new possibilities for material design and technological advancements.