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이론 및 계산재료과학

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A primary goal of the research of the theoretical and computational materials physics group in KIAS is to understand and predict material properties at the most fundamental level using atomistic firstprinciples, or ab initio, quantum-mechanical calculations. A variety of different computational approaches are used that require only atomic numbers and positions as input. In the past, calculation results from such first principle methods have agreed with experiments excellently, except for some materials showing strong electron correlations. The computational materials physics group in KIAS has been engaged in research in the fields of computational condensed matter physics and (nano)material science. We have focused on materials of finite size or low dimensions, such as carbon nanostructures, complexes of organic molecules, nanoparticle clusters, and carbon nanomaterials on the bulk surfaces. Phenomena of interest include fundamental electronic and magnetic properties of nanomaterials, electron field emission properties, various spectroscopic signatures of materials such as scanning tunneling microscopic image and spectroscopy, angle-resolved photoemission spectroscopy and Raman spectroscopy, equilibrium and non-equilibrium charge transport, magnetism in organic materials and superconductivity, etc.

Theoretical and Computational Materials Figure 1

Figure 1

Calculated energy band structure of a zigzag graphene nanoribbon and their wavefunctions at different crystal momentum. By calculating wavefuctions from first-principles, we can learn special physical properties of this nanomaterial.(Reference, Y.-W. Son et al, PRL(06), Nature (06))

Theoretical and Computational Materials Figure 2

Figure 2

Simulated scanning tunneling microscope images of graphene grown on top of silicon carbide surfaces with different temperatures (the left image for graphene grown around 1100 C and the right for one around 1300 C). First-principle calculations help to understand atomic structures of the complex system by comparing simulated spectroscopic signals with experiments. (Reference. S. Kim et al, PRL(08))