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Ground state of spin chain system by Density Functional Theory AITranslate

Vietnam National University Hanoi; Vietnam National University Hanoi
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Publisher: Elsevier
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Abstract AITranslate

The Cu–O based spin chain system A2CuO3 (A = Sr, Ca) has attracted considerable attention of scientists during the last decades due to its unique electronic structure. This paper presents a ground state optimization for the periodic structure of Ca2CuO3 using the Density Functional Theory (DFT). The electronic structure analysis was carried out on the basis of cell optimization using the PBE functional with DNP basis set. Until now, the numerical results were obtained only with exclusion of CaO bilayers from full ab initio treatment. We demonstrate here that the correct covalent insulating ground state may be obtained if the antiferromagnetic interaction along the spin chain is included. The best estimated band gap is 0.79 eV. We also show that the CaO bilayers sufficiently contributed to the distribution of d-states above Fermi level.

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DOI:https://doi.org/10.1016/j.commatsci.2010.04.002

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Citation Information:

The Cu–O based spin chain system A2CuO3 (A = Sr, Ca) has attracted considerable attention of scientists during the last decades due to its unique electronic structure. This paper presents a ground state optimization for the periodic structure of Ca2CuO3 using the Density Functional Theory (DFT). The electronic structure analysis was carried out on the basis of cell optimization using the PBE functional with DNP basis set. Until now, the numerical results were obtained only with exclusion of CaO bilayers from full ab initio treatment. We demonstrate here that the correct covalent insulating ground state may be obtained if the antiferromagnetic interaction along the spin chain is included. The best estimated band gap is 0.79 eV. We also show that the CaO bilayers sufficiently contributed to the distribution of d-states above Fermi level.

quote

GB/T 7714-2015 [1] Hoang Nam Nhat, Nguyen Thuy Trang. Computational Materials Science, 2010(49). DOI:10.1016/j.commatsci.2010.04.002.
MLA [1] Hoang Nam Nhat, and Nguyen Thuy Trang. Computational Materials Science, no. 49, 2010, https://doi.org/10.1016/j.commatsci.2010.04.002.
APA [1] Hoang Nam Nhat, & Nguyen Thuy Trang. (2010). Computational Materials Science(49). https://doi.org/10.1016/j.commatsci.2010.04.002
IEEE [1] Hoang Nam Nhat and Nguyen Thuy Trang, Computational Materials Science, no. 49, 2010, doi: 10.1016/j.commatsci.2010.04.002.