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On the structure of Si(100) surface: importance of higher order correlations for buckled dimer.

ABSTRACT: We revisit a dangling theoretical question of whether the surface reconstruction of the Si(100) surface would energetically favor the symmetric or buckled dimers on the intrinsic potential energy surfaces at 0 K. This seemingly simple question is still unanswered definitively since all existing density functional based calculations predict the dimers to be buckled, while most wavefunction based correlated treatments prefer the symmetric configurations. Here, we use the doubly hybrid density functional (DHDF) geometry optimizations, in particular, XYGJ-OS, complete active space self-consistent field theory, multi-reference perturbation theory, multi-reference configuration interaction (MRCI), MRCI with the Davidson correction (MRCI + Q), multi-reference average quadratic CC (MRAQCC), and multi-reference average coupled pair functional (MRACPF) methods to address this question. The symmetric dimers are still shown to be lower in energy than the buckled dimers when using the CASPT2 method on the DHDF optimized geometries, consistent with the previous results using B3LYP geometries [Y. Jung, Y. Shao, M. S. Gordon, D. J. Doren, and M. Head-Gordon, J. Chem. Phys. 119, 10917 (2003)]. Interestingly, however, the MRCI + Q, MRAQCC, and MRACPF results (which give a more refined description of electron correlation effects) suggest that the buckled dimer is marginally more stable than its symmetric counterpart. The present study underlines the significance of having an accurate description of the electron-electron correlation as well as proper multi-reference wave functions when exploring the extremely delicate potential energy surfaces of the reconstructed Si(100) surface.

SUBMITTER: Back S

PROVIDER: S-EPMC3683056 | biostudies-other | 2013 May

REPOSITORIES: biostudies-other

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Project description:In brain imaging, accurate alignment of cortical surfaces is fundamental to the statistical sensitivity and spatial localisation of group studies, and cortical surface-based alignment has generally been accepted to be superior to volume-based approaches at aligning cortical areas. However, human subjects have considerable variation in cortical folding, and in the location of functional areas relative to these folds. This makes alignment of cortical areas a challenging problem. The Multimodal Surface Matching (MSM) tool is a flexible, spherical registration approach that enables accurate registration of surfaces based on a variety of different features. Using MSM, we have previously shown that driving cross-subject surface alignment, using areal features, such as resting state-networks and myelin maps, improves group task fMRI statistics and map sharpness. However, the initial implementation of MSM's regularisation function did not penalize all forms of surface distortion evenly. In some cases, this allowed peak distortions to exceed neurobiologically plausible limits, unless regularisation strength was increased to a level which prevented the algorithm from fully maximizing surface alignment. Here we propose and implement a new regularisation penalty, derived from physically relevant equations of strain (deformation) energy, and demonstrate that its use leads to improved and more robust alignment of multimodal imaging data. In addition, since spherical warps incorporate projection distortions that are unavoidable when mapping from a convoluted cortical surface to the sphere, we also propose constraints that enforce smooth deformation of cortical anatomies. We test the impact of this approach for longitudinal modelling of cortical development for neonates (born between 31 and 43 weeks of post-menstrual age) and demonstrate that the proposed method increases the biological interpretability of the distortion fields and improves the statistical significance of population-based analysis relative to other spherical methods.

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On the structure of Si(100) surface: importance of higher order correlations for buckled dimer.

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