Predicting and understanding structure and materials properties from first principles benefits heavily from the reach and relative computational ease of density fuctional methods today. For few-atom structures, serial structure screening, exhaustive structure predictions and meaningful time scales in molecular dynamics are now routinely possible; the ongoing challenges are at least two-fold:
(i) the affordability and accuracy of the physical approximations [in density functional theory (DFT), primarily the exchange-correlation functional], (ii) the affordability and accuracy of all other numerical approximations that lead to a total energy for a given structure. This talk covers some of our efforts to push the reach of first-principles methods past these limits. On the implementation side, the work is based on the numeric atom-centered orbital code package FHI-aims [1], which implements all-electron DFT and perturbative methods "beyond". The code is currently aimed at system sizes from a few up to a few thousand of atoms, handled efficiently in parallel from few-core computers up to massively parallel architectures. In particular, a goal has been to create a robust, conventional (matrix based) eigensolver framework [2] that does not become a botteneck for the goals mentioned above. In a nutshell, we are thus able to address structure and dynamics starting from small systems (e.g., few atom peptide molecules) but in large numbers (exploring conformational space) all the way up to large-scale nanostructured systems. For example, well-defined large-scale surface reconstructions can be effectively prepared and have a long history of use in experiment; in particular, we address Au(100 and Pt(100) [3]. We then show how biomolecular structure and dynamics can be accurately predicted for individual, large peptide molecules, here Polyalanine in direct comparison to gas-phase experiments [4,5]. Finally, we explore the potential of a first-principles "serial conformer screening" for systems which are not conclusively covered by faster coarse-grained models (force-fields): the case of ion-peptide interactions.
[1] V. Blum, R. Gehrke, F. Hanke, P. Havu, V. Havu, X. Ren, K. Reuter and M. Scheffler, Comput. Phys. Commun. 2009, 180, 2175-2196; http://www.fhi-berlin.mpg.de/aims/ .
[2] "Eigensolvers for Petaflop Applications (ELPA)". http://elpa.rzg.mpg.de .
[3] P. Havu, V. Blum, V. Havu, P. Rinke and M. Scheffler, Phys. Rev. B 2010, 82, 161418(R).
[4] A. Tkatchenko, M. Rossi, V. Blum, J. Ireta and M. Scheffler, Phys. Rev. Lett. 2011, 106, 118102.
[5] M. Rossi, V. Blum, P. Kupser, G. von Helden, F. Bierau, K. Pagel, G. Meijer and M. Scheffler, J. Phys. Chem. Lett. 2010, 1, 3465-3470.
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