Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

On the search for novel materials: insight and discovery through sharing of big data.

2,037 views

Published on

Plenary lecture of the XIV SBPMat Meeting, given by Prof. Claudia Draxl (Humboldt University, Germany) on October 1, 2015, in Rio de Janeiro (Brazil).

Published in: Science
  • Be the first to comment

  • Be the first to like this

On the search for novel materials: insight and discovery through sharing of big data.

  1. 1. Samsung Galaxy Round Philips Lumiblade
  2. 2. Level Properties Methods Size I Atomic positions and nuclear charges, properties of free atoms, symmetry, temperature, pressure Input: definition of material „gene” 10 kB - 10 MB II Total energy, electron density, potential, wavefunctions, atomic forces, optimized geometry, elastic constants, etc. Density-functional theory (DFT) and ab initio molecular dynamics (MD) 10 MB - 10 TB III Excitation energies, dielectric screening, matrix elements of Coulomb interaction, etc. optical spectra, electrical conductivity, phonon spectra, thermal conductivity, etc. Many-body perturbation theory (MBPT), DF perturbation theory, and ab initio MD 1 GB - 1 TB IV Efficiency of solar cell, thermoelectric figure of merit, turn-over frequency of catalyst, etc. as a function of temperature and pressure Modeling, output derived from levels I-III „phenotype” 10 kB - 1 MB
  3. 3. The NoMaD Repository is a joint effort by the groups of Matthias Scheffler, FHI Berlin and Claudia Draxl, HU Berlin, and the Computer Center of the Max-Planck Society.
  4. 4. Feb 6, 2015: “… That data underlying scientific publications are not available for confirmatory analysis, reuse, and repurposing is an anachronism that we aim to address. …”
  5. 5. https://www.youtube.com/watch?v=L-nmRSH4NQM
  6. 6. http://www.wpclipart.com Dmitri Mendeleev (1834-1907)
  7. 7. Arndt Bode LRZ Munich Alessandro De Vita Kings College London Claudia Draxl HU Berlin Daan Frenkel Univ. Cambridge Stefan Heinzel MPSCD Garching Francesc Illas Univ. Barcelona Kimmo Koski CSC Helsinki Jose Maria Cela BSC Barcelona Risto Nieminen Aalto Univ. Helsinki Ciaran Clissman Pintail Dublin Matthias Scheffler FHI Berlin Kristian Thygesen DTU Lyngby Angel Rubio MPSD Hamburg
  8. 8. Existing resources Conversion layers Big-data analytics WP4 VisualizeWP3 WP1 Search & retrieve WP2 WP7WP5 Dissemination & outreach WP2 WP1 WP6 HPC expertise & hardware
  9. 9. Calculate properties and functions, P, for many materials, i DFT Find the appropriate descriptor di; build a “table”: i di Pi Calculate properties and functions for new materials Find function P(d); do cross validation Statistical learning
  10. 10. Calculate properties and functions, P, for many materials, i DFT Find the appropriate descriptor di; build a “table”: i di Pi Calculate properties and functions for new materials Find function P(d); do cross validation Statistical learning
  11. 11. J. A. Van Vechten, PRB 182 , 891 (1969). J. C. Phillips, Rev. Mod. Phys. 42, 317 (1970). A. Zunger, PRB 22, 5839 (1980). D. G. Pettifor, Solid State Commun. 51, 31 (1984). Y. Saad, D. Gao, T. Ngo, S. Bobbitt, J. R. Chelikowsky, and W. Andreoni, PRB 85, 104104 (2012). L. Ghiringhelli J. Vybiral M. SchefflerS. Levchenko
  12. 12. d1 d2
  13. 13. zincblende rocksalt Eh, C related to band gap, dielectric constant, nearest-neighbor distance L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015). J. A. Van Vechten, PRB 182 , 891 (1969). J. C. Phillips, RMP 42, 317 (1970).
  14. 14. L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015). Free atoms Free dimers free atoms
  15. 15. zincblende rocksalt Eh, C related to band gap, dielectric constant, nearest-neighbor distance L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015). Descriptor ZA, ZB Z*A, Z*B 1D 2D 3D 5D MAE 1*10-4 3*10-3 0.12 0.08 0.07 0.05 MaxAE 8*10-4 0.03 0.32 0.32 0.24 0.20 MAE, CV 0.13 0.14 0.12 0.09 0.07 0.05 MaxAE, CV 0.43 0.42 0.27 0.18 0.16 0.12
  16. 16. L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015).
  17. 17. Relevanceofa newtechnology Time

×