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

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Page 1: On the search for novel materials: insight and discovery through sharing of big data
Page 2: On the search for novel materials: insight and discovery through sharing of big data

Samsung Galaxy Round

Philips Lumiblade

Page 3: On the search for novel materials: insight and discovery through sharing of big data
Page 4: On the search for novel materials: insight and discovery through sharing of big data
Page 5: On the search for novel materials: insight and discovery through sharing of big data

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

Page 6: On the search for novel materials: insight and discovery through sharing of big data
Page 7: On the search for novel materials: insight and discovery through sharing of big data
Page 8: On the search for novel materials: insight and discovery through sharing of big data
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Page 10: On the search for novel materials: insight and discovery through sharing of big data

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.

Page 11: On the search for novel materials: insight and discovery through sharing of big data

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. …”

Page 12: On the search for novel materials: insight and discovery through sharing of big data

https://www.youtube.com/watch?v=L-nmRSH4NQM

Page 13: On the search for novel materials: insight and discovery through sharing of big data
Page 14: On the search for novel materials: insight and discovery through sharing of big data

http://www.wpclipart.com

Dmitri Mendeleev (1834-1907)

Page 15: On the search for novel materials: insight and discovery through sharing of big data
Page 16: On the search for novel materials: insight and discovery through sharing of big data

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

Page 17: On the search for novel materials: insight and discovery through sharing of big data
Page 18: On the search for novel materials: insight and discovery through sharing of big data
Page 19: On the search for novel materials: insight and discovery through sharing of big data

Existing resources

Conversion layers

Big-data analytics

WP4

Visualize WP3

WP1

Search & retrieve WP2

WP7 WP5

Dissemination & outreach

WP2

WP1

WP6 HPC expertise & hardware

Page 20: On the search for novel materials: insight and discovery through sharing of big data
Page 21: On the search for novel materials: insight and discovery through sharing of big data
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Page 27: On the search for novel materials: insight and discovery through sharing of big data

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

Page 28: On the search for novel materials: insight and discovery through sharing of big data

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

Page 29: On the search for novel materials: insight and discovery through sharing of big data
Page 30: On the search for novel materials: insight and discovery through sharing of big data

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. Scheffler S. Levchenko

Page 31: On the search for novel materials: insight and discovery through sharing of big data
Page 32: On the search for novel materials: insight and discovery through sharing of big data

d1

d2

Page 33: On the search for novel materials: insight and discovery through sharing of big data

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).

Page 34: On the search for novel materials: insight and discovery through sharing of big data

L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015).

Free atoms

Free dimers

free atoms

Page 35: On the search for novel materials: insight and discovery through sharing of big data
Page 36: On the search for novel materials: insight and discovery through sharing of big data

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

Page 37: On the search for novel materials: insight and discovery through sharing of big data

L.M. Ghiringhelli, J. Vybiral, S.V. Levchenko, C. Draxl, and M. Scheffler, PRL 114, 105503 (2015).

Page 38: On the search for novel materials: insight and discovery through sharing of big data
Page 39: On the search for novel materials: insight and discovery through sharing of big data

Rele

vanc

e of

a

new

tech

nolo

gy

Time

Page 40: On the search for novel materials: insight and discovery through sharing of big data