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Functional magnetic materials by DFT. The Quest for Ultra-High-Density Magnetic Recording. K u. : Anisotropy. V: Grain v

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Large scale ab initio simulations of functional magnetic materials M. E. Gruner Department of Physics, University of Duisburg-Essen, 47048 Duisburg, Germany

G. Rollmann, A. Hucht, A. Dannenberg, P. Entel A.T. Zayak, W. A. Adeagbo

Functional magnetic materials by DFT

The Quest for Ultra-High-Density Magnetic Recording •

Exponential increase in storage densities in the past → still going on Recent values: ~ 600 GBit/in2 → long term goal: 10-50 TBit/in2



Major obstacle for media: Superparamagnetic limit

High-anisotropy recording materials: Increasing Ku to decrease V

 Ku V  kBT

 N   0 exp 

 Ku: Anisotropy   V: Grain volume

Patterned media: One particle per bit Current media:

Fe, Co Pt

c

a

L10: Fct layered along c-axis with c/a < 1

L10-FePt: Ku  7 · 107 erg/cm3 L10-CoPt: Ku  5 · 107 erg/cm3

0

1

1

Sun et al., Science 287, 1989 (2000)

Functional magnetic materials by DFT

FePt-Nanoparticles from Gas-Phase Experiments Cuboctahedron: Single crystalline fct

Decahedron: Multiply twinned fct

2 nm

2 nm HRTEM images of ordered Fe-Pt nanoparticles (O. Dmitrieva, et al.)

Multiple twinning incompatible with large magnetocrystalline anisotropy! Fabrication of fct L10-FePt nanoparticles increasingly difficult with decreasing sizes

Functional magnetic materials by DFT

Surface vs. volume energy Toy model: Potential energy in Lennard-Jones particles [E. g.: Doye, Miller and Wales, J. Chem. Phys. 111, 8417 (1999); Doye and Calvo, PRL 86, 3570 (2001)]



Icosahedron: lower surface energy



Cuboctahedron (fcc): No twinning, lower core energy MEG, G.Rollmann, A. Hucht, P. Entel, in: Advances in Solid State Physics, vol. 47, Springer, Berlin (2008) p. 117

→ Competition of structures as a function of particle size

Functional magnetic materials by DFT

Density functional theory calculations of large systems

[Kresse and Furthmüller, PRB 54, 11169 (1996); Kresse and Joubert, PRB 59, 1758 (1999)]



Plane wave basis (Ecut = 268 eV)



Reciprocal space integration restricted to Γ-point



PAW method for interaction with core and nuclei



GGA exchange correlation functional (PW91)



Colinear spin moments



Structure optimization on the Born-Oppenheimer surface using conjugate gradient method

Fe561: • • •

Diameter: Valence electrons: Memory requirement:

 2.5 nm 4488 66 GByte

Functional magnetic materials by DFT

Scaling of the numerical demand on a single CPU IBM Blue Gene/L, PPC440d

JUGENE (#6 on top500.org)

Functional magnetic materials by DFT

Efficiency of VASP on the BlueGene/L: Scaling of Fe561 IBM Blue Gene/L      

1024 nodes in one rack 2xPPC440d @ 700MHz (double FPU) per node 512 MBytes per node 3-fold high-speed communication network No virtual memory, restricted OS on nodes Air cooled…

IBM Blue Gene/P    

1024 nodes in one rack 4xPPC450d @ 850MHz (double FPU) per node 2 GByte per node SMT on node possible

BG/L Reasonable scaling up to1024 cores

Functional magnetic materials by DFT

Efficiency of VASP on the BlueGene/L: Scaling of Fe561 IBM Blue Gene/L      

1024 nodes in one rack 2xPPC440d @ 700MHz (double FPU) per node 512 MBytes per node 3-fold high-speed communication network No virtual memory, restricted OS on nodes Air cooled…

35 %

Quad-Opteron: Good scaling only up to ~100 cores

BG/L: Reasonable scaling up to1024 cores

Functional magnetic materials by DFT

Structure of nanoclusters: Size dependence • N  O (102): Systematical scan of potential energy surface impossible  Educated guess of favorable structures  Restriction to “magical” cluster numbers: Na = 1/3 ( 10 n3 + 15 n2 + 11 n + 3) = 13, 55, 147, 309, 561, 923…

Available morphologies:    

n: number of complete geometrical shells

perfect icosahedra perfect cuboctrahedra (fcc) truncated decahedra bcc (Bain-transformed cuboctahedra)

• For binary particles: Compositional degrees of freedom…

Functional magnetic materials by DFT

Structural Transformations: Bain and Mackay Path

FCC↔BCC: Bain-transformation

Ico↔Cubo: Mackay-transformation

E. C. Bain, Trans. Am. Inst. Min. Met. Eng. 70, 25 (1924)

A. L. Mackay, Acta Cryst. 15, 916 (1962)

Functional magnetic materials by DFT

Ground-State Properties of Fe-Nanoparticles

ΔE  290 K

G. Rollmann, MEG, A. Hucht et al., PRL 99, 083402 (2007)

• •

Exp.: Billas et al., PRL 71, 4067 (1993)

Lowest energy for BCC (Bain transformed Cubo) for N ≥ 147 Ico and Cubo unstable against transformation along Mackay-path

Functional magnetic materials by DFT

Shell-wise Mackay transformation (SMT) in Fe561

Gradual transformation from icosahedron to cuboctahedron towards the center

Functional magnetic materials by DFT

Common Neighbor Analysis of SMT Fe561 Standard tool for structure identification:

Jónsson and Andersen, PRL 60, 2295 (1988) Faken and Jónsson, Comp. Mat. Sci. 2, 279(1994)

body centered cubic

cuboctahedron (fcc)



icosahedron

Outermost shells prefer bcc-like coordination, the core remains fcc G.Rollmann, MEG, A. Hucht et al., PRL 99, 083402 (2007)

Functional magnetic materials by DFT

Size dependent properties of Fe-Pt Nanoparticles • Binary system → variety of morphologies to be considered: Cuboctahedra, icosahedra, decahedra, ordered/disordered,core-shell • Calculations iso-stoichiometric (for each size), composition according to L10-ordered cuboctahedron • Two [001] surfaces covered by one element: cPt≠cFe • [001] surfaces preferred by Pt → cPt>cFe MEG, J. Phys. D: Appl. Phys., 41, 134015

Functional magnetic materials by DFT

Morphologies of Fe-Pt Particles

L10-Ordered Cuboctahedron

Disordered Cuboctahedron

Disordered Icosahedron

Disordered Decahedron

Core-Shell Icosahedra Ordered Decahedron

ΔE  300 K

MEG, G.Rollmann, P. Entel, M. Farle, PRL 100, 087203 (2008)

Ordered Icosahedron

“Alternating” Icosahedra

Functional magnetic materials by DFT

Larger particle sizes: Preliminary results

Functional magnetic materials by DFT

Magnetism of Fe-Pt Particles

Disordered Cuboctahedron

Disordered Icosahedron

L10-Ordered Cuboctahedron

Ordered Icosahedron

Core-Shell Icosahedron

Ferrimagnetism in core-shell structures

Ordered Decahedron

Functional magnetic materials by DFT

Ferrimagnetism in Core-Shell Isomers

Core-Shell isomers: Shell-wise alternating Moments in the pure Fe-core

MEG, G.Rollmann, A. Hucht, P. Entel, in: Advances in Solid State Physics, Vol. 47, Springer, Berlin (2008), p. 117 MEG, G. Rollmann, S. Sahoo, P. Entel, Phase Transitions 79, 701 (2006)

Functional magnetic materials by DFT

Antiferromagnetism in L10 FePt Bulk calculations: AF and FM solutions very close in energy Zeng, Sabirianov, Mryasov et al., PRB 66, 184425 (2002) Brown, Kraczek, Janotti et al., PRB 68, 052405 (2003)

Similar situation in perfectly L10 ordered cuboctahedra! MEG, J. Phys. D: Appl. Phys., 41, 134015

Functional magnetic materials by DFT

Multiple twinning: Exploring chemical trends

Functional magnetic materials by DFT

Co-Pt

L10-Ordered Cuboctahedron

Disordered Cuboctahedron

Disordered Icosahedron

Disordered Decahedron “Alternating” Icosahedra

Ordered Decahedron ΔE  1000 K!

MEG, G.Rollmann, P. Entel, M. Farle, PRL 100, 087203 (2008) Ordered Icosahedron

Core-Shell Icosahedra

Functional magnetic materials by DFT

Electronic structure of Fe265Pt296 Fe-Pt Co-Pt Fe Co

Pt

Mn: [Ar] 3d5 4s2 Fe: [Ar] 3d6 4s2 Co: [Ar] 3d7 4s2

Stability of icosahedral structures influenced by filling of 3d minority states

Functional magnetic materials by DFT

Mn-Pt

L10-Ordered Cuboctahedron

Disordered Cuboctahedron

Disordered Icosahedron

Disordered Decahedron “Alternating” Icosahedra

Ordered Decahedron

Ordered Icosahedron

Antiferromagnetic L10 Cuboctahedra

Functional magnetic materials by DFT

Structural instability of the ordered Mn-Pt icosahedron

Geometric optimization procedure leads to tranformation into ordered cuboctahedral L10 structure along the Mackay-path

Functional magnetic materials by DFT

Magnetic shape change by field induced reorientation Archetypical system: Ni-Mn-Ga }

+ + +

Entirely in the martensitic phase Strain up to10% (Ni-Mn-Ga) High frequencies possible

6…10 %

Ullako et al., Appl. Phys. Lett. 69, 1966 (1996)

Functional magnetic materials by DFT

Magnetic shape change by field induced reorientation Requirements:

Archetypical system: Ni-Mn-Ga

• Ferromagnetic, martensitic phase stable around (and above) room temperature • Considerable magnetocrystalline anisotropy energy (MAE)

• Highly mobile martensitic twin boundaries • Single crystals benefical for large strains Goal:

Understanding phase stability, MAE and twin boundary mobility from microscopic (electronic structure) point of view

}

6…10 %

Ullako et al., Appl. Phys. Lett. 69, 1966 (1996)

Functional magnetic materials by DFT

Density functional theory electronic structure calculations • Energy surfaces and twin boundary motion: Vienna Ab initio Simulation Package (VASP) – GGA exchange correlation functional (PW91,PBE) – PAW method for interaction with core and nuclei. – Valence: Ga → 3d104s2p1/4s2p1, Mn → 3d64s1, Ni → 3d94s1. Ecutoff = 337 eV. – Ab initio molecular statics/dynamics on the Born-Oppenheimer surface

JUGENE: Rank #6 on top500.org

• Phonon dispersions: VASP + PHONON (K. Parlinski) – Direct (supercell) approach: 1 x 5 x 1 unit cells (40 atoms)

• Magnetocrystalline anisotropy energy (MAE): Full-potential localized-orbital minimum-basis code (FPLO) – In cooperation with I. Opahle and M. Richter, IFW Dresden

Functional magnetic materials by DFT

Martensitic phases in the MSM Heusler system Ni-Mn-Ga

Parent phase: Cubic L21

Experiment: V. V. Khovailo et. al., Phys. Rev. B 72, 224408 (2005)

a

5M modulated martensitic phase:

Relevant for the MSM effect!

c

Functional magnetic materials by DFT

Phonon softening in the parent L21 phase

Mañosa et al.

Experiment (e.g.): Zheludev et al., PRB 54, 15045,(1996) Mañosa et al., PRB 64, 024305 (2001)

Symbols (exp.): T. Mehaddene et al.

Theory, DFT, T=0 (e.g.): Zayak et al., PRB 68, 132402 (2003)

Functional magnetic materials by DFT

Nesting features of the Fermi surfaces (e.g.): Lee, Rhee, Harmon, PRB 66, 054424 (2002) Bungaro, Rabe, Dal Corso, PRB 68, 134104 (2003)

L21 Ni2MnGa M = 4.05 μB/f.u.

A. Hucht et al.

Functional magnetic materials by DFT

Magnetism and stability of the austenitic phase

Energy

M = 3.8 μB/f.u.: unstable

M = 3.6 μB/f.u.: ~ stable

Stability of phases affected by magnetism (temperature)

E(c/a,M) by fixed-spin-moment approach

M. E. Gruner et al., Eur. Phys. J. – Special Topics 158, 193 (2008) P. Entel et al., Mater. Sci. Forum 583, 21 (2008)

Functional magnetic materials by DFT

Magnetocrystalline Anisotropy in Ni2MnGa FPLO (LSDA): •

Magnetocrystalline anisotropy energy (MAE) largest for c/a1.2



Change of direction: [001] is easy axis for c/a1 (easy plane instead)

Enkovaara et al., PRB 65, 134442 (2002) M. E. Gruner, P. Entel, I. Opahle, M. Richter, J. Mater. Sci. 43, 3825 (2008)

Functional magnetic materials by DFT

Ab initio modelling of twin boundary motion 3d periodic boundary conditions

• Line defects important for realistic description of twin boundary motion Pond, Celotto, Int. Mater. Rev. 48, 225 (2003); Müllner, Kostorz, Mater. Sci. Forum 583, 43 (2008)

x1  F x  c

eˆ z nˆ

nˆ  eˆ z

x2  G x  d

Very large systems required: Not possible by ab initio so far! • Instead: Construction of perfect twin boundary

• Direct simulation of MSM effect requires spin-orbit terms → too expensive • But simulation of shear induced twin boundary motion is feasible

Austenite

Martensite

Ball, James, Arch. Rat. Mech. Anal. 100, 13 (1987) Bhattacharya, Microstructure of martensite, Oxford (2003)

Shear

Relaxation

Functional magnetic materials by DFT

Example of a double L10 Twin Boundary (c/a=1.25)

256 atoms (2x2x4 unit cells), doubled in each direction

Functional magnetic materials by DFT

256 atom supercell (4x replicated) with two twin boundaries

Activation energy in L10 phase (c/a=1.25) more than one order of magnitude larger than total MAE M. E. Gruner, P. Entel, I. Opahle, M. Richter, J. Mater. Sci. 43, 3825 (2008)

Functional magnetic materials by DFT

Simplified twin boundary motion in L10 Ni2.2Mn0.8Ga Ni2.2Mn0.8Ga, 512 atoms (2x2x8 unit cells)

Comparison with MSM-relevant (modulated) phases will help to understand origin of high mobility from first principles (…but they are rather difficult to stabilize)

Functional magnetic materials by DFT

Conclusions • Ab initio determination of materials properties of nano-objects with more than 900 spin-polarized atoms on state-of-the-art supercomputers → Blue Gene/P: 1400 TM atoms or more: Ø of 3.5 - 4 nm possible!

• Fe nanoparticles: – Size dependence of structures (bcc from 100…150 atoms on) – New conformation discovered (shell-wise Mackay-transformed structure)

• Binary TM nanoparticles for magnetic data recording (FePt, CoPt): – Multiple twinning and segregation may prevent formation of high uniaxial magnetocrystalline anisotropy – Multiply twinned structures lower in energy up to 3 nm – Relative stability can be controlled by filling of 3d minority states

• Magnetic Shape Memory materials: – Simplified models of twin boundary motion can be handled with first principles methods on contemporary supercomputers

Functional magnetic materials by DFT

Acknowledgements O. Dmitrieva (now@MPIE), D. Sudfeld (now@FEI), M. Spasova, C. Antoniak, N. Friedenberger, M. Farle, Universität Duisburg-Essen K. Albe,

TU Darmstadt

U. Wiedwald Universität Ulm M. L. Tiago, ICES, Univ. of Texas, Austin A. T. Zayak, J. R. Chelikowsky,

I. Opahle (now@Frankfurt), M. Richter, U. K. Rössler, S. Fähler IFW, Dresden

W. A. Adeagbo

MPI Halle

A. T. Zayak,

ICES, Univ. of Texas, Austin

M. Acet, S. Aksoy, E. F. Wassermann, Universität Duisburg-Essen M. Ogura, H. Akai, Osaka University

John von Neumann Institute for Computing and JSC @ FZ Jülich for computational resources and support P. Vezolle,

IBM Montpellier

Deutsche Forschungsgemeinschaft: SPP

1239:

Change of Microstructure and Shape of Solid Materials by External Magnetic Fields

SFB

445:

Nanoparticles from the Gas-Phase: Formation, Structure, Properties

Functional magnetic materials by DFT

Three good reasons for doing more computational materials science on world leading supercomputers: • It is more reliable than a weather forecast • It has more technological relevance than QCD • It is (potentially) much less harmful than simulations of military devices making use of nuclear reactions There is plenty of room at the TOP500!

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