Report

An Introduction to Atomistic Spin Models T. Ostler Dept. of Physics, The University of York, York, United Kingdom. December 2014 Overview • Introduction – why atomistic modeling – – – • Essentials of atomistic spin models – – – – • Time/length scales. What is a spin model? When is it appropriate to use a spin model? Types of systems. The Hamiltonian terms and typical values. Numerical approaches and the Landau-Lifshitz-Gilbert equation. Numerical integration methods. Typical calculations/simulations. Examples of where atomistic spin models are appropriate: – – Fe/FePt/Fe interface. Typical calculations by example GdFeCo. For anyone interested the slides are available at http://tomostler.co.uk/wp-content/uploads/2014/12/IOP2014.pptx Why do we need atomistic models? • Back in (computing) ancient times (1956) a hard drive was born. • In 1953 IBM launched first commercial HHD with data transfer rate of 8,800 characters per second and drive size of around 3.75Mb. Me IBM 350 • Fifty 24-inch (610 mm) diameter disks with 100 recording surfaces. We are storing more on smaller things kb 25TB daily log 100TB storage MB (10002) GB (10003) TB (10004) A few GB to TB’s Christmas Cracker Fact • • 2.5PB 24PB daily • PB (10005) 4ZB is around 1015 IBM 350’s The area of the IBM 350 is 1.12m2 and 1015 of them would cover 1x10615m2 EB (1000 ) The surface area of the earth is 5.1x1014m2 ZB (10007) 330 EB demand in 2011 Estimated size of the internet 4ZB Time and length scales • As we decrease the size of devices we have to go to ever smaller and shorter timescales to describe the physics. Length 10-10 m (Å) Time 10-16 s (<fs) 10-9 m (nm) Superdiffusive spin transport 10-12 s (ps) Langevin Dynamics on atomic level s (ns) 10-3 m (mm) TDFT/ab-initio spin dynamics 10-15 s (fs) 10-9 10-6 m (μm) Micromagnetics /LLB 10-6 s (µs) 10-3 s (ms) 10-0 s (s)+ http://www.psi.ch/swissfel/ultrafast-manipulation-of-the-magnetization Kinetic Monte Carlo http://www.castep.org/ What is a spin model? • It is the magnetic equivalent of molecular dynamics. MD • • • ASD • The important variables in MD are the positions and velocities. The forces arise due to the interaction potentials. The configuration of the atoms is determined by the form of the interaction potential. V(r) • • The important variables in ASD are the spin vectors (atomic positions fixed). The fields arise due to the terms in the magnetic Hamiltonian. The ground state is (mostly) determined by the fields. FM Repulsive AFM r Attractive bcc Fe (Pajda PRB 64, 174402 (2001)) What is a spin model? Ab-initio calculations Exchange interactions Interaction potentials phonons To obtain the collective dynamics in both cases an iterative process of solving the time-dependent equations for each atom/spin is performed http://www.fhi-berlin.mpg.de/~hermann/Balsac/BalsacPictures/Phono1.gif spinwaves Types of systems the atomistic approach is useful for • This type of approach is particularly important when the physics at the atomic level is important. Phys. Rev. B 79, 020403(R) Interfaces/layered systems Anisotropic Exchange (Dzyaloshinskii-Moriya) Four spin interactions in FeRh (metamagnetic phase transitions) Above: one monolayer IrMn3 of Mn on W(110) Nat Nanotech, 8, 438-444 (2013) arXiv:1405.3043 Overview • Introduction – why atomistic modeling – – – • Essentials of atomistic spin models – – – – • Time/length scales. What is a spin model? When is it appropriate to use a spin model? Types of systems. The Hamiltonian terms and typical values. Numerical approaches and the Landau-Lifshitz-Gilbert equation. Numerical integration methods. Typical calculations/simulations. Examples of where atomistic spin models are appropriate: – – Fe/FePt/Fe interface. Typical calculations by example GdFeCo. The Hamiltonian • • • To do atomistic modelling we really need information about the Hamiltonian. The terms have different origins and span a wide range of energies and depend on the system of interest. Computationally they vary in complexity and computational “cost” with increasing numbers of spins (N). Simple form Difficulty to determine/cost Energy range Usually pretty straight forward and computationally cheap (scales with N) 10-25 - 10-22J/at Can be difficult to determine. (usually scales with N) • 10-25 - 10-22J/at Easy to determine but computationally expensive (without tricks scales with N2) 10-25 - 10-23J/at Most difficult to determine, in general long-ranged. (can scale as N2) 10-23 - 10-21J/at What is the effect of these microscopic parameters on the resulting magnetic structure? Effect of the terms in the Hamiltonian • The magnetic moments will always try to align with the magnetic field. The strength depends on the moments and the size of the field. • The minimization of the anisotropy depends on the form(s). For example first order uniaxial anisotropy. • Depends on the magnetic moments and the positions of those moments in space (the shape). Tends to demagnetize the system. B • • In the simplest picture if J>0 the moments align (dot product of two spins minimizes energy). If J<0 anti-alignment (antiferromagnetism) is the minimum. FM • • AFM Question for later: how are the parameters determined? What can we do with the Hamiltonian? • Since we have large numbers of interacting atoms it is (in most cases) impossible to solve the system analytically. We require a numerical approach. What kind of calculation Time-dependent properties/dynamics Equilibrium Free energy surfaces Constrained montecarlo Metropolis monte carlo Time integration of the LLG equation Time-quantified monte-carlo Metadynamics References Constrained Monte Carlo Phys. Rev. B 82, 054415 (2010) Time-quantified Monte Carlo Phys. Rev. Lett, 84, 163 (2000) Metadynamics Phys. Rev. E. 81, 055701(R) (2010) The Landau-Lifshitz-Gilbert Equation • One of the most common methods used with this type of atomistic modeling is to integrate the Landau-Lifshitz-Gilbert (LLG) equation. H SxSxH SxH S • • • • The first term is the usual precession term and the second is the damping (λ). The damping is a phenomenological parameter that ignores how the magnetization is damped. There are some links to simple sample programs in the slides at the end to demonstrate the implementation. There are a number of extensions to this equation, for example taking into account spintransfer torque. IEEE Transactions on Magnetics, 6, 3443–3449 (2004) Numerical Integration Methods • Heun Scheme (predictor-corrector algorithm) Loop over time • Loop over spins • Calculate a field acting on each spin. • The field is the sum of the terms that we include in our Hamiltonian. • Solve using numerical integration. Predictor step (e.g Euler scheme) Predicted spin spin at current timestep s x H … based on spin at current timestep Corrector step spin at next timestep spin at current timestep See this link for the derivation of the correlator. [1] – PRL 102, 057203 (2009) s x H … based on spin at current time s x H … for predicted spin How to introduce temperature effects • To simulate thermal effects we include a stochastic term. This is an additional “field” that mimics thermal fluctuations: Damping Precession Noise • • In it’s simplest form the noise is “white”, i.e. it is uncorrelated in both time and space (can be coloured [1]). The mean and variance of the process can be shown through fluctuation dissipation theorem to be equal to: See this link for the derivation of the correlator. [1] – PRL 102, 057203 (2009) • In terms of implementation the noise is Gaussian distributed about zero and multiplied by: Typical values for different energy terms Fe (bcc) Co (hcp) Ni (fcc) K1 [J/m3] 54,800 760,000 -126,300 [J/at] 6.43 x 10-25 8.53 x 10-24 1.38 x 10-24 • • • • • • • • L10 FePt: likely candidate for Heat Assisted Magnetic Recording. Zeeman in 2T field: ~5x10-23 J/at MC Anisotropy: ~5x10-22 J/at (@ 0K). Effective exchange: ~3x10-21 J (per nn interaction). Permalloy: high permeability shields/vortex cores. Zeeman in 2T field: ~2.5x10-23 J/at. MC Anisotropy: ~10-25 J/at. Effective exchange: ~4x10-21 J (per nn interaction). These effective parameters appear similar but their form on the atomic level can be very different. Table of anisotropy constants: http://www.ifmpan.poznan.pl/~urbaniak/Wyklady2012/urbifmpan2012lect5_03.pdf Possible Calculations • There are a wide range of possible kinds of calculations. Here is a (not so extensive) list of measurements/calculations and if they are accessible with the atomistic model. Kind of measurement or calculation Temperature dependent magnetization Possible with atomistic model (+comments) ✔ Accessible experimentally (+comments) ✔ Free energy surfaces ✔ - metadynamics or constrained monte carlo ✗ Spinwave dispersion ✔ - calculations time 2-4 days ✗ - low k (magnetostatic) modes not accessible ✔ - requires a neutron source for high k (edge of BZ) Spin-spin correlations ✔ Magnetization dynamics ✔ Element resolved dynamics ✔ Atomic structure of domain wall dynamics ✔ Ferromagnetic resonance Pulsed laser excitation [1] - Nature Materials, 12, 293-298 (2013). ✗ - larger scale models (micromagnetics)[2] ✔ [2] – PRB 90, 094402 (2014) ✔ - for high resolution requires linear accelerator (~10nm) [1] ✔ ✔ - High harmonic generation ✔ - XMCD (synchrotron) [3] ✗ ✔ ✔ [3] – Nature 472, 205-208 (2011) Overview • Introduction – why atomistic modeling – – – • Essentials of atomistic spin models – – – – • Time/length scales. What is a spin model? When is it appropriate to use a spin model? Types of systems. The Hamiltonian terms and typical values. Numerical approaches and the Landau-Lifshitz-Gilbert equation. Numerical integration methods. Typical calculations/simulations. Examples of where atomistic spin models are appropriate: – – Fe/FePt/Fe interface. Dynamics and switching in GdFeCo. Another Christmas Cracker Fact • • Assuming the write speed of 8,800 bytes/sec the IBM 350 would take 1.44x1010 years to “write” the internet. This is 3 times longer than the age of the earth. Question from earlier slide: how do we determine the terms in the Hamiltonian? Magnetic moments and where they are in space gives us the Zeeman and demagnetizing terms. The exchange to determine the ordering (at least on a short range). Anisotropy for each moment. B Electronic structure calculations provide direct information on the atomic information Can also get a lot of information from experimental observations Example System: Fe/FePt/Fe • As mentioned in the introduction one of the examples where atomistic spin models are most powerful is at interfaces. Semi-infinite Fe Semi-infinite Fe FePt • How do the magnetic parameters vary across this system? Spin moment [μB] http://arxiv.org/pdf/1306.3642.pdf • Let’s look at an Fe/FePt/Fe interface system. Potential application as exchange spring system for magnetic recording. • Magnetic moment, anisotropy and exchange. Atomic layer Example System: Fe/FePt/Fe Semi-infinite Fe Semi-infinite Fe FePt Effective Exchange (sum over all layers) acting on layer i J (mev) K1 (mev) Anisotropy Atomic layer Atomic layer • http://arxiv.org/pdf/1306.3642.pdf So what? So what? Semi-infinite Fe Semi-infinite Fe FePt • mz • • Domain wall coordinate http://arxiv.org/pdf/1306.3642.pdf Domain wall profiles and energies are just one type of calculation that is possible with the atomistic model. When the exchange is calculated properly the structure of the domain wall is shown to have a sharp jump due to reduced exchange at the interface. This is important for the magnetic reversal process in exchange spring media. Example GdFeCo • Initial interest in this material came from experiments of helicity dependent, all-optical switching (AOS). • • • Little was know from the theory point of view about the magnetic processes in AOS. Aim: to understand more about the dynamics using a spin model. Why do we need a spin model for this system? Fe-Gd interactions are antiferromagnetic (J<0) Fe-Fe and Gd-Gd interactions are ferromagnetic (J>0) PRL 99, 047601 (2007) Atomic Level Sub-lattice magnetization Example GdFeCo • • The samples of GdFeCo measured were amorphous so parameters very tricky to calculate abinitio. By comparing equilibrium properties (element resolved M(T), hysteresis) could construct a model. PRB 84, 024407 (2011) Example GdFeCo • By varying the exchange parameters the magnetization curves the important points on the magnetization curves can be shown to agree (Curie temperature, compensation temperature). PRB 84, 024407 (2011) Example GdFeCo • By matching the model to experiments for the static properties the time-resolved dynamics give good agreement with experiment. Experiment Nature 472, 205-208 (2011) Model results Spinwave Dispersion • The spinwave dispersion is experimentally obtainable from Neutron scattering (see Christy Kinane’s talk at 17:00 today) and can be determined by calculating the following: Linear spinwave theory • • The longer the runtime the better the resolution of low lying modes. Requires large system sizes. Typical calculation time around 1 week. Nature Scientific Reports, 3, 3262 (2013). Summary • Atomistic spin models are most powerful when considering scenarios where complex exchange interactions are required (interfaces, exotic exchange etc). • Can account for on-site variations in parameters at the atomic level. • Limitations of time and length-scale. Often for generic/static properties other models more appropriate (micromagnetics, mean field, LLB). • Can include a number of effects to simulate specific systems (fluctuations in moments, spin transport effects, laser experiments). • Models take into account excitations across the entire Brillouin zone which can reveal interesting physics behind processes. Thanks for listening FFT Method • We can write the field for each spin: • Then the Fourier components of the components of the field can be written: • Where the elements of the tensor are: • In terms of the algorithm: Calculate the elements of the tensor FFT time loop t=0 store in memory It should be noted that the spin arrays have to be zero padded (twice as long in each dimension). Exit FFT Spins Convolute [1] – More info PRB 90, 094402 (2014). t < num timesteps? Update spin positions (LLG) IFFT Spins LLG No Damping: Maple • If we consider the Zeeman energy only we can write the field: Only applied field (no interactions) Write a DE for each component • The LLG equation for this single spin is then: In general we solve it numerically Worksheet available at this link. There is also a C++ version that uses the Heun scheme for numerical integration here. Distribution of spinwave energies • The distribution of spinwave energies can be determined dynamically from: • • Example: heat induced switching in ferrimagnets[1,2]. Large systems required for smooth data but only care about 10-50ps. Typical calculation time ~1-2 days. 1090K 975K X/2 X/2 M/2 M/2 No significant change. Larger spread in across BZ around Γpoint (demagnetization) [1] Nature Communications, 3, 666 (2012). [2] Nature Scientific Reports, 3, 3262 (2013). FeCo Gd Excited region during switching Basic Formalism • Within this approach the exchange is written in Heisenberg form between spins in neighbouring atoms. • This assumes that the magnetic moment is localised to atomic sites. • OK for systems with well localised magnetic moments, BUT what about metallic magetic systems? • We have to define the atomic moment in this case as “the integral of the spin dependent electron density over the atomic (Wigner-Seitz) volume”. • As long as we can write the terms in the Hamiltonian we can determine the magnetic properties. Time-average electron spin within the atomic volume Time larger than electron relaxation time (~10-15s) but less than spinwave excitation (~10-13s). LLG+ • There have been some extensions to the LLG equation to incorporate different effects: – spin torque (Phys. Rev. B. 68, 024404 (2003)): – Moments with fluctuating length (see Phys. Rev. B. 86, 054416 (2012)). – Models for conducting ferromagnets (see Phys. Rev. Lett. 102, 086601 (2009)). Dipole-Dipole Interaction • As long as we know the magnetic moments we can calculate the dipole field. • Due to the double sum the calculation scales as N2. This can potentially be the most computationally expensive part of the entire calculation. There are a number of ways of speeding this up: • – – – Super cell/macro cell method[2]. Discrete convolution theorem and using FFT’s[1]. Fast multipole methods[3]. • In the super cell method spins are groups together as one large volume of magnetization which substantially reduces the number of pairwise interactions. • Some more information on the FFT method at the end of the presentation. [1] – JMMM, 221, 365-372 (2000) [2] – J. Phys.: Cond. Mat 26, 103202 (2014) [3] – JMMM, 227, 9913-9932 (2008)