FEMSIM + HRMC: Simulation of and structural refinement using fluctuation electron microscopy for amorphous materials

Maldonis, Jason J.; Hwang, Jinwoo; Voyles, Paul M.

doi:10.1016/j.cpc.2016.12.006

Cited by 11 publications

(10 citation statements)

References 30 publications

(42 reference statements)

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“…Direct inversion from FTEM measurement to atomic configuration is not possible with current computational capabilities. Instead, a forward calculation of FTEM from candidate atomic configurations has proven useful in constructing configurations which match experiment [6].…”

Section: Ftem Simulationmentioning

confidence: 99%

“…Summing real-valued diffraction contributions, omitting the wave phase encoded in complex values, loses information about the limited coherence volume which originally motivated FTEM method development [4]. Model size (including thickness) is notably limited in FEMSIM because calculations scale quadratically with the number of atoms [6].…”

Section: Ftem Simulationmentioning

confidence: 99%

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MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

Julian

Rudd

et al. 2018

Ultramicroscopy

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Atomic configurations of glassy or amorphous materials containing medium-range order (MRO) may be identified by comparing fluctuation transmission electron microscopy (FTEM) measurements to FTEM simulations obtained using model configurations. Candidate model sizes have traditionally been much thinner than the samples measured experimentally, and publicly available FTEM simulation software has until now omitted microscope parameters, dynamical scattering, and the phase of the diffracted electron wave. We introduce MS-STEM-FEM, an open-source software package for simulating FTEM experiments using established multi-slice TEM simulation techniques to emulate experiment more closely by incorporating microscope parameters and simulating electron scattering and propagation as a complex valued wave. Simulations using established models are compared with results of experimental STEM-FEM to validate the software. Several statistical measures of diffraction are implemented and their responses to model features are compared. Dynamical scattering is found to be less influential than the variety of crystallite orientations which occur in thicker models. Simulations of variable resolution microscopy confirm that cumulative intensity of the FTEM signal decreases with reduced model MRO and increased coherence volume. Advantageous model scaling characteristics and efficient processor performance scaling are demonstrated, along with a study of convergence with respect to pertinent simulation parameters to identify accuracy requirements.

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Section: Ftem Simulationmentioning

confidence: 99%

Section: Ftem Simulationmentioning

confidence: 99%

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

Julian

Rudd

et al. 2018

Ultramicroscopy

View full text Add to dashboard Cite

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“…Often the goal of these structure determination methods is to predict the lowest energy structure of a given stoichiometry under specific thermodynamic constraints [18,19]. In addition, there are a number of applications of optimization approaches for structure optimization incorporating forward simulations of experiments, e.g., in glass alloy structure determination [20][21][22][23]. The challenges of such optimization often requires the quantitative comparison to various sources of experimental characterization data [6], meaning "goodness-of-fit" values for multiple types of forward simulations need to be integrated into the optimization.…”

Section: Introductionmentioning

confidence: 99%

“…The stability of the structure can be calculated at various levels of theory by atomistic modeling methods, although interatomic potentials of some kind are the most common approach [25]. Forward simulations are used to predict images or spectra of an atomic structure associated with a given characterization method and also can be implemented at various levels of fidelity [22,[26][27][28]. StructOpt incorporates both types of calculations by constructing an objective function to evaluate an atomic structure's energy and agreement of multiple forward simulations to experimental data.…”

Section: Introductionmentioning

confidence: 99%

StructOpt: A modular materials structure optimization suite incorporating experimental data and simulated energies

Maldonis

Song

et al. 2019

Computational Materials Science

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“…Typically, this method is used to detect changes between samples, relating differences in variance and average bond length to changes in MRO arising from processing or sample compositions. Additionally, the FEM variance data can be used as a constraint in reverse Monte Carlo calculations [7] to solve for atomic coordinates. This method has been successfully applied to understand structural evolution of a variety of amorphous systems.…”

mentioning

confidence: 99%

Characterizing Magnetic Anisotropy in Amorphous Metal Films Using Tilted Fluctuation Electron Microscopy

et al. 2018

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Compounds consisting of transition metals and rare earth elements often exhibit desirable magnetic properties for application in memory devices. For example, sputtered amorphous TbxCo1-x (a-Tb-Co) thin films are magnetically anisotropic under certain growth conditions, with the easy axis perpendicular to the plane of the film [1]. This magnetic anisotropy depends on growth conditions, composition, and postgrowth heat treatment. Although it is thought that the origin of the magnetic anisotropy is the single ion anisotropy of Tb together with an anisotropic local structure induced by the growth process, how the magnetic properties of this material depend on structure, and why it depends on both growth temperature and evolves with annealing, are unknown [2,3]. Due to the lack of long-range order in a-Tb-Co and other disordered materials, it is difficult to relate the changes in magnetic properties to changes in structure. Although X-ray diffraction has not shown significant changes in short-range order in a-Tb-Co, EXAFS studies have measured structural changes in a similar system with strong out-of-plane anisotropy, a-TbFe [4,5]. The enhanced Tb-Fe correlations, as well as changes in interatomic spacing in the in-plane vs. out-of-plane directions, observed in [4] and [5] indicate that structural features are indeed correlated to the magnetic anisotropy in these systems. To better understand the relationship between structure, sample growth and treatment, and magnetic properties in these systems, it is desirable to measure the local ordering and symmetry in the 2-4 nm range in structurally and magnetically anisotropic systems.Fluctuation electron microscopy (FEM) is a focused-probe, scanning nanodiffraction technique that is sensitive to medium range order in disordered materials (Fig. 1). By measuring a series of diffraction patterns and calculating the variance in intensity as a function of spatial frequency, FEM has been used to determine the relative amount of medium range on the size scale of the probe used [6]. Typically, this method is used to detect changes between samples, relating differences in variance and average bond length to changes in MRO arising from processing or sample compositions. Additionally, the FEM variance data can be used as a constraint in reverse Monte Carlo calculations [7] to solve for atomic coordinates. This method has been successfully applied to understand structural evolution of a variety of amorphous systems. However, a drawback of FEM is that it typically assumes an isotropic sample. Therefore, we have extended FEM to probe directionally-dependent properties of anisotropic materials by tilting the sample during sequential data scans. Since diffracted intensity depends most strongly on inplane periodicities (i.e., periodic structures that lie in the plane perpendicular to the beam direction), this method probes in-plane and out-of-plane structures as the sample's tilt is changed. This allows for comparison to in-plane and out-of-plane variance as a way to determine differences i...

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FEMSIM + HRMC: Simulation of and structural refinement using fluctuation electron microscopy for amorphous materials

Cited by 11 publications

References 30 publications

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

MS–STEM–FEM: A parallelized multi-slice fluctuation TEM simulation tool

StructOpt: A modular materials structure optimization suite incorporating experimental data and simulated energies

Characterizing Magnetic Anisotropy in Amorphous Metal Films Using Tilted Fluctuation Electron Microscopy

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