Application of Monte Carlo techniques to grain boundary structure optimization in silicon and silicon-carbide

Guziewski, Matthew; Banadaki, Arash Dehghan; Patala, Srikanth; Coleman, Shawn P.

doi:10.1016/j.commatsci.2020.109771

Cited by 22 publications

(16 citation statements)

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“…The metastable configurations for both CSL families were obtained using a recently developed, computationally efficient, Monte Carlo grain boundary optimization technique specific to multicomponent and covalently bonded systems. 10 This protocol consists of (i) constructing a random grain boundary configuration and (ii) iteratively swapping, adding, or removing Si and C atoms in the grain boundary region. The resultant (metastable) structure is accepted or rejected according to the Metropolis criterion.…”

Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

“…The resultant (metastable) structure is accepted or rejected according to the Metropolis criterion. Further details on the methodology used to generate the metastable grain boundary states are provided in Guziewski et al 10 As shown in Figure 1, for both CSL families, we sampled three atomic-basis sets, resulting in a distribution of metastable states comprising 30,000 grain boundaries (10,000 states per atomic basis). These three basis sets correspond to the terminating chemistries of the two crystals to form Si ↔ C (Basis 1 in Figure 1), Si ↔ Si (Basis 2 in Figure 1), and C ↔ C (Basis 3 in Figure 1) transition structures.…”

Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

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Characterizing the Tensile Strength of Metastable Grain Boundaries in Silicon Carbide Using Machine Learning

et al. 2020

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The local atomic structure, local chemistry, and stoichiometry of grain boundaries control in part the strength and fracture toughness of silicon carbide components. The predictions of the structure and properties of these grain boundaries are generally limited to their ground-state configurations. We investigated the tensile strength behavior of metastable grain boundaries in silicon carbide using high-throughput atomistic simulations combined with machine learning techniques. We analyzed and compared the ∑5 ⟨100⟩{120} and ∑9 ⟨110⟩{122} tilt grain boundary metastable configurations to identify structural and chemical attributes that dominate their tensile strength. We characterized these metastable grain boundaries using a set of microscopic descriptors representing the local grain boundary atomic structure and the local grain boundary stoichiometry and chemical-bound types. We used a boosted regression tree surrogate model for the successful prediction of metastable grain boundary strength as a function of these descriptors. Our results show that the tensile strength of generic (i.e., any random grain boundary from the entire grain boundary population), metastable grain boundaries is primarily dominated by the grain boundary excess free volume, closely followed by the type of structure composing the boundary and the amount of C–C bonds. The 5% strongest metastable grain boundaries have particular characteristics with a low amount of free volume and the highest density of C–C bonds. Our results reveal that the 5% strongest and weakest metastable grain boundaries are most sensitive to the local stoichiometry, regardless of the local atomic structure composing the grain boundary as compared to any other generic metastable grain boundaries. We show that the strongest and weakest metastable grain boundary configurations can be identified as specific regions in a low-dimensional-representation space of their microscopic descriptors. Taken together, these findings showcase the effectiveness and validity of using a low-dimensional representation of the grain boundary structure and machine-learned surrogate models to rapidly assess metastable grain boundary strength without the need to perform actual tensile simulations.

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Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

Characterizing the Tensile Strength of Metastable Grain Boundaries in Silicon Carbide Using Machine Learning

et al. 2020

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“…The GB character distribution (GBCD) function λ(∆g, n) with misorientation ∆g and plane normal n statistically defines the GB character in polycrystals [46]. Additionally, considering atomic arrangements in crystals, three microscopic degrees of freedom are employed to describe grain translation at the in-planar boundary plane and at the normal GB plane [47,48]. The GB energy and properties depend on the degrees of freedom, and it is crucial to link GB energy/properties to degrees of freedom through GB engineering and design [49,50].…”

Section: Additional Gb Terminology 131 Gb Charactermentioning

confidence: 99%

A Review of Grain Boundary and Heterointerface Characterization in Polycrystalline Oxides by (Scanning) Transmission Electron Microscopy

et al. 2021

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Interfaces such as grain boundaries (GBs) and heterointerfaces (HIs) are known to play a crucial role in structure-property relationships of polycrystalline materials. While several methods have been used to characterize such interfaces, advanced transmission electron microscopy (TEM) and scanning TEM (STEM) techniques have proven to be uniquely powerful tools, enabling quantification of atomic structure, electronic structure, chemistry, order/disorder, and point defect distributions below the atomic scale. This review focuses on recent progress in characterization of polycrystalline oxide interfaces using S/TEM techniques including imaging, analytical spectroscopies such as energy dispersive X-ray spectroscopy (EDXS) and electron energy-loss spectroscopy (EELS) and scanning diffraction methods such as precession electron nano diffraction (PEND) and 4D-STEM. First, a brief introduction to interfaces, GBs, HIs, and relevant techniques is given. Then, experimental studies which directly correlate GB/HI S/TEM characterization with measured properties of polycrystalline oxides are presented to both strengthen our understanding of these interfaces, and to demonstrate the instrumental capabilities available in the S/TEM. Finally, existing challenges and future development opportunities are discussed. In summary, this article is prepared as a guide for scientists and engineers interested in learning about, and/or using advanced S/TEM techniques to characterize interfaces in polycrystalline materials, particularly ceramic oxides.

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“…The probability of a specific site being operated upon is a function of the difference between its energy and CNP and those of found further from the interface within the bulk crystal. A deeper discussion of the probability functionals, and the Monte Carlo algorithm in general, is available [ 78 ].…”

Section: Molecular Dynamics Simulationsmentioning

confidence: 99%

A Multi-Scale Approach for Phase Field Modeling of Ultra-Hard Ceramic Composites

et al. 2021

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Diamond-silicon carbide (SiC) polycrystalline composite blends are studied using a computational approach combining molecular dynamics (MD) simulations for obtaining grain boundary (GB) fracture properties and phase field mechanics for capturing polycrystalline deformation and failure. An authentic microstructure, reconstructed from experimental lattice diffraction data with locally refined discretization in GB regions, is used to probe effects of local heterogeneities on material response in phase field simulations. The nominal microstructure consists of larger diamond and SiC (cubic polytype) grains, a matrix of smaller diamond grains and nanocrystalline SiC, and GB layers encasing the larger grains. These layers may consist of nanocrystalline SiC, diamond, or graphite, where volume fractions of each phase are varied within physically reasonable limits in parametric studies. Distributions of fracture energies from MD tension simulations are used in the phase field energy functional for SiC-SiC and SiC-diamond interfaces, where grain boundary geometries are obtained from statistical analysis of lattice orientation data on the real microstructure. An elastic homogenization method is used to account for distributions of second-phase graphitic inclusions as well as initial voids too small to be resolved individually in the continuum field discretization. In phase field simulations, SiC single crystals may twin, and all phases may fracture. The results of MD calculations show mean strengths of diamond-SiC interfaces are much lower than those of SiC-SiC GBs. In phase field simulations, effects on peak aggregate stress and ductility from different GB fracture energy realizations with the same mean fracture energy and from different random microstructure orientations are modest. Results of phase field simulations show unconfined compressive strength is compromised by diamond-SiC GBs, graphitic layers, graphitic inclusions, and initial porosity. Explored ranges of porosity and graphite fraction are informed by physical observations and constrained by accuracy limits of elastic homogenization. Modest reductions in strength and energy absorption are witnessed for microstructures with 4% porosity or 4% graphite distributed uniformly among intergranular matrix regions. Further reductions are much more severe when porosity is increased to 8% relative to when graphite is increased to 8%.

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Application of Monte Carlo techniques to grain boundary structure optimization in silicon and silicon-carbide

Cited by 22 publications

References 48 publications

Characterizing the Tensile Strength of Metastable Grain Boundaries in Silicon Carbide Using Machine Learning

Characterizing the Tensile Strength of Metastable Grain Boundaries in Silicon Carbide Using Machine Learning

A Review of Grain Boundary and Heterointerface Characterization in Polycrystalline Oxides by (Scanning) Transmission Electron Microscopy

A Multi-Scale Approach for Phase Field Modeling of Ultra-Hard Ceramic Composites

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