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Register a new userCrater functions for compound materials: a route to parameter estimation in coupled-PDE models of ion bombardment
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During the ion bombardment of targets containing multiple component species, highly-ordered arrays of nanostructures are sometimes observed. Models incorporating coupled partial differential equations, describing both morphological and chemical evolution, seem to offer the most promise of explaining these observations. However, these models contain many unknown parameters, which must satisfy specific conditions in order to explain observed behavior. The lack of knowledge of these parameters is therefore an important barrier to the comparison of theory with experiment. Here, by adapting the recent theory of crater functions to the case of binary materials, we develop a generic framework in which many of the parameters of such models can be estimated using the results of molecular dynamics simulations. As a demonstration, we apply our framework to the recent theory of Bradley and Shipman, for the case of Ar-irradiated GaSb, in which ordered patterns were first observed. In contrast to the requirements therein that sputtered atoms form the dominant component of the collision cascade, and that preferential redistribution play an important stabilizing role, we find instead that the redistributed atoms dominate the collision cascade, and that preferential redistribution appears negligible. Hence, the actual estimated parameters for this system do not seem to satisfy the requirements imposed by current theory, motivating the consideration of other potential pattern-forming mechanisms.
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A versatile method for combining density functional theory (DFT) in the local density approximation (LDA) with dynamical mean-field theory (DMFT) is presented. Starting from a general basis-independent formulation, we use Wannier functions as an interface between the two theories. These functions are used for the physical purpose of identifying the correlated orbitals in a specific material, and also for the more technical purpose of interfacing DMFT with different kinds of band-structure methods (with three different techniques being used in the present work). We explore and compare two distinct Wannier schemes, namely the maximally-localized-Wannier-function (MLWF) and the $N$-th order muffin-tin-orbital (NMTO) methods. Two correlated materials with different degrees of structural and electronic complexity, SrVO3 and BaVS3, are investigated as case studies. SrVO3 belongs to the canonical class of correlated transition-metal oxides, and is chosen here as a test case in view of its simple structure and physical properties. In contrast, the sulfide BaVS3 is known for its rich and complex physics, associated with strong correlation effects and low-dimensional characteristics. New insights into the physics associated with the metal-insulator transition of this compound are provided, particularly regarding correlation-induced modifications of its Fermi surface. Additionally, the necessary formalism for implementing self-consistency over the electronic charge density in a Wannier basis is discussed.
In recent years, observations of highly-ordered, hexagonal arrays of self-organized nanostructures on binary or impurity-laced targets under normal-incidence ion irradiation have excited interest in this phenomenon as a potential route to high-throughput, low-cost manufacture of nanoscale devices or nanostructured coatings. The currently-prominent explanation for these structures is a morphological instability driven by ion erosion discovered by Bradley and Shipman; however, recent parameter estimates via molecular dynamics simulations suggest that this erosive instability may not be active for the representative GaSb system in which hexagonal structures were first observed. Motivated by experimental and numerical evidence suggesting the possible importance of phase separation in ion-irradiated compounds, we here generalize the Bradley-Shipman theory to include the effect of ion-assisted phase separation. The resulting system admits a chemically-driven finite-wavelength instability that can explain the order of observed patterns even when the erosive Bradley-Shipman instability, and in a relevant simplifying limit, provides an intuitive instability criteria that agrees qualitatively with experimental observations on pattern wavelengths. Finally, we identify a characteristic experimental signature that distinguishes the chemical and morphological instabilities, and highlights the need for specific additional experimental data on the GaSb system.
Similarity analysis is used to identify the control parameter $R_A$ for the subset of avalanching systems that can exhibit Self- Organized Criticality (SOC). This parameter expresses the ratio of driving to dissipation. The transition to SOC, when the number of excited degrees of freedom is maximal, is found to occur when $R_A to 0$. This is in the opposite sense to (Kolmogorov) turbulence, thus identifying a deep distinction between turbulence and SOC and suggesting an observable property that could distinguish them. A corollary of this similarity analysis is that SOC phenomenology, that is, power law scaling of avalanches, can persist for finite $R_A$, with the same $R_A to 0$ exponent, if the system supports a sufficiently large range of lengthscales; necessary for SOC to be a candidate for physical ($R_A$ finite) systems.
Estimating parameters of Partial Differential Equations (PDEs) is of interest in a number of applications such as geophysical and medical imaging. Parameter estimation is commonly phrased as a PDE-constrained optimization problem that can be solved iteratively using gradient-based optimization. A computational bottleneck in such approaches is that the underlying PDEs needs to be solved numerous times before the model is reconstructed with sufficient accuracy. One way to reduce this computational burden is by using Model Order Reduction (MOR) techniques such as the Multiscale Finite Volume Method (MSFV). In this paper, we apply MSFV for solving high-dimensional parameter estimation problems. Given a finite volume discretization of the PDE on a fine mesh, the MSFV method reduces the problem size by computing a parameter-dependent projection onto a nested coarse mesh. A novelty in our work is the integration of MSFV into a PDE-constrained optimization framework, which updates the reduced space in each iteration. We also present a computationally tractable way of differentiating the MOR solution that acknowledges the change of basis. As we demonstrate in our numerical experiments, our method leads to computational savings particularly for large-scale parameter estimation problems and can benefit from parallelization.
We present a model for the effect of stress on thin amorphous films that develop atop ion-irradiated silicon, based on the mechanism of ion-induced anisotropic plastic flow. Using only parameters directly measured or known to high accuracy, the model exhibits remarkably good agreement with the wavelengths of experimentally-observed patterns, and agrees qualitatively with limited data on ripple propagation speed. The predictions of the model are discussed in the context of other mechanisms recently theorized to explain the wavelengths, including extensive comparison with an alternate model of stress.
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