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Peter Brommer

Publications and source records attributed to Peter Brommer.

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First Principles Validation of Energy Barriers in Ni$_{75}$Al$_{25}$

Precipitates in Nickel-based superalloys form during heat treatment on a time scale inaccessible to direct molecular dynamics simulation, but could be studied using kinetic Monte Carlo (KMC). This requires reliable values for the barrier energies separating distinct configurations over the trajectory of the system. In this study, we validate vacancy migration barriers found with the Activation-Relaxation Technique nouveau (ARTn) method in partially ordered Ni$_{75}$Al$_{25}$ with a monovacancy using published potentials for the atomic interactions against first-principles methods. In a first step, we confirm that the ARTn barrier energies agree with those determined with the nudged elastic band (NEB) method. As the number of atoms used in those calculations is too great for direct ab initio calculations, we then cut the cell size to 255 atoms, thus controlling finite size effects. We then use the plane-wave density functional theory (DFT) code CASTEP and its inbuilt NEB method in the smaller cells. This provides us with a continuous validation chain from first principles to kinetic Monte Carlo simulations with interatomic potentials. We then evaluate the barrier energies of five further interatomic potentials with NEB, demonstrating that none yields these with sufficient reliability for KMC simulations, with some of them failing completely. This is a first step towards quantifying the errors incurred in KMC simulations of precipitate formation and evolution.

cond-mat.mtrl-sci

Dislocation dynamics in Ni-based superalloys: Parameterising dislocation trajectories from atomistic simulations

Nanoscale precipitates in the microstructure of nickel-based superalloys hinder dislocation motion, which results in an extraordinary strengthening effect at elevated temperatures. We used molecular dynamics (MD) with classical effective potential to observe the movement of an $\frac{a}{2}\langle110\rangle\{111\}$ edge dislocation under shear in pure Ni, which represents the Ni solid solution matrix, and extracted the locations of the dislocations. We show how a Differential Evolution Monte Carlo (DE-MC) analysis is an effective way to find the parameters of an equation of motion for the dislocation lines with quantified uncertainties. The parameters of interest were the effective mass, drag coefficient, and force experienced by the dislocation. The marginal parameter and joint posterior distributions were estimated from the accepted samples produced by the DE-MC algorithm. The equation of motion and parameter distributions were used to predict the dislocation positions and velocities at the simulation timesteps, and the mean fit was found to match the MD trajectories with a root mean square error (RMSE) of \SI{0.2}{\nano\metre}. We also discuss how the selected model can be extended to account for the presence of multiple dislocations as well as dislocation-precipitate interactions. This work serves as the first step towards building a predictive surrogate model that describes the deformation behaviour of Ni-based superalloys.

cond-mat.mtrl-sci

Uncertainty quantification for classical effective potentials: an extension to potfit

Effective potentials are an essential ingredient of classical molecular dynamics (MD) simulations. Little is understood of the consequences of representing the complex energy landscape of an atomic configuration by an effective potential or force field containing considerably fewer parameters. The probabilistic potential ensemble method has been implemented in the potfit force matching code. This introduces uncertainty quantification into the interatomic potential generation process. Uncertainties in the effective potential are propagated through MD to obtain uncertainties in quantities of interest, which are a measure of the confidence in the model predictions. We demonstrate the technique using three potentials for nickel: two simple pair potentials, Lennard-Jones and Morse, and a local density dependent embedded atom method (EAM) potential. A potential ensemble fit to density functional theory (DFT) reference data is constructed for each potential to calculate the uncertainties in lattice constants, elastic constants and thermal expansion. We quantitatively illustrate the cases of poor model selection and fit, highlighted by the uncertainties in the quantities calculated. This shows that our method can capture the effects of the error incurred in quantities of interest resulting from the potential generation process without resorting to comparison with experiment or DFT, which is an essential part to assess the predictive power of MD simulations.

cond-mat.mtrl-sci

A KIM-compliant potfit for fitting sloppy interatomic potentials: Application to the EDIP model for silicon

Fitted interatomic potentials are widely used in atomistic simulations thanks to their ability to compute the energy and forces on atoms quickly. However, the simulation results crucially depend on the quality of the potential being used. Force matching is a method aimed at constructing reliable and transferable interatomic potentials by matching the forces computed by the potential as closely as possible, with those obtained from first principles calculations. The potfit program is an implementation of the force-matching method that optimizes the potential parameters using a global minimization algorithm followed by a local minimization polish. We extended potfit in two ways. First, we adapted the code to be compliant with the KIM Application Programming Interface (API) standard (part of the Knowledgebase of Interatomic Models Project). This makes it possible to use potfit to fit many KIM potential models, not just those prebuilt into the potfit code. Second, we incorporated the geodesic Levenberg--Marquardt (LM) minimization algorithm into potfit as a new local minimization algorithm. The extended potfit was tested by generating a training set using the KIM Environment-Dependent Interatomic Potential (EDIP) model for silicon and using potfit to recover the potential parameters from different initial guesses. The results show that EDIP is a "sloppy model" in the sense that its predictions are insensitive to some of its parameters, which makes fitting more difficult. We find that the geodesic LM algorithm is particularly efficient for this case. The extended potfit code is the first step in developing a KIM-based fitting framework for interatomic potentials for bulk and two dimensional materials. The code is available for download via https://www.potfit.net.

cond-mat.other

Classical interaction potentials for diverse materials from ab initio data: a review of potfit

Force matching is an established technique to generate effective potentials for molecular dynamics simulations from first-principles data. This method has been implemented in the open source code potfit. Here, we present a review of the method and describe the main features of the code. Particular emphasis is placed on the features added since the initial release: interactions represented by analytical functions, differential evolution as optimization method, and a greatly extended set of interaction models. Beyond the initially present pair and embedded-atom method potentials, potfit can now also optimize angular dependent potentials, charge and dipolar interactions, and electron-temperature-dependent potentials. We demonstrate the functionality of these interaction models using three example systems: phonons in type I clathrates, fracture of α-alumina, and laser-irradiated silicon.

cond-mat.mtrl-sci

Understanding long-time vacancy aggregation in iron: a kinetic activation-relaxation technique study

Vacancy diffusion and clustering processes in body-centered-cubic (bcc) Fe are studied using the kinetic activation-relaxation technique (k-ART), an off-lattice kinetic Monte Carlo method with on-the-fly catalog building capabilities. For monovacancies and divacancies, k-ART recovers previously published results while clustering in a 50-vacancy simulation box agrees with experimental estimates. Applying k-ART to the study of clustering pathways for systems containing from one to six vacancies, we find a rich set of diffusion mechanisms. In particular, we show that the path followed to reach a hexavacancy cluster influences greatly the associated mean-square displacement. Aggregation in a 50-vacancy box also shows a notable dispersion in relaxation time associated with effective barriers varying from 0.84 to 1.1 eV depending on the exact pathway selected. We isolate the effects of long-range elastic interactions between defects by comparing to simulations where those effects are deliberately suppressed. This allows us to demonstrate that in bcc Fe, suppressing long-range interactions mainly influences kinetics in the first 0.3 ms, slowing down quick energy release cascades seen more frequently in full simulations, whereas long-term behavior and final state are not significantly affected.

cond-mat.mtrl-sci

Probing potential energy surface exploration strategies for complex systems

The efficiency of minimum-energy configuration searching algorithms is closely linked to the energy landscape structure of complex systems. Here we characterize this structure by following the time evolution of two systems, vacancy aggregation in Fe and energy relaxation in ion-bombarded c-Si, using the kinetic Activation-Relaxation Technique (k-ART), an off-lattice kinetic Monte Carlo (KMC) method, and the well-known Bell-Evans-Polanyi (BEP) principle. We also compare the efficiency of two methods for handling non-diffusive flickering states -- an exact solution and a Tabu-like approach that blocks already visited states. Comparing these various simulations allow us to confirm that the BEP principle does not hold for complex system since forward and reverse energy barriers are completely uncorrelated. This means that following the lowest available energy barrier, even after removing the flickering states, leads to rapid trapping: relaxing complex systems requires crossing high-energy barriers in order to access new energy basins, in agreement with the recently proposed replenish-and-relax model [Béland et al., PRL 111, 105502 (2013)] This can be done by forcing the system through these barriers with Tabu-like methods. Interestingly, we find that following the fundamental kinetics of a system, though standard KMC approach, is at least as efficient as these brute-force methods while providing the correct kinetics information.

cond-mat.mtrl-sci

Replenish and relax: explaining logarithmic annealing in disordered materials

Fatigue and aging of materials are, in large part, determined by the evolution of the atomic-scale structure in response to strains and perturbations. This coupling between microscopic structure and long time scales remains one of the main challenges in materials study. Focusing on a model system, ion-damaged crystalline silicon, we combine nanocalorimetric experiments with an off-lattice kinetic Monte Carlo simulation to identify the atomistic mechanisms responsible for the structural relaxation over long time scales. We relate the logarithmic relaxation, observed in a number of systems, with heat-release measurements. The microscopic mechanism associated with logarithmic relaxation can be described as a two-step replenish and relax process. As the system relaxes, it reaches deeper energy states with logarithmically growing barriers that need to be unlocked to replenish the heat-releasing events leading to lower energy configurations.

cond-mat.mtrl-sci

Influence of polarizability on metal oxide properties studied by molecular dynamics simulations

We have studied the dependence of metal oxide properties in molecular dynamics (MD) simulations on the polarizability of oxygen ions. We present studies of both liquid and crystalline structures of silica (SiO2), magnesia (MgO) and alumina (Al2O3). For each of the three oxides, two separately optimized sets of force fields were used: (i) Long-range Coulomb interactions between oxide and metal ions combined with a short-range pair potential. (ii) Extension of force field (i) by adding polarizability to the oxygen ions. We show that while an effective potential of type (i) without polarizable oxygen ions can describe radial distributions and lattice constants reasonably well, potentials of type (ii) are required to obtain correct values for bond angles and the equation of state. The importance of polarizability for metal oxide properties decreases with increasing temperature.

cond-mat.mtrl-sci

Embedded atom method potentials for Al-Pd-Mn phases

A novel embedded atom method (EAM) potential for the Xi-phases of Al-Pd-Mn has been determined with the force-matching method. Different combinations of analytic functions were tested for the pair and transfer part. The best results are obtained, if one allows for oscillations on two different length scales. These potentials stabilize structure models of the Xi-phases and describe their energy with high accuracy. Simulations at temperatures up to 1200 K show very good agreement with ab-initio results with respect to stability and dynamics of the system.

cond-mat.mtrl-sci

Ab initio based polarizable force field generation and application to liquid silica and magnesia

We extend the program potfit, which generates effective atomic interaction potentials from ab initio data, to electrostatic interactions and induced dipoles. The potential parametrization algorithm uses the Wolf direct, pairwise summation method with spherical truncation. The polarizability of oxygen atoms is modeled with the Tangney-Scandolo interatomic force field approach. Due to the Wolf summation, the computational effort in simulation scales linearly in the number of particles, despite the presence of electrostatic interactions. Thus, this model allows to perform large-scale molecular dynamics simulations of metal oxides with realistic potentials. Details of the implementation are given, and the generation of potentials for SiO2 and MgO is demonstrated. The approach is validated by simulations of microstructural, thermodynamic and vibrational properties of liquid silica and magnesia.

cond-mat.mtrl-sci

Kinetic Activation Relaxation Technique

We present a detailed description of the kinetic Activation-Relaxation Technique (k-ART), an off-lattice, self-learning kinetic Monte Carlo algorithm with on-the-fly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, k-ART can be applied to complex materials with atoms in off-lattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of k-ART by applying the algorithm to three challenging systems: self-defect annihilation in c-Si (crystalline silicon), self-interstitial diffusion in Fe and structural relaxation in a-Si (amorphous silicon).

physics.comp-ph

Direct Wolf summation of a polarizable force field for silica

We extend the Wolf direct, pairwise r^(-1) summation method with spherical truncation to dipolar interactions in silica. The Tangney-Scandolo interatomic force field for silica takes regard of polarizable oxygen atoms whose dipole moments are determined by iteration to a self-consistent solution. With Wolf summation, the computational effort scales linearly in the system size and can easily be distributed among many processors, thus making large-scale simulations of dipoles possible. The details of the implementation are explained. The approach is validated by estimations of the error term and simulations of microstructural and thermodynamic properties of silica.

cond-mat.mtrl-sci

Potfit: effective potentials from ab-initio data

We present a program called potfit which generates an effective atomic interaction potential by matching it to a set of reference data computed in first-principles calculations. It thus allows to perform large-scale atomistic simulations of materials with physically justified potentials. We describe the fundamental principles behind the program, emphasizing its flexibility in adapting to different systems and potential models, while also discussing its limitations. The program has been used successfully in creating effective potentials for a number of complex intermetallic alloys, notably quasicrystals.

cond-mat.mtrl-sci

Effective potentials for quasicrystals from ab-initio data

Classical effective potentials are indispensable for any large-scale atomistic simulations, and the relevance of simulation results crucially depends on the quality of the potentials used. For complex alloys like quasicrystals, however, realistic effective potentials are practically inexistent. We report here on our efforts to develop effective potentials especially for quasicrystalline alloy systems. We use the so-called force matching method, in which the potential parameters are adapted so as to optimally reproduce the forces and energies in a set of suitably chosen reference configurations. These reference data are calculated with ab-initio methods. As a first application, EAM potentials for decagonal Al-Ni-Co, icosahedral Ca-Cd, and both icosahedral and decagonal Mg-Zn quasicrystals have been constructed. The influence of the potential range and degree of specialisation on the accuracy and other properties is discussed and compared.

cond-mat.mtrl-sci