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We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated alloys. From this, other physical properties can be inferred, enabling accelerated exploration. A significant challenge is that the number of sampled compositions and descriptors required to accurately predict fields like the electron density increases rapidly with species. To address this, we employ Bayesian Active Learning (AL), which minimizes training data requirements by leveraging uncertainty quantification capabilities of Bayesian Neural Networks. Compared to strategic tessellation of the composition space, Bayesian-AL reduces the number of training data points by a factor of 2.5 for ternary (SiGeSn) and 1.7 for quaternary (CrFeCoNi) systems. We also introduce easy-to-optimize, body-attached-frame descriptors, which respect physical symmetries and maintain approximately the same descriptor-vector size as alloy elements increase. Our ML models demonstrate high accuracy and generalizability in predicting both electron density and energy across composition space.

Grain boundaries (GBs) in polycrystalline materials are powerful sinks for irradiation defects. While standard theories assume that the sink efficiency of a grain boundary is defined solely by its character before irradiation, recent evidence conclusively shows that the irradiation sink efficiency is a highly dynamic property controlled by the intrinsic metastability of GBs under far-from-equilibrium irradiation conditions. In this paper, we reveal that the denuded (i.e., defect-free) zone, typically the signature of a strong sink, can collapse as irradiation damage accumulates. We propose a radiation damage evolution model that captures this behavior based on the emergence of a series of irradiation defect-enabled metastable GB microstate changes that dynamically alter the ability of the GB to absorb further damage. We show that these microstate changes control further defect absorption and give rise to the formation of a defect network that manifests itself as a net Nye-tensor signal detectable via lattice curvature experiments.

In this work we develop a stochastic algorithm to integrate the Cahn-Hilliard equations. The algorithm is based on Gillespie's stochastic simulation algorithm, also known as kinetic Monte Carlo. The deterministic integration of the phase field equations leads to the closest minimum of free energy and does not overcome free energy barriers. However, in the nucleation and growth regime of the phase diagram, free energy barriers need to be thermally overcome for the system to phase separate to reach equilibrium. We show in this work that the proposed stochastic integration algorithm indeed allows the system to overcome free energy barriers. We discuss the results in terms of fluctuation distributions, grid sizes and efficiency.

Refractory multi-element alloys (RMEA) with body-centered cubic (bcc) structure have been the object of much research over the last decade due to their high potential as candidate materials for high-temperature applications. Most of these alloys display a remarkable strength at high temperatures, which cannot be explained by the standard model of bcc plasticity dominated by thermally-activated screw dislocation motion. Recent research on Nb-Mo-Ta-W alloys points to a heightened role of edge dislocations on deformation, which is generally attributed to atomic-level chemical fluctuations in the material and their interactions with dislocation cores during slip. However, while this model accounts for a strengthening effect due to the chemical complexity of the alloy, it is not sufficient to explain its strength across the entire thermal range. Here we propose a new mechanism that captures the existing theories about enhanced lattice strengthening and a thermally-activated component that emanates directly from the chemical complexity of the RMEA. This compositional complexity results in unique vacancy formation energy distributions with tails that extend into negative energies, leading to spontaneous, i.e., athermal, vacancy formation at edge dislocation cores. These vacancies relax into atomic-sized super-jogs on the dislocation line, acting as extra pinning points that increase the activation stress of the dislocation. At the same time, these super-jogs can displace diffusively along the glide direction, relieving with their motion some of the extra stress, thus countering the hardening effect due to jog-pinning. The interplay between these two processes as a function of temperature confers an extra strength to edge dislocation at intermediate-to-high temperatures, in remarkable agreement with experimental measurements in Nb-Mo-Ta-W and across a number of different RMEA.

Percolation phenomena are pervasive in nature, ranging from capillary flow, crack propagation, ionic transport, fluid permeation, etc. Modeling percolation in highly-branched media requires the use of numerical solutions, as problems can quickly become intractable due to the number of pathways available. This becomes even more challenging in dynamic scenarios where the generation of pathways can quickly become a combinatorial problem. In this work, we develop a new constriction percolation paradigm, using cellular automata to predict the transport of oxygen through a stochastically cracked Zr oxide layer within a coupled diffusion-reaction framework. We simulate such branching trees by generating a series porosity-controlled media. Additionally, we develop an analytical criterion based on compressive yielding for bridging the transition state in corrosion regime, where the percolation threshold has been achieved. Our model extends Dijkstras shortest path method to constriction pathways and predicts the arrival rate of oxygen ions at the oxide interface. This is a critical parameter to predict oxide growth in the so-called post-transition regime, when bulk diffusion is no longer the rate-limiting phenomenon., Comment: 16 pages, 14 figures

Surface erosion and secondary electron emission (SEE) have been identified as the most critical life-limiting factors in channel walls of Hall-effect thrusters for space propulsion. Recent wall concepts based on micro-architected surfaces have been proposed to mitigate surface erosion and SEE. The idea behind these designs is to take advantage of very-high surface-to-volume ratios to reduce SEE and ion erosion by internal trapping and redeposition. This has resulted in renewed interest to study electron-electron processes in relevant thruster wall materials. In this work, we present calculations of SEE yields in micro-porous hexagonal BN surfaces using stochastic simulations of electron-material interactions in discretized surface geometries. Our model consists of two complementary parts. First we study SEE as a function of primary electron energy and incidence angle in flat surfaces using Monte Carlo simulations of electron multi-scattering processes. The results are then used to represent the response function of discrete surface elements to individual electron rays generated using a ray-tracing Monte Carlo model. We find that micro-porous surfaces result in SEE yield reductions of over 50% in the energy range experienced in Hall thrusters. This points to the suitability of these micro-architected surface concepts to mitigate SEE-related issues in compact electric propulsion devices.

Secondary electron emission (SEE) from inner linings of plasma chambers in electric thrusters for space propulsion can have a disruptive effect on device performance and efficiency. SEE is typically calculated using elastic and inelastic electron scattering theory by way of Monte Carlo simulations of independent electron trajectories. However, in practice the method can only be applied for ideally smooth surfaces and thin films, not representative of real material surfaces. Recently, micro-architected surfaces with nanometric features have been proposed to mitigate SEE and ion-induced erosion in plasma-exposed thruster linings. In this paper, we propose an approach for calculating secondary electron yields from surfaces with arbitrarily-complex geometries using an extension of the \emph{ray tracing} Monte Carlo (RTMC) technique. We study nanofoam structures with varying porosities as representative micro-architected surfaces, and use RTMC to generate primary electron trajectories and track secondary electrons until their escape from the outer surface. Actual surfaces are represented as a discrete finite element meshes obtained from X-ray tomography images of tungsten nanofoams. At the local level, primary rays impinging into surface elements produce daughter rays of secondary electrons whose number, energies and angular characteristics are set by pre-calculated tables of SEE yields and energies from ideally-flat surfaces. We find that these micro-architected geometries can reduce SEE by up to 50\% with respect to flat surfaces depending on porosity and primary electron energy.

We use atomistic simulations to investigate grain boundary (GB) phase transitions in el- emental body-centered cubic (bcc) metal tungsten. Motivated by recent modeling study of grain boundary phase transitions in [100] symmetric tilt boundaries in face-centered cu- bic (fcc) copper, we perform a systematic investigation of [100] and [110] symmetric tilt high-angle and low-angle boundaries in bcc tungsten. The structures of these boundaries have been investigated previously by atomistic simulations in several different bcc metals including tungsten using the the {\gamma}-surface method, which has limitations. In this work we use a recently developed computational tool based on the USPEX structure prediction code to perform an evolutionary grand canonical search of GB structure at 0 K. For high-angle [100] tilt boundaries the ground states generated by the evolutionary algorithm agree with the predictions of the {\gamma}-surface method. For the [110] tilt boundaries, the search predicts novel high-density low-energy grain boundary structures and multiple grain boundary phases within the entire misorientation range. Molecular dynamics simulation demonstrate that the new structures are more stable at high temperature. We observe first-order grain boundary phase transitions and investigate how the structural multiplicity affects the mechanisms of the point defect absorption. Specifically, we demonstrate a two-step nucleation process, when initially the point defects are absorbed through a formation of a metastable GB structure with higher density, followed by a transformation of this structure into a GB interstitial loop or a different GB phase., Comment: 40 pages, 19 figures

We present calculations of secondary electron emission (SEE) yields in tungsten as a function of primary electron energies between 50 eV and 1 keV and incidence angles between 0 and 90{\deg}. We conduct a review of the established Monte Carlo methods to simulate multiple electron scattering in solids and select the best suited to study SEE in high-Z metals. We generate secondary electron yield and emission energy functions of the incident energy and angle and fit them to bivariate fitting functions using symbolic regression. We compare the numerical results with experimental data, with good agreement found. Our calculations are the first step towards studying SEE in nanoarchitected surfaces for electric propulsion chamber walls.

Interactions among dislocations and solute atoms are the basis of several important processes in metals plasticity. In body-centered cubic (bcc) metals and alloys, low-temperature plastic flow is controlled by screw dislocation glide, which is known to take place by the nucleation and sideward relaxation of kink pairs across two consecutive \emph{Peierls} valleys. In alloys, dislocations and solutes affect each other's kinetics via long-range stress field coupling and short-range inelastic interactions. It is known that in certain substitutional bcc alloys a transition from solute softening to solute hardening is observed at a critical concentration. In this paper, we develop a kinetic Monte Carlo model of screw dislocation glide and solute diffusion in substitutional W-Re alloys. We find that dislocation kinetics is governed by two competing mechanisms. At low solute concentrations, nucleation is enhanced by the softening of the Peierls stress, which overcomes the elastic repulsion of Re atoms on kinks. This trend is reversed at higher concentrations, resulting in a minimum in the flow stress that is concentration and temperature dependent. This minimum marks the transition from solute softening to hardening, which is found to be in reasonable agreement with experiments.

Plastic deformation in polycrystals is governed by the interplay between intra-granular slip and grain boundary-mediated plasticity. However, while the role played by bulk dislocations is relatively well-understood, the contribution of grain boundaries (GBs) has only recently begun to be studied. GB plasticity is known to play a key role along with bulk plasticity under a wide range of conditions, such as dynamic recovery, superplasticity, severe plastic deformation , etc., and developing models capable of simultaneously capturing GB and bulk plasticity has become a topic of high relevance. In this paper we develop a thermodynamically-consistent polycrystal plasticity model capable of simulating a variety of grain boundary-mediated plastic processes in conjunction with bulk dislocation slip. The model starts from the description of a single crystal and creates lattice strain-free polycrystalline configurations by using a specially-designed multiplicative decomposition developed by the authors. This leads to the introduction of a particular class of geometrically necessary dislocations (GND) that define fundamental GB features such as misorientation and inclination. The evolution of the system is based on an energy functional that uses a non-standard function of the GND tensor to account for the grain boundary energy, as well as for the standard elastic energy. Our implementation builds on smooth descriptions of GBs inspired on diffuse-interface models of grain evolution for numerical convenience. We demonstrate the generality and potential of the methodology by simulating a wide variety of phenomena such as shear-induced GB sliding, coupled GB motion, curvature-induced grain rotation and shrinkage, and polygonization via dislocation sub-grain formation., Comment: 35 pages, Submitted to International Journal of Plasticity

The standard way of modeling plasticity in polycrystals is by using the crystal plasticity model for single crystals in each grain, and imposing suitable traction and slip boundary conditions across grain boundaries. In this fashion, the system is modeled as a collection of boundary-value problems with matching boundary conditions. In this paper, we develop a diffuse-interface crystal plasticity model for polycrystalline materials that results in a single boundary-value problem with a single crystal as the reference configuration. Using a multiplicative decomposition of the deformation gradient into lattice and plastic parts, i.e. F(X,t) = F^L(X,t) F^P(X,t), an initial stress-free polycrystal is constructed by imposing F^L to be a piecewise constant rotation field R^0(X), and F^P = R^0(X)^T, thereby having F(X,0) = I, and zero elastic strain. This model serves as a precursor to higher order crystal plasticity models with grain boundary energy and evolution., Comment: 18 pages, 7 figures

High-temperature, high-dose, neutron irradiation of W results in the formation of Re-rich clusters at concentrations one order of magnitude lower than the thermodynamic solubility limit. These clusters may eventually transform into brittle W-Re intermetallic phases, which can lead to high levels of hardening and thermal conductivity losses. Standard theories of radiation enhanced diffusion and precipitation cannot explain the formation of these precipitates and so understanding the mechanism by which nonequilibrium clusters form under irradiation is crucial to predict materials degradation and devise mitigation strategies. Here we carry out a thermodynamic study of W-Re alloys and conduct kinetic Monte Carlo simulations of Re cluster formation in irradiated W-2Re alloys using a generalized Hamiltonian for crystals containing point defects parameterized entirely with electronic structure calculations. Our model incorporates recently-gained mechanistic information of mixed-interstitial solute transport, which is seen to control cluster nucleation and growth by forming quasi-spherical nuclei after an average incubation time of 20 s at 1800 K. These nuclei are seen to grow by attracting more mixed interstitials bringing solute atoms, which in turns attracts vacancies leading to recombination and solute agglomeration. The clusters grow to a maximum size of approximately 4-nm radius, and are not fully dense with Re, containing 50% or less near the center. Our simulations are in reasonable agreement with recent atom probe examinations of ion irradiated W-2Re systems at 773 K.

Dislocation motion in body centered cubic (bcc) metals displays a number of specific features that result in a strong temperature dependence of the flow stress, and in shear deformation asymmetries relative to the loading direction as well as crystal orientation. Here we develop a generalized dislocation mobility law in bcc metals, and demonstrate its use in discrete Dislocation Dynamics (DD) simulations of plastic flow in tungsten (W) micro pillars. We present the theoretical background for dislocation mobility as a motivating basis for the developed law. Analytical theory, molecular dynamics (MD) simulations, and experimental data are used to construct a general phenomenological description. The usefulness of the mobility law is demonstrated through its application to modeling the plastic deformation of W micro pillars. The model is consistent with experimental observations of temperature and orientation dependence of the flow stress and the corresponding dislocation microstructure.

We derive the atomistic representations of the elastic tensors appearing in the linearized theory of first strain-gradient elasticity for an arbitrary multi-lattice. In addition to the classical (2nd-Piola) stress and elastic moduli tensors, these include the rank-three double-stress tensor, the rank-five tensor of mixed elastic moduli, and the rank-six tensor of strain-gradient elastic moduli. The atomistic representations are closed-form analytical expressions in terms of the first and second derivatives of the interatomic potential with respect to interatomic distances, and dyadic products of relative atomic positions. Moreover, all expressions are local, in the sense that they depend only on the atomic neighborhood of a lattice site. Our results emanate from the condition of energetic equivalence between continuum and atomistic representations of a crystal, when the kinematics of the latter is governed by the Cauchy-Born rule. Using the derived expressions, we prove that the odd-order tensors vanish if the lattice basis admits central-symmetry. The analytical expressions are implemented as a KIM compliant algorithm to compute the strain gradient elastic tensors for various materials. Numerical results are presented to compare representative interatomic potentials used in the literature for cubic crystals, including simple lattices and multi-lattices. We observe that central potentials exhibit generalized Cauchy relations for the rank-six tensor of strain-gradient elastic moduli. In addition, this tensor is found to be indefinite for many potentials. We discuss the relationship between indefiniteness and material stability. Finally, the atomistic representations are specialized to central potentials in simple lattices. These expressions are used with analytical potentials to study the sensitivity of the elastic tensors to the choice of the cutoff radius.

Due to their high strength and advantageous high-temperature properties, tungsten-based alloys are being considered as plasma-facing candidate materials in fusion devices. Under neutron irradiation, rhenium, which is produced by nuclear transmutation, has been found to precipitate in elongated precipitates forming thermodynamic intermetallic phases at concentrations well below the solubility limit. Recent measurements have shown that Re precipitation can lead to substantial hardening, which may have a detrimental effect on the fracture toughness of W alloys. This puzzle of sub-solubility precipitation points to the role played by irradiation induced defects, specifically mixed solute-W interstitials. Here, using first-principles calculations based on density functional theory, we study the energetics of mixed interstitial defects in W-Re, W-V, and W-Ti alloys, as well as the heat of mixing for each substitutional solute. We find that mixed interstitials in all systems are strongly attracted to each other with binding energies of -2.4 to -3.2 eV and form interstitial pairs that are aligned along parallel first-neighbor <111> strings. Low barriers for defect translation and rotation enable defect agglomeration and alignment even at moderate temperatures. We propose that these elongated agglomerates of mixed-interstitials may act as precursors for the formation of needle-shaped intermetallic precipitates. This interstitial-based mechanism is not limited to radiation induced segregation and precipitation in W-Re alloys but is also applicable to other body-centered cubic alloys., Comment: 8 pages, 7 figures

We derive an Ising Hamiltonian for kinetic simulations involving interstitial and vacancy defects in binary alloys. Our model, which we term `ABVI', incorporates solute transport by both interstitial defects and vacancies into a mathematically-consistent framework , and thus represents a generalization to the widely-used ABV model for alloy evolution simulations. The Hamiltonian captures the three possible interstitial configurations in a binary alloy: A-A, A-B, and B-B, which makes it particularly useful for irradiation damage simulations. All the constants of the Hamiltonian are expressed in terms of bond energies that can be computed using first-principles calculations. We implement our ABVI model in kinetic Monte Carlo simulations and perform a verification exercise by comparing our results to published irradiation damage simulations in simple binary systems with Frenkel pair defect production and several microstructural scenarios, with matching agreement found.

Germanium is an extremely important material used for numerous functional applications in many fields of nanotechnology. In this paper, we study the crystallization of amorphous Ge using atomistic simulations of critical nano-metric nuclei at high temperatures. We find that crystallization occurs by the recurrent transfer of atoms via a diffusive process from the amorphous phase into suitably-oriented crystalline layers. We accompany our simulations with a comprehensive thermodynamic and kinetic analysis of the growth process, which explains the energy balance and the interfacial growth velocities governing grain growth. For the $\langle111\rangle$ crystallographic orientation, we find a degenerate atomic rearrangement process, with two zero-energy modes corresponding to a perfect crystalline structure and the formation of a $\Sigma3$ twin boundary. Continued growth in this direction results in the development a twin network, in contrast with all other growth orientations, where the crystal grows defect-free. This particular mechanism of crystallization from amorphous phases is also observed during solid-phase epitaxial growth of $\langle111\rangle$ semiconductor crystals, where growth is restrained to one dimension. We calculate the equivalent X-ray diffraction pattern of the obtained nanotwin networks, providing grounds for experimental validation.

Materials subjected to neutron irradiation will suffer from a build-up of damage caused by the displacement cascades initiated by nuclear reactions. Previously, the main "measure" of this damage accumulation has been through the displacements per atom (dpa) index. There are known limitations associated with the dpa quantity and its domain of application and therefore this paper describes a more rigorous methodology to calculate the primary atomic recoil events (often called the primary knock-on atoms or PKAs) that lead to cascade damage events as a function of energy and recoiling species for any simulated or measured neutron irradiation scenario. Via examples of fusion relevant materials, it is shown that the PKA spectra can be complex, involving many different recoiling species, potentially differing in both proton and neutron number from the original target nuclei, including high energy recoils of light emitted particles such as alpha-particles and protons. The variations in PKA spectra as a function of time, neutron field, and material are explored. Example PKA spectra are applied to radiation damage quantification using the binary collision approximation and stochastic cluster dynamics, and the results from these different approaches are discussed and compared., Comment: 27 pages, 12 numbers figures

We use a physically-based crystal plasticity model to predict the yield strength of body-centered cubic (bcc) tungsten single crystals subjected to uniaxial loading. Our model captures the thermally-activated character of screw dislocation motion and full non-Schmid effects, both of which are known to play a critical role in bcc plasticity. The model uses atomistic calculations as the sole source of constitutive information, with no parameter fitting of any kind to experimental data. Our results are in excellent agreement with experimental measurements of the yield stress as a function of temperature for a number of loading orientations. The validated methodology is then employed to calculate the temperature and strain-rate dependence of the yield strength for 231 crystallographic orientations within the standard stereographic triangle. We extract the strain-rate sensitivity of W crystals at different temperatures, and finish with the calculation of yield surfaces under biaxial loading conditions that can be used to define effective yield criteria for engineering design models.

An improved version of a recently developed stochastic cluster dynamics (SCD) method {[}Marian, J. and Bulatov, V. V., {\it J. Nucl. Mater.} \textbf{415} (2014) 84-95{]} is introduced as an alternative to rate theory (RT) methods for solving coupled ordinary differential equation (ODE) systems for irradiation damage simulations. SCD circumvents by design the curse of dimensionality of the variable space that renders traditional ODE-based RT approaches inefficient when handling complex defect population comprised of multiple (more than two) defect species. Several improvements introduced here enable efficient and accurate simulations of irradiated materials up to realistic (high) damage doses characteristic of next-generation nuclear systems. The first improvement is a procedure for efficiently updating the defect reaction-network and event selection in the context of a dynamically expanding reaction-network. Next is a novel implementation of the $\tau$-leaping method that speeds up SCD simulations by advancing the state of the reaction network in large time increments when appropriate. Lastly, a volume rescaling procedure is introduced to control the computational complexity of the expanding reaction-network through occasional reductions of the defect population while maintaining accurate statistics. The enhanced SCD method is then applied to model defect cluster accumulation in iron thin films subjected to triple ion-beam ($\text{Fe}^{3+}$, $\text{He}^{+}$ and $ $$\text{H\ensuremath{{}^{+}}}$$ $) irradiations, for which standard RT or spatially-resolved kinetic Monte Carlo simulations are prohibitively expensive.

Thermally-activated $\small{\nicefrac{1}{2}}<111>$ screw dislocation motion is the controlling plastic mechanism at low temperatures in body-centered cubic (bcc) crystals. Motion proceeds by the nucleation and propagation of atomic-sized kink pairs susceptible of being studied using molecular dynamics (MD). However, MD's natural inability to properly sample thermally-activated processes as well as to capture $\{110\}$ screw dislocation glide calls for the development of other methods capable of overcoming these limitations. Here we develop a kinetic Monte Carlo (kMC) approach to study single screw dislocation dynamics from room temperature to $0.5T_m$ and at stresses $0<\sigma<0.9\sigma_P$, where $T_m$ and $\sigma_P$ are the melting point and the Peierls stress. The method is entirely parameterized with atomistic simulations using an embedded atom potential for tungsten. To increase the physical fidelity of our simulations, we calculate the deviations from Schmid's law prescribed by the interatomic potential used and we study single dislocation kinetics using both projections. We calculate dislocation velocities as a function of stress, temperature, and dislocation line length. We find that considering non-Schmid effects has a strong influence on both the magnitude of the velocities and the trajectories followed by the dislocation. We finish by condensing all the calculated data into effective stress and temperature dependent mobilities to be used in more homogenized numerical methods.

The kinetic Monte Carlo (kMC) method is used in many scientific fields in applications involving rare-event transitions. Due to its discrete stochastic nature, efforts to parallelize kMC approaches often produce unbalanced time evolutions requiring complex implementations to ensure correct statistics. In the context of parallel kMC, the sequential update technique has shown promise by generating high quality distributions with high relative efficiencies for short-range systems. In this work, we provide an extension of the sequential update method in a parallel context that rigorously obeys detailed balance, which guarantees exact equilibrium statistics for all parallelization settings. Our approach also preserves nonequilibrium dynamics with minimal error for many parallelization settings, and can be used to achieve highly precise sampling.

Germanium is the base element in many phase-change materials, i.e. systems that can undergo reversible transformations between their crystalline and amorphous phases. They are widely used in current digital electronics and hold great promise for the next generation of non-volatile memory devices. However, the ultra fast phase transformations required for these applications can be exceedingly complex even for single component systems, and a full physical understanding of these phenomena is still lacking. In this paper we study nucleation and growth of crystalline Ge from amorphous thin films at high temperature using phase field models informed by atomistic calculations of fundamental material properties. The atomistic calculations capture the full anisotropy of the Ge crystal lattice, which results in orientation dependences for interfacial energies and mobilities. These orientation relations are then exactly recovered by the phase field model at finite thickness via a novel parametrization strategy based on invariance solutions of the Allen-Cahn equations. By means of this multiscale approach, we study the interplay between nucleation and growth and find that the relation between the mean radius of the crystallized Ge grains and the nucleation rate follows simple Avrami-type scaling laws. We argue that these can be used to cover a wide region of the nucleation rate space, hence facilitating comparison with experiments.

We conduct dislocation dynamics (DD) simulations of Fe periodic single crystals under tensile load at several high strain rates and temperatures. The simulations are enabled by the recent development of temperature-dependent dislocation mobility relations obtained from atomistic calculations. The plastic evolution in the simulations is governed by rapid initial dislocation multiplication, followed by a saturation of the flow stress when the subpopulation of slow plastic carriers becomes stabilized by dislocation annihilation. Above 500 K, edge dislocations coexist with screw dislocations and contribute proportionaly to the value of the flow stress. The DD simulations are used to interpret shock-loading experiments in Fe in terms of the relative importance of different strengthening mechanisms. We find that in the $10^4$-to-$10^6$ s$^{-1}$ strain rate regime, work hardening explains the hardening of shock-loaded bulk Fe crystals.

Metals which can form intermetallic compounds by an exothermic reaction constitute a class of reactive materials with multiple applications. Ni-Al laminates of thin alternating layers are being considered as model nanometric metallic multilayers for studying various reaction processes. However, the reaction kinetics at short timescales after mixing are not entirely understood. In this work, we calculate the free energies of Ni-Al alloys as a function of composition and temperature for different solid phases using thermodynamic integration based on state-of-the-art interatomic potentials. We use this information to interpret molecular dynamics (MD) simulations of bilayer systems at 800 K and zero pressure, both in isothermal and isenthalpic conditions. We find that a disordered phase always forms upon mixing as a precursor to a more stable nano crystalline B2 phase. We construe the reactions observed in terms of thermodynamic trajectories governed by the state variables computed. Simulated times of up to 30 ns were achieved, which provides a window to phenomena not previously observed in MD simulations. Our results provide insight into the early experimental reaction timescales and suggest that the path (segregated reactants)$\rightarrow$(disordered phase)$\rightarrow$(B2 structure) is always realized irrespective of the imposed boundary conditions.

In body-centered cubic (bcc) crystals, ${1}{2}111$ screw dislocations exhibit high intrinsic lattice friction as a consequence of their non-planar core structure, which results in a periodic energy landscape known as the Peierls potential, $U_P$. The main features determining plastic flow, including its stress and temperature dependences, can be derived directly from this potential, hence its importance. In this Letter, we use thermodynamic integration to provide a full thermodynamic extension of $U_P$ for bcc Fe. We compute the Peierls free energy path as a function of stress and temperature and show that the critical stress vanishes at 700K, supplying the qualitative elements that explain plastic behavior in the athermal limit.

The Fe-Cu system has attracted much attention over the last several decades due to its technological importance as a model alloy for Cu steels. In spite of these efforts several aspects of its phase diagram remain unexplained. Here we use atomistic simulations to characterize the polymorphic phase diagram of Cu precipitates in body-centered cubic (BCC) Fe and establish a consistent link between their thermodynamic and mechanical properties in terms of thermal stability, shape, and strength. The size at which Cu precipitates transform from BCC to a close-packed 9R structure is found to be strongly temperature dependent, ranging from approximately 4 nm in diameter (~2,700 atoms) at 200 K to about 8 nm (~22,800 atoms) at 700 K. These numbers are in very good agreement with the interpretation of experimental data given Monzen et al. [Phil. Mag. A 80, 711 (2000)]. The strong temperature dependence originates from the entropic stabilization of BCC Cu, which is mechanically unstable as a bulk phase. While at high temperatures the transition exhibits first-order characteristics, the hysteresis, and thus the nucleation barrier, vanish at temperatures below approximately 300\,K. This behavior is explained in terms of the mutual cancellation of the energy differences between core and shell (wetting layer) regions of BCC and 9R nanoprecipitates, respectively. The proposed mechanism is not specific for the Fe--Cu system but could generally be observed in immiscible systems, whenever the minority component is unstable in the lattice structure of the host matrix. Finally, we also study the interaction of precipitates with screw dislocations as a function of both structure and orientation. The results provide a coherent picture of precipitate strength that unifies previous calculations and experimental observations., Comment: 15 pages, 15 figures

Screw dislocations in bcc metals display non-planar cores at zero temperature which result in high lattice friction and thermally activated strain rate behavior. In bcc W, electronic structure molecular statics calculations reveal a compact, non-degenerate core with an associated Peierls stress between 1.7 and 2.8 GPa. However, a full picture of the dynamic behavior of dislocations can only be gained by using more efficient atomistic simulations based on semiempirical interatomic potentials. In this paper we assess the suitability of five different potentials in terms of static properties relevant to screw dislocations in pure W. As well, we perform molecular dynamics simulations of stress-assisted glide using all five potentials to study the dynamic behavior of screw dislocations under shear stress. Dislocations are seen to display thermally-activated motion in most of the applied stress range, with a gradual transition to a viscous damping regime at high stresses. We find that one potential predicts a core transformation from compact to dissociated at finite temperature that affects the energetics of kink-pair production and impacts the mechanism of motion. We conclude that a modified embedded-atom potential achieves the best compromise in terms of static and dynamic screw dislocation properties, although at an expense of about ten-fold compared to central potentials.

Ion-implantation is a useful technique to study irradiation damage in nuclear materials. To study He effects in nuclear fusion conditions, He is co-implanted with damage ions to reproduce the correct He/dpa ratios in the desired or available depth range. However, the short-term fate of these He ions, i.e over the time scales of their own collisional phase, has not been yet unequivocally established. Here we present an atomistic study of the short-term evolution of He implantation in an Fe substrate to approximate the conditions encountered in dual ion-implantation studies in ferritic materials. Specifically, we calculate the fraction of He atoms that end up in substitutional sites shortly after implantation, i.e. before they contribute to long-term miscrostructural evolution. We find that fractions of at most 3% should be expected for most implantation studies. In addition, we carry out an exhaustive calculation of interstitial He migration energy barriers in the vicinity of matrix vacancies and find that they vary from approximately 20 to 60 meV depending on the separation and orientation of the He-vacancy pair., Comment: 7 pages, 6 figures, 2 tables

An extension of the synchronous parallel kinetic Monte Carlo (pkMC) algorithm developed by Martinez {\it et al} [{\it J.\ Comp.\ Phys.} {\bf 227} (2008) 3804] to discrete lattices is presented. The method solves the master equation synchronously by recourse to null events that keep all processors time clocks current in a global sense. Boundary conflicts are rigorously solved by adopting a chessboard decomposition into non-interacting sublattices. We find that the bias introduced by the spatial correlations attendant to the sublattice decomposition is within the standard deviation of the serial method, which confirms the statistical validity of the method. We have assessed the parallel efficiency of the method and find that our algorithm scales consistently with problem size and sublattice partition. We apply the method to the calculation of scale-dependent critical exponents in billion-atom 3D Ising systems, with very good agreement with state-of-the-art multispin simulations.