The dissolution and depletion of chromium (Cr) in salt facing nickel (Ni) alloy surfaces is one of the predominant degradation mechanisms of structural components in molten salt technology. In this work, we use density functional theory to investigate the role of electronic level interactions that may underlie the depletion phenomenon of Cr in a Ni 100 surface exposed to various adsorbed salt species. Our results show that, under vacuum, Ni preferentially segregates to the surface layer. Conversely, in the presence of adsorbed anionic salt species (e.g., chlorine (Cl), fluorine (F) or the impurity oxygen (O)) Cr segregation becomes more favorable. In these cases, Cl has the weakest effect on segregation, while O has the strongest effect. Our analysis reveals the strong correlation between Cr segregation and the amount of valence charge transferred between the Cr atom and surface adsorbate: the greater the charge transfer, the lower the segregation energy. We also show that, when considered, secondary cations screen Cr-anion interactions, which in turn reduce the magnitude of the anions effect on segregation. These results shed light on the role of salt impurities likely play in the overall corrosion phenomena in molten salt environments. This work provides insights into the atomic level interactions fundamental to molten salt corrosion and on the importance of maintaining salt purity.
Co-deposited, immiscible alloy systems form hierarchical microstructures under specific deposition conditions that accentuate the difference in constituent element mobility. The mechanism leading to the formation of these unique hierarchical morphologies during the deposition process is difficult to identify, since the characterization of these microstructures is typically carried out post-deposition. We employ phase-field modeling to study the evolution of microstructures during deposition combined with microscopy characterization of experimentally deposited thin films to reveal the origin of the formation mechanism of hierarchical morphologies in co-deposited, immiscible alloy thin films. Our results trace this back to the significant influence of a local compositional driving force that occurs near the surface of the growing thin film. We show that local variations in the concentration of the vapor phase near the surface, resulting in nuclei (i.e., a cluster of atoms) on the film’s surface with an inhomogeneous composition, can trigger the simultaneous evolution of multiple concentration modulations across multiple length scales, leading to hierarchical morphologies. We show that locally, the concentration must be above a certain threshold value in order to generate distinct hierarchical morphologies in a single domain.
Ni-Cr alloys exhibit oscillatory segregation behaviors near low index surfaces, in which the preferred segregation species changes from Ni in the first layer to Cr in the second layer. In many dilute-alloy systems, this oscillatory pattern is attributed to the elastic release of stresses in the local lattice around the segregating solute or impurity atom. These stresses are mostly thought to originate from mismatches in the atomic size of the solute and host atoms. In Ni-Cr alloys, however, an appreciable mismatch in atomic size is not present, leading to questions about the origins of the oscillatory behavior in this alloy. Using density functional theory, we have modeled the segregation of a single Cr atom in the (100) and (111) surfaces of FCC Ni, an alloy which exhibits this oscillatory behavior. Using Bader charge analysis, we show that the negative energy correlates directly with the amount of charge on the Cr atom. As Ni atoms strip valence charge from the Cr, the Cr contracts slightly in size. The greatest contraction and highest positive charge for the Cr occurs when it is in the second layer of the surface where the system exhibits the oscillating negative segregation energy. We then find that this behavior persists in other alloy systems (Ag-Nb, Cu-Cr, Pt-Nb, and Pt-V), which exhibit similar atomic radii and electronegativity differences between host and solute to Ni-Cr. These represent alloys in which the host metal exhibits an FCC ground-state structure while the solute metal exhibits a BCC ground-state structure.
Metamaterials are artificial structures that can manipulate and control sound waves in ways not possible with conventional materials. While much effort has been undertaken to widen the bandgaps produced by these materials through design of heterogeneities within unit cells, comparatively little work has considered the effect of engineering heterogeneities at the structural scale by combining different types of unit cells. In this paper, we use the relaxed micromorphic model to study wave propagation in heterogeneous metastructures composed of different unit cells. We first establish the efficacy of the relaxed micromorphic model for capturing the salient characteristics of dispersive wave propagation through comparisons with direct numerical simulations for two classes of metamaterial unit cells: namely phononic crystals and locally resonant metamaterials. We then use this model to demonstrate how spatially arranging multiple unit cells into metastructures can lead to tailored and unique properties such as spatially-dependent broadband wave attenuation, rainbow trapping, and pulse shaping. In the case of the broadband wave attenuation application, we show that by building layered metastructures from different metamaterial unit cells, we can slow down or stop wave packets in an enlarged frequency range, while letting other frequencies through. In the case of the rainbow-trapping application, we show that spatial arrangements of different unit cells can be designed to progressively slow down and eventually stop waves with different frequencies at different spatial locations. Finally, in the case of the pulse-shaping application, our results show that heterogeneous metastructures can be designed to tailor the spatial profile of a propagating wave packet. Collectively, these results show the versatility of the relaxed micromorphic model for effectively and accurately simulating wave propagation in heterogeneous metastructures, and how this model can be used to design heterogeneous metastructures with tailored wave propagation functionalities.
Echeverria, Marco J.; Galitskiy, Sergey; Mishra, Avanish; Dingreville, Remi; Dongare, Avinash M.
A hybrid atomic-scale and continuum-modeling framework is used to study the microstructural evolution during the laser-induced shock deformation and failure (spallation) of copper microstructures. A continuum two-temperature model (TTM) is used to account for the interaction of Cu atoms with a laser in molecular dynamics (MD) simulations. The MD-TTM simulations study the effect of laser-loading conditions (laser fluence) on the microstructure (defects) evolution during various stages of shock wave propagation, reflection, and interaction in single-crystal (sc) Cu systems. In addition, the role of the microstructure is investigated by comparing the defect evolution and spall response of sc-Cu and nanocrystalline Cu systems. The defect (stacking faults and twin faults) evolution behavior in the metal at various times is further characterized using virtual in situ selected area electron diffraction and x-ray diffraction during various stages of evolution of microstructure. The simulations elucidate the uncertain relation between spall strength and strain-rate and the much stronger relation between the spall strength and the temperatures generated due to laser shock loading for the small Cu sample dimensions considered here.
Designing next generation thin films, tailor-made for specific applications, relies on the availability of robust processing-structure-property relationships. Traditional structure zone diagrams are limited to low-dimensional mappings, with machine-learning methods only recently attempting to relate multiple processing parameters to the final microstructure. Despite this progress, structure-processing relationships are unknown for processing conditions that vary during thin-film deposition, limiting the range of microstructures and properties achievable. In this project, we employed a phase-field computational model combined with a genetic algorithm (GA) to identify and design time-dependent processing protocols that achieve tailor-made microstructures. We simulate the physical vapor deposition of a binary-alloy thin film by employing a phase-field model, where deposition rates and diffusivities are controlled via the genetic algorithm. Our GA-guided protocols achieve targeted microstructures with lateral and vertical concentration modulations, as well as more complex, hierarchical microstructures previously not described in simple structure zone diagrams. Our algorithm provides insight to experimentalists looking for additional avenues to design novel thin-film microstructures.
With the rapid proliferation of additive manufacturing and 3D printing technologies, architected cellular solids including truss-like 3D lattice topologies offer the opportunity to program the effective material response through topological design at the mesoscale. The present report summarizes several of the key findings from a 3-year Laboratory Directed Research and Development Program. The program set out to explore novel lattice topologies that can be designed to control, redirect, or dissipate energy from one or multiple insult environments relevant to Sandia missions, including crush, shock/impact, vibration, thermal, etc. In the first 4 sections, we document four novel lattice topologies stemming from this study: coulombic lattices, multi-morphology lattices, interpenetrating lattices, and pore-modified gyroid cellular solids, each with unique properties that had not been achieved by existing cellular/lattice metamaterials. The fifth section explores how unintentional lattice imperfections stemming from the manufacturing process, primarily sur face roughness in the case of laser powder bed fusion, serve to cause stochastic response but that in some cases such as elastic response the stochastic behavior is homogenized through the adoption of lattices. In the sixth section we explore a novel neural network screening process that allows such stocastic variability to be predicted. In the last three sections, we explore considerations of computational design of lattices. Specifically, in section 7 using a novel generative optimization scheme to design novel pareto-optimal lattices for multi-objective environments. In section 8, we use computational design to optimize a metallic lattice structure to absorb impact energy for a 1000 ft/s impact. And in section 9, we develop a modified micromorphic continuum model to solve wave propagation problems in lattices efficiently.
We investigate the unitary mechanisms related to the surface migration of vacancies in dilute Ni-Cr alloys via first-principle calculations. We survey a complete set of surface and sub-surface migration paths for vacancies near the (100) free surface and calculate the corresponding migration barriers. Our results show that a vacancy migrating towards the free surface will face lower energy barriers to migrate via atomic exchange with a neighboring Cr atom rather than with a Ni atom. Once a vacancy reaches the free surface, it will be trapped there. Our results also reveal that, when a Cr atom sits in the atomic plane just below the free surface, any in-plane vacancy hopping jump that would result in the vacancy sitting on top a subsurface Cr atom is energetically unfavorable. Taken together, these fundamental unitary surface migration mechanisms offer insights into the complex interactions between surface segregation and vacancy migration phenomena in Ni-Cr-based alloys.
This project focused on providing a fundamental physico-chemical understanding of the coupling mechanisms of corrosion- and radiation-induced degradation at material-salt interfaces in Ni-based alloys operating in emulated Molten Salt Reactor(MSR) environments through the use of a unique suite of aging experiments, in-situ nanoscale characterization experiments on these materials, and multi-physics computational models. The technical basis and capabilities described in this report bring us a step closer to accelerate the deployment of MSRs by closing knowledge gaps related to materials degradation in harsh environments.
Nanostructures with a high density of interfaces, such as in nanoporous materials and nanowires, resist radiation damage by promoting the annihilation and migration of defects. This study details the size effect and origins of the radiation damage mechanisms in nanowires and nanoporous structures in model face-centered (gold) and body-centered (niobium) cubic nanostructures using accelerated multi-cascade atomistic simulations and in-situ ion irradiation experiments. Our results reveal three different size-dependent mechanisms of damage accumulation in irradiated nanowires and nanoporous structures: sputtering for very small nanowires and ligaments, the formation and accumulation of point defects and dislocation loops in larger nanowires, and a face-centered-cubic to hexagonal-close-packed phase transformation for a narrow range of wire diameters in the case of gold nanowires. Smaller nanowires and ligaments have a net effect of lowering the radiation damage as compared to larger wires that can be traced back to the fact that smaller nanowires transition from a rapid accumulation of defects to a saturation and annihilation mechanism at a lower dose than larger nanowires. These irradiation damage mechanisms are accompanied with radiation-induced surface roughening resulting from defect-surface interactions. Comparisons between nanowires and nanoporous structures show that the various mechanisms seen in nanowires provide adequate bounds for the defect accumulation mechanisms in nanoporous structures with the difference attributed to the role of nodes connecting ligaments in nanoporous structures. Taken together, our results shed light on the compounded, size-dependent mechanisms leading to the radiation resistance of nanowires and nanoporous structures.
Twin boundaries play an important role in the thermodynamics, stability, and mechanical properties of nanocrystalline metals. Understanding their structure and chemistry at the atomic scale is key to guide strategies for fabricating nanocrystalline materials with improved properties. We report an unusual segregation phenomenon at gold-doped platinum twin boundaries, which is arbitrated by the presence of disconnections, a type of interfacial line defect. By using atomistic simulations, we show that disconnections containing a stacking fault can induce an unexpected transition in the interfacial-segregation structure at the atomic scale, from a bilayer, alternating-segregation structure to a trilayer, segregation-only structure. This behavior is found for faulted disconnections of varying step heights and dislocation characters. Supported by a structural analysis and the classical Langmuir-McLean segregation model, we reveal that this phenomenon is driven by a structurally induced drop of the local pressure across the faulted disconnection accompanied by an increase in the segregation volume.
Temperature- and irradiation-assisted failure mechanisms in miscible phase boundaries are clarified via atomistic calculations. We first establish the temperature-dependent brittle-to-ductile transition in U–Zr miscible phase boundaries. Our results confirm that these boundaries are mostly brittle at low temperatures and ductile at elevated temperatures. We then investigate the changes induced by irradiation on the fracture mechanisms in such phase boundaries. The irradiation-induced defect accumulation follows a multi-stage process that starts with the accumulation of isolated small dislocation loops before transitioning to the saturation and growth of larger dislocation loops and end up with a reorganization into forest dislocations. The accumulation of loops is the primary feature to participate in the delineation between brittle and ductile interfacial fracture in irradiated phase boundaries. At low damage levels, radiation defect interactions with the crack tip are limited and U–Zr miscible boundaries fail through the emission of dislocations ahead of the crack tip followed by brittle cleavage in agreement with the classical Griffith’s criterion for crack stability. At higher damage levels, the failure mode transitions from brittle crack growth to ductile void growth. In this case, the microcrack tip is blunted by the high density of pre-existing, radiation-induced defects in the vicinity of the crack. This interaction leads to the development and growth of a cavity at the interface as opposed to interfacial cleavage.
Grain boundaries in metallic materials can exist in a wide range of stable and metastable structures. In addition, the properties of a grain boundary may be altered through solute segregation. In this work, we present a formulation that combines the spectrum of embrittling potencies associated with solute segregation with site-occupancy statistics. As a prototype problem, we illustrate the relation between segregation and embrittlement in the case of S segregation to grain boundaries in Ni. To obtain a population of site segregation energies, we perform molecular statics calculations on 378 different symmetric-tilt grain boundaries and their free surface equivalents, using an embedded-atom method interatomic potential developed specifically for studying embrittlement. Our results show that it is important to consider both the energies associated with embrittlement and the probability of occupancy to describe the general embrittling nature of a grain boundary. When analyzed in isolation, certain grain boundaries show large embrittling potencies; however, that effect is diminished when the probability of S segregation to that grain boundary is considered within a polycrystal. We propose a new quantity, the embrittling estimator, which not only categorizes grain boundaries as embrittling or strengthening, but also considers site occupancy probabilities, so that the embrittlement behavior of grain boundaries within a network of grain boundaries can be compared. Finally, we examine the relationship between embrittlement behavior and innate grain boundary properties, such as the free volume, and find statistical evidence that the complex nature of embrittlement cannot be explained by linear correlations with excess volumes or energies. Ultimately, this combined approach provides a theoretical tool to assist grain boundary engineering of metastable alloys.
Predicting the properties of grain boundaries poses a challenge because of the complex relationships between structural and chemical attributes both at the atomic and continuum scales. Grain boundary systems are typically characterized by parameters used to classify local atomic arrangements in order to extract features such as grain boundary energy or grain boundary strength. The present work utilizes a combination of high-throughput atomistic simulations, macroscopic and microscopic descriptors, and machine-learning techniques to characterize the energy and strength of silicon carbide grain boundaries. A diverse data set of symmetric tilt and twist grain boundaries are described using macroscopic metrics such as misorientation, the alignment of critical low-index planes, and the Schmid factor, but also in terms of microscopic metrics, by quantifying the local atomic structure and chemistry at the interface. These descriptors are used to create random-forest regression models, allowing for their relative importance to the grain boundary energy and decohesion stress to be better understood. Results show that while the energetics of the grain boundary were best described using the microscopic descriptors, the ability of the macroscopic descriptors to reasonably predict grain boundaries with low energy suggests a link between the crystallographic orientation and the resultant atomic structure that forms at the grain boundary within this regime. For grain boundary strength, neither microscopic nor macroscopic descriptors were able to fully capture the response individually. However, when both descriptor sets were utilized, the decohesion stress of the grain boundary could be accurately predicted. These results highlight the importance of considering both macroscopic and microscopic factors when constructing constitutive models for grain boundary systems, which has significant implications for both understanding the fundamental mechanisms at work and the ability to bridge length scales.
The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures and associated properties for a wide variety of physical, chemical, and biological systems. However, existing high-fidelity phase-field models are inherently computationally expensive, requiring high-performance computing resources and sophisticated numerical integration schemes to achieve a useful degree of accuracy. In this paper, we present a computationally inexpensive, accurate, data-driven surrogate model that directly learns the microstructural evolution of targeted systems by combining phase-field and history-dependent machine-learning techniques. We integrate a statistically representative, low-dimensional description of the microstructure, obtained directly from phase-field simulations, with either a time-series multivariate adaptive regression splines autoregressive algorithm or a long short-term memory neural network. The neural-network-trained surrogate model shows the best performance and accurately predicts the nonlinear microstructure evolution of a two-phase mixture during spinodal decomposition in seconds, without the need for “on-the-fly” solutions of the phase-field equations of motion. We also show that the predictions from our machine-learned surrogate model can be fed directly as an input into a classical high-fidelity phase-field model in order to accelerate the high-fidelity phase-field simulations by leaping in time. Such machine-learned phase-field framework opens a promising path forward to use accelerated phase-field simulations for discovering, understanding, and predicting processing–microstructure–performance relationships.
Understanding phase transformations in 2D materials can unlock unprecedented developments in nanotechnology, since their unique properties can be dramatically modified by external fields that control the phase change. Here, experiments and simulations are used to investigate the mechanical properties of a 2D diamond boron nitride (BN) phase induced by applying local pressure on atomically thin h-BN on a SiO2 substrate, at room temperature, and without chemical functionalization. Molecular dynamics (MD) simulations show a metastable local rearrangement of the h-BN atoms into diamond crystal clusters when increasing the indentation pressure. Raman spectroscopy experiments confirm the presence of a pressure-induced cubic BN phase, and its metastability upon release of pressure. Å-indentation experiments and simulations show that at pressures of 2–4 GPa, the indentation stiffness of monolayer h-BN on SiO2 is the same of bare SiO2, whereas for two- and three-layer-thick h-BN on SiO2 the stiffness increases of up to 50% compared to bare SiO2, and then it decreases when increasing the number of layers. Up to 4 GPa, the reduced strain in the layers closer to the substrate decreases the probability of the sp2-to-sp3 phase transition, explaining the lower stiffness observed in thicker h-BN.
The accumulation of point defects and defect clusters in materials, as seen in irradiated metals for example, can lead to the formation and growth of voids. Void nucleation is derived from the condensation of supersaturated vacancies and depends strongly on the stress state. It is usually assumed that such stress states can be produced by microstructural defects such dislocations, grain boundaries or triple junctions, however, much less attention has been brought to the formation of voids near microcracks. In this paper, we investigate the coupling between point-defect diffusion/recombination and concentrated stress fields near mode-I crack tips via a spatially-resolved rate theory approach. A modified chemical potential enables point-defect diffusion to be partially driven by the mechanical fields in the vicinity of the crack tip. Simulations are carried out for microcracks using the Griffith model with increasing stress intensity factor K1. Our results show that below a threshold for the stress intensity factor, the microcrack acts purely as a microstructural sink, absorbing point defects. Above this threshold, vacancies accumulate at the crack tip. These results suggest that, even in the absence of plastic deformation, voids can form in the vicinity of a microcrack for a given load when the crack’s characteristic length is above a critical length. While in ductile metals, irradiation damage generally causes hardening and corresponding quasi-brittle cleavage, our results show that irradiation conditions can favor void formation near microstructural stressors such as crack tips leading to lower resistance to crack propagation as predicted by traditional failure analysis.
This report details the current benchmark results to verify, validate and demonstrate the capabilities of the in-house multi-physics phase-field modeling framework Mesoscale Multiphysics Phase Field Simulator (MEMPHIS) developed at the Center for Integrated Nanotechnologies (CINT). MEMPHIS is a general phase-field capability to model various nanoscience and materials science phenomena related to microstructure evolution. MEMPHIS has been benchmarked against a suite of reported classical phase-field benchmark problems to verify and validate the correctness, accuracy and precision of the models and numerical methods currently implemented into the code.
Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.
While lattice metamaterials can achieve exceptional energy absorption by tailoring periodically distributed heterogeneous unit cells, relatively little focus has been placed on engineering heterogeneity above the unit-cell level. In this work, the energy-absorption performance of lattice metamaterials with a heterogeneous spatial layout of different unit cell architectures was studied. Such multi-morphology lattices can harness the distinct mechanical properties of different unit cells while being composed out of a single base material. A rational design approach was developed to explore the design space of these lattices, inspiring a non-intuitive design which was evaluated alongside designs based on mixture rules. Fabrication was carried out using two different base materials: 316L stainless steel and Vero White photopolymer. Results show that multi-morphology lattices can be used to achieve higher specific energy absorption than homogeneous lattice metamaterials. Additionally, it is shown that a rational design approach can inspire multi-morphology lattices which exceed rule-of-mixtures expectations.
The self-interstitial atom (SIA) is one of two fundamental point defects in bulk Si. Isolated Si SIAs are extremely difficult to observe experimentally. Even at very low temperatures, they anneal before typical experiments can be performed. Given the challenges associated with experimental characterization, accurate theoretical calculations provide valuable information necessary to elucidate the properties of these defects. Previous studies have applied Kohn-Sham density functional theory (DFT) to the Si SIA, using either the local density approximation or the generalized gradient approximation to the exchange-correlation (XC) energy. The consensus of these studies indicates that a Si SIA may exist in five charge states ranging from -2 to +2 with the defect structure being dependent on the charge state. This study aims to re-examine the existence of these charge states in light of recently derived "approximate bounds"on the defect levels obtained from finite-size supercell calculations and new DFT calculations using both semi-local and hybrid XC approximations. We conclude that only the neutral and +2 charge states are directly supported by DFT as localized charge states of the Si SIA. Within the current accuracy of DFT, our results indicate that the +1 charge state likely consists of an electron in a conduction-band-like state that is coulombically bound to a +2 SIA. Furthermore, the -1 and -2 charge states likely consist of a neutral SIA with one and two additional electrons in the conduction band, respectively.
The interaction of energetic ions with the electronic and ionic system of target materials is an interesting but challenging multiscale problem, and understanding of the early stages after impact of heavy, initially charged ions is particularly poor. At the same time, energy deposition during these early stages determines later formation of damage cascades. We address the multiscale character by combining real-time time-dependent density functional theory for electron dynamics with molecular dynamics simulations of damage cascades. Our first-principles simulations prove that core electrons affect electronic stopping and have an unexpected influence on the charge state of the projectile. We show that this effect is absent for light projectiles, but dominates the stopping physics for heavy projectiles. By parametrizing an inelastic energy loss friction term in the molecular dynamics simulations using our first-principles results, we also show a qualitative influence of electronic stopping physics on radiation-damage cascades.
This report details the current benchmark results to verify, validate and demonstrate the capabilities of the in-house multi-physics phase-field modeling framework Mesoscale Multiphysics Phase Field Simulator (MEMPHIS) developed at the Center for Integrated Nanotechnologies (CINT). MEMPHIS is a general phase-field capability to model various nanoscience and materials science phenomena related to microstructure evolution. MEMPHIS has been benchmarked against a suite of reported 'classical' phase-field benchmark problems to verify and validate the correctness, accuracy and precision of the models and numerical methods currently implemented into the code.
Atomistic modeling of radiation damage through displacement cascades is deceptively non-trivial. Due to the high energy and stochastic nature of atomic collisions, individual primary knock-on atom (PKA) cascade simulations are computationally expensive and ill-suited for length and dose upscaling. Here, we propose a reduced-order atomistic cascade model capable of predicting and replicating radiation events in metals across a wide range of recoil energies. Our methodology approximates cascade and displacement damage production by modeling the cascade as a core-shell atomic structure composed of two damage production estimators, namely an athermal recombination corrected displacements per atom (arc-dpa) in the shell and a replacements per atom (rpa) representing atomic mixing in the core. These estimators are calibrated from explicit PKA simulations and a standard displacement damage model that incorporates cascade defect production efficiency and mixing effects. We illustrate the predictability and accuracy of our reduced-order atomistic cascade method for the cases of copper and niobium by comparing its results with those from full PKA simulations in terms of defect production as well as the resulting cascade evolution and structure. We provide examples for simulating high energy cascade fragmentation and large dose ion-bombardment to demonstrate its possible applicability. Finally, we discuss the various practical considerations and challenges associated with this methodology especially when simulating subcascade formation and dose effects.
Since the landmark development of the Scherrer method a century ago, multiple generations of width methods for X-ray diffraction originated to non-invasively and rapidly characterize the property-controlling sizes of nanoparticles, nanowires, and nanocrystalline materials. However, the predictive power of this approach suffers from inconsistencies among numerous methods and from misinterpretations of the results. Therefore, we systematically evaluated twenty-two width methods on a representative nanomaterial subjected to thermal and mechanical loads. To bypass experimental complications and enable a 1:1 comparison between ground truths and the results of width methods, we produced virtual X-ray diffractograms from atomistic simulations. These simulations realistically captured the trends that we observed in experimental synchrotron diffraction. To comprehensively survey the width methods and to guide future investigations, we introduced a consistent, descriptive nomenclature. Alarmingly, our results demonstrated that popular width methods, especially the Williamson-Hall methods, can produce dramatically incorrect trends. We also showed that the simple Scherrer methods and the rare Energy methods can well characterize unloaded and loaded states, respectively. Overall, this work improved the utility of X-ray diffraction in experimentally evaluating a variety of nanomaterials by guiding the selection and interpretation of width methods.
The predictions of scaling laws for the structure and properties of defect clusters are generally limited to small defect clusters in their ground-state configurations. We investigated the size and geometrical configuration dependence of nano-sized defect clusters in niobium (Nb) using molecular dynamics. We studied the structure and stability of large clusters of size up to fifty defects for vacancies and one hundred defects for interstitials, as well as the role of helium and metastable configurations on the stability of these clusters. We compared three different interatomic potentials in order to determine the relative stability of these clusters as a function of their size and geometrical configurations. Additionally, we conducted a statistical analysis to predict the formation and binding energies of interstitial clusters as a function of both their size and configuration. We find that the size dependence of vacancy and interstitial clusters can be approximated by functional forms that account for bulk and surface effects as well as some considerations of elastic interactions. We also find that helium and metastable configurations can make vacancy and interstitial clusters thermally stable depending on the configuration. Our parameterized functional forms for the formation and binding energies are valid for a very broad range of defect sizes and configurations making it possible to be used directly in a coarse-grained modeling strategy such as Monte Carlo, cluster dynamics or dislocation dynamics which look at defect accumulation and evolution in microstructures.
The embrittling or strengthening effect of solute atoms at grain boundaries (GBs), commonly known as the embrittling potency, is an essential thermodynamic property for characterizing the effects of solute segregation on GB fracture. One of the more technologically relevant material systems related to embrittlement is the Ni-S system where S has a deleterious effect on fracture behavior in polycrystalline Ni. In this work, we develop a Ni-S embedded-atom method (EAM) interatomic potential that accounts for the embrittling behavior of S at Ni GBs. Results using this new interatomic potential are then compared to previous density functional theory studies and a reactive force-field potential via a layer-by-layer segregation analysis. Our potential shows strong agreement with existing literature and performs well in predicting properties that are not included in the fitting database. Finally, we calculate embrittling potencies and segregation energies for six [100] symmetric-tilt GBs using the new EAM potential. We observe that embrittling potency is dependent on GB structure, indicating that specific GBs are more susceptible to sulfur-induced embrittlement.
