Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such evolution remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, and atomistic simulation to elucidate how radiation damage and interfacial defects interplay to control grain boundary (GB) motion. While classical notions of boundary evolution under irradiation rest on simple ideas of curvature-driven motion, the reality is far more complex. Focusing on an ion-irradiated Pt Σ3 GB, we show how this boundary evolves by the motion of 120° facet junctions separating nanoscale {112} facets. Our analysis considers the short- and mid-range ion interactions, which roughen the facets and induce local motion, and longer-range interactions associated with interfacial disconnections, which accommodate the intergranular misorientation. We suggest how climb of these disconnections could drive coordinated facet junction motion. These findings emphasize that both local and longer-range, collective interactions are important to understanding irradiation-induced interfacial evolution.
This review discusses atomistic modeling techniques used to simulate radiation damage in crystalline materials. Radiation damage due to energetic particles results in the formation of defects. The subsequent evolution of these defects over multiple length and time scales requiring numerous simulations techniques to model the gamut of behaviors. This work focuses attention on current and new methodologies at the atomistic scale regarding the mechanisms of defect formation at the primary damage state.
Diffraction techniques can powerfully and nondestructively probe materials while maintaining high resolution in both space and time. Unfortunately, these characterizations have been limited and sometimes even erroneous due to the difficulty of decoding the desired material information from features of the diffractograms. Currently, these features are identified non-comprehensively via human intuition, so the resulting models can only predict a subset of the available structural information. In the present work we show (i) how to compute machine-identified features that fully summarize a diffractogram and (ii) how to employ machine learning to reliably connect these features to an expanded set of structural statistics. To exemplify this framework, we assessed virtual electron diffractograms generated from atomistic simulations of irradiated copper. When based on machine-identified features rather than human-identified features, our machine-learning model not only predicted one-point statistics (i.e. density) but also a two-point statistic (i.e. spatial distribution) of the defect population. Hence, this work demonstrates that machine-learning models that input machine-identified features significantly advance the state of the art for accurately and robustly decoding diffractograms.
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.
Cellini, Filippo C.; Lavini, Francesco L.; Chen, Elton Y.; Bongiorno, Angelo B.; Popovic, Filip P.; Hartman, Ryan H.; Dingreville, Remi P.; Riedo, Elisa R.
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.
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.
Irradiation resistance of metallic nanostructured multilayers is determined by the interactions between defects and phase boundaries. However, the dose-dependent interfacial morphology evolution can greatly change the nature of the defect-boundary interaction mechanisms over time. In the present study, we used atomistic models combined with a novel technique based on the accumulation of Frenkel pairs to simulate irradiation processes. We examined dose effects on defect evolutions near zirconium-niobium multilayer phase boundaries. Our simulations enabled us to categorize defect evolution mechanisms in bulk phases into progressing stages of dislocation accumulation, saturation, and coalescence. In the metallic multilayers, we observed a phase boundary absorption mechanism early on during irradiation, while at higher damage levels, the increased irradiation intermixing triggered a phase transformation in the Zr-Nb mixture. This physical phenomenon resulted in the emission of a large quantity of small immobile dislocation loops from the phase boundaries.
Semi-coherent cube-on-cube miscible U–Zr interfaces were studied using molecular dynamics simulations. The misfit accommodation of such semi-coherent phase boundaries was characterized by a two-dimensional dislocation network model utilizing a combination of theoretical predictions and analysis of the atomic system. The dislocation networks were discussed for various stacking orientation of the adjoining phases in terms of the composition of the dislocation sets, the partitioning between edge and screw components and the associated residual elastic fields. These analyses showed that the patterning of the network of dislocations forming these phase boundaries results from the competition between a structurally-driven process (i.e., function of the lattice misfit) and a chemically-driven process (i.e., due to the miscibility between U and Zr).