Computationally-efficient stochastic cluster dynamics method for modeling damage accumulation in irradiated materials

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

Prediction of Bubble and Cavity Nucleation in High Damage Rate Irradiation of Simulated Fe-Cr Alloys Using a Hybrid Cluster Dynamics Model

A new generation of safer, more efficient nuclear reactors is perhaps the most viable way to combat climate change by weening the power grid from carbon-laden fossil fuels. However, many of these advanced designs require high temperatures, corrosive environments, and large irradiation doses which degrade structural components. Development of radiation-tolerant materials is crucial, but conventionally requires long, expensive test reactor irradiations which activate the sample, making examination difficult and costly as well. Ion irradiation experiments present an extremely appealing alternative, as they can introduce decades of radiation damage in a matter of days with minimal activation. Unfortunately, these accelerated testing techniques come with a cost of several experimental artefacts which must be accounted for, the most fundamental of which is that damage rate itself has a tremendous impact on its accumulation. Material degradation on an engineering scale is the result of an extraordinary number of individual atomic-scale picosecond damage events generating defects that migrate, coalesce, and dissociate in just nanoseconds continuously over decades of reactor operation. Clever kinetic models that bridge this massive gap in length and time scales are necessary to gain physical insight into radiation damage which will aid in the development of candidate materials designed on a microscopic scale to minimize defect accumulation. This gap is particularly pronounced for the slow, but often life-limiting phenomenon of swelling, where vacant lattice sites eventually accumulate into sizable cavities which uniformly increase the volume of a component beyond its tolerance. The objective of this work is to use cluster dynamics modeling to better understand the temperature, helium generation, and dose rate dependencies of swelling behavior in simulated Ferritic-Martensitic (FM) steels. An initial study using a conventional modeling approach based on reaction rate theory was fundamentally incapable of reproducing several key experimental swelling observations, but most of these were recovered by iteratively adding novel physical mechanisms. Foremost among these discrepancies was an overprediction of swelling rates, a complete lack of incubation periods, and an almost negligible effect of co-generated helium. Introducing a bias toward interstitials to cavities informed by molecular statics calculations, presented a new barrier to cavity nucleation that could only be overcome through the accumulation of stabilizing helium. Since FM steels have low transmutation rates, helium generation rates are relatively low, resulting in long incubation periods and low swelling rates. Second, the temperature shift—an offset in optimal swelling temperature between high and low dose rate conditions—was overpredicted. A heterogeneous nucleation mechanism, promoting helium self-clustering, weakened dose rate dependence by disproportionately facilitating cavity nucleation at low dose rate, decreasing temperature shift. Finally, observations of swelling without helium were rationalized with bias suppression catalyzed by segregation of chemical impurities to the cavity surface. These mechanisms ultimately combine to constitute a more complete, nuanced understanding of cavity nucleation as a function of temperature, dose rate, and helium generation rate. This creates a more complete account of how microstructures evolve under irradiation and strengthens the predictive link between accelerated ion irradiation experiments and the reactor conditions they seek to emulate. Therefore, in addition to contributions to the fundamental science of irradiation damage, this model could inform the design of future experiments to optimize their investigative potential, hastening the qualification of candidate materials.PHDNuclear Engineering & Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162957/1/gvanc_1.pd

A First-Passage Kinetic Monte Carlo Algorithm for Complex Diffusion-Reaction Systems

We develop an asynchronous event-driven First-Passage Kinetic Monte Carlo (FPKMC) algorithm for continuous time and space systems involving multiple diffusing and reacting species of spherical particles in two and three dimensions. The FPKMC algorithm presented here is based on the method introduced in [Phys. Rev. Lett., 97:230602, 2006] and is implemented in a robust and flexible framework. Unlike standard KMC algorithms such as the n-fold algorithm, FPKMC is most efficient at low densities where it replaces the many small hops needed for reactants to find each other with large first-passage hops sampled from exact time-dependent Green's functions, without sacrificing accuracy. We describe in detail the key components of the algorithm, including the event-loop and the sampling of first-passage probability distributions, and demonstrate the accuracy of the new method. We apply the FPKMC algorithm to the challenging problem of simulation of long-term irradiation of metals, relevant to the performance and aging of nuclear materials in current and future nuclear power plants. The problem of radiation damage spans many decades of time-scales, from picosecond spikes caused by primary cascades, to years of slow damage annealing and microstructure evolution. Our implementation of the FPKMC algorithm has been able to simulate the irradiation of a metal sample for durations that are orders of magnitude longer than any previous simulations using the standard Object KMC or more recent asynchronous algorithms.Comment: See also arXiv:0905.357

IM3D: A parallel Monte Carlo code for efficient simulations of primary radiation displacements and damage in 3D geometry

SRIM-like codes have limitations in describing general 3D geometries, for modeling radiation displacements and damage in nanostructured materials. A universal, computationally efficient and massively parallel 3D Monte Carlo code, IM3D, has been developed with excellent parallel scaling performance. IM3D is based on fast indexing of scattering integrals and the SRIM stopping power database, and allows the user a choice of Constructive Solid Geometry (CSG) or Finite Element Triangle Mesh (FETM) method for constructing 3D shapes and microstructures. For 2D films and multilayers, IM3D perfectly reproduces SRIM results, and can be ∼10[superscript 2] times faster in serial execution and > 10[superscript 4] times faster using parallel computation. For 3D problems, it provides a fast approach for analyzing the spatial distributions of primary displacements and defect generation under ion irradiation. Herein we also provide a detailed discussion of our open-source collision cascade physics engine, revealing the true meaning and limitations of the “Quick Kinchin-Pease” and “Full Cascades” options. The issues of femtosecond to picosecond timescales in defining displacement versus damage, the limitation of the displacements per atom (DPA) unit in quantifying radiation damage (such as inadequacy in quantifying degree of chemical mixing), are discussed.National Natural Science Foundation (China) (Grant 11275229)National Natural Science Foundation (China) (Grant 11475215)National Natural Science Foundation (China) (Grant NSAF U1230202)National Natural Science Foundation (China) (Grant 11534012)National Basic Research Program of China (973 Program) (Grant 2012CB933702)Hefei Center for Physical Science and Technology (Grant 2012FXZY004)Chinese Academy of Sciences (Hefei Institutes of Physical Science (CASHIPS) Director Grant)National Science Foundation (U.S.) (DMR-1410636)National Science Foundation (U.S.) (DMR-1120901

Perspectives on multiscale modelling and experiments to accelerate materials development for fusion

Prediction of material performance in fusion reactor environments relies on computational modelling, and will continue to do so until the first generation of fusion power plants come on line and allow long-term behaviour to be observed. In the meantime, the modelling is supported by experiments that attempt to replicate some aspects of the eventual operational conditions. In 2019, a group of leading experts met under the umbrella of the IEA to discuss the current position and ongoing challenges in modelling of fusion materials and how advanced experimental characterisation is aiding model improvement. This review draws from the discussions held during that workshop. Topics covering modelling of irradiation-induced defect production and fundamental properties, gas behaviour, clustering and segregation, defect evolution and interactions are discussed, as well as new and novel multiscale simulation approaches, and the latest efforts to link modelling to experiments through advanced observation and characterisation techniques.MRG, SLD, and DRM acknowledge funding by the RCUK Energy Programme [grant number EP/T012250/1]. Part of this work has been carried out within the framework of the EUROFusion Consortium and has received funding from the Euratom research and training programme 2014–2018 and 2019–2020 under grant Agreement No. 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission. JRT acknowledges funding from the US Department of Energy (DOE) through grant DE-SC0017899. ZB, LY,BDW, and SJZ acknowledge funding through the US DOE Fusion Energy Sciences grant DE-SC0006661ZB, LY and BDW also were partially supported from the US DOE Office of Science, Office of Fusion Energy Sciences and Office of Advanced Scientific Computing Research through the Scientific Discovery through Advanced Computing (SciDAC) project on Plasma-Surface Interactions. JMa acknowledges support from the US-DOEs Office of Fusion Energy Sciences (US-DOE), project DE-SC0019157. Pacific Northwest National Laboratory is operated by Battelle Memorial Institute for the US Department of Energy (DOE) under contract DE-AC05-76RL01830. YO and YZ were supported as part of the Energy Dissipation to Defect Evolution (EDDE), an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under contract number DE-AC05-00OR22725. TS and TT are supported by JSPS KAKENHI Grant Number 19K05338

Development of Hybrid Deterministic-Statistical Models for Irradiation Influenced Microstructural Evolution.

Ion irradiation holds promise as a cost-effective approach to developing structured nano--porous and nano--fiberous semiconductors. Irradiation of certain semiconductors leads to the development of these structures, with exception of the much desired silicon. Hybrid deterministic-statistical models were developed to better understand the dominating mechanisms during structuring. This dissertation focuses on the application of hybrid models to two different radiation damage behavior: (1) precipitate evolution in a binary two-phase system and (2) void nucleation induced nano--porous structuring. Phenomenological equations defining the deterministic behavior were formulated by considering the expected kinetic and phenomenological behavior. The statistical component of the models is based on the Potts Monte Carlo (PMC) method. It has been demonstrated that hybrid models efficiently simulate microstructural evolution, while retaining the correct kinetics and physics. The main achievement was the development of computational methods to simulate radiation induced microstructural evolution and highlight which processes and materials properties could be essential for nano--structuring. Radiation influenced precipitate evolution was modeled by coupling a set of non-linear partial differential equations to the PMC model. The simulations considered the effects of dose rate and interfacial energy. Precipitate growth becomes retarded with increased damage due to diffusion of the radiation defects countering capillarity driven precipitate growth. The effects of grain boundaries (GB) as sinks was studied by simulating precipitate growth in an irradiated bi-crystalline matrix. Qualitative comparison to experimental results suggest that precipitate coverage of the GB is due to kinetic considerations and increased interfacial energy effects. Void nucleation induced nano--porous/fiberous structuring was modeled by coupling rate theory equations, kinetic Monte Carlo swelling algorithm and the PMC model. Point defect (PD) diffusivities were parameterized to study their influence on nano--structuring. The model showed that PD kinetic considerations are able to describe the formation of nano--porous structures. As defects diffuse faster, void nucleation becomes limited due to the fast removal of the defects. It was shown that as the diffusivities' ratio diverges from unity, the microstructures become statistically similar and uniform. Consequently, the computational results suggest that nano--pore structuring require interstitials that are much faster than the slow diffusing vacancies, which accumulate and cluster into voids.PhDNuclear Engineering and Radiological SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111424/1/efrainhr_1.pd