Efficient Parallel Algorithm for Statistical Ion Track Simulations in Crystalline Materials

We present an efficient parallel algorithm for statistical Molecular Dynamics simulations of ion tracks in solids. The method is based on the Rare Event Enhanced Domain following Molecular Dynamics (REED-MD) algorithm, which has been successfully applied to studies of, e.g., ion implantation into crystalline semiconductor wafers. We discuss the strategies for parallelizing the method, and we settle on a host-client type polling scheme in which a multiple of asynchronous processors are continuously fed to the host, which, in turn, distributes the resulting feed-back information to the clients. This real-time feed-back consists of, e.g., cumulative damage information or statistics updates necessary for the cloning in the rare event algorithm. We finally demonstrate the algorithm for radiation effects in a nuclear oxide fuel, and we show the balanced parallel approach with high parallel efficiency in multiple processor configurations.Comment: 17 pages, seven figures, four table

Simulation of ion track ranges in uranium oxide

Direct comparisons between statistically sound simulations of ion-tracks and published experimental measurements of range densities of iodine implants in uranium dioxide have been made with implant energies in the range of 100-800 keV. Our simulations are conducted with REED-MD (Rare Event Enhanced Domain-following Molecular Dynamics) in order to account for the materials structure in both single crystalline and polycrystalline experimental samples. We find near-perfect agreement between REED-MD results and experiments for polycrystalline target materials.Comment: Eleven pages, four figures

Review of the Synergies Between Computational Modeling and Experimental Characterization of Materials Across Length Scales

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many applications in the development, characterization and design of complex material systems. This manuscript provides a broad and comprehensive overview of recent trends where predictive modeling capabilities are developed in conjunction with experiments and advanced characterization to gain a greater insight into structure-properties relationships and study various physical phenomena and mechanisms. The focus of this review is on the intersections of multiscale materials experiments and modeling relevant to the materials mechanics community. After a general discussion on the perspective from various communities, the article focuses on the latest experimental and theoretical opportunities. Emphasis is given to the role of experiments in multiscale models, including insights into how computations can be used as discovery tools for materials engineering, rather than to "simply" support experimental work. This is illustrated by examples from several application areas on structural materials. This manuscript ends with a discussion on some problems and open scientific questions that are being explored in order to advance this relatively new field of research.Comment: 25 pages, 11 figures, review article accepted for publication in J. Mater. Sc

Adaptive moving environment for efficient molecular dynamics simulations of high-fluence ion irradiation

Ion-beam processing of materials is widely supported by atomistic simulations by means of molecular dynamics. Although the approach has given several valuable insights, it has a limited operational window in both time and length scales. In particular, for high-fluence ion irradiation with multiple consecutive cascades, the direct molecular dynamics method becomes prohibitively time consuming. In this work, we propose a speed-up algorithm for molecular-dynamics simulations of multiple consecutive collision cascades employing an adaptive moving environment model. In the model, the computational power is primarily focused on calculating the atomic movement in the propagating cascade regions, while thermally equilibrated regions outside the cascades are excluded. Up to a five-fold efficiency increase was seen with the adaptive moving environment compared to classical molecular dynamics, without any significant statistical difference in the results of multiple individual ion-cascade simulations in a heterostructure of alternating Si and SiO2 layers. Simulations of temperature-driven dynamic annealing during high-fluence ion irradiation of Si nanopillars at elevated temperatures using the adaptive moving environment showed similar trends as experiments with respect to temperature dependence. The model is included in the atomistic simulator toolkit, COSIRMA (COmputer Simulator for IRradiation of MAterials), and can easily be enabled through the user-friendly graphical interface.Peer reviewe

Fundamental Phenomena and Applications of Swift Heavy Ion Irradiations

Peer reviewe

Molecular Dynamics for Efficient Simulations of High-Fluence Ion-Beam Irradiation of Materials

There has been a stagnation in the development of power-storage devices since the lithium-ion battery in 2019, and alternative ways to save power in devices connected to the Internet-of-Things (IoT) are highly sought for. One very promising way is to produce power-saving CMOS-compatible single-electron transistors (SETs) made of silicon, insulated with silica. Excessive silicon introduced into the silica matrix, through ion-induced atomic mixing, will self-assemble into a silicon nanodot acting as the quantum island of the SET during thermal annealing. Molecular dynamics (MD) has been used for decades to simulate the dynamics of atomistic systems exposed to ion beams, which also made MD the perfect choice for this study as well. We implemented a few speed-up models to make the irradiation simulation faster and at the same time more appealing to the industry for testing out irradiation conditions before applying them experimentally. We even included a graphical user interface to make the simulator more user friendly for external audiences. During the study we came up with a reliable way of combining layers of silicon-based materials to merge together the target structures. We used the merged structures to investigate the physical processes related to the irradiation-driven atomic mixing we were looking for. An understanding of the processes helps the community to more accurately apply the irradiation condition in the already available silicon-based processes used by the semiconductor industry when creating CMOS components. We found a connection between the initial momentum transfer from ions hitting a nanopillar perpendicularly at the tip and the ion hammering effect on nanoscale. The built-up tension directed downwards during the ballistic phase of the cascade and the low-energetic collisions of the fading cascade would start to press the atoms laterally outwards. Other noticeable effects during the irradiation were crystalline-to-amorphous phase shifts and local densifications of the silica.Utvecklingen av batterier har drastiskt stagnerat sen upptäckten av litiumjonbatteriet 2019. Som bäst undersöks alternativa metoder för att spara ström i apparater som kopplas trådlöst till internet och ett väldigt lovande alternativ är CMOS-kompatibla singelelektrontransistorer (SET) tillverkade av kisel och kiseldioxid. Med hjälp av jonstrålar kan man orsaka atomblanding över gränsskiktena mellan de ledande och isolerande lagren, som i sin tur orsakar ett överskott av obundna kiselatomer i den isolerande kiseldioxidmatrisen. Under uppvärmning formar överskottet av kiselatomer nanokristaller inuti isolatorn. Med rätt storlek, form och avstånd kan dessa nanokristaller fungera som en isolerad "kvantö", på vilken SETens hela grundprincip baseras. Molekyldynamik (MD) har under årtionden använts för att simulera rörelsen i atomistiska system exponerade för jonstrålar, vilket gjorde valet av MD perfekt för den här studien. Vi utvecklade uppsnabbningsmodeller för att göra bestrålningssimuleringarna mera effektiva och därmed också mera attraktiva för industriell applicering. För att göra simulatorn mera användarvänlig har vi också utvecklat ett grafiskt användargränssnitt för att förbereda MD-simuleringarna. Under studien kom vi på ett pålitligt sätt att kombinera lager av kiselbaserade material för att skapa stabila målstrukturer. Vi använde strukturerna för att undersöka vilka fysikaliska processer som driver den intressanta atomblandningen. Genom att bilda en bättre förståelse av processerna kan man lättare applicera strålningsförhållandet i existerande kiselbaserade tillverkningsprocesser inom halvledarindustrin för att skapa CMOS-kompatibla komponenter. Vi upptäckte en koppling mellan den överförda rörelsemängden från de mobila jonerna som träffade en nanopelare och jonhamringseffekten på nanoskala. Spänningen som byggdes upp längs med pelaren under den ballistiska fasen av jonkaskaderna och de lågenergetiska kollisionerna i slutskedet av kaskaderna pressade atomerna vinkelrätt utåt från ursprungsriktningen av jonerna. Andra synliga effekter jonstrålen hade på kiselnanostrukturerna var fasövergångar från kristallin till amorf fas, samt lokala förtätningar i kiseldioxiden

Fundamentals of Ion-Solid Interaction: A Compact Introduction

Abstrac

A Practical Guide to Surface Kinetic Monte Carlo Simulations

This review article is intended as a practical guide for newcomers to the field of kinetic Monte Carlo (KMC) simulations, and specifically to lattice KMC simulations as prevalently used for surface and interface applications. We will provide worked out examples using the kmos code, where we highlight the central approximations made in implementing a KMC model as well as possible pitfalls. This includes the mapping of the problem onto a lattice and the derivation of rate constant expressions for various elementary processes. Example KMC models will be presented within the application areas surface diffusion, crystal growth and heterogeneous catalysis, covering both transient and steady-state kinetics as well as the preparation of various initial states of the system. We highlight the sensitivity of KMC models to the elementary processes included, as well as to possible errors in the rate constants. For catalysis models in particular, a recurrent challenge is the occurrence of processes at very different timescales, e.g. fast diffusion processes and slow chemical reactions. We demonstrate how to overcome this timescale disparity problem using recently developed acceleration algorithms. Finally, we will discuss how to account for lateral interactions between the species adsorbed to the lattice, which can play an important role in all application areas covered here.Comment: This document is the final Author's version of a manuscript that has been peer reviewed and accepted for publication in Frontiers in Chemistry. To access the final edited and published work see https://www.frontiersin.org/articles/10.3389/fchem.2019.00202/abstrac

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