Doctorat (2013)
Aujourd’hui
Maintenant boursier postdoctoral du FRQNT et associé de recherche postdoctoral au Laboratoire National d¹Oak Ridge, Tennessee, ÉtatsUnis.
Activités de recherche
Il simule plusieurs métaux et alliages sous irradiation dans le but de
développer des nouveaux matériaux nucléaires.
Liens
Articles en collaboration

K. Ferasat, Y. N. Osetsky, A. V. Barashev, Y. Zhang, Z. Yao, L. K. Béland, Accelerated kinetic Monte Carlo: A case study; vacancy and dumbbell interstitial diffusion traps in concentrated solid solution alloys, The Journal of Chemical Physics 153, 074109 (2020).

K. Ferasat, Y. N. Osetsky, A. V. Barashev, Y. Zhang, Z. Yao, L. K. Béland, Accelerated kinetic Monte Carlo: A case study; vacancy and dumbbell interstitial diffusion traps in concentrated solid solution alloys, The Journal of Chemical Physics 153, 074109 (2020).Résumé : Vacancy and selfinterstitial atomic diffusion coefficients in concentrated solid solution alloys can have a nonmonotonic concentration dependence. Here, the kinetics of monovacancies and ⟨100⟩ dumbbell interstitials in Ni–Fe alloys are assessed using lattice kinetic Monte Carlo (kMC). The nonmonotonicity is associated with superbasins, which impels using accelerated kMC methods. Detailed implementation prescriptions for first passage time analysis kMC (FPTAkMC), mean rate method kMC (MRMkMC), and accelerated superbasin kMC (ASkMC) are given. The accelerated methods are benchmarked in the context of diffusion coefficient calculations. The benchmarks indicate that MRMkMC underestimates diffusion coefficients, while ASkMC overestimates them. In this application, MRMkMC and ASkMC are computationally more efficient than the more accurate FPTAkMC. Our calculations indicate that composition dependence of migration energies is at the origin of the vacancy’s nonmonotonic behavior. In contrast, the difference between formation energies of Ni–Ni, Ni–Fe, and Fe–Fe dumbbell interstitials is at the origin of their nonmonotonic diffusion behavior. Additionally, the migration barrier crossover composition—based on the situation where Ni or Fe atom jumps have lower energy barrier than the other one—is introduced. KMC simulations indicate that the interplay between composition dependent crossover of migration energy and geometrical site percolation explains the nonmonotonic concentrationdependence of atomic diffusion coefficients.

M. Trochet, N. Mousseau, L. K. Béland, G. Henkelman, dans Handbook of Materials Modeling : Methods: Theory and Modeling, W. Andreoni, S. Yip, Éd. (Springer International Publishing, Cham, 2019), p. 129.Résumé : Exact modeling of the dynamics of chemical and material systems over experimentally relevant time scales still eludes us even with modern computational resources. Fortunately, many systems can be described as rare event systems where atoms vibrate around equilibrium positions for a long time before a transition is made to a new atomic state. For those systems, the kinetic Monte Carlo (KMC) algorithm provides a powerful solution. In traditional KMC, mechanism and rates are computed beforehand, limiting moves to discretized positions and largely ignoring strain. Many systems of interest, however, are not wellrepresented by such latticebased models. Moreover, materials often evolve with complex and concerted mechanisms that cannot be anticipated before the start of a simulation. In this chapter, we describe a class of algorithms, called offlattice or adaptive KMC, which relaxes both limitations of traditional KMC, with atomic configurations represented in the full configuration space and reaction events are calculated onthefly, with the possible use of catalogs to speed up calculations. We discuss a number of implementations of offlattice KMC developed by different research groups, emphasizing the similarities between the approaches that open modeling to new classes of problems.

G. K. N'Tsouaglo, L. K. Béland, J.  F. Joly, P. Brommer, N. Mousseau, P. Pochet, Probing potential energy surface exploration strategies for complex systems, J. Chem. Theory Comput. 11, 19701977 (2015).Résumé : The efficiency of minimumenergy configuration searching algorithms is closely linked to the energy landscape structure of complex systems. Here we characterize this structure by following the time evolution of two systems, vacancy aggregation in Fe and energy relaxation in ionbombarded cSi, using the kinetic ActivationRelaxation Technique (kART), an offlattice kinetic Monte Carlo (KMC) method, and the wellknown BellEvansPolanyi (BEP) principle. We also compare the efficiency of two methods for handling nondiffusive flickering states  an exact solution and a Tabulike approach that blocks already visited states. Comparing these various simulations allow us to confirm that the BEP principle does not hold for complex system since forward and reverse energy barriers are completely uncorrelated. This means that following the lowest available energy barrier, even after removing the flickering states, leads to rapid trapping: relaxing complex systems requires crossing highenergy barriers in order to access new energy basins, in agreement with the recently proposed replenishandrelax model [Béland et al., PRL 111, 105502 (2013)] This can be done by forcing the system through these barriers with Tabulike methods. Interestingly, we find that following the fundamental kinetics of a system, though standard KMC approach, is at least as efficient as these bruteforce methods while providing the correct kinetics information.

M. Trochet, L. K. Béland, P. Brommer, J.  F. Joly, N. Mousseau, Diffusion of point defects in crystalline silicon using the kinetic ART method, Phys. Rev. B 91, 224106 (2015).

N. Mousseau, P. Brommer, J.  F. Joly, L. K. Béland, F. ElMellouhi, G. K. N'Tsouaglo, et al., Following atomistic kinetics on experimental timescales with the kinetic ActivationRelaxation Technique, Computational Materials Science 100, 111123 (2015).

L. K. Béland, E. MachadoCharry, P. Pochet, N. Mousseau, Strain effects and intermixing at the Si surface: Importance of longrange elastic corrections in firstprinciples calculations, Phys. Rev. B 90, 155302 (2014).

P. Brommer, L. K. Béland, J.  F. Joly, N. Mousseau, Understanding longtime vacancy aggregation in iron: A kinetic activationrelaxation technique study, Phys. Rev. B 90, 134109 (2014).

J.  F. Joly, L. K. Béland, P. Brommer, N. Mousseau, Contribution of vacancies to relaxation in amorphous materials: A kinetic activationrelaxation technique study, Physical Review B 87, 144204 (2013).Résumé : The nature of structural relaxation in disordered systems such as amorphous silicon (aSi) remains a fundamental issue in our attempts at understanding these materials. While a number of experiments suggest that mechanisms similar to those observed in crystals, such as vacancies, could dominate the relaxation, theoretical arguments point rather to the possibility of more diverse pathways. Using the kinetic activationrelaxation technique, an offlattice kinetic Monte Carlo method with onthefly catalog construction, we resolve this question by following 1000 independent vacancies in a wellrelaxed aSi model at 300 K over a timescale of up to one second. Less than one percent of these survive over this period of time and none diffuse more than once, showing that relaxation and diffusion mechanisms in disordered systems are fundamentally different from those in the crystal.

L. K. Béland, Y. Anahory, D. Smeets, M. Guihard, P. Brommer, J.  F. Joly, et al., Replenish and Relax: Explaining Logarithmic Annealing in IonImplanted cSi, Physical Review Letters 111, 105502 (2013).Résumé : We study iondamaged crystalline silicon by combining nanocalorimetric experiments with an offlattice kinetic Monte Carlo simulation to identify the atomistic mechanisms responsible for the structural relaxation over long time scales. We relate the logarithmic relaxation, observed in a number of disordered systems, with heatrelease measurements. The microscopic mechanism associated with this logarithmic relaxation can be described as a twostep replenish and relax process. As the system relaxes, it reaches deeper energy states with logarithmically growing barriers that need to be unlocked to replenish the heatreleasing events leading to lowerenergy configurations.

L. K. Béland, N. Mousseau, Longtime relaxation of ionbombarded silicon studied with the kinetic activationrelaxation technique: Microscopic description of slow aging in a disordered system, Physical Review B 88, 214201 (2013).Résumé : Diffusion and relaxation of defects in bulk systems is a complex process that can only be accessed directly through simulations. We characterize the mechanisms of lowtemperature aging in selfimplanted crystalline silicon, a model system used extensively to characterize both amorphization and return to equilibrium processes, over 11 orders of magnitudes in time, from 10 ps to 1 s, using a combination of molecular dynamics and kinetic activationrelaxation technique simulations. These simulations allow us to reassess the atomistic mechanisms responsible for structural relaxations and for the overall logarithmic relaxation, a process observed in a large number of disordered systems and observed here over the whole simulation range. This allows us to identify three microscopic regimes, annihilation, aggregation, and reconstruction, in the evolution of defects and to propose atomistic justification for an analytical model of logarithmic relaxation. Furthermore, we show that growing activation barriers and configurational space exploration are kinetically limiting the system to a logarithmic relaxation. Overall, our longtime simulations do not support the amorphous cluster model but point rather to a relaxation driven by elastic interactions between defect complexes of all sizes.

J.  F. Joly, L. K. Béland, P. Brommer, F. ElMellouhi, N. Mousseau, Optimization of the Kinetic ActivationRelaxation Technique, an offlattice and selflearning kinetic MonteCarlo method, Journal of Physics: Conference Series 341, 012007 (2012).Résumé : We present two major optimizations for the kinetic ActivationRelaxation Technique (kART), an offlattice selflearning kinetic Monte Carlo (KMC) algorithm with onthefly event search THAT has been successfully applied to study a number of semiconducting and metallic systems. KART is parallelized in a nontrivial way: A master process uses several worker processes to perform independent event searches for possible events, while all bookkeeping and the actual simulation is performed by the master process. Depending on the complexity of the system studied, the parallelization scales well for tens to more than one hundred processes. For dealing with large systems, we present a near order 1 implementation. Techniques such as Verlet lists, cell decomposition and partial force calculations are implemented, and the CPU time per time step scales sublinearly with the number of particles, providing an efficient use of computational resources.

P. Ganster, L. K. Béland, N. Mousseau, First stages of silicon oxidation with the activation relaxation technique, Physical Review B 86, 075408 (2012).Résumé : Using the art nouveau method, we study the initial stages of silicon oxide formation. After validating the method's parameters with the characterization of point defects diffusion mechanisms in pure StillingerWeber silicon, which allows us to recover some known results and to detail vacancy and selfinterstitial diffusion paths, the method is applied onto a system composed of an oxygen layer deposited on a silicon substrate. We observe the oxygen atoms as they move rapidly into the substrate. From these art nouveau simulations, we extract the energy barriers of elementary mechanisms involving oxygen atoms and leading to the formation of an amorphouslike silicon oxide. We show that the kinetics of formation can be understood in terms of the energy barriers between various coordination environments.

N. Mousseau, L. K. Béland, P. Brommer, J.  F. Joly, F. ElMellouhi, E. MachadoCharry, et al., The ActivationRelaxation Technique: ART Nouveau and Kinetic ART, Journal of Atomic, Molecular, and Optical Physics 2012, 925278 (2012).Résumé : The evolution of many systems is dominated by rare activated events that occur on timescale ranging from nanoseconds to the hour or more. For such systems, simulations must leave aside the full thermal description to focus specifically on mechanisms that generate a configurational change. We present here the activation relaxation technique (ART), an openended saddle point search algorithm, and a series of recent improvements to ART nouveau and kinetic ART, an ARTbased onthefly offlattice selflearning kinetic Monte Carlo method.

L. K. Béland, P. Brommer, F. ElMellouhi, J.  F. Joly, N. Mousseau, Kinetic activationrelaxation technique, Physical Review E 84, 046704 (2011).Résumé : We present a detailed description of the kinetic activationrelaxation technique (kART), an offlattice, selflearning kinetic Monte Carlo (KMC) algorithm with onthefly event search. Combining a topological classification for local environments and event generation with ART nouveau, an efficient unbiased sampling method for finding transition states, kART can be applied to complex materials with atoms in offlattice positions or with elastic deformations that cannot be handled with standard KMC approaches. In addition to presenting the various elements of the algorithm, we demonstrate the general character of kART by applying the algorithm to three challenging systems: selfdefect annihilation in cSi (crystalline silicon), selfinterstitial diffusion in Fe, and structural relaxation in aSi (amorphous silicon).

N. Mousseau, E. MachadoCharry, L. K. Béland, D. Caliste, L. Genovese, T. Deutsch, et al., Optimized energy landscape exploration using the ab initio based activationrelaxation technique, The Journal of Chemical Physics 135, 034102 (2011).Résumé : Unbiased openended methods for finding transition states are powerful tools to understand diffusion and relaxation mechanisms associated with defect diffusion, growth processes, and catalysis. They have been little used, however, in conjunction with ab initio packages as these algorithms demanded large computational effort to generate even a single event. Here, we revisit the activationrelaxation technique (ART nouveau) and introduce a twostep convergence to the saddle point, combining the previously used Lanczós algorithm with the direct inversion in interactive subspace scheme. This combination makes it possible to generate events (from an initial minimum through a saddle point up to a final minimum) in a systematic fashion with a net 300–700 force evaluations per successful event. ART nouveau is coupled with BigDFT, a KohnSham density functional theory (DFT) electronic structure code using a wavelet basis set with excellent efficiency on parallel computation, and applied to study the potential energy surface of C20 clusters, vacancydiffusion in bulk silicon, and reconstruction of the 4HSiC surface.