Theoretical And Computational Studies Of Diffusion Of Adatom Islands And Reactions Of Molecules On Surfaces

The work presented in this dissertation focuses on the study of post deposition spatial and temporal evolution of adatom islands and molecules on surfaces using ab initio and semiemperical methods. It is a microscopic study of the phenomena of diffusion and reaction on nanostructured surfaces for which we have developed appropriate computational tools, as well as implemented others that are available. To map out the potential energy surface on which the adatom islands and molecules move, we have carried out ab initio electronic structure calculations based on density functional theory (DFT) for selected systems. For others, we have relied on semiempirical interatomic potentials derived from the embedded atom method. To calculate the activation energy barriers, we have employed the drag method in most cases and verified its reliability by employing the more accurate nudged elastic band method for selected systems. Temporal and spatial evolution of the systems of interest have been calculated using the kinetic Monte Carlo (KMC), or the more accurate (complete) Self Learning kinetic Monte Carlo (SLKMC) method in the majority of cases, and ab initio molecular dynamics simulations in others. We have significantly enhanced the range of applicability of the SLKMC method by introducing a new pattern recognition scheme which by allowing occupancy of the fcc and hcp sites (and inclusion of top site in the pattern recognition as well) is capable of simulating the morphological evolution of iii three dimensional adatom islands, a feature not feasible via the earlier - proposed SLKMC method. Using SLKMC (which allows only fcc site occupancy on fcc(111) surface), our results of the coarsening of Ag islands on the Ag(111) surface show that during early stages, coarsening proceeds as a sequence of selected island sizes, creating peaks and valleys in the island-size distribution. This island size selectivity is independent of initial conditions and results from the formation of kinetically stable islands for certain sizes as dictated by the relative energetics of edge atom detachment/attachment processes together with the large activation barrier for kink detachment. On applying the new method, SLKMC-II, to examine the self diffusion of small adatom islands (1-10 atoms) of Cu on Cu(111), Ag on Ag(111) and Ni on Ni(111), we find that for the case of Cu and Ni islands, diffusion is dominated by concerted processes (motion of island as a whole), whereas in the case of Ag, islands of size 2-9 atoms diffuse through concerted motion whereas the 10-atom island diffuses through single atom processes. Effective energy barriers for the self diffusion of these small Cu islands is 0.045 eV/atom, for Ni it is 0.060 eV/atom and for Ag it is 0.049 eV/atom, increasing almost linearly with island size. Application of DFT based techniques have allowed us to address a few issues stemming from experimental observations on the effect of adsorbates such as CO on the structure iv and stability of bimetallic systems (nanoparticles and surfaces). Total energy calculations of Ni-Au nanoparticles show Ni atoms to prefer to be in the interior of the nanoparticle. CO molecules, however, prefer to bind to a Ni atom if present on the surface. Using ab initio molecular dynamics simulations, we confirm that the presence of CO molecule induces diffusion of Ni atom from the core of the Ni-Au nanoparticle to its surface, making the nanoparticle more reactive. These results which help explain a set of experimental data are rationalized through charge transfer analysis. Similar to the case of Ni-Au system, it is found that methoxy (CH3O) may also induce diffusion of inner atoms to the surface on bimetallic Au-Pt systems. Our total energy DFT calculations show that it is more favorable for methoxy to bind to a Pt atom in the top Au layer than to a Au atom in Au-Pt system thereby explaining experimental observations. To understand questions related to the dependence of product selectivity on ambient pressure for ammonia decomposition on RuO2(110), we have carried out an extensive calculation of the reaction pathways and energy barriers for a large number of intermediate products. On combining the reaction energetics from DFT, with KMC simulations, we show that under UHV conditions, selectivity switches from N2 ( ∼ 100 % selectivity) at T = 373K to NO at T = 630K, whereas under ambient conditions, N2 is still the dominant product but maximum selectivity is only 60%. An analysis based on thermodynamics alone shows a contradiction between experimental data at UHV with those under ambient pressure. Our calculations of the reaction rates which are essential for KMC simulations removes this apv parent inconsistency and stresses the need to incorporate kinetics of processes in order to extract information on reaction selectivity

Island Size Selectivity and island-shape analysis during 2D Island Coarsening of Ag/Ag (111) Surface

In our earlier study of Ag island coarsening on Ag(111) surface using kinetic Monte Carlo (KMC) simulations we found that during early stages coarsening proceeds as a sequence of selected island sizes resulting in peaks and valleys in the island-size distribution and that this selectivity is independent of initial conditions and dictated instead by the relative energetics of edge-atom diffusion and detachment/attachment processes and by the large activation barrier for kink detachment. In this paper we present a detailed analysis of the shapes of various island sizes observed during these KMC simulations and show that selectivity is due to the formation of kinetically stable island shapes which survive longer than non-selected sizes, which decay into nearby selected sizes. The stable shapes have a closed-shell structure - one in which every atom on the periphery having at least three nearest neighbors. Our KMC simulations were carried out using a very large database of processes identified by each atom's unique local environment, the activation barriers of which were calculated using semi-empirical interaction potentials based on the embedded-atom method.Comment: 17 pages, 11 figure

SLKMC-II study of self-diffusion of small Ni clusters on Ni (111) surface

We studied self-diffusion of small 2D Ni islands (consisting of up to 10 atoms) on Ni (111) surface using a self-learning kinetic Monte Carlo (SLKMC-II) method with an improved pattern-recognition scheme that allows inclusion of both fcc and hcp sites in the simulations. In an SLKMC simulation, a database holds information about the local neighborhood of an atom and associated processes that is accumulated on-the-fly as the simulation proceeds. In this study, these diffusion processes were identified using the drag method, and their activation barriers calculated using a semi-empirical interaction potential based on the embedded-atom method. Although a variety of concerted, multi-atom and single-atom processes were automatically revealed in our simulations, we found that these small islands diffuse primarily via concerted diffusion processes. We report diffusion coefficients for each island size at various tepmratures, the effective energy barrier for islands of each size and the processes most responsible for diffusion of islands of various sizes, including concerted and multi-atom processes that are not accessible under SLKMC-I or in short time-scale MD simulations

New off-lattice Pattern Recognition Scheme for off-lattice kinetic Monte Carlo Simulations

We report the development of a new pattern-recognition scheme for the off- lattice self-learning kinetic Monte Carlo (KMC) method that is simple and flex ible enough that it can be applied to all types of surfaces. In this scheme, to uniquely identify the local environment and associated processes involving three-dimensional (3D) motion of an atom or atoms, 3D space around a central atom or leading atom is divided into 3D rectangular boxes. The dimensions and the number of 3D boxes are determined by the type of the lattice and by the ac- curacy with which a process needs to be identified. As a test of this method we present the application of off-lattice KMC with the pattern-recognition scheme to 3D Cu island decay on the Cu(100) surface and to 2D diffusion of a Cu monomer and a dimer on the Cu (111) surface. We compare the results and computational efficiency to those available in the literature.Comment: 25 pages, 12 figure

Extended Pattern Recognition Scheme for Self-learning Kinetic Monte Carlo (SLKMC-II) Simulations

We report the development of a pattern-recognition scheme that takes into account both fcc and hcp adsorption sites in performing self-learning kinetic Monte Carlo (SLKMC-II) simulations on the fcc(111) surface. In this scheme, the local environment of every under-coordinated atom in an island is uniquely identified by grouping fcc sites, hcp sites and top-layer substrate atoms around it into hexagonal rings. As the simulation progresses, all possible processes including those like shearing, reptation and concerted gliding, which may involve fcc-fcc, hcp-hcp and fcc-hcp moves are automatically found, and their energetics calculated on the fly. In this article we present the results of applying this new pattern-recognition scheme to the self-diffusion of 9-atom islands (M9) on M(111), where M = Cu, Ag or Ni

Kinetically driven shape changes in early stages of two-dimensional island coarsening: Ag/Ag(111)

We present here a detailed analysis of the shapes of two-dimensional Ag islands of various sizes observed during the early stages of coarsening on the Ag(111) surface, using kinetic Monte Carlo (KMC) simulations, and show that selectivity is due to the formation of kinetically stable island shapes that survive longer than nonselected sizes, which decay into nearby selected sizes. The stable shapes have a closed-shell structure-one in which every atom on the periphery has at least three nearest neighbors. These findings further explain our earlier study in which we found that in the early stages coarsening proceeds as a sequence of selected island sizes resulting in peaks and valleys in the island size distribution [G. Nandipati, A. Kara, S. I. Shah, and T. S. Rahman, J. Phys.: Condens. Matter 23, 262001 (2011)]. This selectivity is dictated by the relative energetics of edge-atom diffusion and detachment and attachment processes and by the large activation barrier for kink detachment. Our simulations were carried out using a very large database of processes identified by each atom\u27s unique local environment using the self-learning KMC scheme. The activation barriers were calculated using semiempirical interaction potentials based on the embedded-atom method

Island Size Selectivity during 2D Ag Island Coarsening on Ag (111)

We report on early stages of submonolayer Ag island coarsening on Ag(111) surface at room temperature ($300$ K) carried out using realistic kinetic Monte Carlo (KMC) simulations. We find that during early stages, coarsening proceeds as a sequence of selected island sizes creating peaks and valleys in the island size distribution. We find that island-size selectivity is due to formation of kinetically stable islands for certain sizes because of adatom detachment/attachment processes and large activation barrier for kink detachment. In addition, we find that the ratio of number of adatom attachment to detachment processes to be independent of parameters of initial configuration and also on the initial shapes of the islands confirming that island-size selectivity is independent of initial conditions.These simulations were carried out using a very large database of processes identified by their local environment and whose activation barriers were calculated using the embedded-atom method

Self-diffusion of small Ni clusters on the Ni(111) surface: A self-learning kinetic Monte Carlo study

We have examined the self-diffusion of small 2D Ni islands (consisting of up to 10 atoms) on the Ni(111) surface using a self-learning kinetic Monte Carlo (SLKMC-II) method with an improved pattern-recognition scheme that allows inclusion of both fcc and hcp sites in the simulations. Activation energy barriers for the identified diffusion processes were calculated on the fly using a semiempirical interaction potential based on the embedded-atom method. Although a variety of concerted, multiatom, and single-atom processes were automatically revealed in our simulations, we found that, in the temperature range of 300 K-700 K, these small islands diffuse primarily via concerted motion. Single-atom processes play an important role in ensuring that diffusion is random for islands containing 5 or more atoms, while multiatom processes (shearing and reptation) come into play for noncompact islands. The effective activation energy barriers obtained from the Arrhenius plot of the diffusion coefficients showed an increase with the size of the island, although there were interesting deviations from linear dependence. Several other processes also contributing to diffusion of islands were identified

The Function of Mitochondrial Calcium Uniporter at the Whole-Cell and Single Mitochondrion Levels in WT, MICU1 KO, and MICU2 KO Cells

Mitochondrial Ca2+ ([Ca2+]M) uptake through its Ca2+ uniporter (MCU) is central to many cell functions such as bioenergetics, spatiotemporal organization of Ca2+ signals, and apoptosis. MCU activity is regulated by several intrinsic proteins including MICU1, MICU2, and EMRE. While significant details about the role of MICU1, MICU2, and EMRE in MCU function have emerged recently, a key challenge for the future experiments is to investigate how these regulatory proteins modulate mitochondrial Ca2+ influx through MCU in intact cells under pathophysiological conditions. This is further complicated by the fact that several variables affecting MCU function change dynamically as cell functions. To overcome this void, we develop a data-driven model that closely replicates the behavior of MCU under a wide range of cytosolic Ca2+ ([Ca2+]C), [Ca2+]M, and mitochondrial membrane potential values in WT, MICU1 knockout (KO), and MICU2 KO cells at the single mitochondrion and whole-cell levels. The model is extended to investigate how MICU1 or MICU2 KO affect mitochondrial function. Moreover, we show how Ca2+ buffering proteins, the separation between mitochondrion and Ca2+-releasing stores, and the duration of opening of Ca2+-releasing channels affect mitochondrial function under different conditions. Finally, we demonstrate an easy extension of the model to single channel function of MCU