Reaction-limited island nucleation in molecular beam epitaxy of compound semiconductors

Modeling of nonequilibrium surface growth by a limited-mobility model with distributed diffusion length

Kinetic Monte Carlo (KMC) simulations are a well-established numerical tool to investigate the time-dependent surface morphology in molecular beam epitaxy experiments. In parallel, simplified approaches such as limited mobility (LM) models characterized by a fixed diffusion length have been studied. Here we investigate an extended LM model to gain deeper insight into the role of diffusional processes concerning the growth morphology. Our model is based on the stochastic transition rules of the Das Sarma-Tamborena model but differs from the latter via a variable diffusion length. A first guess for this length can be extracted from the saturation value of the mean-squared displacement calculated from short KMC simulations. Comparing the resulting surface morphologies in the sub- and multilayer growth regime to those obtained from KMC simulations, we find deviations which can be cured by adding fluctuations to the diffusion length. This mimics the stochastic nature of particle diffusion on a substrate, an aspect which is usually neglected in LM models. We propose to add fluctuations to the diffusion length by choosing this quantity for each adsorbed particle from a Gaussian distribution, where the variance of the distribution serves as a fitting parameter. We show that the diffusional fluctuations have a huge impact on cluster properties during submonolayer growth as well as on the surface profile in the high coverage regime. The analysis of the surface morphologies on one- and two-dimensional substrates during sub- and multilayer growth shows that the LM model can produce structures that are indistinguishable to the ones from KMC simulations at arbitrary growth conditions.

The diffusion of a Ga atom on GaAs(001)β2(2 × 4): Local superbasin kinetic Monte Carlo

We use first-principles density-functional theory to characterize the binding sites and diffusion mechanisms for a Ga adatom on the GaAs(001)β2(2 × 4) surface. Diffusion in this system is a complex process involving eleven unique binding sites and sixteen different hops between neighboring binding sites. Among the binding sites, we can identify four different superbasins such that the motion between binding sites within a superbasin is much faster than hops exiting the superbasin. To describe diffusion, we use a recently developed local superbasin kinetic Monte Carlo (LSKMC) method, which accelerates a conventional kinetic Monte Carlo (KMC) simulation by describing the superbasins as absorbing Markov chains. We find that LSKMC is up to 4300 times faster than KMC for the conditions probed in this study. We characterize the distribution of exit times from the superbasins and find that these are sometimes, but not always, exponential and we characterize the conditions under which the superbasin exit-time distribution should be exponential. We demonstrate that LSKMC simulations assuming an exponential superbasin exit-time distribution yield the same diffusion coefficients as conventional KMC.

Directed Kinetic Self-Assembly of Mounds on Patterned GaAs (001): Tunable Arrangement, Pattern Amplification and Self-Limiting Growth

We present results demonstrating directed self-assembly of nanometer-scale mounds during molecular beam epitaxial growth on patterned GaAs (001) surfaces. The mound arrangement is tunable via the growth temperature, with an inverse spacing or spatial frequency which can exceed that of the features of the template. We find that the range of film thickness over which particular mound arrangements persist is finite, due to an evolution of the shape of the mounds which causes their growth to self-limit. A difference in the film thickness at which mounds at different sites self-limit provides a means by which different arrangements can be produced.

Optimization algorithm for rate equations with an application to epitaxial graphene

We describe an algorithm that searches the parameter space of rate theories to optimize the associated rate coefficients based on a fit to experimental (or any other) data. Beginning with an initial set of parameters, which may be estimated, partially calculated, or indeed random, the algorithm follows a path, calculating the error at each point, until a minimum error is reached. We illustrate our method by correcting a previously proposed rate theory for the nucleation and growth of graphene on Ru(0 0 0 1) and Ir(1 1 1) to account for the temperature dependence of the graphene island density. This quantity shows an exponential decrease as the temperature is raised, in contrast to the power law decrease predicted by conventional nucleation theory, which indicates that a qualitatively different mechanism is operative for graphene island formation. Other applications of our method are also discussed.

Density functional theory in materials science

Materials science is a highly interdisciplinary field. It is devoted to the understanding of the relationship between (a) fundamental physical and chemical properties governing processes at the atomistic scale with (b) typically macroscopic properties required of materials in engineering applications. For many materials, this relationship is not only determined by chemical composition, but strongly governed by microstructure. The latter is a consequence of carefully selected process conditions (e.g., mechanical forming and annealing in metallurgy or epitaxial growth in semiconductor technology). A key task of computational materials science is to unravel the often hidden composition-structure-property relationships using computational techniques. The present paper does not aim to give a complete review of all aspects of materials science. Rather, we will present the key concepts underlying the computation of selected material properties and discuss the major classes of materials to which they are applied. Specifically, our focus will be on methods used to describe single or polycrystalline bulk materials of semiconductor, metal or ceramic form.

Epitaxial growth of visible to infra-red transparent conducting In2O3 nanodot dispersions and reversible charge storage as a Li-ion battery anode

Unique bimodal distributions of single crystal epitaxially grown In2O3 nanodots on silicon are shown to have excellent IR transparency greater than 87% at IR wavelengths up to 4 μm without sacrificing transparency in the visible region. These broadband antireflective nanodot dispersions are grown using a two-step metal deposition and oxidation by molecular beam epitaxy, and backscattered diffraction confirms a dominant (111) surface orientation. We detail the growth of a bimodal size distribution that facilitates good surface coverage (80%) while allowing a significant reduction in In2O3 refractive index. This unique dispersion offers excellent surface coverage and three-dimensional volumetric expansion compared to a thin film, and a step reduction in refractive index compared to bulk active materials or randomly porous composites, to more closely match the refractive index of an electrolyte, improving transparency. The (111) surface orientation of the nanodots, when fully ripened, allows minimum lattice mismatch strain between the In2O3 and the Si surface. This helps to circumvent potential interfacial weakening caused by volume contraction due to electrochemical reduction to lithium, or expansion during lithiation. Cycling under potentiodynamic conditions shows that the transparent anode of nanodots reversibly alloys lithium with good Coulombic efficiency, buffered by co-insertion into the silicon substrate. These properties could potentially lead to further development of similarly controlled dispersions of a range of other active materials to give transparent battery electrodes or materials capable of non-destructive in situ spectroscopic characterization during charging and discharging.

Critical role of two-dimensional island-mediated growth on the formation of semiconductor heterointerfaces

We experimentally demonstrate a sigmoidal variation of the composition profile across semiconductor heterointerfaces. The wide range of material systems (III-arsenides, III-antimonides, III-V quaternary compounds, III-nitrides) exhibiting such a profile suggests a universal behavior. We show that sigmoidal profiles emerge from a simple model of cooperative growth mediated by two-dimensional island formation, wherein cooperative effects are described by a specific functional dependence of the sticking coefficient on the surface coverage. Experimental results confirm that, except in the very early stages, island growth prevails over nucleation as the mechanism governing the interface development and ultimately determines the sigmoidal shape of the chemical profile in these two-dimensional-grown layers. In agreement with our experimental findings, the model also predicts a minimum value of the interfacial width, with the minimum attainable value depending on the chemical identity of the species.

Catalytic role of gold nanoparticle in GaAs nanowire growth: a density functional theory study

The energetics of Ga, As, and GaAs species on the Au(111) surface (employed as a model for Au nanoparticles) is investigated by means of density functional calculations. Apart from formation of the compound Au(7)Ga(2), Ga is found to form a surface alloy with gold with comparable ΔH ~ -0.5 eV for both processes. Dissociative adsorption of As(2) is found to be exothermic by more than 2 eV on both clean Au(111) and AuGa surface alloys. The As-Ga species formed by reaction of As with the surface alloy is sufficiently stable to cover the surface of an Au particle in vacuo in contact with a GaAs substrate. The results of the calculations are interpreted in the context of Au-catalyzed growth of GaAs nanowires. We argue that arsenic is supplied to the growth zone of the nanowire mainly by impingement of molecules on the gold particle and identify a regime of temperatures and As(2) partial pressures suitable for Au-catalyzed nanowire growth in molecular beam epitaxy.

Detailed modeling of the epitaxial growth of GaAs nanowires

A detailed continuum model is presented for predicting the growth characteristics of GaAs nanowires during chemical beam epitaxy. The model describes the transport processes of Ga and As adatoms on the substrate and nanowire sidewalls, and through the nanoparticle and the nanowire-catalyst interface (NCI). The growth mechanisms of nanowires within the NCI are described using an extended step-flow kinetic model. The vapor-liquid-solid and vapor-solid-solid growth mechanisms are both described in the kinetic model. The growth rate of the nanowires, the surface and bulk concentrations of adatoms, and the role of transport processes of Ga and As adatoms during chemical beam epitaxy were investigated. The growth mechanisms of the nanowires were found to vary with increasing length of the nanowire.

Renormalization of stochastic lattice models: epitaxial surfaces

We present the application of a method [C. A. Haselwandter and D. D. Vvedensky, Phys. Rev. E 76, 041115 (2007)] for deriving stochastic partial differential equations from atomistic processes to the morphological evolution of epitaxial surfaces driven by the deposition of new material. Although formally identical to the one-dimensional (1D) systems considered previously, our methodology presents substantial additional technical issues when applied to two-dimensional (2D) surfaces. Once these are addressed, subsequent coarse-graining is accomplished as before by calculating renormalization-group (RG) trajectories from initial conditions determined by the regularized atomistic models. Our applications are to the Edwards-Wilkinson (EW) model [S. F. Edwards and D. R. Wilkinson, Proc. R. Soc. London, Ser. A 381, 17 (1982)], the Wolf-Villain (WV) model [D. E. Wolf and J. Villain, Europhys. Lett. 13, 389 (1990)], and a model with concurrent random deposition and surface diffusion. With our rules for the EW model no appreciable crossover is obtained for either 1D or 2D substrates. For the 1D WV model, discussed previously, our analysis reproduces the crossover sequence known from kinetic Monte Carlo (KMC) simulations, but for the 2D WV model, we find a transition from smooth to unstable growth under repeated coarse-graining. Concurrent surface diffusion does not change this behavior, but can lead to extended transient regimes with kinetic roughening. This provides an explanation of recent experiments on Ge(001) with the intriguing conclusion that the same relaxation mechanism responsible for ordered structures during the early stages of growth also produces an instability at longer times that leads to epitaxial breakdown. The RG trajectories calculated for concurrent random deposition and surface diffusion reproduce the crossover sequences observed with KMC simulations for all values of the model parameters, and asymptotically always approach the fixed point corresponding to the equation proposed by Villain [J. Phys. I 1, 19 (1991)] and by Lai and Das Sarma [Phys. Rev. Lett. 66, 2899 (1991)]. We conclude with a discussion of the application of our methodology to other growth settings.

Renormalization of stochastic lattice models: basic formulation

We describe a general method for the multiscale analysis of stochastic lattice models. Beginning with a lattice Langevin formulation of site fluctuations, we derive stochastic partial differential equations by regularizing the transition rules of the model. Subsequent coarse graining is accomplished by calculating renormalization-group (RG) trajectories from initial conditions determined by the regularized atomistic models. The RG trajectories correspond to hierarchies of continuum equations describing lattice models over expanding length and time scales. These continuum equations retain a quantitative connection over different scales, as well as to the underlying atomistic dynamics. This provides a systematic method for the derivation of continuum equations from the transition rules of lattice models for any length and time scales. As an illustration we consider the one-dimensional (1D) Wolf-Villain (WV) model [Europhys. Lett. 13, 389 (1990)]. The RG analysis of this model, which we develop in detail, is generic and can be applied to a wide range of conservative lattice models. The RG trajectory of the 1D WV model shows a complex crossover sequence of linear and nonlinear stochastic differential equations, which is in excellent agreement with kinetic Monte Carlo simulations of this model. We conclude by discussing possible applications of the multiscale method described here to other nonequilibrium systems.

Langevin equations for fluctuating surfaces

Exact Langevin equations are derived for the height fluctuations of surfaces driven by the deposition of material from a molecular beam. We consider two types of model: deposition models, where growth proceeds by the deposition and instantaneous local relaxation of particles, with no subsequent movement, and models with concurrent random deposition and surface diffusion. Starting from a Chapman-Kolmogorov equation the deposition, relaxation, and hopping rules of these models are first expressed as transition rates within a master equation for the joint height probability density function. The Kramers-Moyal-van Kampen expansion of the master equation in terms of an appropriate "largeness" parameter yields, according to a limit theorem due to Kurtz [Stoch. Proc. Appl. 6, 223 (1978)], a Fokker-Planck equation that embodies the statistical properties of the original lattice model. The statistical equivalence of this Fokker-Planck equation, solved in terms of the associated Langevin equation, and solutions of the Chapman-Kolmogorov equation, as determined by kinetic Monte Carlo (KMC) simulations of the lattice transition rules, is demonstrated by comparing the surface roughness and the lateral height correlations obtained from the two formulations for the Edwards-Wilkinson [Proc. R. Soc. London Ser. A 381, 17 (1982)] and Wolf-Villain [Europhys. Lett. 13, 389 (1990)] deposition models, and for a model with random deposition and surface diffusion. In each case, as the largeness parameter is increased, the Langevin equation converges to the surface roughness and lateral height correlations produced by KMC simulations for all times, including the crossover between different scaling regimes. We conclude by examining some of the wider implications of these results, including applications to heteroepitaxial systems and the passage to the continuum limit.

Critical epinucleation on reconstructured surfaces and first-principle calculation of homonucleation on Si(100)

We introduce the concept of "critical epinucleation to distinguish nucleation on surfaces with and without reconstruction. On a reconstructed surface, the critical classical nucleus is stable against dissociation, but may not yet break the underlying surface reconstruction. Consequently, there must exist a "critical epinucleus" that is not only stable but also has established the epiconfiguration by unreconstructing the underlying substrate. We illustrate this concept by first-principle calculation of homonucleation on reconstructed Si(001) surface where the critical epinucleus consists of six adatoms.

The steady state of heterogeneous catalysis, studied by first-principles statistical mechanics

The turnover frequency of the catalytic oxidation of CO at RuO2(110) was calculated as a function of temperature and partial pressures using ab initio statistical mechanics. The underlying energetics of the gas-phase molecules, dissociation, adsorption, surface diffusion, surface chemical reactions, and desorption were obtained by all-electron density-functional theory. The resulting CO2 formation rate [in the full (T,p(CO),p(O2)) space], the movies displaying the atomic motion and reactions over times scales from picoseconds to seconds, and the statistical analyses provide insight into the concerted actions ruling heterogeneous catalysis and open thermodynamic systems in general.

Self-compensation in manganese-doped ferromagnetic semiconductors

We present a theory of interstitial Mn in Mn-doped ferromagnetic semiconductors. Using density-functional theory, we show that under the nonequilibrium conditions of growth, interstitial Mn is easily formed near the surface by a simple low-energy adsorption pathway. In GaAs, isolated interstitial Mn is an electron donor, each compensating two substitutional Mn acceptors. Within an impurity-band model, partial compensation promotes ferromagnetic order below the metal-insulator transition, with the highest Curie temperature occurring for 0.5 holes per substitutional Mn.

Arsenic flux dependence of island nucleation on InAs(001)

The initial stages of InAs(001) homoepitaxial growth are investigated using a combination of kinetic Monte Carlo simulations based on ab initio density functional theory and scanning tunneling microscopy. In the two dimensional island nucleation mode investigated, the island number density is found to decrease with increasing As. This behavior is explained by a suppression of the effective In-adatom density leading to a reduction in island nucleation. The relevant microscopic processes responsible for this reduction are identified.