Altaf Karim

Self-learning kinetic Monte Carlo method: Application to Cu(111)

We present a method of performing kinetic Monte Carlo simulations that does not require an a priori list of diffusion processes and their associated energetics and reaction rates. Rather, at any time during the simulation, energetics for all possible single- or multiatom processes, within a specific interaction range, are either computed accurately using a saddle-point search procedure, or retrieved from a database in which previously encountered processes are stored. This self-learning procedure enhances the speed of the simulations along with a substantial gain in reliability because of the inclusion of many-particle processes. Accompanying results from the application of the method to the case of two-dimensional Cu adatom-cluster diffusion and coalescence on Cu111 with detailed statistics of involved atomistic processes and contributing diffusion coefficients attest to the suitability of the method for the purpose.

Site-Dependent Activity of Atomic Ti Catalysts in Al-Based Hydrogen Storage Materials

Doping catalytically inactive materials with dispersed atoms of an active species is a promising route toward realizing ultradilute binary catalyst systems. Beyond catalysis, strategically placed metal atoms can accelerate a wide range of solid-state reactions, particularly in hydrogen storage processes. Here we analyze the role of atomic Ti catalysts in the hydrogenation of Al-based hydrogen storage materials. We show that Ti atoms near the Al surface activate gas-phase H(2), a key step toward hydrogenation. By controlling the placement of Ti, we have found that the overall reaction, comprising H(2) dissociation and H spillover onto the Al surface, is governed by a pronounced trade-off between lowering of the H(2) dissociation barrier and trapping of the products near the active site, with a sharp maximum in the overall activity for Ti in the subsurface layer. Our findings demonstrate the importance of controlling the placement of the active species in optimizing the activity of dilute binary systems.

Directed assembly of nanodiamond nitrogen-vacancy centers on a chemically modified patterned surface.

Nitrogen-vacancy (NV) centers in nanodiamond (ND) particles are an attractive material for photonic, quantum information, and biological sensing technologies due to their optical properties-bright single photon emission and long spin coherence time. To harness these features in practical devices, it is essential to realize efficient methods to assemble and pattern NDs at the micro-/nanoscale. In this work, we report the large scale patterned assembly of NDs on a Au surface by creating hydrophobic and hydrophilic regions using self-assembled monolayer (SAM). Hydrophobic regions are created using a methyl (-CH3) terminated SAM of octadecanethiol molecules. Evaporating a water droplet suspension of NDs on the SAM patterned surface assembles the NDs in the bare Au, hydrophilic regions. Using this procedure, we successfully produced a ND structures in the shape of dots, lines, and rectangles. Subsequent photoluminescence imaging of the patterned NDs confirmed the presence of optically active NV centers. Experimental evidence in conjunction with computational analysis indicates that the surface wettability of the SAM modified Au surface plays a dominant role in the assembly of NDs as compared to van der Waals and other substrate-ND interactions.

Cluster Diffusion and Coalescence on Metal Surfaces: applications of a Self-learning Kinetic Monte-Carlo method

The Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But the method generally has limited predictive power because of its reliance on predetermined atomic events and their energetics as input. We present a novel method, within the lattice gas model in which we combine standard KMC with automatic generation of a table of microscopic events, facilitated by a pattern recognition scheme. Each time the system encounters a new configuration, the algorithm initiates a procedure for saddle point search around a given energy minimum. Nontrivial paths are thus selected and the fully characterized transition path is permanently recorded in a database for future usage. The system thus automatically builds up all possible single and multiple atom processes that it needs for a sustained simulation. Application of the method to the examination of the diffusion of 2-dimensional adatom clusters on Cu(111) displays the key role played by specific diffusion processes and also reveals the presence of a number of multiple atom processes, whose importance is found to decrease with increasing cluster size and decreasing surface temperature. Similarly, the rate limiting steps in the coalescence of adatom islands are determined. Results are compared with those from experiments where available and with those from KMC simulations based on a fixed catalogue of diffusion processes.

Atomistic studies of thin film growth

We present here a summary of some recent techniques used for atomistic studies of thin film growth and morphological evolution. Specific attention is given to a new kinetic Monte Carlo technique in which the usage of unique labeling schemes of the environment of the diffusing entity allows the development of a closed data base of 49 single atom diffusion processes for periphery motion. The activation energy barriers and diffusion paths are calculated using reliable manybody interatomic potentials. The application of the technique to the diffusion of 2-dimensional Cu clusters on Cu(111) shows interesting trends in the diffusion rate and in the frequencies of the microscopic mechanisms which are responsible for the motion of the clusters, as a function of cluster size and temperature. The results are compared with those obtained from yet another novel kinetic Monte Carlo technique in which an open data base of the energetics and diffusion paths of microscopic processes is continuously updated as needed. Comparisons are made with experimental data where available.

Paths, Barriers, and Prefactors for Adatom Descent from Ag Clusters on Ag(111)

We have calculated the energetics and the dynamics for the diffusion of Ag adatoms which land on top of small two-dimensional Ag clusters on Ag(111), using realistic many-body interaction potentials. Purely energetic considerations of the descent of the adatoms from the islands show exchange mechanism to dominate over hopping and the process to favor the formation of 100-microfacetted steps (A-type) over the 111-microfacetted ones (B-type). Accompanying molecular dynamics simulations validate these findings at low temperatures, but show a reversal in the trend above room temperature making the formation of B-type step more probable. Calculations of the diffusion coefficient confirm that the pre-exponential factor for the processes leading to the formation of the A and B type steps are significantly different.