The Activation-Relaxation Technique : ART nouveau and kinetic ART

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 open-ended saddle point search algorithm, and a series of recent improvements to ART nouveau and kinetic ART, an ART-based on-the-fly off-lattice self-learning kinetic Monte Carlo method

Large-N solutions of the Heisenberg and Hubbard-Heisenberg models on the anisotropic triangular lattice: application to Cs2_2CuCl4_4 and to the layered organic superconductors κ\kappa-(BEDT-TTF)2_2X

We solve the Sp(N) Heisenberg and SU(N) Hubbard-Heisenberg models on the anisotropic triangular lattice in the large-N limit. These two models may describe respectively the magnetic and electronic properties of the family of layered organic materials $\kappa$-(BEDT-TTF)$_2$X. The Heisenberg model is also relevant to the frustrated antiferromagnet, Cs$_2$CuCl$_4$. We find rich phase diagrams for each model. The Sp(N) antiferromagnet is shown to have five different phases as a function of the size of the spin and the degree of anisotropy of the triangular lattice. The effects of fluctuations at finite-N are also discussed. For parameters relevant to Cs$_2$CuCl$_4$ the ground state either exhibits incommensurate spin order, or is in a quantum disordered phase with deconfined spin-1/2 excitations and topological order. The SU(N) Hubbard-Heisenberg model exhibits an insulating dimer phase, an insulating box phase, a semi-metallic staggered flux phase (SFP), and a metallic uniform phase. The uniform and SFP phases exhibit a pseudogap. A metal-insulator transition occurs at intermediate values of the interaction strength.Comment: Typos corrected, one reference added. 20 pages, 17 figures, RevTeX 3.

Phase Diagram of β′\beta'-(BEDT-TTF)2_2ICl2_2 under High Pressure Based on the First-Principles Electronic Structure

We present a theoretical study on the superconductivity of $\beta'$-(BEDT-TTF)$_2$ICl$_2$ at $T_{\rm c}=$14.2 K under a high hydrostatic pressure recently found, which is the highest among organic superconductors. In the present work, we study an effective model using the fluctuation-exchange (FLEX) approximation based on the results of first-principles calculation. In the obtained phase diagram, the superconductivity with $d_{xy}$-like symmetry is realized next to the antiferromagnetic phase, as a result of the one-dimensional to two-dimensional crossover driven by the pressure.Comment: 4 pages, 3 figures. accepted for publication in J. Phys. Soc. Jpn. errors correcte

Diffusion rates of Cu adatoms on Cu(111) in the presence of an adisland nucleated at FCC or HCP sites

The surface diffusion of Cu adatoms in the presence of an adisland at FCC or HCP sites on Cu(111) is studied using the EAM potential derived by Mishin {\it et al.} [Phys. Rev. B {\bf 63} 224106 (2001)]. The diffusion rates along straight (with close-packed edges) steps with (100) and (111)-type microfacets (resp. step A and step B) are first investigated using the transition state theory in the harmonic approximation. It is found that the classical limit beyond which the diffusion rates follow an Arrhenius law is reached above the Debye temperature. The Vineyard attempt frequencies and the (static) energy barriers are reported. Then a comparison is made with the results of more realistic classical molecular dynamic simulations which also exhibit an Arrhenius-like behavior. It is concluded that the corresponding energy barriers are completely consistent with the static ones within the statistical errors and that the diffusion barrier along step B is significantly larger than along step A. In contrast the prefactors are very different from the Vineyard frequencies. They increase with the static energy barrier in agreement with the Meyer-Neldel compensation rule and this increase is well approximated by the law proposed by Boisvert {\it et al.} [Phys. Rev. Lett. {\bf 75} 469 (1995)]. As a consequence, the remaining part of this work is devoted to the determination of static energy barriers for a large number of diffusion events that can occur in the presence of an adisland. In particular, it is found that the corner crossing diffusion process for triangular adislands is markedly different for the two types of borders (A or B). From this set of results the diffusion rates of the most important atomic displacements can be predicted and used as input in Kinetic Monte-Carlo simulations

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

Predicting Transitions in Fischer-Tropsch Reactors

The Fischer-Tropsch process has the potential to be fundamental to a future without dependence on fossil fuels. It converts syngas, a readily available resource, into high quality hydrocarbons, with water being the primary byproduct. Like many gas-to-liquid processes, it is catalysed on a transition metal surface, and the lifetime of the catalyst bed largely dictates the process’s economic viability. Predictive computational models can shed light on the mechanisms driving catalyst deactivation. This work focuses particularly on reactors with a titania-supported cobalt catalyst. One part of this project is an investigation using VASP studying the adsorption and mobility of several cobalt species that might form on the TiO2 support surface. It is found that reactor species generally have a strong effect on the binding properties of cobalt, and that this effect could either strengthen or weaken its bond to the surface depending on how reactive the functional group is with the support surface. In particular, the carbon monoxide feedstock was found to favourably bind to surface- adsorbed cobalt and create highly mobile species. In practice the support surface is rarely dry, and this effect is also found on a model hydrated surface. This painted a clear picture that the carbon monoxide feed may have an effect on the sintering process by inducing surface and gas-phase transport of highly dispersed cobalt. Plane-wave DFT suffers from unfavourable cubic scaling and its extended basis makes vacuum space costly, limiting its applicability to large clusters and surface structures. The linear-scaling DFT code ONETEP is a good candidate for investigating these classes of system. While its metals treatment for systems smaller than the thousands of atoms scale using ensemble DFT (EDFT) is also cubic-scaling, it is able to offload a lot of the cost of the calculation onto linear-scaling parts and also maintains a linear-scaling memory cost. Another part of this project was to develop ONETEP to be able to perform studies of chemistry on adsorbed and free catalyst nanoparticles. Two main pieces of crucial functionality have been added to ONETEP - free-spin EDFT and nudged elastic band transition-state searching. The former allows ensemble DFT to be performed at non-integer net spin and non-integer charge, and also adds the ability to relax the spin state during a calculation - previously ONETEP was constrained to fixed integer net spin. This is crucial in cases where the net spin of a magnetic system is not necessarily known or may be altered by, for example, surface adsorbates. The latter is a popular and robust transition state searching method that reliably minimizes a path connecting a product and reactant. The dimer method is also being developed for ONETEP primarily as a transition state refinement tool. Early applications of the new functionality in ONETEP is demonstrated in an investigation of carbon monoxide binding on cobalt HCP and FCC nanoparticles of around 50 atoms. These adsorption energies are compared, where available, to surface adsorption energies from literature. Generally, the abundance of edges on these small particles make surface adsorption energies site dependent and different to clean surface values, and adsorption sites near edges are generally stronger than the surface values. Additionally, two CO dissociation pathways on the FCC cluster are examined, starting from the surface making up the majority on the FCC Wulff particle. A modest decrease in activation energy is identified, and the presence of new pathways involving particle edges is highlighted for future study.This work was carried out with funding and advisor support from Shell Technology Center Bangalore. Funding was provided through the EPSRC CDT in Computational Methods for Materials Science. This work was performed in part using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). I am grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by EPSRC (EP/P020194/1)