Computational methods for the exploration of potential energy surfaces with applications to nanoalloy materials.

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We develop high performance computational methods to explore potential*energy surfaces (PES, mathematical functions that describe how the energy of*molecules changes when the geometry of the molecule changes), thus providing the*foundation for studies of molecular structure and chemical reactivity. Successful implementation*of this proposal will create a unique set of computational tools for studying*molecular structures, transition states, and reaction paths,*and for the simulation of systems with hundreds of atoms. These tools*will be of great importance to researchers in Canada and beyond.*One of our methods mimics DFT and gives a computational speed-up of *4 to 6 orders of magnitude. It will allow the study of nanoalloys*with potential applications in catalysis and data storage devices.*Taking clues from our recent discovery of bimetallic cages,*we will search for new and bigger all-metal cages.**Minima of the PES are equilibrium geometries of molecules; saddle points are*transition states; steepest descent lines connecting saddle points to minima are reaction paths;*low energy regions in the vicinity of steepest-descent lines are important*for detailed models of reaction mechanisms. We will continue to make*expert use of quantum chemistry and density functional theory*(DFT), combined with our own computer codes, to investigate PES. **Students will get trained in research projects that combine method development*and applications and will acquire a variety of skills: expertise in UNIX*and quantum chemistry software, programming and shell scripting, mathematical*modeling, and general scientific literacy. The projects are designed at*various levels to address the needs and capabilities of undergraduate, *postgraduate, and postdoctoral students.**We will work on three fronts to study nanoalloys that have interesting*properties and potential use in catalysis and information technologies.** (1) Global optimization. Evolutionary computing methods, like Genetic*Algorithms (GA), will be developed to determine the geometric structure*of nanoalloy clusters.** (2) Reaction mechanisms. We have used Particle Swarm Optimization (PSO)*to discover, without human supervision, the sequence of geometric transformations*that occur in molecules during chemical reactions (``reaction mechanisms''). We will*create a new method, based on chemical intuition and optimization techniques, to find a priori*(without any DFT calculation) reaction mechanisms. We will find, on a *case-by-case basis, whether this mechanism is a good approximation to the*lowest-energy reaction path (the true mechanism), and will classify chemical reactions accordingly.** (3) Atomistic simulations. We developed a new fitting method for creating*high-dimensional PES that is fully automated, does not require*the user to input a function form, and which works for practically any*chemical composition. This PES function mimics an accurate method (DFT) and offers a*speed-up of 4 to 6 orders of magnitude relative to DFT. We will use it to carry out*accurate Monte Carlo (AIMC) simulations where the PES is used with "importance sampling"*to give great computational speed-up. We will also take a two-pronged approach*to global optimization where we use the PES function for screening*a large number of geometric structures and generate a much smaller subset*for which the DFT energy gets calculated.**Working on those three fronts we will try to uncover the principles that*govern the relative stability and geometric structure, and the magnetic,*electronic and chemical properties of bimetallic clusters. Based on these*principles, and novel methods unique to our group, we will design stable*nanoalloys for possible applications in catalysis and magnetic*data storage devices.