QuantumATK: an integrated platform of electronic and atomic-scale modelling tools.

QuantumATK is an integrated set of atomic-scale modelling tools developed since 2003 by professional software engineers in collaboration with academic researchers. While different aspects and individual modules of the platform have been previously presented, the purpose of this paper is to give a general overview of the platform. The QuantumATK simulation engines enable electronic-structure calculations using density functional theory or tight-binding model Hamiltonians, and also offers bonded or reactive empirical force fields in many different parametrizations.

Benchmarks for Characterization of Minima, Transition States, and Pathways in Atomic, Molecular, and Condensed Matter Systems.

A set of benchmark systems is defined to compare different computational approaches for characterizing local minima, transition states, and pathways in atomic, molecular, and condensed matter systems. Comparisons between several commonly used methods are presented. The strengths and weaknesses are discussed, as well as implementation details that are important for achieving good performance.

Distributed replica dynamics.

A distributed replica dynamics (DRD) method is proposed to calculate rare-event molecular dynamics using distributed computational resources. Similar to Voter's parallel replica dynamics (PRD) method, the dynamics of independent replicas of the system are calculated on different computational clients. In DRD, each replica runs molecular dynamics from an initial state for a fixed simulation time and then reports information about the trajectory back to the server.

A theoretical and experimental approach for correlating nanoparticle structure and electrocatalytic activity.

The objective of the research described in this Account is the development of high-throughput computational-based screening methods for discovery of catalyst candidates and subsequent experimental validation using appropriate catalytic nanoparticles. Dendrimer-encapsulated nanoparticles (DENs), which are well-defined 1-2 nm diameter metal nanoparticles, fulfill the role of model electrocatalysts. Effective comparison of theory and experiment requires that the theoretical and experimental models map onto one another perfectly.

Probing the Limits of Conventional Extended X-ray Absorption Fine Structure Analysis Using Thiolated Gold Nanoparticles.

We present a method for quantifying the accuracy of extended X-ray absorption fine structure (EXAFS) fitting models. As a test system, we consider the structure of bare Au147 nanoparticles as well as particles bound with thiol ligands, which are used to systematically vary disorder in the atomic structure of the nanoparticles. The accuracy of the fitting model is determined by comparing two distributions of bond lengths: (1) a direct average over a molecular dynamics (MD) trajectory using forces and energies from density functional theory (DFT) and (2) a fit to the theoretical EXAFS spectra generated from that same trajectory.

Molecular dynamics saddle search adaptive kinetic Monte Carlo.

A method for accelerating molecular dynamics simulations in rare event systems is described. From each new state visited, high temperature molecular dynamics trajectories are used to discover the set of escape mechanisms and rates. This event table is provided to the adaptive kinetic Monte Carlo algorithm to model the evolution of the system from state to state.

Database of atomistic reaction mechanisms with application to kinetic Monte Carlo.

Kinetic Monte Carlo is a method used to model the state-to-state kinetics of atomic systems when all reaction mechanisms and rates are known a priori. Adaptive versions of this algorithm use saddle searches from each visited state so that unexpected and complex reaction mechanisms can also be included. Here, we describe how calculated reaction mechanisms can be stored concisely in a kinetic database and subsequently reused to reduce the computational cost of such simulations.

Assessment of the Performance of the M05-2X and M06-2X Exchange-Correlation Functionals for Noncovalent Interactions in Biomolecules.

The highly parametrized, empirical exchange-correlation functionals, M05-2X and M06-2X, developed by Zhao and Truhlar have been shown to describe noncovalent interactions better than density functionals which are currently in common use. However, these methods have yet to be fully benchmarked for the types of interactions important in biomolecules. M05-2X and M06-2X are claimed to capture "medium-range" electron correlation; however, the "long-range" electron correlation neglected by these functionals can also be important in the binding of noncovalent complexes.