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. Density functional theory is implemented using either a plane-wave basis or expansion of electronic states in a linear combination of atomic orbitals. The platform includes a long list of advanced modules, including Green's-function methods for electron transport simulations and surface calculations, first-principles electron-phonon and electron-photon couplings, simulation of atomic-scale heat transport, ion dynamics, spintronics, optical properties of materials, static polarization, and more. Seamless integration of the different simulation engines into a common platform allows for easy combination of different simulation methods into complex workflows. Besides giving a general overview and presenting a number of implementation details not previously published, we also present four different application examples. These are calculations of the phonon-limited mobility of Cu, Ag and Au, electron transport in a gated 2D device, multi-model simulation of lithium ion drift through a battery cathode in an external electric field, and electronic-structure calculations of the composition-dependent band gap of SiGe alloys.

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. Here we test M05-2X and M06-2X for the nucleic acid base pairs in the JSCH-2005 database. Using the CCSD(T) binding energies as a benchmark, the performance of these functionals is compared to that of a nonempirical density functional, PBE, and also to that of PBE plus Grimme's empirical dispersion correction, PBE-D. Due to the importance of "long-range" electron correlation in hydrogen-bonded and interstrand base pairs, PBE-D provides more accurate interaction energies on average for the JSCH-2005 database when compared to M05-2X or M06-2X. M06-2X does, however, perform somewhat better than PBE-D for interactions between stacked base pairs.

In this paper we present a new methodology for the analysis of 1-2 nm nanoparticles using extended X-ray absorption fine structure (EXAFS) spectroscopy. Different numbers of thiols were introduced onto the surfaces of dendrimer-encapsulated Au nanoparticles, consisting of an average of 147 atoms, to systematically tune the nanoparticle disorder. An analogous system was investigated using density functional theory molecular dynamics (DFT-MD) simulations to produce theoretical EXAFS signals that could be directly compared to the experimental results. Validation of the theoretical results by comparing to experiment allows us to infer previously unknown details of structure and dynamics of the nanoparticles. Additionally, the structural information that is learned from theoretical studies can be compared with traditional EXAFS fitting results to identify and rationalize any errors in the experimental fit. This study demonstrates that DFT-MD simulations accurately depict complex experimental systems in which we have control over nanoparticle disorder, and shows the advantages of using a combined experimental/theoretical approach over standard EXAFS fitting methodologies for determining the structural parameters of metallic nanoparticles.

ATK-ForceField is a software package for atomistic simulations using classical interatomic potentials. It is implemented as a part of the Atomistix ToolKit (ATK), which is a Python programming environment that makes it easy to create and analyze both standard and highly customized simulations. This paper will focus on the atomic interaction potentials, molecular dynamics, and geometry optimization features of the software, however, many more advanced modeling features are available. The implementation details of these algorithms and their computational performance will be shown. We present three illustrative examples of the types of calculations that are possible with ATK-ForceField: modeling thermal transport properties in a silicon germanium crystal, vapor deposition of selenium molecules on a selenium surface, and a simulation of creep in a copper polycrystal.

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. All of the benchmarks and methods are provided in an online database to make the implementation details available and the results reproducible. While this paper provides a snapshot of the benchmark results, the online framework is structured to be dynamic and incorporate new methods and codes as they are developed.