Gaussian Approximation Potential: an interatomic potential derived from first principles Quantum Mechanics

Simulation of materials at the atomistic level is an important tool in studying microscopic structure and processes. The atomic interactions necessary for the simulation are correctly described by Quantum Mechanics. However, the computational resources required to solve the quantum mechanical equations limits the use of Quantum Mechanics at most to a few hundreds of atoms and only to a small fraction of the available configurational space. This thesis presents the results of my research on the development of a new interatomic potential generation scheme, which we refer to as Gaussian Approximation Potentials. In our framework, the quantum mechanical potential energy surface is interpolated between a set of predetermined values at different points in atomic configurational space by a non-linear, non-parametric regression method, the Gaussian Process. To perform the fitting, we represent the atomic environments by the bispectrum, which is invariant to permutations of the atoms in the neighbourhood and to global rotations. The result is a general scheme, that allows one to generate interatomic potentials based on arbitrary quantum mechanical data. We built a series of Gaussian Approximation Potentials using data obtained from Density Functional Theory and tested the capabilities of the method. We showed that our models reproduce the quantum mechanical potential energy surface remarkably well for the group IV semiconductors, iron and gallium nitride. Our potentials, while maintaining quantum mechanical accuracy, are several orders of magnitude faster than Quantum Mechanical methods.

First-principles energetics of water: a many-body analysis

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for solid, liquid and cluster forms of water. We use a many-body separation of the total energy into its 1-body, 2-body (2B) and beyond-2-body (B2B) components to analyze the deficiencies of two popular DFT approximations. We show how machine-learning methods make this analysis possible for ice structures as well as for water clusters. We find that the crucial energy balance between compact and extended geometries can be distorted by 2B and B2B errors, and that both types of first-principles error are important.

Fibers with integrated mechanochemical switches: minimalistic design principles derived from fibronectin.

Inspired by molecular mechanisms that cells exploit to sense mechanical forces and convert them into biochemical signals, chemists dream of designing mechanochemical switches integrated into materials. Using the adhesion protein fibronectin, whose multiple repeats essentially display distinct molecular recognition motifs, we derived a computational model to explain how minimalistic designs of repeats translate into the mechanical characteristics of their fibrillar assemblies. The hierarchy of repeat-unfolding within fibrils is controlled not only by their relative mechanical stabilities, as found for single molecules, but also by the strength of cryptic interactions between adjacent molecules that become activated by stretching. The force-induced exposure of cryptic sites furthermore regulates the nonlinearity of stress-strain curves, the strain at which such fibers break, and the refolding kinetics and fraction of misfolded repeats. Gaining such computational insights at the mesoscale is important because translating protein-based concepts into novel polymer designs has proven difficult.

Key principles for developing industrially relevant strategic technology management toolkits

When considering the potential uptake and utilization of technology management tools by industry, it must be recognized that companies face the difficult challenges of selecting, adopting and integrating individual tools into a toolkit that must be implemented within their current organizational processes and systems. This situation is compounded by the lack of sound advice on integrating well-founded individual tools into a robust toolkit that has the necessary degree of flexibility such that they can be tailored for application to specific problems faced by individual organizations. As an initial stepping stone to offering a toolkit with empirically proven utility, this paper provides a conceptual foundation to the development of toolkits by outlining an underlying philosophical position based on observations from multiple research and commercial collaborations with industry. This stance is underpinned by a set of operationalized principles that can offer guidance to organizations when deciding upon the appropriate form, functions and features that should be embodied by any potential tool/toolkit. For example, a key objective of any tool is to aid decision-making and a core set of powerful, flexible, scaleable and modular tools should be sufficient to allow users to generate, explore, shape and implement possible solutions across a wide array of strategic issues. From our philosophical stance, the preferred mode of engagement is facilitated workshops with a participatory process that enables multiple perspectives and structures the conversation through visual representations in order to manage the cognitive load in the collaborative environment. The generic form of the tools should be configurable for the given context and utilized in a lightweight manner based on the premise of 'start small and iterate fast'. © 2012 Elsevier Inc.

First-principles energetics of water clusters and ice: a many-body analysis.

Standard forms of density-functional theory (DFT) have good predictive power for many materials, but are not yet fully satisfactory for cluster, solid, and liquid forms of water. Recent work has stressed the importance of DFT errors in describing dispersion, but we note that errors in other parts of the energy may also contribute. We obtain information about the nature of DFT errors by using a many-body separation of the total energy into its 1-body, 2-body, and beyond-2-body components to analyze the deficiencies of the popular PBE and BLYP approximations for the energetics of water clusters and ice structures. The errors of these approximations are computed by using accurate benchmark energies from the coupled-cluster technique of molecular quantum chemistry and from quantum Monte Carlo calculations. The systems studied are isomers of the water hexamer cluster, the crystal structures Ih, II, XV, and VIII of ice, and two clusters extracted from ice VIII. For the binding energies of these systems, we use the machine-learning technique of Gaussian Approximation Potentials to correct successively for 1-body and 2-body errors of the DFT approximations. We find that even after correction for these errors, substantial beyond-2-body errors remain. The characteristics of the 2-body and beyond-2-body errors of PBE are completely different from those of BLYP, but the errors of both approximations disfavor the close approach of non-hydrogen-bonded monomers. We note the possible relevance of our findings to the understanding of liquid water.

First principles interatomic potential for tungsten based on Gaussian process regression

An accurate description of atomic interactions, such as that provided by first principles quantum mechanics, is fundamental to realistic prediction of the properties that govern plasticity, fracture or crack propagation in metals. However, the computational complexity associated with modern schemes explicitly based on quantum mechanics limits their applications to systems of a few hundreds of atoms at most. This thesis investigates the application of the Gaussian Approximation Potential (GAP) scheme to atomistic modelling of tungsten - a bcc transition metal which exhibits a brittle-to-ductile transition and whose plasticity behaviour is controlled by the properties of $\frac{1}{2} \langle 111 \rangle$ screw dislocations. We apply Gaussian process regression to interpolate the quantum-mechanical (QM) potential energy surface from a set of points in atomic configuration space. Our training data is based on QM information that is computed directly using density functional theory (DFT). To perform the fitting, we represent atomic environments using a set of rotationally, permutationally and reflection invariant parameters which act as the independent variables in our equations of non-parametric, non-linear regression. We develop a protocol for generating GAP models capable of describing lattice defects in metals by building a series of interatomic potentials for tungsten. We then demonstrate that a GAP potential based on a Smooth Overlap of Atomic Positions (SOAP) covariance function provides a description of the $\frac{1}{2} \langle 111 \rangle$ screw dislocation that is in agreement with the DFT model. We use this potential to simulate the mobility of $\frac{1}{2} \langle 111 \rangle$ screw dislocations by computing the Peierls barrier and model dislocation-vacancy interactions to QM accuracy in a system containing more than 100,000 atoms.

New robotics: design principles for intelligent systems.

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

First-principles prediction of the magnetism of 3d transition-metal-doped Rocksalt MgO

Using first-principles band structure methods, we have systematically studied the electronic structures, magnetic stabilities, and half-metal properties of 3d transition-metal (TM) doped Rocksalt MgO compounds TMMg3O4 (TM = V, Cr, Mn, Fe, Co, and Ni). The calculations reveal that only CrMg3O4 has a ferromagnetic stability among the six compounds, which is explained by double-exchange mechanism. The magnetic stability is affected by the doping concentration of TM if the top valance band is composed of partially occupied t(2g) states. In addition, CrMg3O4 is a half-metallic ferromagnet. The origins of half-metallic and ferromagnetic properties are explored. The Curie temperature (T-c) of CrMg3O4 is 182 K. And it is hard for CrMg3O4 to deform due to the large bulk modulus and shear modulus, so it is a promising spintronic material. Our calculations provide the first available information on the magnetic properties of 3d TM-doped MgO.

First-principles LDA plus U and GGA plus U study of neptunium dioxide

We have performed a systematic first-principles investigation to calculate the electronic structures, mechanical properties, and phonon-dispersion curves of NpO2. The local-density approximation+U and the generalized gradient approximation+U formalisms have been used to account for the strong on-site Coulomb repulsion among the localized Np 5f electrons. By choosing the Hubbard U parameter around 4 eV, the orbital occupancy characters of Np 5f and O 2p are in good agreement with recent experiments [A. Seibert, T. Gouder, and F. Huber, J. Nucl. Mater. 389, 470 (2009)]. Comparing to our previous study of ThO2, we note that stronger covalency exists in NpO2 due to the more localization behavior of 5f electrons of Np in line with the localization-delocalization trend exhibited by the actinides series.

First-principles study of UC2 and U2C3

The electronic structure and mechanical properties Of UC2 and U2C3 have been systematically investigated using first-principles calculations by the projector-augmented-wave (PAW) method. Furthermore, in order to describe precisely the strong on-site Coulomb repulsion among the localized U 5f electrons, we adopt the generalized gradient approximation +U formalisms for the exchange-correlation term. We show that our calculated structural parameters and electronic properties for UC2 and U2C3 are in good agreement with the experimental data by choosing an appropriate Hubbard U = 3 eV. As for the chemical bonding nature, the contour plot of charge density and total density of states suggest that UC2 and U2C3 are metallic mainly contributed by the 5f electrons, mixed with significant covalent component resulted from the strong C-C bonds. The present results also illustrate that the metal-carbon (U-C) bonding and the carbon-carbon covalent bonding in U2C3 are somewhat weaker than those in UC2, leading to the weaker thermodynamic stability at high temperature as observed by experiments.

First-principles study on the structural and electronic properties of ultrathin ZnO nanofilms

First-principles calculations; ZnO nanofilms; Electronic properties; Quantum effects； NANOBELTS; NANORINGS; WURTZITE; ENERGY Abstract: Using first-principles density-functional calculations, we have studied the structural and electronic properties Of Ultrathin ZnO {0001} nanofilms. The structural parameters, the charge densities, band structures and density of states have been investigated. The results show that there are remarkable charge transfers from Zn to O atoms in the ZOO nanofilms. All the ZOO nanofilms exhibit direct wide band gaps compared with bulk counterpart, and the gap decreases with increased thickness of the nanofilms. The decreased band gap is associated with the weaker ionic bonding within layers and the less localization of electrons in thicker films. A staircase-like density of states occurs at the bottom of conduction band, indicating the two-dimensional quantum effects in ZnO nanofilms.