Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package

This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange–correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear–electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an “open teamware” model and an increasingly modular design

High-frequency light-matter interaction in atoms and molecules

The field of attosecond science is a novel and fast-evolving research area that aims at unravelling the motion of particles in atoms, molecules, and solids. Therein, attochemistry thrives to understand, monitor, and one-day control the movement of electrons in molecules, which will open a new path to steer nuclear dynamics and photochemical reactions. In order to observe the motion of electrons, attosecond resolution and, thus, attosecond light pulses are needed. These attosecond pulses are inherently rooted in the high-frequency regime, ranging from XUV to soft and hard x-ray radiation. Depending on the energy, intensity, and aimed-at observable, different light-matter interactions can be studied. In this work, we tackle three different kinds of high-frequency light-matter interaction that originate in three different energy regimes and allow us to gain novel insight into the dynamics of molecules. In the XUV regime, the ionisation dynamics of correlated, multi-particle systems is studied together with few-cycle effects. In the soft x-ray regime, attosecond x-ray absorption is introduced as a novel tool to observe coupled electron and nuclear dynamics in a neutral molecule. In the hard x-ray regime, we focus on ultrafast, non-resonant x-ray scattering, which can be transformed into a future technology capable of observing electron dynamics. We are confident that this work will benefit the general understanding of high-frequency light-matter interaction in atoms and molecules, as well as aid and initiate new experiments in the field of attochemistry using XUV ionisation, x-ray absorption, and x-ray scattering

Granular media at multiple scales: mathematical analysis, modelling and computation

There are many challenges in modelling granular media, in particular due to hard particle interactions such as collisions. Modelling and simulating at a microscopic level produces very accurate results, but simulations are generally restricted to relatively small systems of particles. It is also difficult to construct a simple continuum model which accurately describes all the properties of granular media. In this thesis, we consider a number of the problems associated with modelling granular media. We first look at the microscopic dynamics of individual particles and how to derive physically appropriate interactions between them, and discuss Event-Driven Particle Dynamics (EDPD) as an accurate and efficient way to model a system of hard, spherical particles. We then present a novel derivation of the weak form of the Liouville equation which can model systems where particles interact instantaneously (e.g. via inelastic collisions). From here we construct the BBGKY hierarchy and use moment closure methods to construct a new, accurate continuum model for granular media, based on Dynamical Density Functional Theory (DDFT). We then use EDPD to construct approximations for the radial correlation function which accounts for friction, packing fraction and inelasticity. This is then included in the DDFT in simulated examples

Gratings: Theory and Numeric Applications, Second Revisited Edition

International audienceThe second Edition of the Book contains 13 chapters, written by an international team of specialist in electromagnetic theory, numerical methods for modelling of light diffraction by periodic structures having one-, two-, or three-dimensional periodicity, and aiming numerous applications in many classical domains like optical engineering, spectroscopy, and optical telecommunications, together with newly born fields such as photonics, plasmonics, photovoltaics, metamaterials studies, cloaking, negative refraction, and super-lensing. Each chapter presents in detail a specific theoretical method aiming to a direct numerical application by university and industrial researchers and engineers.In comparison with the First Edition, we have added two more chapters (ch.12 and ch.13), and revised four other chapters (ch.6, ch.7, ch.10, and ch.11

Gratings: Theory and Numeric Applications

International audienceThe book containes 11 chapters written by an international team of specialist in electromagnetic theory, numerical methods for modelling of light diffraction by periodic structures having one-, two-, or three-dimensional periodicity, and aiming numerous applications in many classical domains like optical engineering, spectroscopy, and optical telecommunications, together with newly born fields such as photonics, plasmonics, photovoltaics, metamaterials studies, cloaking, negative refraction, and super-lensing. Each chapter presents in detail a specific theoretical method aiming to a direct numerical application by university and industrial researchers and engineers

Crystal Cartography: Mapping Nanostructure with Scanning Electron Diffraction

Nanostructure describes the network of defective and distorted atomic structure existing on the nanoscale within materials. This nanostructure bridges the gap between idealised crys- talline structure and real materials, playing a deterministic role in tailoring physico-chemical properties, as well as providing a basis for mechanistic understanding of complex processes such as mechanical deformation and phase transformation. Characterising nanostructure, to develop understanding of materials, requires experimental techniques capable of probing the structure with spatial resolution on the order of nanometres and across regions of interest up to micrometres. Recent developments in electron microscopy, enabling the acquisition of numerous diffraction patterns in a spatially resolved manner, combined with modern computational power, provides a route to meet this need as developed in this work. Scanning electron diffraction (SED) involves the acquisition of a two-dimensional elec- tron diffraction pattern at each probe position in a two-dimensional scan of a specimen. An information rich 4-dimensional (4D-SED) dataset is obtained that can be analysed extensively post-facto using a wide-range of computational methods. The acquisition of such 4D-SED data from the specimen at numerous orientations may also enable the reconstruction of nanostructure in three-dimensions via tomographic methods. In this work, methods for the acquisition and analysis of 4D-SED data are developed and applied to reveal nanostructure in two and three-dimensions. These methods are applied to various prototypical characterisation challenges in materials science, particularly: strain mapping in two and three dimensions, revealing inter-phase crystallographic relationships, mapping grains in two-dimensional materials, and probing nanostructure in polyethylene

Computational modeling of metallic nanoclusters and nano-alloys for catalytic and corrosion applications.

The field of Material Science within the realm of Nanophysics has become one of the most thriving research areas. Indeed, due to its emphasis on practical applications, it is a decisive ally to face the challenges of the humankind. Nowadays, one of these challenges comprises the discovery and efficiency of new materials. As such, protection against degradation becomes a fundamental part in Nanoscience. When dealing with metals, an ubiquitous degradation of these comes in the form of their interaction with the atmosphere. Oxidation and the attack of several corroding agents imply the loss of the metallic surface. This undermines the metallic properties and can result in the collapse of the metallic structure if nothing is done to stop the electrochemical reaction. The corrosion problem entails a huge economic cost for the industry, being addressed through available control practices: techniques such as galvanization and stainless-steel alloys are used to prevent metals from rusting, and are widely used for such purpose. The galvanization is the process of applying a protective zinc coating over the metallic surface. After reacting with the atmospheric oxygen and corroding agents, it is the oxidized zinc layer and the related corrosion products the ones that protect the metal from corroding, either with oxygen or any other corroding agent. This way, the zinc layer serves as a sacrificial coating which provides barrier and galvanic protection to the steel substrates employed in industry. It has been found however, that adding magnesium to the zinc layer to form an alloy improves the protective properties of the coating. Not only the oxidized protective layer is created faster, but also the time for growing significant amounts of rust upon corrosion is longer compared to bare zinc. More in detail, the Zn11Mg2 y Zn2Mg stoichiometries have been found to be the most suitable to optimize the protection against corrosion according to experimental evidence. The reasons for such quality are, however, not well known. The intricate physical, chemical and thermodynamical processes involved are difficult to understand in depth without a quantum-mechanical analysis. The objective of this thesis is to unveil the fundamental aspects that trigger the optimal anticorrosive properties of Zn-Mg coatings. Given the vastness of the problem, we will focus on the formation of the initial oxidized surface layer, over which the corrosion products would grow to ultimately conform the protective layer. To this aim, a detailed quantum-mechanical treatment relying on ab-initio techniques, particularly Density Functional Theory based methods, is performed. To study the complex corrosion process, we rely on cluster models. These are simple yet useful computational models for an initial study of the intricate processes that operate in the real extended surfaces. Characterisation of structures is a central task in this thesis, so the development of algorithms and protocols to seek and discover stable structures comprises the core of this work. One of these methods entails novel Machine Learning methods, such as the Neural Network potentials. These are shown to clearly outperform standard empirical potentials. Afterwards, an analysis of the initial stages of the corrosion problem by means of ab-initio methods is performed. It is found that small amounts of Mg create a very positive synergy between Zn and Mg that increases the reactivity to oxygen while reducing, at the same time, the stress induced on the cluster substrate, both facts working in favor of promoting the growth of the oxide crust whilst protecting the core. Moreover, stoichiometries close to the Mg2Zn11 and MgZn2 compositions are found to be the best candidates to optimize the protection against corrosion in Zn-Mg alloys, in agreement with the experimental observations.El campo de la Ciencia de Materiales se ha convertido en una de las áreas más prolíficas de investigación. Dado su especial énfasis en las aplicaciones prácticas, se ha convertido en un aliado decisivo a la hora de afrontar los retos que tiene la humanidad. Hoy en día, uno de estos retos incluye el descubrimiento de nuevos materiales, así como la eficiencia de los mismos. De esta manera, la protección frente a la degradación de estos materiales toma una importancia central. En sistemas basados en metal, una interacción omnipresente en la atmósfera terrestre es la de la corrosión, consistente en el deterioro del metal a consecuencia de la oxidación y de otros ataques electroquímicos. Se trata de un problema industrial de gran importancia y de alto costo económico. De este modo, varias técnicas como el galvanizado y las aleaciones inoxidables se emplean de forma sistemática. En el caso del galvanizado o cincado, el metal a proteger se recubre con una capa de zinc. Además de mejorar su aspecto visual, el zinc, al reaccionar con el oxígeno y otros agentes corrosivos como Cl- y agua, forma una capa de óxido y otros productos derivados de la corrosión que protege el interior del metal de la oxidación y corrosión. Sin embargo, se ha encontrado que la incorporación de magnesio para formar una aleación con el zinc resulta en una creación más eficiente de la capa protectora: la formación de la capa de óxido es más rápida, y es más efectiva en el aislamiento del exterior. En particular, las composiciones Zn11Mg2 y Zn2Mg se encuentran como las más indicadas para maximizar la eficiencia de la capa protectora según la evidencia experimental. Las razones de esta cualidad no son, sin embargo, bien conocidas. El proceso de la corrosión implica procesos físicos, químicos y termodinámicos en diferentes etapas, que resultan en la capa aislante final. Este proceso intermedio de corrosión es, en consecuencia, muy complejo de estudiar y de modelizar a escala nanométrica y donde, en todo caso, reside la respuesta al interrogante. El objeto de esta tesis consiste en estudiar detalladamente los mecanismos físico-químicos que determinan el proceso de corrosión sobre la aleación Zn-Mg, mediante un detallado análisis mecánico-cuántico empleando métodos ab-initio o de primeros principios basados fundamentalmente en la Teoría del Funcional de la Densidad (DFT). Para estudiar el complejo problema de la corrosión, en esta tesis se emplean modelos basados en agregados atómicos o clústers. El problema de la búsqueda estructural es central en esta tesis, tanto en la localización de agregados de mínima energía como en la obtención de productos derivados de la corrosión. De este modo, en primer lugar se desarrollan técnicas para la obtención de estructuras de mínima energía, basadas en modelos numéricos que aproximadamente representen las interacciones atómicas en el sistema. Una de éstas se basa en una técnica de Machine Learning: los potenciales basados en redes neuronales. Se encuentra que su rendimiento es mucho mayor comparado con los potenciales empíricos estándar. Posteriormente, se inicia el estudio inicial de la corrosión sobre clústers de 20 átomos, de diferentes estequiometrías. Se encuentra una positiva sinergia entre el zinc y el magnesio, la cual produce un crecimiento homogéneo de la superficie oxidada al mismo tiempo que protege el interior del agregado. Del mismo modo, se encuentra que las composiciones cercanas a Mg2Zn11 y MgZn2 son las más adecuadas para optimizar la protección frente a la corrosión, en acuerdo con la evidencia experimental. Una última etapa, basada en la formación completa de la capa protectora queda pendiente de explorar.Escuela de DoctoradoDoctorado en Físic