Ordered arrays of multiferroic epitaxial nanostructures

Epitaxial heterostructures combining ferroelectric (FE) and ferromagnetic (FiM) oxides are a possible route to explore coupling mechanisms between the two independent order parameters, polarization and magnetization of the component phases. We report on the fabrication and properties of arrays of hybrid epitaxial nanostructures of FiM NiFe(2)O(4) (NFO) and FE PbZr(0.52)Ti(0.48)O(3) or PbZr(0.2)Ti(0.8)O(3), with large range order and lateral dimensions from 200 nm to 1 micron. METHODS: The structures were fabricated by pulsed-laser deposition. High resolution transmission electron microscopy and high angle annular dark-field scanning transmission electron microscopy were employed to investigate the microstructure and the epitaxial growth of the structures. Room temperature ferroelectric and ferrimagnetic domains of the heterostructures were imaged by piezoresponse force microscopy (PFM) and magnetic force microscopy (MFM), respectively. RESULTS: PFM and MFM investigations proved that the hybrid epitaxial nanostructures show ferroelectric and magnetic order at room temperature. Dielectric effects occurring after repeated switching of the polarization in large planar capacitors, comprising ferrimagnetic NiFe2O4 dots embedded in ferroelectric PbZr0.52Ti0.48O3 matrix, were studied. CONCLUSION: These hybrid multiferroic structures with clean and well defined epitaxial interfaces hold promise for reliable investigations of magnetoelectric coupling between the ferrimagnetic / magnetostrictive and ferroelectric / piezoelectric phases.

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

First-Principles Study of the Electronic and Magnetic Properties of Defects in Carbon Nanostructures

Understanding the magnetic properties of graphenic nanostructures is instrumental in future spintronics applications. These magnetic properties are known to depend crucially on the presence of defects. Here we review our recent theoretical studies using density functional calculations on two types of defects in carbon nanostructures: Substitutional doping with transition metals, and sp$^3$-type defects created by covalent functionalization with organic and inorganic molecules. We focus on such defects because they can be used to create and control magnetism in graphene-based materials. Our main results are summarized as follows: i)Substitutional metal impurities are fully understood using a model based on the hybridization between the $d$ states of the metal atom and the defect levels associated with an unreconstructed D$_{3h}$ carbon vacancy. We identify three different regimes, associated with the occupation of distinct hybridization levels, which determine the magnetic properties obtained with this type of doping; ii) A spin moment of 1.0 $\mu_B$ is always induced by chemical functionalization when a molecule chemisorbs on a graphene layer via a single C-C (or other weakly polar) covalent bond. The magnetic coupling between adsorbates shows a key dependence on the sublattice adsorption site. This effect is similar to that of H adsorption, however, with universal character; iii) The spin moment of substitutional metal impurities can be controlled using strain. In particular, we show that although Ni substitutionals are non-magnetic in flat and unstrained graphene, the magnetism of these defects can be activated by applying either uniaxial strain or curvature to the graphene layer. All these results provide key information about formation and control of defect-induced magnetism in graphene and related materials.

Morphologically Diverse Cerium Oxide Nanostructures and Nanofields for Multi functional applications.

The prospective impact of nanomaterials in science and technology has followed an increasing trend due to their unique chemical and physical properties compared to bulk. Significant advances in current technologies in areas such as clean energy production, electronics, medicine, and environment have fuelled major research and development efforts in nanotechnology around the world. This leads to the opportunity to use such nanostructured materials in novel applications and devices. Ceria, zirconia, alumina and titania are some of the major oxides which find vast applications as a nanomaterial on a wider side.

Hierarchical concept of optimization based path planning for autonomous driving

Otto-von Guericke-Universität Magdeburg, Fakultät für Maschinenbau, Dissertation, 2016

Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.

Photochemical dynamics of laser-irradiated semiconductor nanostructures

Thesis (Ph.D.)--University of Washington, 2016-08

STRAINING ENGINEERING OF GRAPHENE AND GRAPHENE-BASED NANOSTRUCTURES

Graphene has emerged as an extraordinary material with its capability to accommodate an array of remarkable electronic, mechanical and chemical properties. Extra-large surface-to-volume ratio renders graphene a highly flexible morphology, giving rise to intriguing observations such as ripples, wrinkles and folds as well as the potential to transform into other novel carbon nanostructures. Ultra-thin, mechanically tough, electrically conductive graphene films promise to enable a wealth of possible applications ranging from hydrogen storage scaffolds, electronic transistors, to bottom-up material designs. Enthusiasm for graphene-based applications aside, there are still significant challenges to their realization, largely due to the difficulty of precisely controlling the graphene properties. Controlling the graphene morphology over large areas is crucial in enabling future graphene-based applications and material design. This dissertation aims to shed lights on potential mechanisms to actively manipulate the graphene morphology and properties and therefore enable the material design principle that delivers desirable mechanical and electronic functionalities of graphene and its derivatives.

Controlling Nanostructures for in-situ TEM Characterization

Low dimensional nanostructures, such as nanotubes and 2D sheets, have unique and promising material properties both from a fundamental science and an application standpoint. Theoretical modelling and calculations predict previously unobserved phenomena that experimental scientists often struggle to reproduce because of the difficulty in controlling and characterizing the small structures under real-world constraints. The goal of this dissertation is to controlling these structures so that nanostructures can be characterized in-situ in transmission electron microscopes (TEM) allowing for direct observation of the actual physical responses of the materials to different stimuli. Of most interest to this work are the thermal and electrical properties of carbon nanotubes, boron nitride nanotubes, and graphene. The first topic of the dissertation is using surfactants for aqueous processing to fabricate, store, and deposit the nanostructures. More specifically, thorough characterization of a new surfactant, ammonium laurate (AL), is provided and shows that this new surfactant outperforms the standard surfactant for these materials, sodium dodecyl sulfate (SDS), in almost all tested metrics. New experimental set-ups have been developed by combining specialized in-situ TEM holders with innovative device fabrication. For example, electrical characterization of graphene was performed by using an STM-TEM holder and depositing graphene from aqueous solutions onto lithographically patterned, electron transparent silicon nitride membranes. These experiments produce exciting information about the interaction between graphene and metal probes and the substrate that it rests on. Then, by adding indium to the backside of the membrane and employing the electron thermal microscopy (EThM) technique, the same type of graphene samples could be characterized for thermal transport with high spatial resolution. It is found that reduced graphene oxide sheets deposited onto a silicon nitride membrane and displaying high levels of wrinkling have higher than expected electrical and thermal conduction properties. We are clearly able to visualize the ability of graphene to spread heat away from an electronic hot spot and into the substrate.

Hierarchical Forest Management Planning: A Bilevel Wood Supply Modelling Approach

Le processus de planification forestière hiérarchique présentement en place sur les terres publiques risque d’échouer à deux niveaux. Au niveau supérieur, le processus en place ne fournit pas une preuve suffisante de la durabilité du niveau de récolte actuel. À un niveau inférieur, le processus en place n’appuie pas la réalisation du plein potentiel de création de valeur de la ressource forestière, contraignant parfois inutilement la planification à court terme de la récolte. Ces échecs sont attribuables à certaines hypothèses implicites au modèle d’optimisation de la possibilité forestière, ce qui pourrait expliquer pourquoi ce problème n’est pas bien documenté dans la littérature. Nous utilisons la théorie de l’agence pour modéliser le processus de planification forestière hiérarchique sur les terres publiques. Nous développons un cadre de simulation itératif en deux étapes pour estimer l’effet à long terme de l’interaction entre l’État et le consommateur de fibre, nous permettant ainsi d’établir certaines conditions pouvant mener à des ruptures de stock. Nous proposons ensuite une formulation améliorée du modèle d’optimisation de la possibilité forestière. La formulation classique du modèle d’optimisation de la possibilité forestière (c.-à-d., maximisation du rendement soutenu en fibre) ne considère pas que le consommateur de fibre industriel souhaite maximiser son profit, mais suppose plutôt la consommation totale de l’offre de fibre à chaque période, peu importe le potentiel de création de valeur de celle-ci. Nous étendons la formulation classique du modèle d’optimisation de la possibilité forestière afin de permettre l’anticipation du comportement du consommateur de fibre, augmentant ainsi la probabilité que l’offre de fibre soit entièrement consommée, rétablissant ainsi la validité de l’hypothèse de consommation totale de l’offre de fibre implicite au modèle d’optimisation. Nous modélisons la relation principal-agent entre le gouvernement et l’industrie à l’aide d’une formulation biniveau du modèle optimisation, où le niveau supérieur représente le processus de détermination de la possibilité forestière (responsabilité du gouvernement), et le niveau inférieur représente le processus de consommation de la fibre (responsabilité de l’industrie). Nous montrons que la formulation biniveau peux atténuer le risque de ruptures de stock, améliorant ainsi la crédibilité du processus de planification forestière hiérarchique. Ensemble, le modèle biniveau d’optimisation de la possibilité forestière et la méthodologie que nous avons développée pour résoudre celui-ci à l’optimalité, représentent une alternative aux méthodes actuellement utilisées. Notre modèle biniveau et le cadre de simulation itérative représentent un pas vers l’avant en matière de technologie de planification forestière axée sur la création de valeur. L’intégration explicite d’objectifs et de contraintes industrielles au processus de planification forestière, dès la détermination de la possibilité forestière, devrait favoriser une collaboration accrue entre les instances gouvernementales et industrielles, permettant ainsi d’exploiter le plein potentiel de création de valeur de la ressource forestière.

Growth and characterization of III-V compound semiconductor nanostructures by metalorganic chemical vapor deposition

Planar <110> GaAs nanowires and quantum dots grown by atmospheric MOCVD have been introduced to non-standard growth conditions such as incorporating Zn and growing them on free-standing suspended films and on 10° off-cut substrates. Zn doped nanowires exhibited periodic notching along the axis of the wire that is dependent on Zn/Ga gas phase molar ratios. Planar nanowires grown on suspended thin films give insight into the mobility of the seed particle and change in growth direction. Nanowires that were grown on the off-cut sample exhibit anti-parallel growth direction changes. Quantum dots are grown on suspended thin films and show preferential growth at certain temperatures. Envisioned nanowire applications include twin-plane superlattices, axial pn-junctions, nanowire lasers, and the modulation of nanowire growth direction against an impeding barrier and varying substrate conditions.

'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'

This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations potentially search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the sub-populations on solution quality are examined for two constrained optimisation problems. We examine a number of recombination partnering strategies in the construction of higher-level individuals and a number of related schemes for evaluating sub-solutions. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Hierarchical Reconstruction Method for Solving Ill-posed Linear Inverse Problems

We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

Processing of hierarchical syntactic strusture in music

Hierarchical structure with nested nonlocal dependencies is a key feature of human language and can be identified theoretically in most pieces of tonal music. However, previous studies have argued against the perception of such structures in music. Here, we show processing of nonlocal dependencies in music. We presented chorales by J. S. Bach and modified versions inwhich the hierarchical structure was rendered irregular whereas the local structure was kept intact. Brain electric responses differed between regular and irregular hierarchical structures, in both musicians and nonmusicians. This finding indicates that, when listening to music, humans apply cognitive processes that are capable of dealing with longdistance dependencies resulting from hierarchically organized syntactic structures. Our results reveal that a brain mechanism fundamental for syntactic processing is engaged during the perception of music, indicating that processing of hierarchical structure with nested nonlocal dependencies is not just a key component of human language, but a multidomain capacity of human cognition.