Coupled electronic and morphologic changes in graphene oxide upon electrochemical reduction

Date of Acceptance: 13/04/2015

Coupled electronic and morphologic changes in graphene oxide upon electrochemical reduction

Date of Acceptance: 13/04/2015

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

3D nanoimprint technology for NIR Fabry-Pérot filter arrays

Im Rahmen dieser Arbeit wird die Herstellung von miniaturisierten NIR-Spektrometern auf Basis von Fabry-Pérot (FP) Filter Arrays behandelt. Bisher ist die kostengünstige Strukturierung von homogenen und vertikal erweiterten Kavitäten für NIR FP-Filter mittels Nanoimprint Technologie noch nicht verfügbar, weil die Qualität der Schichten des Prägematerials unzureichend ist und die geringe Mobilität der Prägematerialien nicht ausreicht, um die vertikal erweiterten Kavitäten zu füllen. Diese Arbeit konzentriert sich auf die Reduzierung des technischen Aufwands zur Herstellung von homogenen und vertikal erweiterten Kavitäten. Zur Strukturierung der Kavitäten wird ein großflächiger substratkonformer UV-Nanoimprint Prozess (SCIL - Substrate Conformal Imprint Lithoghaphy) verwendet, der auf einem Hybridstempel basiert und Vorteile von harten und weichen Stempeln vereint. Um die genannten Limitierungen zu beseitigen, werden alternative Designs der Kavitäten untersucht und ein neues Prägematerial eingesetzt. Drei Designlösungen zur Herstellung von homogenen und erweiterten Kavitäten werden untersucht und verglichen: (i) Das Aufbringen des Prägematerials mittel mehrfacher Rotationsbeschichtung, um eine höhere Schichtdicke des Prägematerials vor dem Prägeprozess zu erzeugen, (ii) die Verwendung einer hybriden Kavität bestehend aus einer strukturierten Schicht des Prägematerials eingebettet zwischen zwei Siliziumoxidschichten, um die Schichtdicke der organischen Kavität zu erweitern und (iii) die Optimierung des Prägeprozesses durch Verwendung eines neuen Prägematerials. Die mit diesen drei Ansätzen hergestellten FP-Filter Arrays zeigen, hohe Transmissionen (beste Transmission > 90%) und kleine Linienbreiten (Halbwertsbreiten <5 nm).

A visual system for distributed mosaics using an auvs fleet

The use of teams of Autonomous Underwater Vehicles for visual inspection tasks is a promising robotic field. The images captured by different robots can be also to aid in the localization/navigation of the fleet. In a previous work, a distributed localization system was presented based on the use of Augmented States Kalman Filter through the visual maps obtained by the fleet. In this context, this paper details a system for on-line construction of visual maps and its use to aid the localization and navigation of the robots. Different aspects related to the capture, treatment and construction of mosaics by fleets of robots are presented. The developed system can be executed on-line on different robotic platforms. The paper is concluded with a series of tests and analyses aiming at to system validation.

Coupled CFD Shape Optimization for aerodynamic profiles

The present document deals with the optimization of shape of aerodynamic profiles -- The objective is to reduce the drag coefficient on a given profile without penalising the lift coefficient -- A set of control points defining the geometry are passed and parameterized as a B-Spline curve -- These points are modified automatically by means of CFD analysis -- A given shape is defined by an user and a valid volumetric CFD domain is constructed from this planar data and a set of user-defined parameters -- The construction process involves the usage of 2D and 3D meshing algorithms that were coupled into own- code -- The volume of air surrounding the airfoil and mesh quality are also parametrically defined -- Some standard NACA profiles were used by obtaining first its control points in order to test the algorithm -- Navier-Stokes equations were solved for turbulent, steady-state ow of compressible uids using the k-epsilon model and SIMPLE algorithm -- In order to obtain data for the optimization process an utility to extract drag and lift data from the CFD simulation was added -- After a simulation is run drag and lift data are passed to the optimization process -- A gradient-based method using the steepest descent was implemented in order to define the magnitude and direction of the displacement of each control point -- The control points and other parameters defined as the design variables are iteratively modified in order to achieve an optimum -- Preliminary results on conceptual examples show a decrease in drag and a change in geometry that obeys to aerodynamic behavior principles

Geophysics: Principles, applications and emerging technologies

This book presents research in the field of Geophysics, particularly referring to principles, applications and emerging technologies. Table of Contents: Preface pp. i-xxi Environmental Geophysics: Techniques, advantages and limitations (Pantelis Soupios and Eleni Kokinou, Department of Environmental and Natural Resources Engineering, Technological Educational Institute of Crete, Dynamics of the Ocean Floor, Helmholtz Centre for Ocean Research Kiel, Geomar)pp i-xxi Application of Innovative Geophysical Techniques in Coastal Areas (V. Di Fiore, M. Punzo, D. Tarallo, and G. Cavuoto, Institute for Marine Coastal Environment, National Research Council, Naples)pp. i-xxi Marine Geophysics of the Naples Bay (Southern Tyrrhenian sea, Italy): Principles, Applications and Emerging Technologies (Gemma Aiello and Ennio Marsella, Institute for Marine Coastal Environment, National Research Council, Naples)pp. i-xxi Oceanic Oscillation Phenomena: Relation to Synchronization and Stochastic Resonance (Shinya Shimokawa and Tomonori Matsuura, National Research Institute for Earth Science and Disaster Prevention, Univ. of Toyama)pp. i-xxi Assessment of ocean variability in the Sicily Channel from a numerical three-dimensional model using EOFs decomposition (R. Sorgente, A. Olita, A.F. Drago, A. Ribotti, L. Fazioli, and C. Tedesco, Institute for Marine Coastal Environment, National Research Council, Oristano)pp. i-xxi Monitoring Test of Crack Opening in Volcanic Tuff (Coroglio Cliff. Italy) Using Distributed Optical Fiber Sensor (A. Minardo, A. Coscetta, M. Caccavale, G. Esposito, F. Matano, M. Sacchi, R. Somma, G. Zeni, and L. Zeni, Department of Industrial and Information Eng., Second University of Naples Aversa, Institute for Marine Coastal Environment, National Research Council Naples, National Institute for Geophysics and Volcanology, Osservatorio Vesuviano Naples, Institute for Electromagnetic Sensing of the Environment, National Research Council Naples)pp. i-xxi

Elastic Computing - a novel paradigm for distributed systems

This talk, which is based on our newest findings and experiences from research and industrial projects, addresses one of the most relevant challenges for a decade to come: How to integrate the Internet of Things with software, people, and processes, considering modern Cloud Computing and Elasticity principles. Elasticity is seen as one of the main characteristics of Cloud Computing today. Is elasticity simply scalability on steroids? This talk addresses the main principles of elasticity, presents a fresh look at this problem, and examines how to integrate people, software services, and things into one composite system, which can be modeled, programmed, and deployed on a large scale in an elastic way. This novel paradigm has major consequences on how we view, build, design, and deploy ultra-large scale distributed systems.

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

A short review of the chemical immobilization principles in some common African wildlife species

Dissertação de Mestrado Integrado em Medicina Veterinária

Elemental Analysis and Forensic Comparison of Soils by Laser-Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS)

The elemental analysis of soil is useful in forensic and environmental sciences. Methods were developed and optimized for two laser-based multi-element analysis techniques: laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and laser-induced breakdown spectroscopy (LIBS). This work represents the first use of a 266 nm laser for forensic soil analysis by LIBS. Sample preparation methods were developed and optimized for a variety of sample types, including pellets for large bulk soil specimens (470 mg) and sediment-laden filters (47 mg), and tape-mounting for small transfer evidence specimens (10 mg). Analytical performance for sediment filter pellets and tape-mounted soils was similar to that achieved with bulk pellets. An inter-laboratory comparison exercise was designed to evaluate the performance of the LA-ICP-MS and LIBS methods, as well as for micro X-ray fluorescence (μXRF), across multiple laboratories. Limits of detection (LODs) were 0.01-23 ppm for LA-ICP-MS, 0.25-574 ppm for LIBS, 16-4400 ppm for µXRF, and well below the levels normally seen in soils. Good intra-laboratory precision (≤ 6 % relative standard deviation (RSD) for LA-ICP-MS; ≤ 8 % for µXRF; ≤ 17 % for LIBS) and inter-laboratory precision (≤ 19 % for LA-ICP-MS; ≤ 25 % for µXRF) were achieved for most elements, which is encouraging for a first inter-laboratory exercise. While LIBS generally has higher LODs and RSDs than LA-ICP-MS, both were capable of generating good quality multi-element data sufficient for discrimination purposes. Multivariate methods using principal components analysis (PCA) and linear discriminant analysis (LDA) were developed for discriminations of soils from different sources. Specimens from different sites that were indistinguishable by color alone were discriminated by elemental analysis. Correct classification rates of 94.5 % or better were achieved in a simulated forensic discrimination of three similar sites for both LIBS and LA-ICP-MS. Results for tape-mounted specimens were nearly identical to those achieved with pellets. Methods were tested on soils from USA, Canada and Tanzania. Within-site heterogeneity was site-specific. Elemental differences were greatest for specimens separated by large distances, even within the same lithology. Elemental profiles can be used to discriminate soils from different locations and narrow down locations even when mineralogy is similar.

Self-assembly of gold nanocrystals into discrete coupled plasmonic structures

Development of methodologies for the controlled chemical assembly of nanoparticles into plasmonic molecules of predictable spatial geometry is vital in order to harness novel properties arising from the combination of the individual components constituting the resulting superstructures. This paper presents a route for fabrication of gold plasmonic structures of controlled stoichiometry obtained by the use of a di-rhenium thio-isocyanide complex as linker molecule for gold nanocrystals. Correlated scanning electron microscopy (SEM)—dark-field spectroscopy was used to characterize obtained discrete monomer, dimer and trimer plasmonic molecules. Polarization-dependent scattering spectra of dimer structures showed highly polarized scattering response, due to their highly asymmetric D∞h geometry. In contrast, some trimer structures displayed symmetric geometry (D3h), which showed small polarization dependent response. Theoretical calculations were used to further understand and attribute the origin of plasmonic bands arising during linker-induced formation of plasmonic molecules. Theoretical data matched well with experimentally calculated data. These results confirm that obtained gold superstructures possess properties which are a combination of the properties arising from single components and can, therefore, be classified as plasmonic molecules

Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks

Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost functions estimated online. Subsequently, we consider Mixed-Integer Linear Programs (MILPs), which are of great interest in smart grid control and cooperative robotics. We propose a distributed methodological framework to compute a feasible solution to the original MILP, with guaranteed suboptimality bounds, and extend it to general nonconvex problems. Monte Carlo simulations highlight that the approach represents a substantial breakthrough with respect to the state of the art, thus representing a valuable solution for new toolboxes addressing large-scale MILPs. We then propose a distributed Benders decomposition algorithm for asynchronous unreliable networks. The framework has been then used as starting point to develop distributed methodologies for a microgrid optimal control scenario. We develop an ad-hoc distributed strategy for a stochastic set-up with renewable energy sources, and show a case study with samples generated using Generative Adversarial Networks (GANs). We then introduce a software toolbox named ChoiRbot, based on the novel Robot Operating System 2, and show how it facilitates simulations and experiments in distributed multi-robot scenarios. Finally, we consider a Pickup-and-Delivery Vehicle Routing Problem for which we design a distributed method inspired to the approach of general MILPs, and show the efficacy through simulations and experiments in ChoiRbot with ground and aerial robots.

Small polarons in spin-orbit coupled osmates

Small polarons (SP) have been thoroughly investigated in 3d transition metal oxides and they have been found to play a crucial role in physical phenomena such as charge transport, colossal magnetoresistance and surface reactivity. However, our knowledge about these quasi-particles in 5d systems remains very limited, since the more delocalised nature of the 5d orbitals reduces the strength of the Electronic Correlation (EC), making SP formation in these compounds rather unexpected. Nevertheless, the Spin-Orbit coupled Dirac-Mott insulator Ba2NaOsO6 (BNOO) represents a good candidate for enabling polaron formation in a relativistic background, due to the relatively large EC (U ∼ 3 eV) and Jahn-Teller activity. Moreover, anomalous peaks in Nuclear Magnetic Resonance (NMR) spectroscopy experiments suggest the presence of thermally activated SP dynamics when BNOO is doped with Ca atoms. We investigate SP formation in BNOO both from an electronic and structural point of view by means of fully relativistic first principles calculations. Our numerical simulations predict a stable SP ground state and agree on the value of 810 K for the dynamical process peak found by NMR experiments.

Analysis and design considerations of resonator arrays for inductive power transfer systems

In the frame of inductive power transfer (IPT) systems, arrays of magnetically coupled resonators have received increasing attention as they are cheap and versatile due to their simple structure. They consist of magnetically coupled coils, which resonate with their self-capacitance or lumped capacitive networks. Of great industrial interest are planar resonator arrays used to power a receiver that can be placed at any position above the array. A thorough circuit analysis has been carried out, first starting from traditional two-coil IPT devices. Then, resonator arrays have been introduced, with particular attention to the case of arrays with a receiver. To evaluate the system performance, a circuit model based on original analytical formulas has been developed and experimentally validated. The results of the analysis also led to the definition of a new doubly-fed array configuration with a receiver that can be placed above it at any position. A suitable control strategy aimed at maximising the transmitted power and the efficiency has been also proposed. The study of the array currents has been carried out resorting to the theory of magneto-inductive waves, allowing useful insight to be highlighted. The analysis has been completed with a numerical and experimental study on the magnetic field distribution originating from the array. Furthermore, an application of the resonator array as a position sensor has been investigated. The position of the receiver is estimated through the measurement of the array input impedance, for which an original analytical expression has been also obtained. The application of this sensing technique in an automotive dynamic IPT system has been discussed. The thesis concludes with an evaluation of the possible applications of two-dimensional resonator arrays in IPT systems. These devices can be used to improve system efficiency and transmitted power, as well as for magnetic field shielding.