Micromechanics modeling of the multifunctional nature of carbon nanotube-polymer nanocomposites

The present work provides a micromechanics approach based on the generalized self-consistent composite cylinders method as a non-Eshelby approach towards for assessing the impact of carbon nanotubes on the multi-functional nature of nanocom-posites in which they are a constituent. Emphasis is placed on the effective elastic properties as well as electrical and thermal conductivities of nanocomposites con-sisting of randomly oriented single walled carbon nanotubes in epoxy. The effective elastic properties of aligned, as well as clustered and well-dispersed nanotubes in epoxy are discussed in the context of nanotube bundles using both the generalized self-consistent composite cylinders method as well as using computational microme-chanics techniques. In addition, interphase regions are introduced into the composite cylinders assemblages to account for the varying degrees of load transfer between nanotubes and the epoxy as a result of functionalization or lack thereof. Model pre-dictions for randomly oriented nanotubes both with and without interphase regions are compared to measured data from the literature with emphasis placed on assessing the bounds of the effective nanocomposite properties based on the uncertainty in the model input parameters. The generalized self-consistent composite cylinders model is also applied to model the electrical and thermal conductivity of carbon nanotube-epoxy nanocomposites. Recent experimental observations of the electrical conductivity of carbon nanotube polymer composites have identified extremely low percolation limits as well as a per-ceived double percolation behavior. Explanations for the extremely low percolation limit for the electrical conductivity of these nanocomposites have included both the creation of conductive networks of nanotubes within the matrix and quantum effects such as electron hopping or tunneling. Measurements of the thermal conductivity have also shown a strong dependence on nanoscale effects. However, in contrast, these nanoscale effects strongly limit the ability of the nanotubes to increase the thermal conductivity of the nanocomposite due to the formation of an interfacial thermal resistance layer between the nanotubes and the surrounding polymer. As such, emphasis is placed here on the incorporation of nanoscale effects, such as elec-tron hopping and interfacial thermal resistance, into the generalized self-consistent composite cylinder micromechanics model

Thermal spin transport and spin-orbit interaction in ferromagnetic/non-magnetic metals

In this article we extend the currently established diffusion theory of spin-dependent electrical conduction by including spin-dependent thermoelectricity and thermal transport. Using this theory, we propose new experiments aimed at demonstrating novel effects such as the spin-Peltier effect, the reciprocal of the recently demonstrated thermally driven spin injection, as well as the magnetic heat valve. We use finite-element methods to model specific devices in literature to demonstrate our theory. Spin-orbit effects such as anomalous-Hall, -Nernst, anisotropic magnetoresistance and spin-Hall are also included in this model

Habitat preferences of baleen whales in a mid-latitude habitat

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 141 (2017): 155-167, doi:10.1016/j.dsr2.2016.07.015.Understanding the dynamics of baleen whale distribution is essential to predict how environmental changes can affect their ecology and, in turn, ecosystem functioning. Recent work showed that mid-latitude habitats along migratory routes may play an important role on the feeding ecology of baleen whales. This study aimed to investigate the function of a mid-latitude habitat for blue (Balaenoptera musculus), fin (B. physalus) and sei (B. borealis) whales occurring in sympatry during spring and summer months and to what extent their environmental niches overlap. We addressed those questions by developing environmental niche models (ENM) for each species and then making pairwise comparisons of niche overlap and relative habitat patch importance among the three species. ENMs were created using sightings from the Azorean Fisheries Observer Program from May to November, between 2004 and 2009, and a set of 18 predictor environmental variables. We then assessed monthly (April-July) overlap among ENMs using a modified Hellinger’s distance metric (I). Results show that the habitat niches of blue and fin whales are strongly influenced by primary productivity and sea surface temperature and are highly dynamic both spatially and temporally due to the oceanography of the region. Niche overlap analyses show that blue and fin whale environmental niches are similar and that the suitable habitats for the two species have high degree of spatial coincidence. These results in combination suggest that this habitat may function as a mid-latitude feeding ground to both species while conditions are adequate. The sei whale model, on the other hand, did not include variables considered to be proxies for prey distribution and little environmental niche overlap was found between this species and the other two. We argue that these results suggest that the region holds little importance as a foraging habitat for the sei whale.This work was supported by FEDER funds, through the Competitiveness Factors Operational Programme - COMPETE, by national funds, through FCT - Foundation for Science and Technology, under project TRACE (PTDC/ MAR/74071/2006), and by regional funds, through DRCT/SRCTE, under project MAPCET (M2.1.2/ F/012/2011). We acknowledge funds provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. RP was supported by an FCT postdoctoral grant (SFRH_BPD_108007_2015); MT’s fellowship was supported by the FCT Exploratory project (IF/00943/2013); MAS has an FCT Investigador contract (IF/00943/2013).2018-08-0

Non-convex myopic electricity markets : the AC transmission network and interdependent reserve types

Electricity markets are particularly complex because they must accommodate the underlying physics that govern the electric power system. These physics present non-convexities in the social welfare maximization problem, also called the economic dispatch problem, solved by the Independent System Operator (ISO), which is the social planner in this context. The non-convexity of this problem presents difficulties in computing the social welfare maximizing dispatch as well as difficulties in deriving a pricing structure that satisfies certain economic requirements such as revenue adequacy of the ISO and non-negative operating profits for market participants. This dissertation analyzes two sources of non-convexity that pertain to two separate market changes that have been recently proposed in Texas. Both proposals pertain to the real-time electricity market, which clears every 5-minutes and is myopic in the sense that only the demand at the end of the upcoming 5-minute interval is considered and no future time intervals are considered in the social welfare maximization problem. The Electric Reliability Council of Texas (ERCOT) is the ISO in Texas and currently neglects resistive losses along transmission lines when formulating the economic dispatch problem. The first part of this dissertation regards a proposed market change to incorporate transmission losses into the economic dispatch problem. Two general approaches are considered to accommodate associated non-convexity. Similar to current practice, the first approach is based on a marginal pricing structure and uses convex approximations that facilitate efficient computation. By utilizing various approximations, the aforementioned economic requirements are proven to be satisfied approximately. The second approach is based on an alternative pricing structure in which prices are chosen to explicitly minimize the worst-case violation of these economic requirements. For example the prices may be chosen to minimize the potential revenue shortfall of the ISO. These alternative prices are termed convex hull prices and can be approximated by use of convex relaxations. The economic dispatch problem currently used by ERCOT does not endogenously represent operating reserves to handle contingencies that may occur. Instead, operating reserves are currently optimized separately from the electric power generation dispatch. The second part of this dissertation regards a proposed market change to co-optimize reserve and generation dispatch in a social welfare maximization problem called a co-optimization problem. Implementation of the real-time co-optimization problem is being pursued simultaneously with a new definition of the primary frequency responsive reserve types considered in the market. One of these reserve types intends to accommodate standard droop control. Another of these reserve types is newly introduced and intends to facilitate participation of fast-acting batteries in primary frequency response. This dissertation derives reserve requirements from first principles that capture the coupling of these two reserve types as well as their ramping abilities. The newly proposed non-convex requirements represent limits on the ramp-constrained primary frequency responsive reserve procurement. Placing these non-convex requirements into a co-optimization problem is proven to result in the satisfaction of the aforementioned economic requirements.Electrical and Computer Engineerin

Multi-Scale Modeling of Mechanical and Electrochemical Properties of 1D and 2D Nanomaterials, Application in Battery Energy Storage Systems

Material properties play a critical role in durable products manufacturing. Estimation of the precise characteristics in different scales requires complex and expensive experimental measurements. Potentially, computational methods can provide a platform to determine the fundamental properties before the final experiment. Multi-scale computational modeling leads to the modeling of the various time, and length scales include nano, micro, meso, and macro scales. These scales can be modeled separately or in correlation with coarser scales. Depend on the interested scales modeling, the right selection of multi-scale methods leads to reliable results and affordable computational cost. The present dissertation deals with the problems in various length and time scales using computational methods include density functional theory (DFT), molecular mechanics (MM), molecular dynamics (MD), and finite element (FE) methods. Physical and chemical interactions in lower scales determine the coarser scale properties. Particles interaction modeling and exploring fundamental properties are significant challenges of computational science. Downscale modelings need more computational effort due to a large number of interacted atoms/particles. To deal with this problem and bring up a fine-scale (nano) as a coarse-scale (macro) problem, we extended an atomic-continuum framework. The discrete atomic models solve as a continuum problem using the computationally efficient FE method. MM or force field method based on a set of assumptions approximates a solution on the atomic scale. In this method, atoms and bonds model as a harmonic oscillator with a system of mass and springs. The negative gradient of the potential energy equal to the forces on each atom. In this way, each bond's total potential energy includes bonded, and non-bonded energies are simulated as equivalent structural strain energies. Finally, the chemical nature of the atomic bond is modeled as a piezoelectric beam element that solves by the FE method. Exploring novel materials with unique properties is a demand for various industrial applications. During the last decade, many two-dimensional (2D) materials have been synthesized and shown outstanding properties. Investigation of the probable defects during the formation/fabrication process and studying their strength under severe service life are the critical tasks to explore performance prospects. We studied various defects include nano crack, notch, and point vacancy (Stone-Wales defect) defects employing MD analysis. Classical MD has been used to simulate a considerable amount of molecules at micro-, and meso- scales. Pristine and defective nanosheet structures considered under the uniaxial tensile loading at various temperatures using open-source LAMMPS codes. The results were visualized with the open-source software of OVITO and VMD. Quantum based first principle calculations have been conducting at electronic scales and known as the most accurate Ab initio methods. However, they are computationally expensive to apply for large systems. We used density functional theory (DFT) to estimate the mechanical and electrochemical response of the 2D materials. Many-body Schrödinger's equation describes the motion and interactions of the solid-state particles. Solid describes as a system of positive nuclei and negative electrons, all electromagnetically interacting with each other, where the wave function theory describes the quantum state of the set of particles. However, dealing with the 3N coordinates of the electrons, nuclei, and N coordinates of the electrons spin components makes the governing equation unsolvable for just a few interacted atoms. Some assumptions and theories like Born Oppenheimer and Hartree-Fock mean-field and Hohenberg-Kohn theories are needed to treat with this equation. First, Born Oppenheimer approximation reduces it to the only electronic coordinates. Then Kohn and Sham, based on Hartree-Fock and Hohenberg-Kohn theories, assumed an equivalent fictitious non-interacting electrons system as an electron density functional such that their ground state energies are equal to a set of interacting electrons. Exchange-correlation energy functionals are responsible for satisfying the equivalency between both systems. The exact form of the exchange-correlation functional is not known. However, there are widely used methods to derive functionals like local density approximation (LDA), Generalized gradient approximation (GGA), and hybrid functionals (e.g., B3LYP). In our study, DFT performed using VASP codes within the GGA/PBE approximation, and visualization/post-processing of the results realized via open-source software of VESTA. The extensive DFT calculations are conducted 2D nanomaterials prospects as anode/cathode electrode materials for batteries. Metal-ion batteries' performance strongly depends on the design of novel electrode material. Two-dimensional (2D) materials have developed a remarkable interest in using as an electrode in battery cells due to their excellent properties. Desirable battery energy storage systems (BESS) must satisfy the high energy density, safe operation, and efficient production costs. Batteries have been using in electronic devices and provide a solution to the environmental issues and store the discontinuous energies generated from renewable wind or solar power plants. Therefore, exploring optimal electrode materials can improve storage capacity and charging/discharging rates, leading to the design of advanced batteries. Our results in multiple scales highlight not only the proposed and employed methods' efficiencies but also promising prospect of recently synthesized nanomaterials and their applications as an anode material. In this way, first, a novel approach developed for the modeling of the 1D nanotube as a continuum piezoelectric beam element. The results converged and matched closely with those from experiments and other more complex models. Then mechanical properties of nanosheets estimated and the failure mechanisms results provide a useful guide for further use in prospect applications. Our results indicated a comprehensive and useful vision concerning the mechanical properties of nanosheets with/without defects. Finally, mechanical and electrochemical properties of the several 2D nanomaterials are explored for the first time—their application performance as an anode material illustrates high potentials in manufacturing super-stretchable and ultrahigh-capacity battery energy storage systems (BESS). Our results exhibited better performance in comparison to the available commercial anode materials

Thermo-Viscoelastic-Viscoplastic-Viscodamage-Healing Modeling of Bituminous Materials: Theory and Computation

Time- and rate-dependent materials such as polymers, bituminous materials, and soft materials clearly display all four fundamental responses (i.e. viscoelasticity, viscoplasticity, viscodamage, and healing) where contribution of each response strongly depends on the temperature and loading conditions. This study proposes a new general thermodynamic-based framework to specifically derive thermo-viscoelastic, thermo-viscoplastic, thermo-viscodamage, and micro-damage healing constitutive models for bituminous materials and asphalt mixes. The developed thermodynamic-based framework is general and can be applied for constitutive modeling of different materials such as bituminous materials, soft materials, polymers, and biomaterials. This framework is build on the basis of assuming a form for the Helmohelotz free energy function (i.e. knowing how the material stores energy) and a form for the rate of entropy production (i.e. knowing how the material dissipates energy). However, the focus in this work is placed on constitutive modeling of bituminous materials and asphalt mixes. A viscoplastic softening model is proposed to model the distinct viscoplastic softening response of asphalt mixes subjected to cyclic loading conditions. A systematic procedure for identification of the constitutive model parameters based on optimized experimental effort is proposed. It is shown that this procedure is simple and straightforward and yields unique values for the model material parameters. Subsequently, the proposed model is validated against an extensive experimental data including creep, creep-recovery, repeated creep-recovery, dynamic modulus, constant strain rate, cyclic stress controlled, and cyclic strain controlled tests in both tension and compression and over a wide range of temperatures, stress levels, strain rates, loading/unloading periods, loading frequencies, and confinement levels. It is shown that the model is capable of predicting time-, rate-, and temperature-dependent of asphalt mixes subjected to different loading conditions

Emergence of complexity in hierarchically organized chiral particles

The structural complexity of composite biomaterials and biomineralized particles arises from the hierarchical ordering of inorganic building blocks over multiple scales. Although empirical observations of complex nanoassemblies are abundant, the physicochemical mechanisms leading to their geometrical complexity are still puzzling, especially for nonuniformly sized components. We report the self-assembly of hierarchically organized particles (HOPs) from polydisperse gold thiolate nanoplatelets with cysteine surface ligands. Graph theory methods indicate that these HOPs, which feature twisted spikes and other morphologies, display higher complexity than their biological counterparts. Their intricate organization emerges from competing chirality-dependent assembly restrictions that render assembly pathways primarily dependent on nanoparticle symmetry rather than size. These findings and HOP phase diagrams open a pathway to a large family of colloids with complex architectures and unusual chiroptical and chemical properties

Uncertainty Quantification and Reduction in Cardiac Electrophysiological Imaging

Cardiac electrophysiological (EP) imaging involves solving an inverse problem that infers cardiac electrical activity from body-surface electrocardiography data on a physical domain defined by the body torso. To avoid unreasonable solutions that may fit the data, this inference is often guided by data-independent prior assumptions about different properties of cardiac electrical sources as well as the physical domain. However, these prior assumptions may involve errors and uncertainties that could affect the inference accuracy. For example, common prior assumptions on the source properties, such as fixed spatial and/or temporal smoothness or sparseness assumptions, may not necessarily match the true source property at different conditions, leading to uncertainties in the inference. Furthermore, prior assumptions on the physical domain, such as the anatomy and tissue conductivity of different organs in the thorax model, represent an approximation of the physical domain, introducing errors to the inference. To determine the robustness of the EP imaging systems for future clinical practice, it is important to identify these errors/uncertainties and assess their impact on the solution. This dissertation focuses on the quantification and reduction of the impact of uncertainties caused by prior assumptions/models on cardiac source properties as well as anatomical modeling uncertainties on the EP imaging solution. To assess the effect of fixed prior assumptions/models about cardiac source properties on the solution of EP imaging, we propose a novel yet simple Lp-norm regularization method for volumetric cardiac EP imaging. This study reports the necessity of an adaptive prior model (rather than fixed model) for constraining the complex spatiotemporally changing properties of the cardiac sources. We then propose a multiple-model Bayesian approach to cardiac EP imaging that employs a continuous combination of prior models, each re-effecting a specific spatial property for volumetric sources. The 3D source estimation is then obtained as a weighted combination of solutions across all models. Including a continuous combination of prior models, our proposed method reduces the chance of mismatch between prior models and true source properties, which in turn enhances the robustness of the EP imaging solution. To quantify the impact of anatomical modeling uncertainties on the EP imaging solution, we propose a systematic statistical framework. Founded based on statistical shape modeling and unscented transform, our method quantifies anatomical modeling uncertainties and establish their relation to the EP imaging solution. Applied on anatomical models generated from different image resolutions and different segmentations, it reports the robustness of EP imaging solution to these anatomical shape-detail variations. We then propose a simplified anatomical model for the heart that only incorporates certain subject-specific anatomical parameters, while discarding local shape details. Exploiting less resources and processing for successful EP imaging, this simplified model provides a simple clinically-compatible anatomical modeling experience for EP imaging systems. Different components of our proposed methods are validated through a comprehensive set of synthetic and real-data experiments, including various typical pathological conditions and/or diagnostic procedures, such as myocardial infarction and pacing. Overall, the methods presented in this dissertation for the quantification and reduction of uncertainties in cardiac EP imaging enhance the robustness of EP imaging, helping to close the gap between EP imaging in research and its clinical application