Dynamic interactions between solids and viscous liquids with free surface = Interacciones dinámicas entre sólidos y líquidos viscosos con superficie libre

En esta tesis se investiga la interacción entre un fluido viscoso y un cuerpo sólido en presencia de una superficie libre. El problema se expresa teóricamente poniendo especial atención a los aspectos de conservación de energía y de la interacción del fluido con el cuerpo. El problema se considera 2D y monofásico, y un desarrollo matemático permite una descomposición de los términos disipativos en términos relacionados con la superficie libre y términos relacionados con la enstrofía. El modelo numérico utilizado en la tesis se basa en el método sin malla Smoothed Particle Hydrodynamics (SPH). De manera análoga a lo que se hace a nivel continuo, las propiedades de conservación se estudian en la tesis con el sistema discreto de partículas. Se tratan también las condiciones de contorno de un cuerpo que se mueve en un flujo viscoso, implementadas con el método ghost-fluid. Se ha desarrollado un algoritmo explícito de interacción fluido / cuerpo. Se han documentado algunos casos de modo detallado con el objetivo de comprobar la capacidad del modelo para reproducir correctamente la disipación de energía y el movimiento del cuerpo. En particular se ha investigado la atenuación de una onda estacionaria, comparando la simulación numérica con predicciones teóricas. Se han realizado otras pruebas para monitorizar la disipación de energía para flujos más violentos que implican la fragmentación de la superficie libre. La cantidad de energía disipada con los diferentes términos se ha evaluado en los casos estudiados con el modelo numérico. Se han realizado otras pruebas numéricas para verificar la técnica de modelización de la interacción fluido / cuerpo, concretamente las fuerzas ejercidas por las olas en cuerpos con formas simples, y el equilibrio de un cuerpo flotante con una forma compleja. Una vez que el modelo numérico ha sido validado, se han realizado simulaciones numéricas para obtener una comprensión más completa de la física implicada en casos (casi) realistas sobre los había aspectos que no se conocían suficientemente. En primer lugar se ha estudiado el el flujo alrededor de un cilindro bajo la superficie libre. El estudio se ha realizado con un número de Reynolds moderado, para un rango de inmersiones del cilindro y números de Froude. La solución numérica permite una investigación de los patrones complejos que se producen. La estela del cilindro interactúa con la superficie libre. Se han identificado algunos inestabilidades características. El segundo estudio se ha realizado sobre el problema de sloshing, tanto experimentalmente como numéricamente. El análisis se restringe a aguas poco profundas y con oscilación horizontal, pero se ha estudiado un gran número de condiciones, lo que lleva a una comprensión bastante completa de los sistemas de onda involucradas. La última parte de la tesis trata también sobre un problema de sloshing pero esta vez el tanque está oscilando con rotación y hay acoplamiento con un sistema mecánico. El sistema se llama pendulum-TLD (Tuned Liquid Damper - con líquido amortiguador). Este tipo de sistema se utiliza normalmente para la amortiguación de las estructuras civiles. El análisis se ha realizado analíticamente, numéricamente y experimentalmente utilizando líquidos con viscosidades diferentes, centrándose en características no lineales y mecanismos de disipación. ABSTRA C T The subject of the present thesis is the interaction between a viscous fluid and a solid body in the presence of a free surface. The problem is expressed first theoretically with a particular focus on the energy conservation and the fluid-body interaction. The problem is considered 2D and monophasic, and some mathematical development allows for a decomposition of the energy dissipation into terms related to the Free Surface and others related to the enstrophy. The numerical model used on the thesis is based on Smoothed Particle Hydrodynamics (SPH): a computational method that works by dividing the fluid into particles. Analogously to what is done at continuum level, the conservation properties are studied on the discrete system of particles. Additionally the boundary conditions for a moving body in a viscous flow are treated and discussed using the ghost-fluid method. An explicit algorithm for handling fluid-body coupling is also developed. Following these theoretical developments on the numerical model, some test cases are devised in order to test the ability of the model to correctly reproduce the energy dissipation and the motion of the body. The attenuation of a standing wave is used to compare what is numerically simulated to what is theoretically predicted. Further tests are done in order to monitor the energy dissipation in case of more violent flows involving the fragmentation of the free-surface. The amount of energy dissipated with the different terms is assessed with the numerical model. Other numerical tests are performed in order to test the fluid/body interaction method: forces exerted by waves on simple shapes, and equilibrium of a floating body with a complex shape. Once the numerical model has been validated, numerical tests are performed in order to get a more complete understanding of the physics involved in (almost) realistic cases. First a study is performed on the flow passing a cylinder under the free surface. The study is performed at moderate Reynolds numbers, for various cylinder submergences, and various Froude numbers. The capacity of the numerical solver allows for an investigation of the complex patterns which occur. The wake from the cylinder interacts with the free surface, and some characteristical flow mechanisms are identified. The second study is done on the sloshing problem, both experimentally and numerically. The analysis is restrained to shallow water and horizontal excitation, but a large number of conditions are studied, leading to quite a complete understanding of the wave systems involved. The last part of the thesis still involves a sloshing problem but this time the tank is rolling and there is coupling with a mechanical system. The system is named pendulum-TLD (Tuned Liquid Damper). This kind of system is normally used for damping of civil structures. The analysis is then performed analytically, numerically and experimentally for using liquids with different viscosities, focusing on non-linear features and dissipation mechanisms.

The Proper Generalized Decomposition With Application In Problems Of Dynamics

In this paper we address the new reduction method called Proper Generalized Decomposition (PGD) which is a discretization technique based on the use of separated representation of the unknown fields, specially well suited for solving multidimensional parametric equations. In this case, it is applied to the solution of dynamics problems. We will focus on the dynamic analysis of an one-dimensional rod with a unit harmonic load of frequency (ω) applied at a point of interest. In what follows, we will present the application of the methodology PGD to the problem in order to approximate the displacement field as the sum of the separated functions. We will consider as new variables of the problem, parameters models associated with the characteristic of the materials, in addition to the frequency. Finally, the quality of the results will be assessed based on an example.

Efficient PGD-based dynamic calculation of non-linear soil behavior

Non-linear behavior of soils during a seismic event has a predominant role in current site response analysis. Soil response analysis consistently indicates that the stress-strain relationship of soils is nonlinear and shows hysteresis. When focusing in forced response simulations, time integrations based on modal analysis are widely considered, however parametric analysis, non-linear behavior and complex damping functions make difficult the online use of standard discretization strategies, e.g. those based on the use of finite element. In this paper we propose a new harmonic analysis formulation, able to address forced response simulation of soils exhibiting their characteristic nonlinear behavior. The solution can be evaluated in real-time from the offline construction of a parametric solution of the associated linearized problem within the Proper Generalized Decomposition framework.

Real-Time Dynamic PGD Calculation of Non-Linear Soil Behavior

El estudio sísmico en los últimos 50 años y el análisis del comportamiento dinámico del suelo revelan que el comportamiento del suelo es altamente no lineal e histéretico incluso para pequeñas deformaciones. El comportamiento no lineal del suelo durante un evento sísmico tiene un papel predominante en el análisis de la respuesta de sitio. Los análisis unidimensionales de la respuesta sísmica del suelo son a menudo realizados utilizando procedimientos lineales equivalentes, que requieren generalmente pocos parámetros conocidos. Los análisis de respuesta de sitio no lineal tienen el potencial para simular con mayor precisión el comportamiento del suelo, pero su aplicación en la práctica se ha visto limitada debido a la selección de parámetros poco documentadas y poco claras, así como una inadecuada documentación de los beneficios del modelado no lineal en relación al modelado lineal equivalente. En el análisis del suelo, el comportamiento del suelo es aproximado como un sólido Kelvin-Voigt con un módulo de corte elástico y amortiguamiento viscoso. En el análisis lineal y no lineal del suelo se están considerando geometrías y modelos reológicos más complejos. El primero está siendo dirigido por considerar parametrizaciones más ricas del comportamiento linealizado y el segundo mediante el uso de multi-modo de los elementos de resorte-amortiguador con un eventual amortiguador fraccional. El uso del cálculo fraccional está motivado en gran parte por el hecho de que se requieren menos parámetros para lograr la aproximación exacta a los datos experimentales. Basándose en el modelo de Kelvin-Voigt, la viscoelasticidad es revisada desde su formulación más estándar a algunas descripciones más avanzada que implica la amortiguación dependiente de la frecuencia (o viscosidad), analizando los efectos de considerar derivados fraccionarios para representar esas contribuciones viscosas. Vamos a demostrar que tal elección se traduce en modelos más ricos que pueden adaptarse a diferentes limitaciones relacionadas con la potencia disipada, amplitud de la respuesta y el ángulo de fase. Por otra parte, el uso de derivados fraccionarios permite acomodar en paralelo, dentro de un análogo de Kelvin-Voigt generalizado, muchos amortiguadores que contribuyen a aumentar la flexibilidad del modelado para la descripción de los resultados experimentales. Obviamente estos modelos ricos implican muchos parámetros, los asociados con el comportamiento y los relacionados con los derivados fraccionarios. El análisis paramétrico de estos modelos requiere técnicas numéricas eficientemente capaces de simular comportamientos complejos. El método de la Descomposición Propia Generalizada (PGD) es el candidato perfecto para la construcción de este tipo de soluciones paramétricas. Podemos calcular off-line la solución paramétrica para el depósito de suelo, para todos los parámetros del modelo, tan pronto como tales soluciones paramétricas están disponibles, el problema puede ser resuelto en tiempo real, porque no se necesita ningún nuevo cálculo, el solucionador sólo necesita particularizar on-line la solución paramétrica calculada off-line, que aliviará significativamente el procedimiento de solución. En el marco de la PGD, parámetros de los materiales y los diferentes poderes de derivación podrían introducirse como extra-coordenadas en el procedimiento de solución. El cálculo fraccional y el nuevo método de reducción modelo llamado Descomposición Propia Generalizada han sido aplicado en esta tesis tanto al análisis lineal como al análisis no lineal de la respuesta del suelo utilizando un método lineal equivalente. ABSTRACT Studies of earthquakes over the last 50 years and the examination of dynamic soil behavior reveal that soil behavior is highly nonlinear and hysteretic even at small strains. Nonlinear behavior of soils during a seismic event has a predominant role in current site response analysis. One-dimensional seismic ground response analysis are often performed using equivalent-linear procedures, which require few, generally well-known parameters. Nonlinear analyses have the potential to more accurately simulate soil behavior, but their implementation in practice has been limited because of poorly documented and unclear parameter selection, as well as inadequate documentation of the benefits of nonlinear modeling relative to equivalent linear modeling. In soil analysis, soil behaviour is approximated as a Kelvin-Voigt solid with a elastic shear modulus and viscous damping. In linear and nonlinear analysis more complex geometries and more complex rheological models are being considered. The first is being addressed by considering richer parametrizations of the linearized behavior and the second by using multi-mode spring-dashpot elements with eventual fractional damping. The use of fractional calculus is motivated in large part by the fact that fewer parameters are required to achieve accurate approximation of experimental data. Based in Kelvin-Voigt model the viscoelastodynamics is revisited from its most standard formulation to some more advanced description involving frequency-dependent damping (or viscosity), analyzing the effects of considering fractional derivatives for representing such viscous contributions. We will prove that such a choice results in richer models that can accommodate different constraints related to the dissipated power, response amplitude and phase angle. Moreover, the use of fractional derivatives allows to accommodate in parallel, within a generalized Kelvin-Voigt analog, many dashpots that contribute to increase the modeling flexibility for describing experimental findings. Obviously these rich models involve many parameters, the ones associated with the behavior and the ones related to the fractional derivatives. The parametric analysis of all these models require efficient numerical techniques able to simulate complex behaviors. The Proper Generalized Decomposition (PGD) is the perfect candidate for producing such kind of parametric solutions. We can compute off-line the parametric solution for the soil deposit, for all parameter of the model, as soon as such parametric solutions are available, the problem can be solved in real time because no new calculation is needed, the solver only needs particularize on-line the parametric solution calculated off-line, which will alleviate significantly the solution procedure. Within the PGD framework material parameters and the different derivation powers could be introduced as extra-coordinates in the solution procedure. Fractional calculus and the new model reduction method called Proper Generalized Decomposition has been applied in this thesis to the linear analysis and nonlinear soil response analysis using a equivalent linear method.

Dynamic modeling of gene expression data

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

Corn stover thermal decomposition in pyrolytic and oxidant atmosphere

The pyrolysis and combustion of corn stover were studied by dynamic thermogravimetry and derivate thermogravimetry (TG-DTG) at heating rates of 5, 10, 20 and 50 K min−1 at atmospheric pressure. For the simulation of pyrolysis and combustion processes a kinetic model based on the distribution of activation energies was used, with three pools of reactants (three pseudocomponents) because of the complexity of the biomass samples of agricultural origin. The experimental thermogravimetric data of pyrolysis and combustion processes were simultaneously fitted to determine a single set of kinetic parameters able to describe both processes at the different heating rates. The model proposed achieves a good correlation between the experimental and calculated curves, with an error of less than 4% for fitting four heating rates simultaneously. The experimental results and kinetic parameters may provide useful data for the design of thermo decomposition processing system using corn stover as feedstock. On the other hand, analysis of the main compounds in the evolved gas is given by means of a microcromatograph.

Thermogravimetric study of the decomposition of printed circuit boards from mobile phones

Thermal decomposition of printed circuits boards (PCB) is studied, using thermogravimetric analysis to compare the thermal behavior of PCB of mobile phones before and after the removal of the metallic fraction by acid washing. Several dynamic and dynamic + isothermal runs have been carried out at different heating rates (5, 10 and 20 K min−1), from room temperature to more than 1100 K. Also runs in the presence and in the absence of oxygen were performed (combustion and pyrolysis runs). Moreover, TG–MS experiments were performed (both in inert and oxidizing atmosphere) in order to better understand the thermal decomposition of these wastes and identify some compounds emitted during the controlled heating of these materials. Different reaction models are proposed, one for pyrolysis and one for combustion of the two kinds of wastes studied, which proved to simulate appropriately the experimental results at all the heating rates simultaneously.

Kinetic study and thermal decomposition behavior of viscoelastic memory foam

A systematic investigation of the thermal decomposition of viscoelastic memory foam (VMF) was performed using thermogravimetric analysis (TGA) to obtain the kinetic parameters, and thermogravimetric analysis coupled to Fourier Transformed Infrared Spectrometry (TGA-FTIR) and thermogravimetric analysis coupled to Mass Spectrometry (TGA-MS) to obtain detailed information of evolved products on pyrolysis and oxidative degradations. Two consecutive nth-order reactions were employed to correlate the experimental data from dynamic and isothermal runs performed at three different heating rates (5, 10 and 20 K/min) under an inert atmosphere. On the other hand, for the kinetic study of the oxidative decomposition, the data from combustion (synthetic air) and poor oxygen combustion (N2:O2 = 9:1) runs, at three heating rates and under dynamic and isothermal conditions, were correlated simultaneously. A kinetic model consisting of three consecutive reactions presented a really good correlation in all runs. TGA-FTIR analysis showed that the main gases released during the pyrolysis of VMF were determined as ether and aliphatic hydrocarbons, whereas in combustion apart from the previous gases, aldehydes, amines and CO2 have also been detected as the main gases. These results were confirmed by the TGA-MS.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

A shape-based decomposition of the yield adjustment term in the arbitrage-free Nelson and Siegel (AFNS) model of the yield curve

The appealing feature of the arbitrage-free Nelson-Siegel model of the yield curve is the ability to capture movements in the yield curve through readily interpretable shifts in its level, slope or curvature, all within a dynamic arbitrage-free framework. To ensure that the level, slope and curvature factors evolve so as not to admit arbitrage, the model introduces a yield-adjustment term. This paper shows how the yield-adjustment term can also be decomposed into the familiar level, slope and curvature elements plus some additional readily interpretable shape adjustments. This means that, even in an arbitrage-free setting, it continues to be possible to interpret movements in the yield curve in terms of level, slope and curvature influences. © 2014 © 2014 Taylor & Francis.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Asymptotic preserving and time diminishing schemes for rarefied gas dynamic

In this work, we introduce a new class of numerical schemes for rarefied gas dynamic problems described by collisional kinetic equations. The idea consists in reformulating the problem using a micro-macro decomposition and successively in solving the microscopic part by using asymptotic preserving Monte Carlo methods. We consider two types of decompositions, the first leading to the Euler system of gas dynamics while the second to the Navier-Stokes equations for the macroscopic part. In addition, the particle method which solves the microscopic part is designed in such a way that the global scheme becomes computationally less expensive as the solution approaches the equilibrium state as opposite to standard methods for kinetic equations which computational cost increases with the number of interactions. At the same time, the statistical error due to the particle part of the solution decreases as the system approach the equilibrium state. This causes the method to degenerate to the sole solution of the macroscopic hydrodynamic equations (Euler or Navier-Stokes) in the limit of infinite number of collisions. In a last part, we will show the behaviors of this new approach in comparisons to standard Monte Carlo techniques for solving the kinetic equation by testing it on different problems which typically arise in rarefied gas dynamic simulations.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Random walk with restart over dynamic graphs

Random Walk with Restart (RWR) is an appealing measure of proximity between nodes based on graph structures. Since real graphs are often large and subject to minor changes, it is prohibitively expensive to recompute proximities from scratch. Previous methods use LU decomposition and degree reordering heuristics, entailing O(|V|^3) time and O(|V|^2) memory to compute all (|V|^2) pairs of node proximities in a static graph. In this paper, a dynamic scheme to assess RWR proximities is proposed: (1) For unit update, we characterize the changes to all-pairs proximities as the outer product of two vectors. We notice that the multiplication of an RWR matrix and its transition matrix, unlike traditional matrix multiplications, is commutative. This can greatly reduce the computation of all-pairs proximities from O(|V|^3) to O(|delta|) time for each update without loss of accuracy, where |delta| (<<|V|^2) is the number of affected proximities. (2) To avoid O(|V|^2) memory for all pairs of outputs, we also devise efficient partitioning techniques for our dynamic model, which can compute all pairs of proximities segment-wisely within O(l|V|) memory and O(|V|/l) I/O costs, where 1<=l<=|V| is a user-controlled trade-off between memory and I/O costs. (3) For bulk updates, we also devise aggregation and hashing methods, which can discard many unnecessary updates further and handle chunks of unit updates simultaneously. Our experimental results on various datasets demonstrate that our methods can be 1–2 orders of magnitude faster than other competitors while securing scalability and exactness.

Compact Ag@fe3o4 Core-shell Nanoparticles By Means Of Single-step Thermal Decomposition Reaction.

A temperature pause introduced in a simple single-step thermal decomposition of iron, with the presence of silver seeds formed in the same reaction mixture, gives rise to novel compact heterostructures: brick-like Ag@Fe3O4 core-shell nanoparticles. This novel method is relatively easy to implement, and could contribute to overcome the challenge of obtaining a multifunctional heteroparticle in which a noble metal is surrounded by magnetite. Structural analyses of the samples show 4 nm silver nanoparticles wrapped within compact cubic external structures of Fe oxide, with curious rectangular shape. The magnetic properties indicate a near superparamagnetic like behavior with a weak hysteresis at room temperature. The value of the anisotropy involved makes these particles candidates to potential applications in nanomedicine.