Littérature scientifique sur le sujet « Intra Cluster Medium »

We present numerical simulations of the dynamical and chemical evolution of galaxy clusters. from X-ray spectra it is evident that the Intra-Cluster Medium (ICM) is abundant in metals. As heavy elements are only produced in stars the processed material must have been ejected by cluster galaxies into the ICM. Several different mechanisms for interaction between the cluster galaxies and the ICM are possible but their efficiency of metal enrichment of the cluster and their time evolution are still not known. Suggested processes which remove enriched material from the galaxies are ram-pressure stripping, galactic winds, superwinds driven by starburst activity and jets from active galaxies. First results of high resolution hydrodynamic simulations on cluster scales are presented to investigate the effect of these different pollution mechanisms.

AbstractMagnetic fields originate small-scale instabilities in the plasma of the intra-cluster medium, and may have a key role to understand particle acceleration mechanisms. Recent observations at low radio frequencies have revealed that synchrotron emission from galaxy clusters is more various and complicated than previously thought, and new types of radio sources have been observed. In the last decade, big steps forward have been done to constrain the magnetic field properties in clusters thanks to a combined approach of polarisation observations and numerical simulations that aim to reproduce Faraday Rotation measures of sources observed through the intra-cluster medium. In this contribution, I will review the results on magnetic fields reached in the last years, and I will discuss the assumptions that have been done so far in light of new results obtained from cosmological simulations. I will also discuss how the next generation of radio instruments, as the SKA, will help improving our knowledge of the magnetic field in the intra-cluster medium.

X-ray observations of the hot gas filling the intra-cluster medium (ICM) provide a wealth of information on the dynamics of clusters of galaxies. The global equilibrium of the ICM is believed to be ensured by non-thermal and thermal pressure support sources, among which gas movements and the dissipation of energy through turbulent motions. Accurate mapping of turbulence using X-ray emission lines is challenging due to the lack of spatially resolved spectroscopy. Only future instruments such as the X-ray Integral Field Unit (X-IFU) on Athena will have the spatial and spectral resolution to quantitatively investigate the ICM turbulence over a broad range of spatial scales. Powerful diagnostics for these studies are line shift and the line broadening maps, and the second-order structure function. When estimating these quantities, instruments will be limited by uncertainties of their measurements, and by the sampling variance (also known as cosmic variance) of the observation. Here, we extend the formalism started in our companion Paper I to include the effect of statistical uncertainties of measurements in the estimation of these line diagnostics, in particular for structure functions. We demonstrate that statistics contribute to the total variance through different terms, which depend on the geometry of the detector, the spatial binning and the nature of the turbulent field. These terms are particularly important when probing the small scales of the turbulence. An application of these equations is performed for the X-IFU, using synthetic turbulent velocity maps of a Coma-like cluster. Results are in excellent agreement with the formulas both for the structure function estimation (≤3%) and its variance (≤10%). The expressions derived here and in Paper I are generic, and ensure an estimation of the total errors in any X-ray measurement of turbulent structure functions. They also open the way for optimisations in the upcoming instrumentation and in observational strategies.

ABSTRACT We investigate how large-scale cosmic filaments impact the quenching of galaxies within one virial radius of 324 simulated clusters from The Three Hundred project. We track cosmic filaments with the versatile, observation-friendly program DisPerSE and identify haloes hosting galaxies with VELOCIRaptor. We find that cluster galaxies close to filaments tend to be more star forming, bluer, and contain more cold gas than their counterparts further away from filaments. This effect is recovered at all stellar masses. This is in stark contrast with galaxies residing outside of clusters, where galaxies close to filaments show clear signs of density related pre-processing. We first show that the density contrast of filaments is reduced inside the intra-cluster medium. Moreover, examination of flows around and into cluster galaxies shows that the gas flows in intra-cluster filaments are colder and tend to stream along with galaxies in their midst, partially shielding them from strangulation by the hot, dense intra-cluster medium. This also preserves accretion on to satellites and limit ram pressure.

Context. X-ray observations of galaxy clusters provide insights into the nature of gaseous turbulent motions, their physical scales, and the fundamental processes to which they are related. Spatially-resolved, high-resolution spectral measurements of X-ray emission lines provide diagnostics on the nature of turbulent motions in emitting atmospheres. Since they are acting on scales comparable to the size of the objects, the uncertainty on these physical parameters is limited by the number of observational measurements, through sample variance. Aims. We propose a different and complementary approach to repeating numerical simulations for the computation of sample variance (i.e. Monte-Carlo sampling) by introducing new analytical developments for lines diagnosis. Methods. We considered the model of a “turbulent gas cloud”, consisting in isotropic and uniform turbulence described by a universal Kolmogorov power-spectrum with random amplitudes and phases in an optically thin medium. Following a simple prescription for the four-term correlation of Fourier coefficients, we derived generic expressions for the sample mean and variance of line centroid shift, line broadening, and projected velocity structure function. We performed a numerical validation based on Monte-Carlo simulations for two popular models of gas emissivity based on the β-model. Results. Generic expressions for the sample variance of line centroid shifts and broadening in arbitrary apertures are derived and match the simulations within their range of applicability. Generic expressions for the mean and variance of the structure function are provided and verified against simulations. An application to the Athena/X-IFU (Advanced Telescope for High-ENergy Astrophysics/X-ray Integral Field Unit) and XRISM/Resolve (X-ray Imaging and Spectroscopy Mission) instruments forecasts the potential of sensitive, spatially-resolved spectroscopy to probe the inertial range of turbulent velocity cascades in a Coma-like galaxy cluster. Conclusions. The formulas provided are of generic relevance and can be implemented in forecasts for upcoming or current X-ray instrumentation and observing programmes.

In this thesis, I study the thermodynamic properties of the intracluster medium out to the virial radius, making use of a unique combination of dedicated XMM-Newton exposures and Planck maps, thus exploiting the capabilities of multi-wavelength observations, to constrain at an unprecedented level the thermodynamic properties in a complete sample of galaxy clusters. I will explore in detail their self-similar properties, their radial dependence, and their implication. This work provides an important legacy value for any future studies of galaxy cluster until the next generation of X-ray telescopes comes along.

Clusters of galaxies are the most massive gravitationally bound systems in the universe. They are permeated by a hot, X-ray emitting, intra-cluster medium (ICM), which represents the dominant baryonic component. The key ICM observable quantities are its density, temperature, and chemical composition (in particular, the so-called metallicity). Measuring the gas density is relatively simple, whereas measuring the temperature and the metallicity of the ICM requires accumulating a spectrum and fitting it with a plasma model. The aim of my thesis is the characterization of the radial properties (especially temperature and metallicity) of the ICM, for a large sample of clusters of galaxies observed with XMM-Newton. Particular attention was paid to investigate and characterize the systematic effects that may affect measurements. I also employed simulations to examine how best to analyze spectra with poor statistical quality and find an unbiased estimator of the temperature (Leccardi & Molendi, 2007). Finally, I reported some preliminary results obtained by investigating thermodynamic and chemical properties of cluster cores for an enlarged sample from z = 0.02 to z = 0.25; these results will be discussed in a forthcoming paper (Leccardi et al., in prep.). The bulk of my thesis is based on two published papers, namely Leccardi & Molendi (2008a) and Leccardi & Molendi (2008b).

2008/2009
The aim of this Thesis was to study the X--ray properties of the IntraCluster Medium (ICM) in a cosmological context resorting to high resolution hydrodynamical simulations. The thermodynamical and chemical properties of the ICM were inspected and studied within a set of galaxy clusters that were simulated with the TREE-SPH Gadget2 code (Springel 2005). This code included a detailed model of chemical evolution (Tornatore et al. 2007) as well as prescriptions for different physical processes: star formation, galactic winds and AGN feedback. We use this large set of simulated galaxy clusters with a twofold aim. First, we study the effect of different sources of feedback on the ICM observable properties, in particular on its metal enrichment and on thermo and chemo--dynamical properties when AGN feedback is at work. Second, we test the robustness of cluster mass proxies against the different physical processes included in the simulations. When exploring the effect on metal enrichment and its evolution we found that among different prescriptions for the stellar Initial Mass Function (IMF), the best results on Iron abundance profiles and global Iron evolution are found when applying the Salpeter IMF (Salpeter 1955). We also found that the positive evolution of the metal abundance in the central regions of simulated clusters can not be simply interpreted as a consequence of an excess of low--redshift star formation. Instead the evolution of the metallicity pattern is driven by the combined action of gas--dynamical processes, which redistribute already enriched gas, and of star formation, which acts both as a source and as a sink of metals (Fabjan et al. 2008, Borgani et al. 2008). Our analysis on the AGN feedback effect on ICM properties lends further support to the idea that a feedback source associated to gas accretion onto super-massive BHs is required by the observational properties of the ICM (e.g. McNamara & Nulsen 2007). However, our results also show that there are still a number of discrepancies between observations and the predictions made by simulations. This is especially true within the core regions of massive clusters, where a more efficient way of extracting and/or thermalising energy released by AGN is required. Our results further demonstrate that different astrophysical feedback sources leave distinct signatures on the pattern of chemical enrichment of the ICM. These differences are much more evident in the outskirts of galaxy clusters, which retain memory of the past efficiency that energy feedback had in displacing enriched gas from star-forming regions and in regulating star formation itself (Fabjan et al. 2010). The characterization of thermal and chemical properties in cluster external regions requires X--ray telescopes with large collecting area and an excellent control of the background, characteristics which should be eventually met by a future generation of X--ray satellites. In the last part of this Thesis we studied the effect that different physical processes included in the simulations have on the mass--observable scaling relations and their evolution with redshift. We focused on two cluster mass proxies, the gas mass M_gas and a new Y_X proxy defined by Kravtsov et al. (2006) as the product of gas mass and cluster temperature and test the robustness of the two relations, M_tot-M_gas and M_tot-Y_X, in simulations before including any observational effect. Furthermore we test the relations against the change of prescription for the physics that describes the ICM, such as viscosity, thermal conduction, star formation, galactic winds and AGN feedback. We found that the evolutions of both relations do not show any significant deviation from the predictions of the simple self--similar model. However we found that the Y_X proxy is less sensitive to the change of physical processes included in simulations. Since Y_X is by definition a measure of the thermal pressure support in the ICM, once the central cluster region is excised, the relation M_tot-Y_X is more stable against the change of physical processes included in the simulations (Fabjan et al., in preparation). In the future, the improved numerical resolution expected to be reached in simulations of the next generation needs to be accompanied by a suitable description of the subresolution physics, both concerning the star formation physics and and the AGN feedback. Within the latter, the inclusion of the jet injection by AGN would of course provide a physically meaningful description of the interplay between BH accretion and ICM properties. While Chandra, XMM and Suzaku will be pushed to their limits in these studies in the next few years, there is no doubt that a detailed knowledge of the ICM out the cluster virial boundaries and reaching very high redshift has to await for the advent of the next generation of X--ray telescopes (Giacconi et al. 2009, Arnaud et al.2009).
XXII Ciclo
1979

La distribution de masse dans l'Univers telle que tracée par les amas de galaxies constitue une sonde cosmologique puissante. La caractérisation des processus associés à l'origine et à la croissance des grandes structures permet de contraindre des paramètres cosmologiques via l'étude de la distribution des amas en fonction de leur masse et de leur redshift. Cependant, il existe un désaccord statistiquement significatif observé entre les contraintes cosmologiques établies par l'étude des anisotropies primaires du fond diffus cosmologique et celles issues de l'analyse de la distribution des amas de galaxies. Cela pourrait signifier que le modèle standard de la cosmologie est incomplet. L'une des méthodes d'observation des amas de galaxie exploite l'effet Sunyaev-Zel'dovich (SZ) qui permet de contraindre la pression du gaz contenu dans ces derniers. Cette observable peut être directement liée à la masse des amas via une relation d'échelle et un profil de pression. Il est donc essentiel de caractériser précisément ces derniers afin de limiter les potentiels biais et effets systématiques affectant les analyses cosmologiques. Cette thèse présente l'ensemble des travaux réalisés dans cet objectif. Elle porte sur des thématiques allant des observations SZ effectuées avec la caméra NIKA2 installée au télescope de 30 mètres de l’IRAM jusqu'à l'estimation des paramètres cosmologiques en passant par l'analyse des données brutes de NIKA2 et des cartes SZ réalisées.Une part du travail de thèse présenté dans ce document est consacrée à l'étude et l’amélioration des différentes étapes effectuées, depuis les observations d'amas de galaxies au télescope avec la caméra NIKA2 jusqu'à la production de cartes de l'effet SZ. Les procédures développées pour estimer les performances instrumentales de NIKA2 sont détaillées et la chaîne d'analyse utilisée pour réduire les données brutes est présentée.Les travaux réalisés dans cette thèse ont également consisté à caractériser les propriétés thermodynamiques d'amas de galaxies via des analyses jointes combinant les cartes SZ NIKA2 avec des données X mesurées par le satellite XMM-Newton. Nous détaillons les méthodes employées dans le logiciel de traitement des données SZ créé pour le grand programme SZ de NIKA2, la procédure de déprojection non-paramétrique développée pour caractériser le profil de pression des amas de galaxies et les résultats de la première observation SZ avec NIKA2.Les dernières activités présentées sont dédiées aux analyses réalisées afin de quantifier l'impact du grand programme SZ de NIKA2 sur la cosmologie. Nous analysons l'effet des perturbations dynamiques du milieu intra-amas sur la caractérisation du profil de pression avec NIKA2 via l'utilisation d'amas de la simulation numérique MUSIC. Finalement, nous détaillons l'étude permettant d'estimer l'impact d'une variation du profil de pression universel sur l'estimation des paramètres cosmologiques déduite du spectre de puissance de l'effet SZ mesuré par Planck
The mass distribution in the Universe, as traced by galaxy clusters is a powerful cosmological probe. The characterization of the processes associated with the origin and the growth of the large scale structures enables constraining cosmological parameters by studying the distribution of clusters according to their mass and redshift. However, a tension is observed between the cosmological constraints established by the study of the primary anisotropies of the cosmological background and those resulting from the analysis of the distribution of galaxy clusters. This may imply that our cosmological model is incomplete. The observation of clusters from the Sunyaev-Zel'dovich (SZ) effect allows us to constrain their gas pressure. This observable can be directly linked to the mass of galaxy clusters via a scaling relation and a pressure profile. It is thus essential to characterize the latter precisely in order to limit the potential bias and systematic effects affecting cosmological analyses. This thesis presents the work carried out to this end. It covers topics ranging from SZ observations made with the NIKA2 camera installed at the IRAM 30-metre telescope to the estimation of cosmological parameters, and including the analysis of NIKA2 raw data and the SZ maps produced.Part of the thesis work presented in this document is dedicated to the study and the improvement of the different tasks carried out, from the observations of galaxy clusters with the NIKA2 camera to the production of maps of the SZ effect. The procedures developed to estimate the NIKA2 instrumental performance are detailed and the analysis pipeline used to analyze the raw data is presented.The work carried out in this thesis also consisted in characterizing the thermodynamic properties of galaxy clusters using joint analyzes that combine the NIKA2 SZ maps with X-ray data measured by the XMM-Newton satellite. We detail the methods used in the SZ data processing software created for the NIKA2 SZ large program, the non-parametric deprojection procedure developed to characterize the pressure profile of galaxy clusters and the results of the first SZ observation with NIKA2.The last activities presented are dedicated to the analyses carried out to quantify the impact of the NIKA2 SZ large program on cosmology. We analyze the effect of dynamic disturbances of the intracluster medium on the characterization of the pressure profile with NIKA2 via the use of clusters from the MUSIC N-body simulation. Finally, we detail the study realized in order to estimate the impact of a modification of the universal pressure profile on the estimation of cosmological parameters derived from the power spectrum of the SZ effect measured by Planck

Les amas de galaxies sont l'une des plus grandes structures dans l'univers et jouent le rôle d'hôte de plusieurs phénomènes complexes. Bien qu'il existe beaucoup d'études portant sur leur formation et leur évolution, l'avènement récent de l'apprentissage automatique en astronomie nous permet d'investiguer des questions qui, jusqu'à maintenant, demeuraient sans réponse. Même si ce mémoire se concentre sur l'application de techniques d'apprentissage automatique aux observations en rayons X des amas de galaxies, nous explorons l'usage de ces techniques à son homologue à une échelle réduite : les galaxies elles-mêmes. Malgré le fait que les trois articles présentés dans ce mémoire se concentrent sur différents aspects de la physique, sur de différentes échelles et sur de différentes techniques, ils forment une base d'études que je continuerai pendant mon doctorat : l'usage des nouvelles techniques pour investiguer la physique des régions galactiques et extragalactiques. Dans le premier article, nous introduisons les premières observations en rayons X d'un amas de galaxies lointain qui détient des attributs particuliers comme une formation stellaire hors pair (∽ 900 M⊙/an). Dans cet article, nous employons les techniques traditionnelles en astronomie rayons X pour déterminer si ce taux de formation stellaire est dû à un courant de refroidissement désinhibé. Puisque l'objet est très lointain (z=1.7), il faut faire nos calculs sans beaucoup de photons et il faut donc utiliser les indices par procuration. Nous déterminons que la galaxie centrale est séparée d'une distance de plus de 50 kpc du coeur froid de l'amas. À cause de cette séparation, le trou noir supermassif central n'est pas alimenté et il ne peut pas prévenir le courant de refroidissement. Ceci est le premier exemple d'un amas de galaxies où nous observons l'échec de la rétroaction d'un trou noir supermassif. De plus, ceci nous fournit un autre mécanisme qui peut créer la lumière intra-amas. Dans le deuxième article présenté ici, nous examinons l'émission rayons X provenant du milieu intra-amas extrêmement chaud des amas de galaxies. Nous développons une méthode compréhensive qui détermine le nombre de composantes thermiques sous-jacentes dans un spectre de plasma. Notre nouvelle technique est basée sur une combinaison d'algorithmes d'apprentissage automatique non supervisé (analyse de composantes principales) et d'apprentissage automatique supervisé (arbre aléatoire). Nous créons un ensemble de 100 000 observations synthétiques et réalistes de Chandra qui représentent le gaz chaud dans les amas de galaxies voisines. Après la réduction de notre ensemble d'entraînement à ses 25 composantes principales, nous entraînons notre classificateur afin qu'il puisse déterminer le nombre de composantes thermiques sous-jacentes. Une fois l'étape d'entraînement terminée et l'optimisation des hyperparamètres terminée, nous appliquons la méthodologie à l'amas de galaxies de Persée. En plus de créer une carte de l'amas qui indique le nombre de composantes thermiques nécessaires afin de modéliser précisément l'émission du gaz chaud, nous avons développé un ensemble d'outils numériques qui calculent les températures associées. Nos résultats sont en accord avec plus d'une décennie d'études sur l'amas de galaxies de Persée et nous indiquent qu'il faut utiliser plusieurs composantes thermiques pour modéliser le milieu intra-amas correctement. Le troisième article présenté dans ce mémoire emploie de nouveau l'apprentissage automatique pour résoudre une question précédemment sans réponse nécessaire pour la caractérisation précise de la cinématique de gaz chaud dans les galaxies. Nous avons construit un réseau de neurones convolutif qui estime la vitesse et l'élargissement des raies d'émission d'un spectre de galaxies en visible. Une fois construit, nous l'appliquons aux données synthétiques qui répliquent les observations réelles de SITELLE du programme SIGNALS. En utilisant notre réseau bien entraîné, nous caractérisons l'émission d'une cible de SIGNALS : la galaxie M33. Nos résultats indiquent que notre algorithme surpasse les méthodes standards et s'adapte bien aux procédures d'ajustement spectral. En outre, notre méthodologie augmente la vitesse des calculs par plus d'un ordre de grandeur. Bien que l'algorithme soit entraîné spécifiquement pour SITELLE, on peut faire de petites modifications pour l'utiliser avec des autres interféromètres tels que MUSE et ses futurs analogues dans la prochaine génération de télescopes. Notez que j'ai mené à titre de premier auteur deux des trois articles présentés dans ce mémoire et apporté des contributions majeures au troisième. Les trois articles ont déjà été acceptés pour publication ou ont déjà été soumis et révisés une fois.
Galaxy clusters are one of the largest structures in the universe and host several complex physical phenomena. Although a wealth of knowledge already exists on their formation and evolution, the recent advent of machine learning in the astronomical sciences has allowed us to probe questions heretofore unanswered. While this thesis does focus heavily on the application of machine learning techniques to X-ray observations of galaxy clusters, it takes the techniques applied there to galaxy cluster's smaller counterparts: the individual galaxies themselves. Although the three papers presented here focus on distinct physics, scales, and techniques, they all form a basis of studies that I will continue during my doctorate: using new techniques to probe the underlying physics of galactic and extragalactic regions. The first paper introduced is a study of a galaxy cluster near the beginning of the epoch of cluster formation exhibiting peculiar attributes such as an elevated stellar formation rate (∽ 900M⊙/yr). In this paper, we employ traditional techniques in X-ray astronomy to determine whether or not the prodigious formation rate is due to an uninhibited cooling core. Since the object is so distant (z=1.7), we must execute our calculations with relatively few photons and thus rely on proxy measures. We determine that there exists a strong cooling flow offset by over 50 kpc from the central galaxy. Because of this offset, the AGN is not fueled and thus fails to heat up the cooling flow. This is the first example of a galaxy cluster in which we observe the failure of AGN feedback. Additionally, this provides another mechanism for the creation of intracluster light. The second article presented here focuses on X-ray emission from the hot intra-cluster medium within the galaxy cluster. We develop a comprehensive method for determining the number of underlying thermal components in the plasma's spectra. Our novel technique relies on a combination of an unsupervised learning algorithm (principal component analysis) and a supervised learning algorithm (random forest classification). We create a set of 100,000 realistic mock Chandra observations of the hot X-ray emitting gas in nearby galaxy clusters. After reducing our synthetic training set to its 25 most important principal components, we trained a random forest classifier to distinguish between the number of underlying thermal components. After successful testing and hyperparameter optimization, we applied the methodology third paper featured in this thesis once again employs machine learning to solve a previously undetermined question necessary for the accurate characterization of the kinematics of the warm gas in galaxies. We constructed a convolutional neural network to estimate the velocity and broadening parameters from the optical spectra of emission-line nebula and applied it to synthetic data replicating real SITELLE observations from the SIGNALS program. With a trained and optimized network in hand, we apply our methodology to a target of the SIGNALS program: the galaxy M33. Our results indicate our algorithm out-performs previous methods and nicely complements spectral fitting procedures. Moreover, the methodology increases calculation speeds by more than an order of magnitude -- thus greatly reducing the time needed to determine the kinematic parameters. Although the algorithm was trained for SITELLE data, this method can be readily ported to other IFUs such as MUSE. I have led two of the papers presented in this memoire and made major contributions to the third. All three papers have been either accepted for publication or have already been submitted and revised once. to the Perseus Cluster. In addition to creating a map of the cluster indicating the number of thermal components required to accurately model the thermal emission, we developed a suite of analysis routines to determine the temperatures of the underlying components. Our results are in agreement with over a decade of studies on the Perseus cluster and indicate that multiple temperature components are required for the accurate study of its intracluster medium.

It has been demonstrated from recent research that nanodiamond(ND)-enabled drug delivery as cancer therapeutics represents an important component of optimized device functionality. The goal of the current research is to develop a multiscale modeling technique to understand the fundamental mechanism of a ND-based cancer therapeutic drug delivery system. The major components of the proposed device include nanodiamonds (ND), parylene buffer layer and doxorubicin (DOX) drugs, where DOX loaded self-assembled nanodiamonds are packed inside parylene capsule. The efficient functioning of the device is characterized by its ability to precisely detect targets (cancer cells) and then to release drugs at a controlled manner. The fundamental science issues concerning the development of the ND-based device includes (a) a precise identification of the equilibrium structure, surface electrostatics and self assembled morphology of nanodiamonds, (b) understanding of the drug/biomarker adsorption and desorption process to and from NDs, (c) rate of drug release through the parylene buffers, and finally, (d) device performance under physiological condition. In this study, we aim to systematically address these issues using a multscale computational framework. Specifically, the structure and electrostatics of the functionalized NDs are predicted by quantum scale calculation (Density Functional Tight Binding). The DFTB) study on smaller NDs suggests a facet dependent charge distributions on ND surfaces. Using the charges for smaller NDs (∼ valid for 1–3.3 nm dia ND), we then determined surface charges for larger (4–10 nm) truncated octahedral nanodiamonds (TOND). We found that the [100] face and the [111] face contain positively and negatively charged atoms, respectively. Employing this surface electrostatics of nanodiamonds, atomistic-scale simulations are performed to simulate the self-assembly process of the NDs and drug molecules in a solution as well as to evaluate nanoscale diffusion coefficient of DOX molecules. In order to quantify the nature of the aggregate morphology, a fractal analysis has been performed. The mass fractal dimensions for a variety of aggregate size have been obtained from molecular simulations assuming ‘diffusion-limited aggregation (DLA)’ process. Then, by considering the experimentally observed aggregate dimensions, by using DLA based fractal analysis and by utilizing Lagvankar-Gemmell Model for aggregate density, a continuum model for larger aggregates will be developed to characterize aggregate strengths and break-up mechanism, which in turn will help us to understand how aggregate size can be reduced. In this talk, an outline for this continuum model will be discussed. In addition, we have been performing molecular simulations on DOX-ND where multiple drug molecules are allowed to interact with a cluster of self-assembled nanodiamonds in pH controlled solution. The purpose of this study is to find the effect of solution pH on the loading and release of drug to and from nanodiamonds. Our initial results show that a higher pH is necessary to ensure drug release from nanodiamonds. Once we completely understand the essential physics of pH controlled drug loading and release, we plan to develop multiscale models of tumor nodules to represent them as a collection of individual tumor cells. Each cell will be then modeled as a deformable body comprised of three homogenous materials: cortex membrane, cytosol and nucleus. The cortex membrane and the cytosol will serve as a weak permeable medium where the absorption coefficients of the doxorubicin remain constant and obey Fick’s law. In this study, it will be assumed that drug release from the microdevice to its outer periphery will be governed by Fickian Diffusion. It will also be assumed that the complex flow of drug through the interstitial fluid of the body will be dictated by Darcy’s law. It will be assumed that the solute drug transport in these regions will be due to a combination of convection, diffusion, elimination in the intra- and extra-cellular space, receptive cell internalization and degradation. Results from this study will provide fundamental insight on the definitive targeting of infected cells and high resolution controlling of drug molecules.