Projective multiscale time-integration for electrostatic particle-in-cell methods

The simulation of problems in kinetic plasma physics is often challenging due to strongly coupled phenomena across multiple scales. In this work, we propose a wavelet-based coarse-grained numerical scheme, based on the framework of Equation-Free Projective Integration, for a kinetic plasma system modeled by the Vlasov–Poisson equations. A kinetic particle-in-cell (PIC) code is used to simulate the meso scale dynamics for short time intervals. This allows the extrapolation over long time-steps of the behavior of a coarse wavelet-based discretization of the system. To validate the approach and the underlying concepts, we perform two 1D1V numerical experiments: nonlinear propagation and steepening of an ion wave, and the expansion of a plasma slab in vacuum. The direct comparisons to resolved PIC simulations show good agreement. We show that the speedup of the projective integration scheme over the full particle scheme scales linearly with the system size, demonstrating efficiency while taking into account fully kinetic, non-Maxwellian effects. This suggests that the approach is potentially interesting for kinetic plasma problems with a large separation of scales

Asymptotic-Preserving methods and multiscale models for plasma physics

The purpose of the present paper is to provide an overview of As ymptotic- Preserving methods for multiscale plasma simulations by ad dressing three sin- gular perturbation problems. First, the quasi-neutral lim it of fluid and kinetic models is investigated in the framework of non magnetized as well as magne- tized plasmas. Second, the drift limit for fluid description s of thermal plasmas under large magnetic fields is addressed. Finally efficient nu merical resolutions of anisotropic elliptic or diffusion equations arising in ma gnetized plasma simu- lation are reviewed

Data-driven modelling of biological multi-scale processes

Biological processes involve a variety of spatial and temporal scales. A holistic understanding of many biological processes therefore requires multi-scale models which capture the relevant properties on all these scales. In this manuscript we review mathematical modelling approaches used to describe the individual spatial scales and how they are integrated into holistic models. We discuss the relation between spatial and temporal scales and the implication of that on multi-scale modelling. Based upon this overview over state-of-the-art modelling approaches, we formulate key challenges in mathematical and computational modelling of biological multi-scale and multi-physics processes. In particular, we considered the availability of analysis tools for multi-scale models and model-based multi-scale data integration. We provide a compact review of methods for model-based data integration and model-based hypothesis testing. Furthermore, novel approaches and recent trends are discussed, including computation time reduction using reduced order and surrogate models, which contribute to the solution of inference problems. We conclude the manuscript by providing a few ideas for the development of tailored multi-scale inference methods.Comment: This manuscript will appear in the Journal of Coupled Systems and Multiscale Dynamics (American Scientific Publishers

Large scale GW calculations

We present GW calculations of molecules, ordered and disordered solids and interfaces, which employ an efficient contour deformation technique for frequency integration, and do not require the explicit evaluation of virtual electronic states, nor the inversion of dielectric matrices. We also present a parallel implementation of the algorithm which takes advantage of separable expressions of both the single particle Green's function and the screened Coulomb interaction. The method can be used starting from density functional theory calculations performed with semi-local or hybrid functionals. We applied the newly developed technique to GW calculations of systems of unprecedented size, including water/semiconductor interfaces with thousands of electrons

Robust trajectory tracking and visual servoing schemes for MEMS manipulation.

International audienceThis paper focuses on the automation of manipulation and assembly of microcomponents using visual feedback controls. Trajectory planning and tracking methods are proposed in order to avoid occlusions during microparts manipulation and to increase the success rate of pick-and-place manipulation cycles. The methods proposed are validated using a five degree-of-freedom (DOF) microrobotic cell including a 3 DOF mobile platform, a 2 DOF micromanipulator, a gripping system and a top-view imaging system. Promising results on accuracy and repeatability of microballs manipulation tasks are obtained and presented

Transport modeling of simple fluids and nano-colloids : thermal conduction mechanisms and coarse projection

Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006.Includes bibliographical references (p. 159-166).In the first part of this thesis, the modes of microscopic energy fluctuations governing heat flow in nano-colloids are quantitatively assessed by combining linear response theory with molecular dynamics (MD) simulations. The intrinsic thermal conductivity is decomposed into self and cross correlations of the three modes that make up the microscopic heat flux vector, namely, the kinetic, the potential and the virial. By this decomposition analysis, the interplay between the molecular mechanisms that govern the variation of the thermal conductivity with volume fraction and solid-fluid interaction is examined. For a specific system of nanosized platinum clusters which interact strongly with host liquid xenon, a significant thermal conductivity enhancement is obtained as a result of self correlation in the potential energy flux. The effect saturates at higher volume fractions due to the cross-mode correlation between the potential and the virial flux. A strong solid-fluid coupling also introduces an amorphous-like structural transition and a pronounced cage effect that significantly reduces the self diffusion of the nano-clusters. These attendant structural and diffusive effects, unlike the self correlation of the potential flux, are amenable to experimental observations. The cluster-fluid interface is characterized by large fluctuations in the potential energy which is indicative of an unusual exchange of potential energy among the interfacial fluid atoms. For small nano-clusters, the interfacial layers interact with each other to form a percolating network. The research findings highlight the importance of surface interactions and show that the interfacial thermal resistance emanating from the self correlation of the collision flux is not the limiting mechanism for heat transfer in nano-colloids.(cont.) This thesis also addresses several theoretical concerns regarding the microscopic thermal transport in colloids by using non-equilibrium molecular dynamics simulations (NEMD). The time averaged microscopic heat flux which assumes spatial homogeneity is shown to be applicable to nano-colloidal systems. Further, it is demonstrated that the thermal conductivity from a NEMD simulation is statistically equivalent to that of an equilibrium linear response evaluation only under certain dynamic conditions at the cluster-fluid interface. The concept of interfacial dynamical similarity is developed to establish this equivalence. The proposed thermal conduction model is consistent with several experimental observations such as the anomalous enhancement at small volume fractions with very small nanoparticles (3-10nm), limiting behavior at higher volume fractions, and the lack of correlation of the enhancement to the intrinsic thermal conductivity of the nano-clusters. The model also suggests possible avenues for optimizing the colloids by developing nano-clusters that have functionalized surface layers to maximize the interactions with the fluid atoms. In the second part of this thesis, smooth field estimators based on statistical inference and smoothing kernels are developed to transfer molecular data to the continuum for hybrid and equation-free multiscale simulations. The field estimators are then employed to implement coarse projection, a multiscale integration scheme, for a shear driven flow in an enclosure. This thesis shows that the spatial continuity and smoothness of the microscopically generated coarse variables, geometrically similar initial conditions and the separation of timescales are essential for the correct coarse field evolution with coarse projection.by Jacob Eapen.Sc.D

Molecular Simulations of Adsorption and Diffusion in Metal-Organic Frameworks (MOFs)

Metal-organic frameworks (MOFs) are a new class of nanoporous materials that have received great interest since they were first synthesized in the late 1990s. Practical applications of MOFs are continuously being discovered as a better understanding of the properties of materials adsorbed within the nanopores of MOFs emerges. One such potential application is as a component of an explosive-sensing system. Another potential application is for hydrogen storage. This work is focused on tailoring MOFs to adsorb/desorb the explosive, RDX. Classical grand canonical Monte Carlo (GCMC) and molecular dynamic (MD) simulations have been performed to calculate adsorption isotherms and self-diffusivities of RDX in several IRMOFs. Because gathering experimental data on explosive compounds is dangerous, data is limited. Simulation can in part fill the gap of missing information. Through these simulations, many of the key issues associated with MOFs preconcentrating RDX have been resolved. The issues include both theoretical issues associated with the computational generation of properties and practical issues associated with the use of MOFs in explosive-sensing system. Theoretically, we evaluate the method for generating partial charges for MOFs and the impact of this choice on the adsorption isotherm and diffusivity. Practically, we show that the tailoring of an MOF with a polar group like an amine can lead to an adsorbent that (i) concentrates RDX from the bulk by as much as a factor of 3000, (ii) is highly selective for RDX, and (iii) retains sufficient RDX mobility allowing for rapid, real time sensing. Many of the impediments to the effective explosive detection can be framed as shortcomings in the understanding of molecule surface interactions. A fundamental, molecular-level understanding of the interaction between explosives and functionalized MOFs would provide the necessary guidance that allows the next generation of sensors to be developed. This is one of the main driving forces behind this dissertation. Another important achievement in this work is the demonstration of a new direction for tailoring MOFs. A new class of tailored MOFs containing porphyrins has been proposed. These tailored MOFs show greater capability for hydrogen storage, which also demonstrated the great functionalization of MOFs and great potential to serve as preconcentrators. The use of a novel multiscale modeling technique to develop equations of state for inhomogeneous fluids is included as a supplement to this dissertation

Advances in Focused Ion Beam Tomography for Three-Dimensional Characterization in Materials Science

Over the years, FIB-SEM tomography has become an extremely important technique for the three-dimensional reconstruction of microscopic structures with nanometric resolution. This paper describes in detail the steps required to perform this analysis, from the experimental setup to the data analysis and final reconstruction. To demonstrate the versatility of the technique, a comprehensive list of applications is also summarized, ranging from batteries to shale rocks and even some types of soft materials. Moreover, the continuous technological development, such as the introduction of the latest models of plasma and cryo-FIB, can open the way towards the analysis with this technique of a large class of soft materials, while the introduction of new machine learning and deep learning systems will not only improve the resolution and the quality of the final data, but also expand the degree of automation and efficiency in the dataset handling. These future developments, combined with a technique that is already reliable and widely used in various fields of research, are certain to become a routine tool in electron microscopy and material characterization

On the nature, formation and diversity of particulate coherent structures in microgravity conditions and their relevance to materials science and problems of astrophysical interest

Different phenomena related to the spontaneous accumulation of solid particles dispersed in a fluid medium in microgravity conditions are discussed, with an emphasis on recent discoveries and potential links with the general field of astrophysical fluid-dynamics on the one hand, and with terrestrial applications in the field of materials science on the other hand. With special attention to the typical physical forces at play in such an environment, namely, surface-tension gradients, oscillatory residual gravity components, inertial disturbances and forces of an electrostatic nature, specific experimental and numerical examples are presented to provide inputs for an increased understanding of the underlying cause-and-effect relationships. Studying these systems can be seen as a matter of understanding how macroscopic scenarios arise from the cooperative behaviour of sub-parts or competing mechanisms (nonlinearities and interdependencies on various spatial and temporal scales). Through a critical assessment of the properties displayed by the resulting structures (which appear in the form of one-dimensional circuits formed by aligned particles, planar accumulation surfaces, three-dimensional compact structures resembling “quadrics”, micro-crystallites or fractal aggregates), we discuss a possible classification of the related particle attractors in the space of parameters according to the prevailing effect