Multiscaling Strategy Research Articles

Characterizing Structural Complexity in Disordered Carbons: From the Slit Pore to Atomistic Models.

The reliable characterization of nanoporous carbons is critical to the design and optimization of their numerous applications; however, the vast majority of carbons in industrial use are highly disordered, with complex structures whose understanding has long challenged researchers. The idealized slit pore model represents the most commonly used approximation to a carbon nanopore; nevertheless, it has been only partially successful in predicting adsorption isotherms and fails significantly in predicting transport properties because of its inability to capture structural disorder and its effect on fluid accessibility. Atomistic modeling of the structure has much potential for overcoming this limitation, and among such approaches, hybrid reverse Monte Carlo simulation has emerged as the most attractive. This method reconstructs the structure of a carbon based on the fitting of its experimentally measured pair distribution function and appropriate properties such as porosity while minimizing the energy. The method is shown to be best implemented using a multistage strategy, with the first stage used to attain a deep minimum of the energy and subsequent stages to refine the structure based on the fitting of specific properties. Methods to determine the accessibility of gases based on the atomistic structure are outlined, and it is shown that energy barriers are very sensitive to small differences in the sizes of constrictions and pore entries. The ability to accurately predict macroscopic transport coefficients of adsorbates in nanoporous carbons appears to be the greatest limitation of such models. Overcoming this will require the fitting of properties more sensitive to long-range disorder than the currently used pair distribution and the use of a suitable multiscaling strategy, which is suggested as a future direction for advancing atomistic models. The inclusion of heteroatoms in the structure is also an important area requiring further attention, particularly in the development of computationally efficient force fields incorporating their interactions.

Multi-resolution subspace-based optimization method for solving three-dimensional inverse scattering problems.

An innovative methodology is proposed to solve quantitative three-dimensional microwave imaging problems formulated within the contrast source framework. The introduced technique is based on the combination of an efficient iterative multiscaling strategy aimed at mitigating local minimum issue arising in inverse scattering problems, and a local search algorithm based on the subspace-based optimization method (SOM) devoted to effectively retrieving both the "deterministic" and the "ambiguous" parts of the unknown contrast currents. To achieve this goal, a nested iteration process is adopted in which the outer loop iteratively refines the region of interest (ROI) where the scatterers are detected, while the inner loop retrieves the dielectric properties of the scatterers within the ROIs. Selected numerical examples are also given to show the validity and robustness of the proposed algorithm in comparison with state-of-the-art techniques.

A Nested Multi-Scaling Inexact-Newton Iterative Approach for Microwave Imaging

A microwave imaging technique based on the integration of the Inexact-Newton method within a multi-scaling strategy is proposed in the framework of the contrast field formulation of the electromagnetic inverse scattering. The inversion problem is solved by means of a nested procedure that considers three different logical levels: (a) an outer multi-focusing loop aimed at implementing a synthetic zoom for focusing the scatterer support within the investigation domain; (b) a local linearization of the original full-nonlinear inverse scattering function; and (c) a truncated Landweber inner loop devoted to regularize the arising ill-posed linear problem. Thanks to the features of the integrated approach, a reliable inversion technique able to suitably face the non-linearity and the ill-posedness/ill-conditioning issues of the imaging problem is designed. A numerical validation dealing with different objects, measurement setups, and noise conditions is carried out to assess the features and the potentialities as well as the limitations of the proposed strategy. Comparisons with bare approaches and other multi-resolution formulations are presented, as well.

Electromagnetic inversion with the multiscaling inexact Newton method—experimental validation

AbstractThe integration of the inexact Newton method within a multiscaling strategy is assessed in the framework of the contrast‐field formulation of the electromagnetic inverse scattering. By using the features of the integrated approach, the technique is expected to suitably face the nonlinearity and the illposedness/ill‐conditioning issues of the imaging problem. A numerical validation dealing with experimental data related to different objects is carried out to provide evidence of the method premises pointing out features and potentialities as well as current limitations. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2834–2838, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26435

Physics-based de novo prediction of RNA 3D structures.

Current experiments on structural determination cannot keep up the pace with the steadily emerging RNA sequences and new functions. This underscores the request for an accurate model for RNA three-dimensional (3D) structural prediction. Although considerable progress has been made in mechanistic studies, accurate prediction for RNA tertiary folding from sequence remains an unsolved problem. The first and most important requirement for the prediction of RNA structure from physical principles is an accurate free energy model. A recently developed three-vector virtual bond-based RNA folding model ("Vfold") has allowed us to compute the chain entropy and predict folding free energies and structures for RNA secondary structures and simple pseudoknots. Here we develop a free energy-based method to predict larger more complex RNA tertiary folds. The approach is based on a multiscaling strategy: from the nucleotide sequence, we predict the two-dimensional (2D) structures (defined by the base pairs and tertiary contacts); based on the 2D structure, we construct a 3D scaffold; with the 3D scaffold as the initial state, we combine AMBER energy minimization and PDB-based fragment search to predict the all-atom structure. A key advantage of the approach is the statistical mechanical calculation for the conformational entropy of RNA structures, including those with cross-linked loops. Benchmark tests show that the model leads to significant improvements in RNA 3D structure prediction.

MULTI-RESOLUTION RETRIEVAL OF NON-MEASURABLE EQUIVALENT CURRENTS IN MICROWAVE IMAGING PROBLEMS-EXPERIMENTAL ASSESSMENT

In this paper, an approach based on a multi-scaling strategy for the reconstruction of the non-measurable components of equivalent current distributions is tested against experimental data. An extensive set of simulations is carried out considering single and multiple scatterers with homogeneous as well as inhomogeneous properties. Selected results are reported and discussed to show potentialities and limitations of the method. (c) The Electromagnetics Academy. The final version of this article is available at the url of the journal “PIER” (Progress In Electromagnetics Research) http://www.jpier.org/PIER/pier.php?paper=09072004

An integrated multiscaling strategy based on a particle swarm algorithm for inverse scattering problems

The application of a multiscale strategy integrated with a stochastic technique to the solution of nonlinear inverse scattering problems is presented. The approach allows the explicit and effective handling of many difficulties associated with such problems ranging from ill-conditioning to nonlinearity and false solutions drawback. The choice of a finite dimensional representation for the unknowns, due to the upper bound to the essential dimension of the data, is iteratively accomplished by means of an adaptive multiresolution model, which offers a considerable flexibility for the use of the information on the scattering domain acquired during the iterative steps of the multiscaling process. Even though a suitable representation of the unknowns could limit the local minima problem, the multiresolution strategy is integrated with a customized stochastic optimizer based on the behavior of a particle swarm, which prevents the solution from being trapped into false solutions without a large increasing of the overall computational burden. Selected examples concerned with a two-dimensional microwave imaging problem are presented for illustrating the key features of the integrated stochastic multiscaling strategy.

Full-Vectorial Three-Dimensional Microwave Imaging Through the Iterative Multiscaling Strategy—A Preliminary Assessment

In this letter, a multiscaling strategy for full-vectorial three-dimensional inverse scattering problems is presented. The approach is fully iterative, and it avoids solving any forward problem at each step. Thanks to the adaptive multiresolution model, which offers considerable flexibility for the inclusion of the a priori knowledge and of the knowledge acquired during the iterative steps of the multiscaling process, the overall computational burden as well as the dimension of the search-space is considerably reduced. This allows to balance effectively the tradeoff between computational costs and achievable resolution accuracy. The effectiveness of the proposed approach is demonstrated through a selected set of preliminary experiments using homogeneous dielectric scatterers in a noisy synthetic environment.