Lee, J F | Search NASA

DOE OSTI2011

Modifications of local structures of Gd{sub 2}O{sub 3} on incorporation of SiO{sub 2}

In the present work we have reported the results of investigations on local structures of e-beam evaporated (Gd{sub 2}O{sub 3}-SiO{sub 2}) composite thin films by synchrotron based EXAFS measurements. The evolution of local structure in the case of the Gd{sub 2}O{sub 3}-SiO{sub 2} system is found to be different from the HfO{sub 2}-SiO{sub 2} system reported by us earlier. The EXAFS analysis has shown that the Gd-O bond length decreases monotonically as SiO{sub 2} content in the films increases. Also the amplitudes of the peaks in the FT-EXAFS spectra of the samples, which depend jointly on the coordination numbers as well as the Debye-Waller factors (measure of disorder) are found to decrease monotonically with increase in SiO{sub 2} contents in the Gd{sub 2}O{sub 3} matrix. Atomic force microscopy (AFM) measurements of the samples also show continuous evolution of amorphous-like denser microstructure with increase in SiO{sub 2} content in the films. Hence incorporation of SiO{sub 2} in the Gd{sub 2}O{sub 3} matrix, results in a continuous change in oxygen coordination yielding a change in the Gd-O bond length and also results in a continuous increase in amorphousness and a smoother morphology of the samples and, unlike the HfO{sub 2}-SiO{sub 2} system, does not show any maximum for a particular SiO{sub 2} concentration.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Automatic Black-Box Model Order Reduction using Radial Basis Functions

Finite elements methods have long made use of model order reduction (MOR), particularly in the context of fast freqeucny sweeps. In this paper, we discuss a black-box MOR technique, applicable to a many solution methods and not restricted only to spectral responses. We also discuss automated methods for generating a reduced order model that meets a given error tolerance. Numerical examples demonstrate the effectiveness and wide applicability of the method. With the advent of improved computing hardware and numerous fast solution techniques, the field of computational electromagnetics are progressed rapidly in terms of the size and complexity of problems that can be solved. Numerous applications, however, require the solution of a problem for many different configurations, including optimization, parameter exploration, and uncertainly quantification, where the parameters that may be changed include frequency, material properties, geometric dimensions, etc. In such cases, thousands of solutions may be needed, so solve times of even a few minutes can be burdensome. Model order reduction (MOR) may alleviate this difficulty by creating a small model that can be evaluated quickly. Many MOR techniques have been applied to electromagnetic problems over the past few decades, particularly in the context of fast frequency sweeps. Recent works have extended these methods to allow more than one parameter and to allow the parameters to represent material and geometric properties. There are still limitations with these methods, however. First, they almost always assume that the finite element method is used to solve the problem, so that the system matrix is a known function of the parameters. Second, although some authors have presented adaptive methods (e.g., [2]), the order of the model is often determined before the MOR process begins, with little insight about what order is actually needed to reach the desired accuracy. Finally, it not clear how to efficiently extend most methods to the multiparameter case. This paper address the above shortcomings be developing a method that uses a block-box approach to the solution method, is adaptive, and is easily extensible to many parameters.

42 ENGINEERING↗