Our discovery that the introduction of living cells (Saccharomyces cerevisiae) alters dramatically the evaporation driven self-assembly of lipid-silica nanostructures suggested the formation of novel bio/nano interfaces useful for cellular interrogation at the nanoscale. This one year ''out of the box'' LDRD focused on the localization of metallic and semi-conducting nanocrystals at the fluid, lipid-rich interface between S. cerevisiae and the surrounding phospholipid-templated silica nanostructure with the primary goal of creating Surface Enhanced Raman Spectroscopy (SERS)-active nanostructures and platforms for cellular integration into electrode arrays. Such structures are of interest for probing cellular responses to the onset of disease, understanding of cell-cell communication, and the development of cell-based bio-sensors. As SERS is known to be sensitive to the size and shape of metallic (principally gold and silver) nanocrystals, various sizes and shapes of nanocrystals were synthesized, functionalized and localized at the cellular surface by our ''cell-directed assembly'' approach. Laser scanning confocal microscopy, SEM, and in situ grazing incidence small angle x-ray scattering (GISAXS) experiments were performed to study metallic nanocrystal localization. Preliminary Raman spectroscopy studies were conducted to test for SERS activity. Interferometric lithography was used to construct high aspect ratio cylindrical holes on patterned gold substrates and electro-deposition experiments were performed in a preliminary attempt to create electrode arrays. A new printing procedure was also developed for cellular integration into nanostructured platforms that avoids solvent exposure and may mitigate osmotic stress. Using a different approach, substrates comprised of self-assembled nanoparticles in a phospholipid templated silica film were also developed. When printed on top of these substrates, the cells integrate themselves into the mesoporous silica film and direct organization of the nanoparticles to the cell surface for integration into the cell.
This report details results from our last year of work (FY2005) on friction in MEMS as funded by the Campaign 6 program for the Microscale Friction project. We have applied different monolayers to a sensitive MEMS friction tester called the nanotractor. The nanotractor is also a useful actuator that can travel {+-}100 {micro}m in 40 nm steps, and is being considered for several MEMS applications. With this tester, we can find static and dynamic coefficients of friction. We can also quantify deviations from Amontons' and Coulomb's friction laws. Because of the huge surface-to-volume ratio at the microscale, surface properties such as adhesion and friction can dominate device performance, and therefore such deviations are important to quantify and understand. We find that static and dynamic friction depend on the monolayer lubricant applied. The friction data can be modeled with a non-zero adhesion force, which represents a deviation from Amontons' Law. Further, we show preliminary data indicating that the adhesion force depends not only on the monolayer, but also on the normal load applied. Finally, we also observe slip deflections before the transition from static to dynamic friction, and find that they depend on the monolayer.
Block-structured adaptively refined meshes (SAMR) strive for efficient resolution of partial differential equations (PDEs) solved on large computational domains by clustering mesh points only where required by large gradients. Previous work has indicated that fourth-order convergence can be achieved on such meshes by using a suitable combination of high-order discretizations, interpolations, and filters and can deliver significant computational savings over conventional second-order methods at engineering error tolerances. In this paper, we explore the interactions between the errors introduced by discretizations, interpolations and filters. We develop general expressions for high-order discretizations, interpolations, and filters, in multiple dimensions, using a Fourier approach, facilitating the high-order SAMR implementation. We derive a formulation for the necessary interpolation order for given discretization and derivative orders. We also illustrate this order relationship empirically using one and two-dimensional model problems on refined meshes. We study the observed increase in accuracy with increasing interpolation order. We also examine the empirically observed order of convergence, as the effective resolution of the mesh is increased by successively adding levels of refinement, with different orders of discretization, interpolation, or filtering.
The goal of this project was to examine the protein-protein docking problem, especially as it relates to homology-based structures, identify the key bottlenecks in current software tools, and evaluate and prototype new algorithms that may be developed to improve these bottlenecks. This report describes the current challenges in the protein-protein docking problem: correctly predicting the binding site for the protein-protein interaction and correctly placing the sidechains. Two different and complementary approaches are taken that can help with the protein-protein docking problem. The first approach is to predict interaction sites prior to docking, and uses bioinformatics studies of protein-protein interactions to predict theses interaction site. The second approach is to improve validation of predicted complexes after docking, and uses an improved scoring function for evaluating proposed docked poses, incorporating a solvation term. This scoring function demonstrates significant improvement over current state-of-the art functions. Initial studies on both these approaches are promising, and argue for full development of these algorithms.
Carbon nanotubes (CNT) are unique nanoscale building blocks for a variety of materials and applications, from nanocomposites, sensors and molecular electronics to drug and vaccine delivery. An important step towards realizing these applications is the ability to controllably self-assemble the nanotubes into larger structures. Recently, amphiphilic peptide helices have been shown to bind to carbon nanotubes and thus solubilize them in water. Furthermore, the peptides then facilitate the assembly of the peptide-wrapped nanotubes into supramolecular, well-aligned fibers. We investigate the role that molecular modeling can play in elucidating the interactions between the peptides and the carbon nanotubes in aqueous solution. Using ab initio methods, we have studied the interactions between water and CNTs. Classical simulations can be used on larger length scales. However, it is difficult to sample in atomistic detail large biomolecules such as the amphiphilic peptide of interest here. Thus, we have explored both new sampling methods using configurational-bias Monte Carlo simulations, and also coarse-grained models for peptides described in the literature. An improved capability to model these inorganichiopolymer interfaces could be used to generate improved understanding of peptide-nanotube self-assembly, eventually leading to the engineering of new peptides for specific self-assembly goals.
We present new methods for resolving IFSAR ambiguities and SAR layover. The analytic properties of these techniques make them well suited for reliable, efficient computation.
We investigate the utility of dual-pump coherent anti-Stokes Raman scattering (CARS) for investigations of fuel-rich flames with soot volume loadings up to 2.2 ppm. Our initial characterization of a gas-phase propellant simulating burner is presented. The burner investigated consists of alternating fuel and oxidizer tubes with the option for injection of aluminum particles into the flame. We focus on a C2H2-N2-O2 flame, in which no aluminum particles are yet added. For the required flow rates, this burner provides an array of heavily sooting and highly luminous diffusion flames whose temperature is measured by dual-pump CARS. The nature of the observed soot-induced interference in the CARS spectra for several different pump 2 frequencies is documented and CARS temperatures obtained from data in a spectrally "quiet" region, with the CARS signal beam near 483 nm, are presented. Soot volume fractions are imaged by absorption-calibrated laser-induced incandescence (LII) to quantify the soot loadings at which our dual-pump CARS facility provides reliable measurements.
Chemical/Biological/Radiological (CBR) contamination events pose a considerable threat to our nation's infrastructure, especially in large internal facilities, external flows, and water distribution systems. Because physical security can only be enforced to a limited degree, deployment of early warning systems is being considered. However to achieve reliable and efficient functionality, several complex questions must be answered: (1) where should sensors be placed, (2) how can sparse sensor information be efficiently used to determine the location of the original intrusion, (3) what are the model and data uncertainties, (4) how should these uncertainties be handled, and (5) how can our algorithms and forward simulations be sufficiently improved to achieve real time performance? This report presents the results of a three year algorithmic and application development to support the identification, mitigation, and risk assessment of CBR contamination events. The main thrust of this investigation was to develop (1) computationally efficient algorithms for strategically placing sensors, (2) identification process of contamination events by using sparse observations, (3) characterization of uncertainty through developing accurate demands forecasts and through investigating uncertain simulation model parameters, (4) risk assessment capabilities, and (5) reduced order modeling methods. The development effort was focused on water distribution systems, large internal facilities, and outdoor areas.
This report describes a project to develop technology to integrate passively pulsating, cavitating nozzles within Polycrystalline Diamond Compact (PDC) bits for use with conventional rig pressures to improve the rock-cutting process in geothermal formations. The hydraulic horsepower on a conventional drill rig is significantly greater than that delivered to the rock through bit rotation. This project seeks to leverage this hydraulic resource to extend PDC bits to geothermal drilling.