Publications

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A few of the many applications for nanowires are high-aspect ratio conductive atomic force microscope (AFM) cantilever tips, force and mass sensors, and high-frequency resonators. Reliable estimates for the elastic modulus of nanowires and the quality factor of their oscillations are of interest to help enable these applications. Furthermore, a real-time, non-destructive technique to measure the vibrational spectra of nanowires will help enable sensor applications based on nanowires and the use of nanowires as AFM cantilevers (rather than as tips for AFM cantilevers). Laser Doppler vibrometry is used to measure the vibration spectra of individual cantilevered nanowires, specifically multiwalled carbon nanotubes (MWNTs) and silver gallium nanoneedles. Since the entire vibration spectrum is measured with high frequency resolution (100 Hz for a 10 MHz frequency scan), the resonant frequencies and quality factors of the nanowires are accurately determined. Using Euler-Bernoulli beam theory, the elastic modulus and spring constant can be calculated from the resonance frequencies of the oscillation spectrum and the dimensions of the nanowires, which are obtained from parallel SEM studies. Because the diameters of the nanowires studied are smaller than the wavelength of the vibrometer's laser, Mie scattering is used to estimate the lower diameter limit for nanowires whose vibration can be measured in this way. The techniques developed in this thesis can be used to measure the vibrational spectra of any suspended nanowire with high frequency resolution Two different nanowires were measured - MWNTs and Ag{sub 2}Ga nanoneedles. Measurements of the thermal vibration spectra of MWNTs under ambient conditions showed that the elastic modulus, E, of plasma-enhanced chemical vapor deposition (PECVD) MWNTs is 37 {+-} 26 GPa, well within the range of E previously reported for CVD-grown MWNTs. Since the Ag{sub 2}Ga nanoneedles have a greater optical scattering efficiency than MWNTs, their vibration spectra was more extensively studied. The thermal vibration spectra of Ag{sub 2}Ga nanoneedles was measured under both ambient and low-vacuum conditions. The operational deflection shapes of the vibrating Ag{sub 2}Ga nanoneedles was also measured, allowing confirmation of the eigenmodes of vibration. The modulus of the crystalline nanoneedles was 84.3 {+-} 1.0 GPa. Gas damping is the dominate mechanism of energy loss for nanowires oscillating under ambient conditions. The measured quality factors, Q, of oscillation are in line with theoretical predictions of air damping in the free molecular gas damping regime. In the free molecular regime, Q{sub gas} is linearly proportional to the density and diameter of the nanowire and inversely proportional to the air pressure. Since the density of the Ag{sub 2}Ga nanoneedles is three times that of the MWNTs, the Ag{sub 2}Ga nanoneedles have greater Q at atmospheric pressures. Our initial measurements of Q for Ag{sub 2}Ga nanoneedles in low-vacuum (10 Torr) suggest that the intrinsic Q of these nanoneedles may be on the order of 1000. The epitaxial carbon that grows after heating (000{bar 1}) silicon carbide (SiC) to high temperatures (1450-1600) in vacuum was also studied. At these high temperatures, the surface Si atoms sublime and the remaining C atoms reconstruct to form graphene. X-ray photoelectron spectroscopy (XPS) and scanning tunneling microscopy (STM) were used to characterize the quality of the few-layer graphene (FLG) surface. The XPS studies were useful in confirming the graphitic composition and measuring the thickness of the FLG samples. STM studies revealed a wide variety of nanometer-scale features that include sharp carbon-rich ridges, moire superlattices, one-dimensional line defects, and grain boundaries. By imaging these features with atomic scale resolution, considerable insight into the growth mechanisms of FLG on the carbon-face of SiC is obtained.

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We describe the implementation of a prototype fully implicit method for solving three-dimensional quasi-steady state magnetic advection-diffusion problems. This method allows us to solve the magnetic advection diffusion equations in an Eulerian frame with a fixed, user-prescribed velocity field. We have verified the correctness of method and implementation on two standard verification problems, the Solberg-White magnetic shear problem and the Perry-Jones-White rotating cylinder problem.

Mainstream cryptographic hashing algorithms are not parallelizable. This limits their speed and they are not able to take advantage of the current trend of being run on multi-core platforms. Being limited in speed limits their usefulness as an authentication mechanism in secure communications. Sandia researchers have created a new cryptographic hashing algorithm, SANDstorm, which was specifically designed to take advantage of multi-core processing and be parallelizable on a wide range of platforms. This report describes a late-start LDRD effort to verify the parallelizability claims of the SANDstorm designers. We have shown, with operating code and bench testing, that the SANDstorm algorithm may be trivially parallelized on a wide range of hardware platforms. Implementations using OpenMP demonstrates a linear speedup with multiple cores. We have also shown significant performance gains with optimized C code and the use of assembly instructions to exploit particular platform capabilities.

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This report summarizes results from a 3-year Laboratory Directed Research and Development project performed in collaboration with researchers at Rensselaer Polytechnic Institute. Our collaborative effort was supported by Sandia's National Institute for Nanoengineering and focused on the study and application of nanoscience and nanoengineering concepts to improve the efficiency of semiconductor light-emitting diodes for solid-state lighting applications. The project explored LED efficiency advances with two primary thrusts: (1) the study of nanoscale InGaN materials properties, particularly nanoscale crystalline defects, and their impact on internal quantum efficiency, and (2) nanoscale engineering of dielectric and metal materials and integration with LED heterostructures for enhanced light extraction efficiency.

Present-day pulsed-power systems operating in the terawatt regime typically use post-hole convolute current adders to operate at sufficiently low impedance. These adders necessarily involve magnetic nulls that connect the positive and negative electrodes. The resultant loss of magnetic insulation results in electron losses in the vicinity of the nulls that can severely limit the efficiency of the delivery of the system's energy to a load. In this report, we describe an alternate transformer-based approach to obtaining low impedance. The transformer consists of coils whose windings are in parallel rather than in series, and does not suffer from the presence of magnetic nulls. By varying the pitch of the coils windings, the current multiplication ratio can be varied, leading to a more versatile driver. The coupling efficiency of the transformer, its behavior in the presence of electron flow, and its mechanical strength are issues that need to be addressed to evaluate the potential of transformer-based current multiplication as a viable alternative to conventional current adder technology.

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The III-nitride (AlGaInN) materials system forms the foundation for white solid-state lighting, the adoption of which could significantly reduce U.S. energy needs. While the growth of GaN-based devices relies on heteroepitaxy on foreign substrates, the heteroepitaxial layers possess a high density of dislocations due to poor lattice and thermal expansion match. These high dislocation densities have been correlated with reduced internal quantum efficiency and lifetimes for GaN-based LEDs. Here, we demonstrate an inexpensive method for dislocation reduction in GaN grown on sapphire and silicon substrates. This technique, which requires no lithographic patterning, GaN is selectively grown through self-assembled layers of silica microspheres which act to filter out dislocations. Using this method, the threading dislocation density for GaN on sapphire was reduced from 3.3 x 10{sup 9} cm{sup -2} to 4.0 x 10{sup 7} cm{sup -2}, and from the 10{sup 10} cm{sup -2} range to {approx}6.0 x 10{sup 7} cm{sup -2} for GaN on Si(111). This large reduction in dislocation density is attributed to a dislocation blocking and bending by the unique interface between GaN and silica microspheres.

Lack of robust manufacturing capabilities have limited our ability to make tailored materials with useful optical and thermal properties. For example, traditional methods such as spontaneous self-assembly of spheres cannot generate the complex structures required to produce a full bandgap photonic crystals. The goal of this work was to develop and demonstrate novel methods of directed self-assembly of nanomaterials using optical and electric fields. To achieve this aim, our work employed laser tweezers, a technology that enables non-invasive optical manipulation of particles, from glass microspheres to gold nanoparticles. Laser tweezers were used to create ordered materials with either complex crystal structures or using aspherical building blocks.

Most engineering materials are inherently inhomogeneous in their processing, internal structure, properties, and performance. Their properties are therefore statistical rather than deterministic. These inhomogeneities manifest across multiple length and time scales, leading to variabilities, i.e. statistical distributions, that are necessary to accurately describe each stage in the process-structure-properties hierarchy, and are ultimately the primary source of uncertainty in performance of the material and component. When localized events are responsible for component failure, or when component dimensions are on the order of microstructural features, this uncertainty is particularly important. For ultra-high reliability applications, the uncertainty is compounded by a lack of data describing the extremely rare events. Hands-on testing alone cannot supply sufficient data for this purpose. To date, there is no robust or coherent method to quantify this uncertainty so that it can be used in a predictive manner at the component length scale. The research presented in this report begins to address this lack of capability through a systematic study of the effects of microstructure on the strain concentration at a hole. To achieve the strain concentration, small circular holes (approximately 100 {micro}m in diameter) were machined into brass tensile specimens using a femto-second laser. The brass was annealed at 450 C, 600 C, and 800 C to produce three hole-to-grain size ratios of approximately 7, 1, and 1/7. Electron backscatter diffraction experiments were used to guide the construction of digital microstructures for finite element simulations of uniaxial tension. Digital image correlation experiments were used to qualitatively validate the numerical simulations. The simulations were performed iteratively to generate statistics describing the distribution of plastic strain at the hole in varying microstructural environments. In both the experiments and simulations, the deformation behavior was found to depend strongly on the character of the nearby microstructure.

A series of poly(sulfone)s with quaternary ammonium groups and another series with aldehyde groups are synthesized and tested for biocidal activity against vegetative bacteria and spores, respectively. The polymers are sprayed onto substrates as coatings which are then exposed to aqueous suspensions of organisms. The coatings are inherently biocidal and do not release any agents into the environment. The coatings adhere well to both glass and CARC-coated coupons and they exhibit significant biotoxicity. The most effective quaternary ammonium polymers kills 99.9% of both gram negative and gram positive bacteria and the best aldehyde coating kills 81% of the spores on its surface.

The Socorro code has been used to obtain density-functional theory results for the Ga vacancy (V{sub Ga}) and the As vacancy (V{sub As}) in GaAs. Calculations were performed in a nominal 216-atom simulation cell using the local-density approximation for exchange and correlation. The results from these calculations include: (1) the charge states, the atomic configurations of stable and metastable states, (2) energy levels in the gap, and (3) activation energies for migration. Seven charge states were found for the Ga vacancy (-3, -2, -1, 0, +1, +2, +3). The stable structures of the -3, -2, -1, and 0 charge states consist of an empty Ga site with four As neighbors displaying T{sub d} symmetry. The stable structures of the +1, +2, and +3 charge states consist of an As antisite next to an As vacancy; AsGa-V{sub As}. Five charge states were found for the As vacancy (-3, -2, -1, 0, +1). The stable structures of the -1, 0, and +1 charge states consist of an empty As site with four Ga neighbors displaying C{sub 2v} symmetry. The stable structures of the -3 and -2 charge states consist of a Ga antisite next to a Ga vacancy; Ga{sub As}-V{sub Ga}. The energy levels of V{sub Ga} lie below mid-gap while the energy levels of As{sub Ga}-V{sub As} lie above and below mid-gap. All but one of the V{sub As} energy levels lie above mid-gap while the As{sub Ga}-V{sub As} energy level lies below mid-gap. The migration activation energies of the defect states were all found to be larger than 1.35 eV.

High-power electronics are central in the development of radar, solid-state lighting, and laser systems. Large powers, however, necessitate improved heat dissipation as heightened temperatures deleteriously affect both performance and reliability. Heat dissipation, in turn, is determined by the cascade of energy from the electronic to lattice system. Full characterization of the transport then requires analysis of each. In response, this four-month late start effort has developed a transient thermoreflectance (TTR) capability that probes the thermal response of electronic carriers with 100 fs resolution. Simultaneous characterization of the lattice carriers with this electronic assessment was then investigated by equipping the optical arrangement to acquire a Raman signal from radiation discarded during the TTR experiment. Initial results show only tentative acquisition of a Raman response at these timescales. Using simulations of the response, challenges responsible for these difficulties are then examined and indicate that with outlined refinements simultaneous acquisition of TTR/Raman signals remains attainable in the near term.

In this work we demonstrate the concept of stress-induced chemical detection using metal-organic frameworks (MOFs) by integrating a thin film of the MOF HKUST-1 with a microcantilever surface. The results show that the energy of molecular adsorption, which causes slight distortions in the MOF crystal structure, can be efficiently converted to mechanical energy to create a highly responsive, reversible, and selective sensor. This sensor responds to water, methanol, and ethanol vapors, but yields no response to either N{sub 2} or O{sub 2}. The magnitude of the signal, which is measured by a built-in piezoresistor, is correlated with the concentration and can be fitted to a Langmuir isotherm. Furthermore, we show that the hydration state of the MOF layer can be used to impart selectivity to CO{sub 2}. We also report the first use of surface-enhanced Raman spectroscopy to characterize the structure of a MOF film. We conclude that the synthetic versatility of these nanoporous materials holds great promise for creating recognition chemistries to enable selective detection of a wide range of analytes. A force field model is described that successfully predicts changes in MOF properties and the uptake of gases. This model is used to predict adsorption isotherms for a number of representative compounds, including explosives, nerve agents, volatile organic compounds, and polyaromatic hydrocarbons. The results show that, as a result of relatively large heats of adsorption (> 20 kcal mol{sup -1}) in most cases, we expect an onset of adsorption by MOF as low as 10{sup -6} kPa, suggesting the potential to detect compounds such as RDX at levels as low as 10 ppb at atmospheric pressure.

We have successfully developed a nucleic acid extraction system based on a microacoustic lysis array coupled to an integrated nucleic acid extraction system all on a single cartridge. The microacoustic lysing array is based on 36{sup o} Y cut lithium niobate, which couples bulk acoustic waves (BAW) into the microchannels. The microchannels were fabricated using Mylar laminates and fused silica to form acoustic-fluidic interface cartridges. The transducer array consists of four active elements directed for cell lysis and one optional BAW element for mixing on the cartridge. The lysis system was modeled using one dimensional (1D) transmission line and two dimensional (2D) FEM models. For input powers required to lyse cells, the flow rate dictated the temperature change across the lysing region. From the computational models, a flow rate of 10 {micro}L/min produced a temperature rise of 23.2 C and only 6.7 C when flowing at 60 {micro}L/min. The measured temperature changes were 5 C less than the model. The computational models also permitted optimization of the acoustic coupling to the microchannel region and revealed the potential impact of thermal effects if not controlled. Using E. coli, we achieved a lysing efficacy of 49.9 {+-} 29.92 % based on a cell viability assay with a 757.2 % increase in ATP release within 20 seconds of acoustic exposure. A bench-top lysing system required 15-20 minutes operating up to 58 Watts to achieve the same level of cell lysis. We demonstrate that active mixing on the cartridge was critical to maximize binding and release of nucleic acid to the magnetic beads. Using a sol-gel silica bead matrix filled microchannel the extraction efficacy was 40%. The cartridge based magnetic bead system had an extraction efficiency of 19.2%. For an electric field based method that used Nafion films, a nucleic acid extraction efficiency of 66.3 % was achieved at 6 volts DC. For the flow rates we tested (10-50 {micro}L/min), the nucleic acid extraction time was 5-10 minutes for a volume of 50 {micro}L. Moreover, a unique feature of this technology is the ability to replace the cartridges for subsequent nucleic acid extractions.

A key aspect of decision making is determining when errors or conflicts exist in information and knowing whether to continue or terminate an action. Understanding the error-conflict processing is crucial in order to emulate higher brain functions in hardware and software systems. Specific brain regions, most notably the anterior cingulate cortex (ACC) are known to respond to the presence of conflicts in information by assigning a value to an action. Essentially, this conflict signal triggers strategic adjustments in cognitive control, which serve to prevent further conflict. The most probable mechanism is the ACC reports and discriminates different types of feedback, both positive and negative, that relate to different adaptations. Unique cells called spindle neurons that are primarily found in the ACC (layer Vb) are known to be responsible for cognitive dissonance (disambiguation between alternatives). Thus, the ACC through a specific set of cells likely plays a central role in the ability of humans to make difficult decisions and solve challenging problems in the midst of conflicting information. In addition to dealing with cognitive dissonance, decision making in high consequence scenarios also relies on the integration of multiple sets of information (sensory, reward, emotion, etc.). Thus, a second area of interest for this proposal lies in the corticostriatal networks that serve as an integration region for multiple cognitive inputs. In order to engineer neurological decision making processes in silicon devices, we will determine the key cells, inputs, and outputs of conflict/error detection in the ACC region. The second goal is understand in vitro models of corticostriatal networks and the impact of physical deficits on decision making, specifically in stressful scenarios with conflicting streams of data from multiple inputs. We will elucidate the mechanisms of cognitive data integration in order to implement a future corticostriatal-like network in silicon devices for improved decision processing.

Development of flexible thin film systems for biomedical, homeland security and environmental sensing applications has increased dramatically in recent years [1,2,3,4]. These systems typically combine traditional semiconductor technology with new flexible substrates, allowing for both the high electron mobility of semiconductors and the flexibility of polymers. The devices have the ability to be easily integrated into components and show promise for advanced design concepts, ranging from innovative microelectronics to MEMS and NEMS devices. These devices often contain layers of thin polymer, ceramic and metallic films where differing properties can lead to large residual stresses [5]. As long as the films remain substrate-bonded, they may deform far beyond their freestanding counterpart. Once debonded, substrate constraint disappears leading to film failure where compressive stresses can lead to wrinkling, delamination, and buckling [6,7,8] while tensile stresses can lead to film fracture and decohesion [9,10,11]. In all cases, performance depends on film adhesion. Experimentally it is difficult to measure adhesion. It is often studied using tape [12], pull off [13,14,15], and peel tests [16,17]. More recent techniques for measuring adhesion include scratch testing [18,19,20,21], four point bending [22,23,24], indentation [25,26,27], spontaneous blisters [28,29] and stressed overlayers [7,26,30,31,32,33]. Nevertheless, sample design and test techniques must be tailored for each system. There is a large body of elastic thin film fracture and elastic contact mechanics solutions for elastic films on rigid substrates in the published literature [5,7,34,35,36]. More recent work has extended these solutions to films on compliant substrates and show that increasing compliance markedly changes fracture energies compared with rigid elastic solution results [37,38]. However, the introduction of inelastic substrate response significantly complicates the problem [10,39,40]. As a result, our understanding of the critical relationship between adhesion, properties, and fracture for hard films on compliant substrates is limited. To address this issue, we integrated nanomechanical testing and mechanics-based modeling in a program to define the critical relationship between deformation and fracture of nanoscale films on compliant substrates. The approach involved designing model film systems and employing nano-scale experimental characterization techniques to isolate effects of compliance, viscoelasticity, and plasticity on deformation and fracture of thin hard films on substrates that spanned more than two orders of compliance magnitude exhibit different interface structures, have different adhesion strengths, and function differently under stress. The results of this work are described in six chapters. Chapter 1 provides the motivation for this work. Chapter 2 presents experimental results covering film system design, sample preparation, indentation response, and fracture including discussion on the effects of substrate compliance on fracture energies and buckle formation from existing models. Chapter 3 describes the use of analytical and finite element simulations to define the role of substrate compliance and film geometry on the indentation response of thin hard films on compliant substrates. Chapter 4 describes the development and application of cohesive zone model based finite element simulations to determine how substrate compliance affects debond growth. Chapter 5 describes the use of molecular dynamics simulations to define the effects of substrate compliance on interfacial fracture of thin hard tungsten films on silicon substrates. Chapter 6 describes the Workshops sponsored through this program to advance understanding of material and system behavior.

In this report we summarize research into new parallel algebraic multigrid (AMG) methods. We first provide a introduction to parallel AMG. We then discuss our research in parallel AMG algorithms for very large scale platforms. We detail significant improvements in the AMG setup phase to a matrix-matrix multiplication kernel. We present a smoothed aggregation AMG algorithm with fewer communication synchronization points, and discuss its links to domain decomposition methods. Finally, we discuss a multigrid smoothing technique that utilizes two message passing layers for use on multicore processors.