Showing papers by "Sandia National Laboratories published in 2016"

MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

Abstract: Summary: The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning a single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.

Real-time, portable genome sequencing for Ebola surveillance

Abstract: A nanopore DNA sequencer is used for real-time genomic surveillance of the Ebola virus epidemic in the field in Guinea; the authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. This paper reports the use of nanopore DNA sequencers (known as MinIONs) for real-time genomic surveillance of the Ebola virus epidemic, in the field in Guinea. The authors demonstrate that it is possible to pack a genomic surveillance laboratory in a suitcase and transport it to the field for on-site virus sequencing, generating results within 24 hours of sample collection. The Ebola virus disease epidemic in West Africa is the largest on record, responsible for over 28,599 cases and more than 11,299 deaths1. Genome sequencing in viral outbreaks is desirable to characterize the infectious agent and determine its evolutionary rate. Genome sequencing also allows the identification of signatures of host adaptation, identification and monitoring of diagnostic targets, and characterization of responses to vaccines and treatments. The Ebola virus (EBOV) genome substitution rate in the Makona strain has been estimated at between 0.87 × 10−3 and 1.42 × 10−3 mutations per site per year. This is equivalent to 16–27 mutations in each genome, meaning that sequences diverge rapidly enough to identify distinct sub-lineages during a prolonged epidemic2,3,4,5,6,7. Genome sequencing provides a high-resolution view of pathogen evolution and is increasingly sought after for outbreak surveillance. Sequence data may be used to guide control measures, but only if the results are generated quickly enough to inform interventions8. Genomic surveillance during the epidemic has been sporadic owing to a lack of local sequencing capacity coupled with practical difficulties transporting samples to remote sequencing facilities9. To address this problem, here we devise a genomic surveillance system that utilizes a novel nanopore DNA sequencing instrument. In April 2015 this system was transported in standard airline luggage to Guinea and used for real-time genomic surveillance of the ongoing epidemic. We present sequence data and analysis of 142 EBOV samples collected during the period March to October 2015. We were able to generate results less than 24 h after receiving an Ebola-positive sample, with the sequencing process taking as little as 15–60 min. We show that real-time genomic surveillance is possible in resource-limited settings and can be established rapidly to monitor outbreaks.

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

Abstract: There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property. The Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.

An integrated diamond nanophotonics platform for quantum optical networks

Abstract: Efficient interfaces between photons and quantum emitters form the basis for quantum networks and enable optical nonlinearities at the single-photon level. We demonstrate an integrated platform for scalable quantum nanophotonics based on silicon-vacancy (SiV) color centers coupled to diamond nanodevices. By placing SiV centers inside diamond photonic crystal cavities, we realize a quantum-optical switch controlled by a single color center. We control the switch using SiV metastable states and observe optical switching at the single-photon level. Raman transitions are used to realize a single-photon source with a tunable frequency and bandwidth in a diamond waveguide. By measuring intensity correlations of indistinguishable Raman photons emitted into a single waveguide, we observe a quantum interference effect resulting from the superradiant emission of two entangled SiV centers.

Resonantly Enhanced Second-Harmonic Generation Using III-V Semiconductor All-Dielectric Metasurfaces.

Abstract: Nonlinear optical phenomena in nanostructured materials have been challenging our perceptions of nonlinear optical processes that have been explored since the invention of lasers. For example, the ability to control optical field confinement, enhancement, and scattering almost independently allows nonlinear frequency conversion efficiencies to be enhanced by many orders of magnitude compared to bulk materials. Also, the subwavelength length scale renders phase matching issues irrelevant. Compared with plasmonic nanostructures, dielectric resonator metamaterials show great promise for enhanced nonlinear optical processes due to their larger mode volumes. Here, we present, for the first time, resonantly enhanced second-harmonic generation (SHG) using gallium arsenide (GaAs) based dielectric metasurfaces. Using arrays of cylindrical resonators we observe SHG enhancement factors as large as 10(4) relative to unpatterned GaAs. At the magnetic dipole resonance, we measure an absolute nonlinear conversion efficiency of ∼2 × 10(-5) with ∼3.4 GW/cm(2) pump intensity. The polarization properties of the SHG reveal that both bulk and surface nonlinearities play important roles in the observed nonlinear process.

Entangling atomic spins with a Rydberg-dressed spin-flip blockade

Abstract: Tunable interactions in quantum many-body systems have practical applications in quantum technologies. The effective spin-dependent long-range interaction known as Rydberg dressing is now exploited to entangle a pair of ultracold neutral atoms.

Enhancing reproducibility for computational methods.

Abstract: Over the past two decades, computational methods have radically changed the ability of researchers from all areas of scholarship to process and analyze data and to simulate complex systems. But with these advances come challenges that are contributing to broader concerns over irreproducibility in the scholarly literature, among them the lack of transparency in disclosure of computational methods. Current reporting methods are often uneven, incomplete, and still evolving. We present a novel set of Reproducibility Enhancement Principles (REP) targeting disclosure challenges involving computation. These recommendations, which build upon more general proposals from the Transparency and Openness Promotion (TOP) guidelines ( 1 ) and recommendations for field data ( 2 ), emerged from workshop discussions among funding agencies, publishers and journal editors, industry participants, and researchers representing a broad range of domains. Although some of these actions may be aspirational, we believe it is important to recognize and move toward ameliorating irreproducibility in computational research.

Scalable gate architecture for a one-dimensional array of semiconductor spin qubits

Abstract: Long coherence times render electron spins in quantum dots promising for scaled-up quantum computation, but large arrays of semiconductor spin qubits have yet to be realized. The authors take the next steps in scaling by demonstrating an array of $n\phantom{\rule{0}{0ex}}i\phantom{\rule{0}{0ex}}n\phantom{\rule{0}{0ex}}e$ quantum dots with low electron occupancy, reproducible single-dot characteristics, and full charge-state readout. Beyond quantum information science, this also represents a major advance for the quantum-dot community, where double and triple quantum dots have been the standard for over a decade.

Oxygen-activated growth and bandgap tunability of large single-crystal bilayer graphene

Abstract: Large, bilayer graphene single crystals can be grown by oxygen-activated chemical vapour deposition. Bernal (AB)-stacked bilayer graphene (BLG) is a semiconductor whose bandgap can be tuned by a transverse electric field, making it a unique material for a number of electronic and photonic devices1,2,3. A scalable approach to synthesize high-quality BLG is therefore critical, which requires minimal crystalline defects in both graphene layers4,5 and maximal area of Bernal stacking, which is necessary for bandgap tunability6. Here we demonstrate that in an oxygen-activated chemical vapour deposition (CVD) process, half-millimetre size, Bernal-stacked BLG single crystals can be synthesized on Cu. Besides the traditional ‘surface-limited’ growth mechanism for SLG (1st layer), we discovered new microscopic steps governing the growth of the 2nd graphene layer below the 1st layer as the diffusion of carbon atoms through the Cu bulk after complete dehydrogenation of hydrocarbon molecules on the Cu surface, which does not occur in the absence of oxygen. Moreover, we found that the efficient diffusion of the carbon atoms present at the interface between Cu and the 1st graphene layer further facilitates growth of large domains of the 2nd layer. The CVD BLG has superior electrical quality, with a device on/off ratio greater than 104, and a tunable bandgap up to ∼100 meV at a displacement field of 0.9 V nm−1.

Broken Symmetry Dielectric Resonators for High Quality Factor Fano Metasurfaces

Abstract: We present a new approach to dielectric metasurface design that relies on a single resonator per unit cell and produces robust, high quality factor Fano resonances. Our approach utilizes symmetry breaking of highly symmetric resonator geometries, such as cubes, to induce couplings between the otherwise orthogonal resonator modes. In particular, we design perturbations that couple “bright” dipole modes to “dark” dipole modes whose radiative decay is suppressed by local field effects in the array. Our approach is widely scalable from the near-infrared to radio frequencies. We first unravel the Fano resonance behavior through numerical simulations of a germanium resonator-based metasurface that achieves a quality factor of ∼1300 at ∼10.8 μm. Then, we present two experimental demonstrations operating in the near-infrared (∼1 μm): a silicon-based implementation that achieves a quality factor of ∼350; and a gallium arsenide-based structure that achieves a quality factor of ∼600, the highest near-infrared qualit...

High-speed and low-energy nitride memristors

Abstract: High-performance memristors based on AlN films have been demonstrated, which exhibit ultrafast ON/OFF switching times (≈85 ps for microdevices with waveguide) and relatively low switching current (≈15 μA for 50 nm devices). Physical characterizations are carried out to understand the device switching mechanism, and rationalize speed and energy performance. The formation of an Al-rich conduction channel through the AlN layer is revealed. The motion of positively charged nitrogen vacancies is likely responsible for the observed switching.

Efficient Polarization-Insensitive Complex Wavefront Control Using Huygens’ Metasurfaces Based on Dielectric Resonant Meta-atoms

Abstract: Metasurfaces have shown great promise for the control of optical wavefronts, thus opening new pathways for the development of efficient flat optics. In particular, Huygens’ metasurfaces based on all-dielectric resonant meta-atoms have already shown a huge potential for practical applications with their polarization insensitivity and high transmittance efficiency. Here, we experimentally demonstrate a polarization-insensitive holographic Huygens’ metasurface based on dielectric resonant meta-atoms capable of complex wavefront control at telecommunication wavelengths. Our metasurface produces a hologram image in the far-field with 82% transmittance efficiency and 40% imaging efficiency. Such efficient complex wavefront control shows that Huygens’ metasurfaces based on resonant dielectric meta-atoms are a big step toward practical applications of metasurfaces in wavefront design related technologies, including computer-generated holograms, ultrathin optics, security, and data storage devices.

The 2016 Thermal Spray Roadmap

Abstract: Considerable progress has been made over the last decades in thermal spray technologies, practices and applications. However, like other technologies, they have to continuously evolve to meet new problems and market requirements. This article aims to identify the current challenges limiting the evolution of these technologies and to propose research directions and priorities to meet these challenges. It was prepared on the basis of a collection of short articles written by experts in thermal spray who were asked to present a snapshot of the current state of their specific field, give their views on current challenges faced by the field and provide some guidance as to the R&D required to meet these challenges. The article is divided in three sections that deal with the emerging thermal spray processes, coating properties and function, and biomedical, electronic, aerospace and energy generation applications.

Mobile genes in the human microbiome are structured from global to individual scales

Abstract: Recent work has underscored the importance of the microbiome in human health, and has largely attributed differences in phenotype to differences in the species present among individuals. However, mobile genes can confer profoundly different phenotypes on different strains of the same species. Little is known about the function and distribution of mobile genes in the human microbiome, and in particular whether the gene pool is globally homogenous or constrained by human population structure. Here, we investigate this question by comparing the mobile genes found in the microbiomes of 81 metropolitan North Americans with those of 172 agrarian Fiji islanders using a combination of single-cell genomics and metagenomics. We find large differences in mobile gene content between the Fijian and North American microbiomes, with functional variation that mirrors known dietary differences such as the excess of plant-based starch degradation genes found in Fijian individuals. Notably, we also observed differences between the mobile gene pools of neighbouring Fijian villages, even though microbiome composition across villages is similar. Finally, we observe high rates of recombination leading to individual-specific mobile elements, suggesting that the abundance of some genes may reflect environmental selection rather than dispersal limitation. Together, these data support the hypothesis that human activities and behaviours provide selective pressures that shape mobile gene pools, and that acquisition of mobile genes is important for colonizing specific human populations.

High-contrast and fast electrochromic switching enabled by plasmonics.

Abstract: With vibrant colours and simple, room-temperature processing methods, electrochromic polymers have attracted attention as active materials for flexible, low-power-consuming devices. However, slow switching speeds in devices realized to date, as well as the complexity of having to combine several distinct polymers to achieve a full-colour gamut, have limited electrochromic materials to niche applications. Here we achieve fast, high-contrast electrochromic switching by significantly enhancing the interaction of light--propagating as deep-subwavelength-confined surface plasmon polaritons through arrays of metallic nanoslits, with an electrochromic polymer--present as an ultra-thin coating on the slit sidewalls. The switchable configuration retains the short temporal charge-diffusion characteristics of thin electrochromic films, while maintaining the high optical contrast associated with thicker electrochromic coatings. We further demonstrate that by controlling the pitch of the nanoslit arrays, it is possible to achieve a full-colour response with high contrast and fast switching speeds, while relying on just one electrochromic polymer.

Metasurface Broadband Solar Absorber

Abstract: We demonstrate a broadband, polarization independent, wide-angle absorber based on a metallic metasurface architecture, which accomplishes greater than 90% absorptance in the visible and near-infrared range of the solar spectrum, and exhibits low absorptivity (emissivity) at mid- and far-infrared wavelengths. The complex unit cell of the metasurface solar absorber consists of eight pairs of gold nano-resonators that are separated from a gold ground plane by a thin silicon dioxide spacer. Our experimental measurements reveal high-performance absorption over a wide range of incidence angles for both s- and p-polarizations. We also investigate numerically the frequency-dependent field and current distributions to elucidate how the absorption occurs within the metasurface structure.

Transforming biomass conversion with ionic liquids: process intensification and the development of a high-gravity, one-pot process for the production of cellulosic ethanol

Abstract: Producing concentrated sugars and minimizing water usage are key elements in the economics and environmental sustainability of advanced biofuels. Conventional pretreatment processes that require a water-wash step can result in losses of fermentable sugars and generate large volumes of wastewater or solid waste. To address these problems, we have developed high gravity biomass processing with a one-pot conversion technology that includes ionic liquid pretreatment, enzymatic saccharification, and yeast fermentation for the production of concentrated fermentable sugars and high-titer cellulosic ethanol. The use of dilute bio-derived ionic liquids (a.k.a. bionic liquids) enables one-pot, high-gravity bioethanol production due to their low toxicity to the hydrolytic enzyme mixtures and microbes used. We increased biomass digestibility at >30 wt% loading by understanding the relationship between ionic liquid and biomass loading, yielding 41.1 g L−1 of ethanol (equivalent to an overall yield of 74.8% on glucose basis) using an integrated one-pot fed-batch system. Our technoeconomic analysis indicates that the optimized one-pot configuration provides significant economic and environmental benefits for cellulosic biorefineries by reducing the amount of ionic liquid required by ∼90% and pretreatment-related water inputs and wastewater generation by ∼85%. In turn, these improvements can reduce net electricity use, greenhouse gas-intensive chemical inputs for wastewater treatment, and waste generation. The result is an overall 40% reduction in the cost of cellulosic ethanol produced and a reduction in local burdens on water resources and waste management infrastructure.

Liquid-Like Ionic Conduction in Solid Lithium and Sodium Monocarba-closo-Decaborates Near or at Room Temperature

Abstract: Both LiCB9H10 and NaCB9H10 exhibit liquid-like cationic conductivities (≥0.03 S cm–1) in their disordered hexagonal phases near or at room temperature. Furthermore, these unprecedented conductivities and favorable stabilities enabled by the large pseudoaromatic polyhedral anions render these materials in their pristine or further modified forms as promising solid electrolytes in next-generation, power devices.

A survey of direct methods for sparse linear systems

Abstract: Wilkinson defined a sparse matrix as one with enough zeros that it pays to take advantage of them.1 This informal yet practical definition captures the essence of the goal of direct methods for solving sparse matrix problems. They exploit the sparsity of a matrix to solve problems economically: much faster and using far less memory than if all the entries of a matrix were stored and took part in explicit computations. These methods form the backbone of a wide range of problems in computational science. A glimpse of the breadth of applications relying on sparse solvers can be seen in the origins of matrices in published matrix benchmark collections (Duff and Reid 1979a, Duff, Grimes and Lewis 1989a, Davis and Hu 2011). The goal of this survey article is to impart a working knowledge of the underlying theory and practice of sparse direct methods for solving linear systems and least-squares problems, and to provide an overview of the algorithms, data structures, and software available to solve these problems, so that the reader can both understand the methods and know how best to use them.

An operationally flexible fuel cell based on quaternary ammonium-biphosphate ion pairs

Abstract: Fuel cells are promising devices for clean power generation in a variety of economically and environmentally significant applications. Low-temperature proton exchange membrane (PEM) fuel cells utilizing Nafion require a high level of hydration, which limits the operating temperature to less than 100 ∘C. In contrast, high-temperature PEM fuel cells utilizing phosphoric acid-doped polybenzimidazole can operate effectively up to 180 ∘C; however, these devices degrade when exposed to water below 140 ∘C. Here we present a different class of PEM fuel cells based on quaternary ammonium-biphosphate ion pairs that can operate under conditions unattainable with existing fuel cell technologies. These fuel cells exhibit stable performance at 80–160 ∘C with a conductivity decay rate more than three orders of magnitude lower than that of a commercial high-temperature PEM fuel cell. By increasing the operational flexibility, this class of fuel cell can simplify the requirements for heat and water management, and potentially reduce the costs associated with the existing fully functional fuel cell systems. There is intensive research underway into the development of fuel cells. Here, the authors present a proton exchange membrane fuel cell based on quaternary ammonium-biphosphate ion pairs, offering promising performance under a wide range of conditions that are unattainable with conventional technologies.

Collective non-perturbative coupling of 2D electrons with high-quality-factor terahertz cavity photons

Abstract: Condensed-matter physics meets quantum optics in a study of light–matter interaction in the strong-coupling regime using a two-dimensional electron gas in a high-quality-factor terahertz cavity.

Sparingly Solvating Electrolytes for High Energy Density Lithium-Sulfur Batteries

Abstract: Moving to lighter and less expensive battery chemistries compared to contemporary lithium-ion requires the control of energy storage mechanisms based on chemical transformations rather than intercalation. Lithium–sulfur (Li/S) has tremendous theoretical specific energy, but contemporary approaches to control this solution-mediated, precipitation–dissolution chemistry require large excesses of electrolyte to fully solubilize the polysulfide intermediates. Achieving reversible electrochemistry under lean electrolyte operation is the most promising path for Li/S to move beyond niche applications to potentially transformational performance. An emerging Li/S research area is the use of sparingly solvating electrolytes and the creation of design rules for discovering new electrolyte systems that fundamentally decouple electrolyte volume from sulfur and polysulfide reaction mechanism. This Perspective presents an outlook for sparingly solvating electrolytes as a key path forward for long-lived, high energy densi...

Mesoporous Silica Nanoparticle-Supported Lipid Bilayers (Protocells) for Active Targeting and Delivery to Individual Leukemia Cells.

Abstract: Many nanocarrier cancer therapeutics currently under development, as well as those used in the clinical setting, rely upon the enhanced permeability and retention (EPR) effect to passively accumulate in the tumor microenvironment and kill cancer cells. In leukemia, where leukemogenic stem cells and their progeny circulate within the peripheral blood or bone marrow, the EPR effect may not be operative. Thus, for leukemia therapeutics, it is essential to target and bind individual circulating cells. Here, we investigate mesoporous silica nanoparticle (MSN)-supported lipid bilayers (protocells), an emerging class of nanocarriers, and establish the synthesis conditions and lipid bilayer composition needed to achieve highly monodisperse protocells that remain stable in complex media as assessed in vitro by dynamic light scattering and cryo-electron microscopy and ex ovo by direct imaging within a chick chorioallantoic membrane (CAM) model. We show that for vesicle fusion conditions where the lipid surface area...

Obtaining lower bounds from the progressive hedging algorithm for stochastic mixed-integer programs

Abstract: We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. We report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.