Lawrence Livermore National Security

Graphene is readily p-doped by adsorbates, but for device applications, it would be useful to access the n-doped material. Individual graphene nanoribbons were covalently functionalized by nitrogen species through high-power electrical joule heating in ammonia gas, leading to n-type electronic doping consistent with theory. The formation of the carbon-nitrogen bond should occur mostly at the edges of graphene where chemical reactivity is high. X-ray photoelectron spectroscopy and nanometer-scale secondary ion mass spectroscopy confirm the carbon-nitrogen species in graphene thermally annealed in ammonia. We fabricated an n-type graphene field-effect transistor that operates at room temperature.

Metal-organic frameworks (MOFs) are a class of hybrid materials with unique optical and electronic properties arising from rational self-assembly of the organic linkers and metal ions/clusters, yielding myriads of possible structural motifs. The combination of order and chemical tunability, coupled with good environmental stability of MOFs, are prompting many research groups to explore the possibility of incorporating these materials as active components in devices such as solar cells, photodetectors, radiation detectors, and chemical sensors. Although this field is only in its incipiency, many new fundamental insights relevant to integrating MOFs with such devices have already been gained. In this review, we focus our attention on the basic requirements and structural elements needed to fabricate MOF-based devices and summarize the current state of MOF research in the area of electronic, opto-electronic and sensor devices. We summarize various approaches to designing active MOFs, creation of hybrid material systems combining MOFs with other materials, and assembly and integration of MOFs with device hardware. Critical directions of future research are identified, with emphasis on achieving the desired MOF functionality in a device and establishing the structure-property relationships to identify and rationalize the factors that impact device performance.

Correction for 'An updated roadmap for the integration of metal-organic frameworks with electronic devices and chemical sensors' by Ivo Stassen et al., Chem. Soc. Rev., 2017, DOI: 10.1039/c7cs00122c.

We present the LGA (Local-Global Alignment) method, designed to facilitate the comparison of protein structures or fragments of protein structures in sequence dependent and sequence independent modes. The LGA structure alignment program is available as an online service at http://PredictionCenter.llnl.gov/local/lga. Data generated by LGA can be successfully used in a scoring function to rank the level of similarity between two structures and to allow structure classification when many proteins are being analyzed. LGA also allows the clustering of similar fragments of protein structures.

increase simulation) for the CMIP6 models of 1.7°C (1.3°C to 3.0°C) is only slightly larger than for the CMIP3 and CMIP5 models. Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions. Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.

The KamLAND experiment has determined a precise value for the neutrino oscillation parameter $\ensuremath{\Delta}{m}_{21}^{2}$ and stringent constraints on ${\ensuremath{\theta}}_{12}$. The exposure to nuclear reactor antineutrinos is increased almost fourfold over previous results to $2.44\ifmmode\times\else\texttimes\fi{}{10}^{32}\text{ }\text{ }\mathrm{proton}\text{ }\mathrm{yr}$ due to longer livetime and an enlarged fiducial volume. An undistorted reactor ${\overline{\ensuremath{\nu}}}_{e}$ energy spectrum is now rejected at $>5\ensuremath{\sigma}$. Analysis of the reactor spectrum above the inverse beta decay energy threshold, and including geoneutrinos, gives a best fit at $\ensuremath{\Delta}{m}_{21}^{2}={7.58}_{\ensuremath{-}0.13}^{+0.14}(\mathrm{stat}{)}_{\ensuremath{-}0.15}^{+0.15}(\mathrm{syst})\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}5}\text{ }\text{ }{\mathrm{eV}}^{2}$ and ${tan}^{2}{\ensuremath{\theta}}_{12}={0.56}_{\ensuremath{-}0.07}^{+0.10}(\mathrm{stat}{)}_{\ensuremath{-}0.06}^{+0.10}(\mathrm{syst})$. Local $\ensuremath{\Delta}{\ensuremath{\chi}}^{2}$ minima at higher and lower $\ensuremath{\Delta}{m}_{21}^{2}$ are disfavored at $>4\ensuremath{\sigma}$. Combining with solar neutrino data, we obtain $\ensuremath{\Delta}{m}_{21}^{2}={7.59}_{\ensuremath{-}0.21}^{+0.21}\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}5}\text{ }\text{ }{\mathrm{eV}}^{2}$ and ${tan}^{2}{\ensuremath{\theta}}_{12}={0.47}_{\ensuremath{-}0.05}^{+0.06}$.

Soil is the largest terrestrial reservoir of organic carbon and is central for climate change mitigation and carbon-climate feedbacks. Chemical and physical associations of soil carbon with minerals play a critical role in carbon storage, but the amount and global capacity for storage in this form remain unquantified. Here, we produce spatially-resolved global estimates of mineral-associated organic carbon stocks and carbon-storage capacity by analyzing 1144 globally-distributed soil profiles. We show that current stocks total 899 Pg C to a depth of 1 m in non-permafrost mineral soils. Although this constitutes 66% and 70% of soil carbon in surface and deeper layers, respectively, it is only 42% and 21% of the mineralogical capacity. Regions under agricultural management and deeper soil layers show the largest undersaturation of mineral-associated carbon. Critically, the degree of undersaturation indicates sequestration efficiency over years to decades. We show that, across 103 carbon-accrual measurements spanning management interventions globally, soils furthest from their mineralogical capacity are more effective at accruing carbon; sequestration rates average 3-times higher in soils at one tenth of their capacity compared to soils at one half of their capacity. Our findings provide insights into the world's soils, their capacity to store carbon, and priority regions and actions for soil carbon management.

Laser powder bed fusion additive manufacturing is an emerging 3D printing technique for the fabrication of advanced metal components. Widespread adoption of it and similar additive technologies is hampered by poor understanding of laser-metal interactions under such extreme thermal regimes. Here, we elucidate the mechanism of pore formation and liquid-solid interface dynamics during typical laser powder bed fusion conditions using in situ X-ray imaging and multi-physics simulations. Pores are revealed to form during changes in laser scan velocity due to the rapid formation then collapse of deep keyhole depressions in the surface which traps inert shielding gas in the solidifying metal. We develop a universal mitigation strategy which eliminates this pore formation process and improves the geometric quality of melt tracks. Our results provide insight into the physics of laser-metal interaction and demonstrate the potential for science-based approaches to improve confidence in components produced by laser powder bed fusion.

UNLABELLED: We announce the release of kSNP3.0, a program for SNP identification and phylogenetic analysis without genome alignment or the requirement for reference genomes. kSNP3.0 is a significantly improved version of kSNP v2. AVAILABILITY AND IMPLEMENTATION: kSNP3.0 is implemented as a package of stand-alone executables for Linux and Mac OS X under the open-source BSD license. The executable packages, source code and a full User Guide are freely available at https://sourceforge.net/projects/ksnp/files/ CONTACT: barryghall@gmail.com.

Coherent x-ray diffraction microscopy is a method of imaging nonperiodic isolated objects at resolutions limited, in principle, by only the wavelength and largest scattering angles recorded. We demonstrate x-ray diffraction imaging with high resolution in all three dimensions, as determined by a quantitative analysis of the reconstructed volume images. These images are retrieved from the three-dimensional diffraction data using no a priori knowledge about the shape or composition of the object, which has never before been demonstrated on a nonperiodic object. We also construct two-dimensional images of thick objects with greatly increased depth of focus (without loss of transverse spatial resolution). These methods can be used to image biological and materials science samples at high resolution with x-ray undulator radiation and establishes the techniques to be used in atomic-resolution ultrafast imaging at x-ray free-electron laser sources.

The National Ignition Facility (NIF) is the world's largest laser system. It contains a 192 beam neodymium glass laser that is designed to deliver 1.8 MJ at 500 TW at 351 nm in order to achieve energy gain (ignition) in a deuterium-tritium nuclear fusion target. To meet this goal, laser design criteria include the ability to generate pulses of up to 1.8 MJ total energy, with peak power of 500 TW and temporal pulse shapes spanning 2 orders of magnitude at the third harmonic (351 nm or 3omega) of the laser wavelength. The focal-spot fluence distribution of these pulses is carefully controlled, through a combination of special optics in the 1omega (1053 nm) portion of the laser (continuous phase plates), smoothing by spectral dispersion, and the overlapping of multiple beams with orthogonal polarization (polarization smoothing). We report performance qualification tests of the first eight beams of the NIF laser. Measurements are reported at both 1omega and 3omega, both with and without focal-spot conditioning. When scaled to full 192 beam operation, these results demonstrate, to the best of our knowledge for the first time, that the NIF will meet its laser performance design criteria, and that the NIF can simultaneously meet the temporal pulse shaping, focal-spot conditioning, and peak power requirements for two candidate indirect drive ignition designs.

Heterocyclic amines (HAs) are formed as pyrolysis products during the cooking of meats/fish. These substances are potent mutagens in the Ames/Salmonella assay and are also carcinogens in laboratory animals. In order to assess the magnitude of the cancer risk posed by their presence in the US diet, we estimated the average intakes of HAs, based on analyses of the concentrations of HAs in cooked foods and data from a dietary survey of the US population and quantified the cancer potencies of the individual compounds using dose-response data from animal bioassays. Measured concentrations of HAs in cooked foods were taken from a major review of the open literature. Only those concentrations that were associated with normal cooking conditions were chosen for use in estimating dietary intakes. The average consumption of HA-bearing foods was determined by analyzing statistically the intakes of 3563 individuals who provided 3 day dietary records in a USDA sponsored random survey of the US population during 1989. Dietary intakes of the five principal HAs in descending order were 2-amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP) > 2-amino-9H-pyrido[2,3-b]indole (A alpha C) > 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) > 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (DiMeIQx) > 2-amino-3-methylimidazo[4,5-f]quinoline (IQ). The carcinogenic potencies, in contrast, were almost the reverse order: IQ > DiMeIQx > MeIQx > PhIP > A alpha C. An upper-bound estimate of the incremental cancer risk is 1.1 x 10(-4), using cancer potencies based on a body surface area basis. Nearly half (46%) of the incremental risk was due to ingestion of PhIP. Consumption of meat and fish products contributed the most (approximately 80%) to total risk.

With an increasing number of vertebrate genomes being sequenced in draft or finished form, unique opportunities for decoding the language of DNA sequence through comparative genome alignments have arisen. However, novel tools and strategies are required to accommodate this large volume of genomic information and to facilitate the transfer of predictions generated by comparative sequence alignment to researchers focused on experimental annotation of genome function. Here, we present the ECR Browser, a tool that provides easy and dynamic access to whole genome alignments of human, mouse, rat and fish sequences. This web-based tool (http://ecrbrowser.dcode.org) provides the starting point for discovery of novel genes, identification of distant gene regulatory elements and prediction of transcription factor binding sites. The genome alignment portal of the ECR Browser also permits fast and automated alignments of any user-submitted sequence to the genome of choice. The interconnection of the ECR Browser with other DNA sequence analysis tools creates a unique portal for studying and exploring vertebrate genomes.

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

Abstract Obtaining a burning plasma is a critical step towards self-sustaining fusion energy 1 . A burning plasma is one in which the fusion reactions themselves are the primary source of heating in the plasma, which is necessary to sustain and propagate the burn, enabling high energy gain. After decades of fusion research, here we achieve a burning-plasma state in the laboratory. These experiments were conducted at the US National Ignition Facility, a laser facility delivering up to 1.9 megajoules of energy in pulses with peak powers up to 500 terawatts. We use the lasers to generate X-rays in a radiation cavity to indirectly drive a fuel-containing capsule via the X-ray ablation pressure, which results in the implosion process compressing and heating the fuel via mechanical work. The burning-plasma state was created using a strategy to increase the spatial scale of the capsule 2,3 through two different implosion concepts 4–7 . These experiments show fusion self-heating in excess of the mechanical work injected into the implosions, satisfying several burning-plasma metrics 3,8 . Additionally, we describe a subset of experiments that appear to have crossed the static self-heating boundary, where fusion heating surpasses the energy losses from radiation and conduction. These results provide an opportunity to study α-particle-dominated plasmas and burning-plasma physics in the laboratory.

A method for simulating two-phase flows including surface tension is presented. The approach is based upon smoothed particle hydrodynamics (SPH). The fully Lagrangian nature of SPH maintains sharp fluid–fluid interfaces without employing high-order advection schemes or explicit interface reconstruction. Several possible implementations of surface tension force are suggested and compared. The numerical stability of the method is investigated and optimal choices for numerical parameters are identified. Comparisons with a grid-based volume of fluid method for two-dimensional flows are excellent. The methods presented here apply to problems involving interfaces of arbitrary shape undergoing fragmentation and coalescence within a two-phase system and readily extend to three-dimensional problems. Boundary conditions at a solid surface, high viscosity and density ratios, and the simulation of free-surface flows are not addressed. Copyright © 2000 John Wiley & Sons, Ltd.

The results of detailed experiments and finite element modeling of metal micro-droplet motion associated with metal additive manufacturing (AM) processes are presented. Ultra high speed imaging of melt pool dynamics reveals that the dominant mechanism leading to micro-droplet ejection in a laser powder bed fusion AM is not from laser induced recoil pressure as is widely believed and found in laser welding processes, but rather from vapor driven entrainment of micro-particles by an ambient gas flow. The physics of droplet ejection under strong evaporative flow is described using simulations of the laser powder bed interactions to elucidate the experimental results. Hydrodynamic drag analysis is used to augment the single phase flow model and explain the entrainment phenomenon for 316 L stainless steel and Ti-6Al-4V powder layers. The relevance of vapor driven entrainment of metal micro-particles to similar fluid dynamic studies in other fields of science will be discussed.

The use of automated, unmanned aerial vehicles (drones) to deliver commercial packages is poised to become a new industry, significantly shifting energy use in the freight sector. Here we find the current practical range of multi-copters to be about 4 km with current battery technology, requiring a new network of urban warehouses or waystations as support. We show that, although drones consume less energy per package-km than delivery trucks, the additional warehouse energy required and the longer distances traveled by drones per package greatly increase the life-cycle impacts. Still, in most cases examined, the impacts of package delivery by small drone are lower than ground-based delivery. Results suggest that, if carefully deployed, drone-based delivery could reduce greenhouse gas emissions and energy use in the freight sector. To realize the environmental benefits of drone delivery, regulators and firms should focus on minimizing extra warehousing and limiting the size of drones.

Large scale scientific simulation codes typically run on a cluster of CPUs that write/read time steps to/from a single file system. As data sets are constantly growing in size, this increasingly leads to I/O bottlenecks. When the rate at which data is produced exceeds the available I/O bandwidth, the simulation stalls and the CPUs are idle. Data compression can alleviate this problem by using some CPU cycles to reduce the amount of data needed to be transfered. Most compression schemes, however, are designed to operate offline and seek to maximize compression, not throughput. Furthermore, they often require quantizing floating-point values onto a uniform integer grid, which disqualifies their use in applications where exact values must be retained. We propose a simple scheme for lossless, online compression of floating-point data that transparently integrates into the I/O of many applications. A plug-in scheme for data-dependent prediction makes our scheme applicable to a wide variety of data used in visualization, such as unstructured meshes, point sets, images, and voxel grids. We achieve state-of-the-art compression rates and speeds, the latter in part due to an improved entropy coder. We demonstrate that this significantly accelerates I/O throughput in real simulation runs. Unlike previous schemes, our method also adapts well to variable-precision floating-point and integer data.

A sample of 4208 objects with magnitude 15 < g* < 22 and colors of main-sequence A stars have been selected from 370 deg(2) of Sloan Digital Sky Survey (SDSS) commissioning observations. The data is from two long, narrow stripes, each with an opening angle of greater than 60 degrees, at Galactic latitudes 36 degrees < \\b\\ < 63 degrees on the celestial equator. Relative photometric calibrations good to 2% and consistent absolute photometry allows this uniform sample to be treated statistically over the large area. An examination of the sample's distribution shows that these stars trace considerable substructure in the halo. Large overdensities of A-colored stars in the north at (l, b, R) = (350 degrees, 50 degrees, 46 kpc) and in the south at (157, -58, 33 kpc) and extending over tens of degrees are present in the halo of the Milky Way. Ivezic ct al. have detected the northern structure from a sample of RR Lyrae stars in the SDSS. Using photometry to separate the stars by surface gravity, both structures are shown to contain a sequence of low surface gravity stars consistent with identification as a blue horizontal branch (BHB). Both structures also contain a population of high surface gravity stars 2 mag fainter than the BHB stars, consistent with their identification as blue stragglers (BSs). The majority of the high surface gravity stars in the Galactic halo may be BS stars like these. A population of F stars associated with the A star excess in the southern structure is detected (the F stars in the northern structure at 46 kpc would be too faint for the SDSS to detect). From the numbers of detected BHB stars, lower limits to the implied mass of the structures are 6 x 10(6) M-circle dot and 2 x 10(6) M-circle dot, although one does not yet know the full spatial extent of the structures. The fact that two such large clumps have been detected in a survey of only 1% of the sky indicates that such structures are not uncommon in the halo. Simple spheroidal parameters are fit to a complete sample of the remaining unclumped BHB stars and yield (at r < 40 kpc) a fit to a halo distribution with flattening (c/a = 0.65 +/- 0.2) and a density falloff exponent of alpha = -3.2 +/- 0.3.