Showing papers by "Argonne National Laboratory published in 2012"
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
9,282 citations
TL;DR: It is shown that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
Abstract: DNA sequencing continues to decrease in cost with the Illumina HiSeq2000 generating up to 600 Gb of paired-end 100 base reads in a ten-day run. Here we present a protocol for community amplicon sequencing on the HiSeq2000 and MiSeq Illumina platforms, and apply that protocol to sequence 24 microbial communities from host-associated and free-living environments. A critical question as more sequencing platforms become available is whether biological conclusions derived on one platform are consistent with what would be derived on a different platform. We show that the protocol developed for these instruments successfully recaptures known biological results, and additionally that biological conclusions are consistent across sequencing platforms (the HiSeq2000 versus the MiSeq) and across the sequenced regions of amplicons.
6,840 citations
Tohoku University1, University of Zurich2, Lawrence Berkeley National Laboratory3, Stanford University4, College of William & Mary5, University of Genoa6, University of Urbino7, CERN8, Budker Institute of Nuclear Physics9, University of California, Irvine10, Cornell University11, Argonne National Laboratory12, ETH Zurich13, Tata Institute of Fundamental Research14, Hillsdale College15, Spanish National Research Council16, Ohio State University17, University of Notre Dame18, Kent State University19, University of California, San Diego20, University of California, Berkeley21, University of Minnesota22, University of Alabama23, University of Helsinki24, Los Alamos National Laboratory25, California Institute of Technology26, George Washington University27, Syracuse University28, Lawrence Livermore National Laboratory29, Oklahoma State University–Stillwater30, University of Washington31, Max Planck Society32, Boston University33, University of California, Los Angeles34, Royal Holloway, University of London35, Université Paris-Saclay36, Fermilab37, University of Pennsylvania38, University of Illinois at Urbana–Champaign39, University of Bristol40, University of Tokyo41, University of Delaware42, Carnegie Mellon University43, University of California, Santa Cruz44, Karlsruhe Institute of Technology45, Heidelberg University46, Florida State University47, Carleton University48, University of Mainz49, University of Edinburgh50, Brookhaven National Laboratory51, Durham University52, University of Lausanne53, Massachusetts Institute of Technology54, University of Southampton55, Nagoya University56, University of Oxford57, Northwestern University58, University of British Columbia59, Columbia University60, Lund University61, University of Sheffield62, University of California, Santa Barbara63, Iowa State University64, University of Alberta65, University of Cambridge66
TL;DR: The Particle Data Group's biennial review as mentioned in this paper summarizes much of particle physics, using data from previous editions, plus 2658 new measurements from 644 papers, and lists, evaluates, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons.
Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions, plus 2658 new measurements from 644 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. Among the 112 reviews are many that are new or heavily revised including those on Heavy-Quark and Soft-Collinear Effective Theory, Neutrino Cross Section Measurements, Monte Carlo Event Generators, Lattice QCD, Heavy Quarkonium Spectroscopy, Top Quark, Dark Matter, V-cb & V-ub, Quantum Chromodynamics, High-Energy Collider Parameters, Astrophysical Constants, Cosmological Parameters, and Dark Matter. A booklet is available containing the Summary Tables and abbreviated versions of some of the other sections of this full Review. All tables, listings, and reviews (and errata) are also available on the Particle Data Group website: http://pdg.lbl.gov.
4,465 citations
TL;DR: It is shown that heat-carrying phonons with long mean free paths can be scattered by controlling and fine-tuning the mesoscale architecture of nanostructured thermoelectric materials, and an increase in ZT beyond the threshold of 2 highlights the role of, and need for, multiscale hierarchical architecture in controlling phonon scattering in bulk thermoeLECTrics.
Abstract: Controlling the structure of thermoelectric materials on all length scales (atomic, nanoscale and mesoscale) relevant for phonon scattering makes it possible to increase the dimensionless figure of merit to more than two, which could allow for the recovery of a significant fraction of waste heat with which to produce electricity.
3,670 citations
TL;DR: The Review will consider some of the current scientific issues underpinning lithium batteries and electric double-layer capacitors.
Abstract: Energy-storage technologies, including electrical double-layer capacitors and rechargeable batteries, have attracted significant attention for applications in portable electronic devices, electric vehicles, bulk electricity storage at power stations, and “load leveling” of renewable sources, such as solar energy and wind power. Transforming lithium batteries and electric double-layer capacitors requires a step change in the science underpinning these devices, including the discovery of new materials, new electrochemistry, and an increased understanding of the processes on which the devices depend. The Review will consider some of the current scientific issues underpinning lithium batteries and electric double-layer capacitors.
2,412 citations
TL;DR: The overall catalytic activities for these reaction as a function of a more fundamental property, a descriptor, OH-M(2+δ) bond strength (0 ≤ δ ≤ 1.5), provide the foundation for rational design of 'active sites' for practical alkaline HER and OER electrocatalysts.
Abstract: Design and synthesis of materials for efficient electrochemical transformation of water to molecular hydrogen and of hydroxyl ions to oxygen in alkaline environments is of paramount importance in reducing energy losses in water–alkali electrolysers. Here, using 3d-M hydr(oxy)oxides, with distinct stoichiometries and morphologies in the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) regions, we establish the overall catalytic activities for these reaction as a function of a more fundamental property, a descriptor, OH–M2+δ bond strength (0 ≤ δ ≤ 1.5). This relationship exhibits trends in reactivity (Mn < Fe < Co < Ni), which is governed by the strength of the OH–M2+δ energetic (Ni < Co < Fe < Mn). These trends are found to be independent of the source of the OH, either the supporting electrolyte (for the OER) or the water dissociation product (for the HER). The successful identification of these electrocatalytic trends provides the foundation for rational design of ‘active sites’ for practical alkaline HER and OER electrocatalysts. Efficient electrochemical transformation of water to molecular hydrogen and of hydroxyl ions to oxygen in alkaline environments is important for reducing energy losses in water–alkali electrolysers. Insight into the activities of hydr(oxy)oxides on platinum catalyst surfaces for hydrogen and oxygen evolution reactions should prove significant for designing practical alkaline electrocatalysts.
2,271 citations
TL;DR: In this article, the authors show that 2 and 5 times higher energy densities are required to meet the performance goals of a future generation of plug-in hybrid-electric vehicles (PHEVs) with a 40-80 mile all-electric range, and all-EVs with a 300-400 mile range, respectively.
Abstract: The escalating and unpredictable cost of oil, the concentration of major oil resources in the hands of a few politically sensitive nations, and the long-term impact of CO2 emissions on global climate constitute a major challenge for the 21st century. They also constitute a major incentive to harness alternative sources of energy and means of vehicle propulsion. Today's lithium-ion batteries, although suitable for small-scale devices, do not yet have sufficient energy or life for use in vehicles that would match the performance of internal combustion vehicles. Energy densities 2 and 5 times greater are required to meet the performance goals of a future generation of plug-in hybrid-electric vehicles (PHEVs) with a 40–80 mile all-electric range, and all-electric vehicles (EVs) with a 300–400 mile range, respectively. Major advances have been made in lithium-battery technology over the past two decades by the discovery of new materials and designs through intuitive approaches, experimental and predictive reasoning, and meticulous control of surface structures and chemical reactions. Further improvements in energy density of factors of two to three may yet be achievable for current day lithium-ion systems; factors of five or more may be possible for lithium–oxygen systems, ultimately leading to our ability to confine extremely high potential energy in a small volume without compromising safety, but only if daunting technological barriers can be overcome.
2,105 citations
TL;DR: Interactions between diverse synthetic, multivalent macromolecules (including multi-domain proteins and RNA) produce sharp liquid–liquid-demixing phase separations, generating micrometre-sized liquid droplets in aqueous solution.
Abstract: Cells are organized on length scales ranging from angstrom to micrometres. However, the mechanisms by which angstrom-scale molecular properties are translated to micrometre-scale macroscopic properties are not well understood. Here we show that interactions between diverse synthetic, multivalent macromolecules (including multi-domain proteins and RNA) produce sharp liquid-liquid-demixing phase separations, generating micrometre-sized liquid droplets in aqueous solution. This macroscopic transition corresponds to a molecular transition between small complexes and large, dynamic supramolecular polymers. The concentrations needed for phase transition are directly related to the valency of the interacting species. In the case of the actin-regulatory protein called neural Wiskott-Aldrich syndrome protein (N-WASP) interacting with its established biological partners NCK and phosphorylated nephrin, the phase transition corresponds to a sharp increase in activity towards an actin nucleation factor, the Arp2/3 complex. The transition is governed by the degree of phosphorylation of nephrin, explaining how this property of the system can be controlled to regulatory effect by kinases. The widespread occurrence of multivalent systems suggests that phase transitions may be used to spatially organize and biochemically regulate information throughout biology.
1,816 citations
TL;DR: A machine learning model is introduced to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only, and applicability is demonstrated for the prediction of molecular atomization potential energy curves.
Abstract: We introduce a machine learning model to predict atomization energies of a diverse set of organic molecules, based on nuclear charges and atomic positions only. The problem of solving the molecular Schrodinger equation is mapped onto a nonlinear statistical regression problem of reduced complexity. Regression models are trained on and compared to atomization energies computed with hybrid density- functional theory. Cross validation over more than seven thousand organic molecules yields a mean absolute error of � 10 kcal=mol. Applicability is demonstrated for the prediction of molecular atomization potential energy curves.
1,755 citations
TL;DR: Ame2012 as discussed by the authors is the second part of the new evaluation of atomic masses, Ame2012. From the results of a least-squares calculation, described in Part I, for all accepted experimental data, derive here tables and graphs to replace those of Ame2003.
Abstract: This paper is the second part of the new evaluation of atomic masses, Ame2012. From the results of a least-squares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs to replace those of Ame2003. The first table lists atomic masses. It is followed by a table of the influences of data on primary nuclides, a table of separation energies and reaction energies, and finally, a series of graphs of separation and decay energies. The last section in this paper lists all references to the input data used in Part I of this Ame2012 and also to the data included in the Nubase2012 evaluation (first paper in this issue).
1,432 citations
TL;DR: Dietary fats, by promoting changes in host bile acid composition, can markedly alter conditions for gut microbial assemblage, resulting in dysbiosis that can perturb immune homeostasis, providing a plausible mechanistic basis by which Western-type diets high in certain saturated fats might increase the prevalence of complex immune-mediated diseases like inflammatory bowel disease in genetically susceptible hosts.
Abstract: The composite human microbiome of Western populations has probably changed over the past century, brought on by new environmental triggers that often have a negative impact on human health. Here we show that consumption of a diet high in saturated (milk-derived) fat, but not polyunsaturated (safflower oil) fat, changes the conditions for microbial assemblage and promotes the expansion of a low-abundance, sulphite-reducing pathobiont, Bilophila wadsworthia. This was associated with a pro-inflammatory T helper type 1 (T(H)1) immune response and increased incidence of colitis in genetically susceptible Il10(−/−), but not wild-type mice. These effects are mediated by milk-derived-fat-promoted taurine conjugation of hepatic bile acids, which increases the availability of organic sulphur used by sulphite-reducing microorganisms like B. wadsworthia. When mice were fed a low-fat diet supplemented with taurocholic acid, but not with glycocholic acid, for example, a bloom of B. wadsworthia and development of colitis were observed in Il10(−/−) mice. Together these data show that dietary fats, by promoting changes in host bile acid composition, can markedly alter conditions for gut microbial assemblage, resulting in dysbiosis that can perturb immune homeostasis. The data provide a plausible mechanistic basis by which Western-type diets high in certain saturated fats might increase the prevalence of complex immune-mediated diseases like inflammatory bowel disease in genetically susceptible hosts.
TL;DR: As the most comprehensive survey of soil taxonomic, phylogenetic, and functional diversity to date, this study demonstrates that metagenomic approaches can be used to build a predictive understanding of how microbial diversity and function vary across terrestrial biomes.
Abstract: For centuries ecologists have studied how the diversity and functional traits of plant and animal communities vary across biomes. In contrast, we have only just begun exploring similar questions for soil microbial communities despite soil microbes being the dominant engines of biogeochemical cycles and a major pool of living biomass in terrestrial ecosystems. We used metagenomic sequencing to compare the composition and functional attributes of 16 soil microbial communities collected from cold deserts, hot deserts, forests, grasslands, and tundra. Those communities found in plant-free cold desert soils typically had the lowest levels of functional diversity (diversity of protein-coding gene categories) and the lowest levels of phylogenetic and taxonomic diversity. Across all soils, functional beta diversity was strongly correlated with taxonomic and phylogenetic beta diversity; the desert microbial communities were clearly distinct from the nondesert communities regardless of the metric used. The desert communities had higher relative abundances of genes associated with osmoregulation and dormancy, but lower relative abundances of genes associated with nutrient cycling and the catabolism of plant-derived organic compounds. Antibiotic resistance genes were consistently threefold less abundant in the desert soils than in the nondesert soils, suggesting that abiotic conditions, not competitive interactions, are more important in shaping the desert microbial communities. As the most comprehensive survey of soil taxonomic, phylogenetic, and functional diversity to date, this study demonstrates that metagenomic approaches can be used to build a predictive understanding of how microbial diversity and function vary across terrestrial biomes.
TL;DR: The Double Chooz experiment presents an indication of reactor electron antineutrino disappearance consistent with neutrino oscillations, and an observed-to-predicted ratio of events of 0.944±0.016 and a deficit can be interpreted as a nonzero value of the still unmeasured neutrinos mixing parameter sin(2)2θ(13).
Abstract: The Double Chooz experiment presents an indication of reactor electron antineutrino disappearance consistent with neutrino oscillations. An observed-to-predicted ratio of events of 0.944±0.016(stat)±0.040(syst) was obtained in 101 days of running at the Chooz nuclear power plant in France, with two 4.25GWth reactors. The results were obtained from a single 10m3 fiducial volume detector located 1050 m from the two reactor cores. The reactor antineutrino flux prediction used the Bugey4 flux measurement after correction for differences in core composition. The deficit can be interpreted as an indication of a nonzero value of the still unmeasured neutrino mixing parameter sin22θ13. Analyzing both the rate of the prompt positrons and their energy spectrum, we find sin22θ13=0.086±0.041(stat)±0.030(syst), or, at 90% C.L., 0.017
TL;DR: In this article, the authors presented calculations on the global fuel energy consumption used to overcome friction in passenger cars in terms of friction in the engine, transmission, tires, and brakes.
Goddard Institute for Space Studies1, Stockholm Environment Institute2, International Institute for Applied Systems Analysis3, United States Environmental Protection Agency4, Middlebury College5, Harvard University6, Argonne National Laboratory7, University of California, San Diego8, Asian Institute of Technology9, King's College London10, United Nations Environment Programme11
TL;DR: 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050 and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond are identified.
Abstract: Tropospheric ozone and black carbon (BC) contribute to both degraded air quality and global warming. We considered ~400 emission control measures to reduce these pollutants by using current technology and experience. We identified 14 measures targeting methane and BC emissions that reduce projected global mean warming ~0.5°C by 2050. This strategy avoids 0.7 to 4.7 million annual premature deaths from outdoor air pollution and increases annual crop yields by 30 to 135 million metric tons due to ozone reductions in 2030 and beyond. Benefits of methane emissions reductions are valued at $700 to $5000 per metric ton, which is well above typical marginal abatement costs (less than $250). The selected controls target different sources and influence climate on shorter time scales than those of carbon dioxide–reduction measures. Implementing both substantially reduces the risks of crossing the 2°C threshold.
TL;DR: A nickel-rich lithium transition-metal oxide with a very high capacity where the nickel concentration decreases linearly whereas the manganese concentration increases linearly from the centre to the outer layer of each particle is reported.
Abstract: Nickel-rich layered lithium transition metal oxides have been investigated as high-energy cathode materials for rechargeable lithium batteries because of their high specific capacity and relatively low cost. Such an oxide with high capacity (215 mA h g-1), where the nickel concentration decreases linearly whereas the manganese concentration increases linearly from the centre to the outer layer of each particle, is now proposed. Nickel-rich layered lithium transition-metal oxides, LiNi1−xMxO2 (M = transition metal), have been under intense investigation as high-energy cathode materials for rechargeable lithium batteries because of their high specific capacity and relatively low cost1,2,3. However, the commercial deployment of nickel-rich oxides has been severely hindered by their intrinsic poor thermal stability at the fully charged state and insufficient cycle life, especially at elevated temperatures1,2,3,4,5,6. Here, we report a nickel-rich lithium transition-metal oxide with a very high capacity (215 mA h g−1), where the nickel concentration decreases linearly whereas the manganese concentration increases linearly from the centre to the outer layer of each particle. Using this nano-functional full-gradient approach, we are able to harness the high energy density of the nickel-rich core and the high thermal stability and long life of the manganese-rich outer layers. Moreover, the micrometre-size secondary particles of this cathode material are composed of aligned needle-like nanosize primary particles, resulting in a high rate capability. The experimental results suggest that this nano-functional full-gradient cathode material is promising for applications that require high energy, long calendar life and excellent abuse tolerance such as electric vehicles.
TL;DR: In this paper, the authors proposed a robust optimization approach to accommodate wind output uncertainty, with the objective of providing a robust unit commitment schedule for the thermal generators in the day-ahead market that minimizes the total cost under the worst wind power output scenario.
Abstract: As renewable energy increasingly penetrates into power grid systems, new challenges arise for system operators to keep the systems reliable under uncertain circumstances, while ensuring high utilization of renewable energy. With the naturally intermittent renewable energy, such as wind energy, playing more important roles, system robustness becomes a must. In this paper, we propose a robust optimization approach to accommodate wind output uncertainty, with the objective of providing a robust unit commitment schedule for the thermal generators in the day-ahead market that minimizes the total cost under the worst wind power output scenario. Robust optimization models the randomness using an uncertainty set which includes the worst-case scenario, and protects this scenario under the minimal increment of costs. In our approach, the power system will be more reliable because the worst-case scenario has been considered. In addition, we introduce a variable to control the conservatism of our model, by which we can avoid over-protection. By considering pumped-storage units, the total cost is reduced significantly.
TL;DR: The results suggested that seasonal changes in environmental variables are more important than trophic interactions, and correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or betweenacteria and environmental variables.
Abstract: Here we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site off Plymouth, UK. Data treatment effected the estimation of community richness over a 6-year period, whereby 8794 operational taxonomic units (OTUs) were identified using single-linkage preclustering and 21 130 OTUs were identified by denoising the data. The Alphaproteobacteria were the most abundant Class, and the most frequently recorded OTUs were members of the Rickettsiales (SAR 11) and Rhodobacteriales. This near-surface ocean bacterial community showed strong repeatable seasonal patterns, which were defined by winter peaks in diversity across all years. Environmental variables explained far more variation in seasonally predictable bacteria than did data on protists or metazoan biomass. Change in day length alone explains >65% of the variance in community diversity. The results suggested that seasonal changes in environmental variables are more important than trophic interactions. Interestingly, microbial association network analysis showed that correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or between bacteria and environmental variables.
09 Feb 2012
TL;DR: This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing.
Abstract: Metagenomics applies a suite of genomic technologies and bioinformatics tools to directly access the genetic content of entire communities of organisms. The field of metagenomics has been responsible for substantial advances in microbial ecology, evolution, and diversity over the past 5 to 10 years, and many research laboratories are actively engaged in it now. With the growing numbers of activities also comes a plethora of methodological knowledge and expertise that should guide future developments in the field. This review summarizes the current opinions in metagenomics, and provides practical guidance and advice on sample processing, sequencing technology, assembly, binning, annotation, experimental design, statistical analysis, data storage, and data sharing. As more metagenomic datasets are generated, the availability of standardized procedures and shared data storage and analysis becomes increasingly important to ensure that output of individual projects can be assessed and compared.
TL;DR: Nika is an Igor Pro-based package for correction, calibration and reduction of two-dimensional area-detector data into one-dimensional data (`lineouts'), open source and highly flexible.
Abstract: Nika is an Igor Pro-based package for correction, calibration and reduction of two-dimensional area-detector data into one-dimensional data (`lineouts'). It is free (although the user needs a paid license for Igor Pro), open source and highly flexible. While typically used for small-angle X-ray scattering (SAXS) data, it can also be used for grazing-incidence SAXS data, wide-angle diffraction data and even small-angle neutron scattering data. It has been widely available to the user community since about 2005, and it is currently used at the SAXS instruments of selected large-scale facilities as their main data reduction package. It is, however, also suitable for desktop instruments when the manufacturer's software is not available or appropriate. Since it is distributed as source code, it can be scrutinized, verified and modified by users to suit their needs.
TL;DR: In this article, localized surface plasmons and their effects on semiconductors, particularly in terms of energy transfer, scattering, and hot electron transfer, are reviewed, and the relevant physics, device geometries, and research progress in this area are discussed.
Abstract: The study of the optoelectronic effects of plasmonic metal nanoparticles on semiconductors has led to compelling evidence for plasmon-enhanced water splitting. We review the relevant physics, device geometries, and research progress in this area. We focus on localized surface plasmons and their effects on semiconductors, particularly in terms of energy transfer, scattering, and hot electron transfer.
TL;DR: In this paper, an updated H2/O2 kinetic model based on that of Li et al. (Int J Chem Kinet 36, 2004, 566-575) is presented and tested against a wide range of combustion targets.
Abstract: An updated H2/O2 kinetic model based on that of Li et al. (Int J Chem Kinet 36, 2004, 566–575) is presented and tested against a wide range of combustion targets. The primary motivations of the model revision are to incorporate recent improvements in rate constant treatment and resolve discrepancies between experimental data and predictions using recently published kinetic models in dilute, high-pressure flames.
Attempts are made to identify major remaining sources of uncertainties, in both the reaction rate parameters and the assumptions of the kinetic model, affecting predictions of relevant combustion behavior. With regard to model parameters, present uncertainties in the temperature and pressure dependence of rate constants for HO2 formation and consumption reactions are demonstrated to substantially affect predictive capabilities at high-pressure, low-temperature conditions. With regard to model assumptions, calculations are performed to investigate several reactions/processes that have not received much attention previously. Results from ab initio calculations and modeling studies imply that inclusion of H + HO2 = H2O + O in the kinetic model might be warranted, though further studies are necessary to ascertain its role in combustion modeling. In addition, it appears that characterization of nonlinear bath-gas mixture rule behavior for H + O2(+ M) = HO2(+ M) in multicomponent bath gases might be necessary to predict high-pressure flame speeds within ∼15%.
The updated model is tested against all of the previous validation targets considered by Li et al. as well as new targets from a number of recent studies. Special attention is devoted to establishing a context for evaluating model performance against experimental data by careful consideration of uncertainties in measurements, initial conditions, and physical model assumptions. For example, ignition delay times in shock tubes are shown to be sensitive to potential impurity effects, which have been suggested to accelerate early radical pool growth in shock tube speciation studies. In addition, speciation predictions in burner-stabilized flames are found to be more sensitive to uncertainties in experimental boundary conditions than to uncertainties in kinetics and transport. Predictions using the present model adequately reproduce previous validation targets and show substantially improved agreement against recent high-pressure flame speed and shock tube speciation measurements. Comparisons of predictions of several other kinetic models with the experimental data for nearly the entire validation set used here are also provided in the Supporting Information. © 2011 Wiley Periodicals, Inc. Int J Chem Kinet 44: 444–474, 2012
TL;DR: It is shown that alumina (Al2O3) overcoating of supported metal nanoparticles (NPs) effectively reduced deactivation by coking and sintering in high-temperature applications of heterogeneous catalysts.
Abstract: We showed that alumina (Al(2)O(3)) overcoating of supported metal nanoparticles (NPs) effectively reduced deactivation by coking and sintering in high-temperature applications of heterogeneous catalysts We overcoated palladium NPs with 45 layers of alumina through an atomic layer deposition (ALD) process that alternated exposures of the catalysts to trimethylaluminum and water at 200°C When these catalysts were used for 1 hour in oxidative dehydrogenation of ethane to ethylene at 650°C, they were found by thermogravimetric analysis to contain less than 6% of the coke formed on the uncoated catalysts Scanning transmission electron microscopy showed no visible morphology changes after reaction at 675°C for 28 hours The yield of ethylene was improved on all ALD Al(2)O(3) overcoated Pd catalysts
TL;DR: The BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications.
Abstract: We present the Biological Observation Matrix (BIOM, pronounced “biome”) format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the “ome-ome”) grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses. The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages. The BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.
TL;DR: The hydrogen evolution reaction rate on a Ni electrode modified by Ni(OH)(2) nanoclusters is about four times higher than on a bare Ni surface.
Abstract: Active in alkaline environment: The activity of nickel, silver, and copper catalysts for the electrochemical transformation of water to molecular hydrogen in alkaline solutions was enhanced by modification of the metal surfaces by Ni(OH)(2) (see picture; I = current density and η = overpotential). The hydrogen evolution reaction rate on a Ni electrode modified by Ni(OH)(2) nanoclusters is about four times higher than on a bare Ni surface.
TL;DR: The AlF(3)-coating enhanced the overall electrochemical characteristics of the electrode while overcoming the typical shortcomings of lithium-enriched cathodes, attributed to the transformation of the initial electrode layer to a spinel phase, induced by the Li chemical leaching effect of the AlF (3) coating layer.
Abstract: A Li[Li(0.19)Ni(0.16)Co(0.08)Mn(0.57)]O(2) cathode was coated with AlF(3) on the surface. The AlF(3)-coating enhanced the overall electrochemical characteristics of the electrode while overcoming the typical shortcomings of lithium-enriched cathodes. This improvement was attributed to the transformation of the initial electrode layer to a spinel phase, induced by the Li chemical leaching effect of the AlF(3) coating layer.
TL;DR: In this article, a multiobjective mixed-integer linear programming (mo-MILP) model is developed that accounts for major characteristics of cellulosic ethanol supply chains, including supply seasonality and geographical diversity.
Abstract: This article addresses the optimal design and planning of cellulosic ethanol supply chains under economic, environmental, and social objectives. The economic objective is measured by the total annualized cost, the environmental objective is measured by the life cycle greenhouse gas emissions, and the social objective is measured by the number of accrued local jobs. A multiobjective mixed-integer linear programming (mo-MILP) model is developed that accounts for major characteristics of cellulosic ethanol supply chains, including supply seasonality and geographical diversity, biomass degradation, feedstock density, diverse conversion pathways and byproducts, infrastructure compatibility, demand distribution, regional economy, and government incentives. Aspen Plus models for biorefineries with different feedstocks and conversion pathways are built to provide detailed techno-economic and emission analysis results for the mo-MILP model, which simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The mo-MILP problem is solved with an e-constraint method; and the resulting Pareto-optimal curves reveal the tradeoff between the economic, environmental, and social dimensions of the sustainable biofuel supply chains. The proposed approach is illustrated through two case studies for the state of Illinois. © 2011 American Institute of Chemical Engineers AIChE J, 2012
TL;DR: A combined search for the Standard Model Higgs boson with the ATLAS experiment at the LHC using datasets corresponding to integrated luminosities from 1.04 fb(-1) to 4.9 fb(1) of pp collisions is described in this paper.