Showing papers by "Pacific Northwest National Laboratory published in 2017"
Atlantic Oceanographic and Meteorological Laboratory1, University of Southern Mississippi2, University of California, San Diego3, University of California, San Francisco4, Indiana University5, IBM6, Broad Institute7, Massachusetts Institute of Technology8, Harvard University9, Northern Arizona University10, Pacific Northwest National Laboratory11, Argonne National Laboratory12, University of Illinois at Chicago13, University of Colorado Boulder14, Cooperative Institute for Research in Environmental Sciences15, University of Southern California16, University of Chicago17, Michigan State University18
TL;DR: A meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project is presented, creating both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.
Abstract: Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity.
1,676 citations
TL;DR: A high-performance atomic Fe catalyst derived from chemically Fe-doped zeolitic imidazolate frameworks (ZIFs) by directly bonding Fe ions to imidAZolate ligands within 3D frameworks holds great promise as a replacement for Pt in future PEMFCs.
Abstract: It remains a grand challenge to replace platinum group metal (PGM) catalysts with earth-abundant materials for the oxygen reduction reaction (ORR) in acidic media, which is crucial for large-scale deployment of proton exchange membrane fuel cells (PEMFCs). Here, we report a high-performance atomic Fe catalyst derived from chemically Fe-doped zeolitic imidazolate frameworks (ZIFs) by directly bonding Fe ions to imidazolate ligands within 3D frameworks. Although the ZIF was identified as a promising precursor, the new synthetic chemistry enables the creation of well-dispersed atomic Fe sites embedded into porous carbon without the formation of aggregates. The size of catalyst particles is tunable through synthesizing Fe-doped ZIF nanocrystal precursors in a wide range from 20 to 1000 nm followed by one-step thermal activation. Similar to Pt nanoparticles, the unique size control without altering chemical properties afforded by this approach is able to increase the number of PGM-free active sites. The best O...
1,086 citations
TL;DR: In this paper, LiPF6 was used as an additive in LiTFSI-LiBOB dual-salt/carbonate-solvent-based electrolytes to enhance the charging capability and cycling stability of Li metal batteries.
Abstract: Batteries using lithium (Li) metal as anodes are considered promising energy storage systems because of their high energy densities. However, safety concerns associated with dendrite growth along with limited cycle life, especially at high charge current densities, hinder their practical uses. Here we report that an optimal amount (0.05 M) of LiPF6 as an additive in LiTFSI–LiBOB dual-salt/carbonate-solvent-based electrolytes significantly enhances the charging capability and cycling stability of Li metal batteries. In a Li metal battery using a 4-V Li-ion cathode at a moderately high loading of 1.75 mAh cm−2, a cyclability of 97.1% capacity retention after 500 cycles along with very limited increase in electrode overpotential is accomplished at a charge/discharge current density up to 1.75 mA cm−2. The fast charging and stable cycling performances are ascribed to the generation of a robust and conductive solid electrolyte interphase at the Li metal surface and stabilization of the Al cathode current collector. Deployment of rechargeable Li metal batteries requires fast charging capability and long-term cycling stability. Here the authors demonstrate the battery application potential of using a small amount of LiPF6 in a dual-salt electrolyte.
955 citations
TL;DR: The Adaptive Poisson-Boltzmann Solver (APBS) as mentioned in this paper was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications.
Abstract: The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this manuscript, we discuss the models and capabilities that have recently been implemented within the APBS software package including: a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory based algorithm for determining p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics.
916 citations
TL;DR: There was some correlation between observed dramatic fluctuations in the gut microbiome and intensified medication due to a flare of the disease, and these results will help guide therapies that will redirect the Gut microbiome towards a healthy state and maintain remission in IBD.
Abstract: Inflammatory bowel disease (IBD) is characterized by flares of inflammation with a periodic need for increased medication and sometimes even surgery. The aetiology of IBD is partly attributed to a deregulated immune response to gut microbiome dysbiosis. Cross-sectional studies have revealed microbial signatures for different IBD subtypes, including ulcerative colitis, colonic Crohn's disease and ileal Crohn's disease. Although IBD is dynamic, microbiome studies have primarily focused on single time points or a few individuals. Here, we dissect the long-term dynamic behaviour of the gut microbiome in IBD and differentiate this from normal variation. Microbiomes of IBD subjects fluctuate more than those of healthy individuals, based on deviation from a newly defined healthy plane (HP). Ileal Crohn's disease subjects deviated most from the HP, especially subjects with surgical resection. Intriguingly, the microbiomes of some IBD subjects periodically visited the HP then deviated away from it. Inflammation was not directly correlated with distance to the healthy plane, but there was some correlation between observed dramatic fluctuations in the gut microbiome and intensified medication due to a flare of the disease. These results will help guide therapies that will redirect the gut microbiome towards a healthy state and maintain remission in IBD.
750 citations
TL;DR: This first of a pair of studies documents the MERRA-2 aerosol assimilation, including a description of the prognostic model, aerosol emissions, and the quality control of ingested observations, and provides initial validation and evaluation of the analyzed AOD fields.
Abstract: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA's previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.
705 citations
01 Sep 2017
TL;DR: Experiments show that while media fact-checking remains to be an open research question, stylistic cues can help determine the truthfulness of text.
Abstract: We present an analytic study on the language of news media in the context of political fact-checking and fake news detection. We compare the language of real news with that of satire, hoaxes, and propaganda to find linguistic characteristics of untrustworthy text. To probe the feasibility of automatic political fact-checking, we also present a case study based on PolitiFact.com using their factuality judgments on a 6-point scale. Experiments show that while media fact-checking remains to be an open research question, stylistic cues can help determine the truthfulness of text.
674 citations
Oklahoma State University–Stillwater1, Macquarie University2, University of Sydney3, University of Utah4, Max Planck Society5, University of Alberta6, University of California, Irvine7, University of New Mexico8, University of Nebraska–Lincoln9, United States Geological Survey10, University of Washington11, University of Arizona12, University of Sheffield13, University of Tasmania14, ETH Zurich15, University of California, Davis16, Los Alamos National Laboratory17, Nanchang Institute of Technology18, University of Wyoming19, Swedish University of Agricultural Sciences20, University of Coimbra21, United States Forest Service22, Northern Arizona University23, Swiss Federal Institute for Forest, Snow and Landscape Research24, University of São Paulo25, University of Oxford26, University of California, Santa Cruz27, Humboldt State University28, Fordham University29, Centre national de la recherche scientifique30, University of Edinburgh31, Hobart Corporation32, Spanish National Research Council33, University of Chile34, Idaho State University35, University of Basilicata36, United States Department of Agriculture37, Colorado State University38, University of Montana39, University of Delaware40, Duke University41, University of Western Ontario42, Sonora Institute of Technology43, Pacific Northwest National Laboratory44
TL;DR: It is shown that, across multiple tree species, loss of xylem conductivity above 60% is associated with mortality, while carbon starvation is not universal, indicating that evidence supporting carbon starvation was not universal.
Abstract: Widespread tree mortality associated with drought has been observed on all forested continents and global change is expected to exacerbate vegetation vulnerability. Forest mortality has implications for future biosphere-atmosphere interactions of carbon, water and energy balance, and is poorly represented in dynamic vegetation models. Reducing uncertainty requires improved mortality projections founded on robust physiological processes. However, the proposed mechanisms of drought-induced mortality, including hydraulic failure and carbon starvation, are unresolved. A growing number of empirical studies have investigated these mechanisms, but data have not been consistently analysed across species and biomes using a standardized physiological framework. Here, we show that xylem hydraulic failure was ubiquitous across multiple tree taxa at drought-induced mortality. All species assessed had 60% or higher loss of xylem hydraulic conductivity, consistent with proposed theoretical and modelled survival thresholds. We found diverse responses in non-structural carbohydrate reserves at mortality, indicating that evidence supporting carbon starvation was not universal. Reduced non-structural carbohydrates were more common for gymnosperms than angiosperms, associated with xylem hydraulic vulnerability, and may have a role in reducing hydraulic function. Our finding that hydraulic failure at drought-induced mortality was persistent across species indicates that substantial improvement in vegetation modelling can be achieved using thresholds in hydraulic function.
651 citations
TL;DR: It is found the formation of the intragranular cracks is directly associated with high-voltage cycling, an electrochemically driven and diffusion-controlled process.
Abstract: LiNi1/3Mn1/3Co1/3O2-layered cathode is often fabricated in the form of secondary particles, consisting of densely packed primary particles. This offers advantages for high energy density and alleviation of cathode side reactions/corrosions, but introduces drawbacks such as intergranular cracking. Here, we report unexpected observations on the nucleation and growth of intragranular cracks in a commercial LiNi1/3Mn1/3Co1/3O2 cathode by using advanced scanning transmission electron microscopy. We find the formation of the intragranular cracks is directly associated with high-voltage cycling, an electrochemically driven and diffusion-controlled process. The intragranular cracks are noticed to be characteristically initiated from the grain interior, a consequence of a dislocation-based crack incubation mechanism. This observation is in sharp contrast with general theoretical models, predicting the initiation of intragranular cracks from grain boundaries or particle surfaces. Our study emphasizes that maintaining structural stability is the key step towards high-voltage operation of layered-cathode materials.
597 citations
TL;DR: In this paper, a series of nanostructured hard carbon materials with controlled architectures is synthesized using a combination of in situ X-ray diffraction mapping, ex situ nuclear magnetic resonance (NMR), electron paramagnetic resonance, electrochemical techniques, and simulations.
Abstract: Hard carbon is one of the most promising anode materials for sodium-ion batteries, but the low Coulombic efficiency is still a key barrier. In this paper, a series of nanostructured hard carbon materials with controlled architectures is synthesized. Using a combination of in situ X-ray diffraction mapping, ex situ nuclear magnetic resonance (NMR), electron paramagnetic resonance, electrochemical techniques, and simulations, an “adsorption–intercalation” mechanism is established for Na ion storage. During the initial stages of Na insertion, Na ions adsorb on the defect sites of hard carbon with a wide adsorption energy distribution, producing a sloping voltage profile. In the second stage, Na ions intercalate into graphitic layers with suitable spacing to form NaC x compounds similar to the Li ion intercalation process in graphite, producing a flat low voltage plateau. The cation intercalation with a flat voltage plateau should be enhanced and the sloping region should be avoided. Guided by this knowledge, nonporous hard carbon material has been developed which has achieved high reversible capacity and Coulombic efficiency to fulfill practical application.
597 citations
TL;DR: Deep neural networks have been widely applied in the field of computational chemistry, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction as discussed by the authors.
Abstract: The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc.
Woods Hole Research Center1, Northern Arizona University2, University of Utah3, Carnegie Institution for Science4, California Institute of Technology5, University of Nevada, Reno6, University of New Mexico7, United States Forest Service8, Princeton University9, Oak Ridge National Laboratory10, University of Maine11, Pacific Northwest National Laboratory12, University of Illinois at Urbana–Champaign13, Auburn University14
TL;DR: This analysis of three independent datasets of gross primary productivity shows that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors.
Abstract: Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.
Pacific Northwest National Laboratory1, University of California, Davis2, University of California, Berkeley3, University of California, Irvine4, Cooperative Institute for Research in Environmental Sciences5, Brookhaven National Laboratory6, Harvard University7, Georgia Institute of Technology8, University of Helsinki9, Colorado State University10, Lund University11, California Institute of Technology12, University of Washington13
TL;DR: In this paper, a review summarizes some of the important developments during the past decade in understanding secondary organic aerosol (SOA) formation, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity.
Abstract: Anthropogenic emissions and land use changes have modified atmospheric aerosol concentrations and size distributions over time. Understanding preindustrial conditions and changes in organic aerosol due to anthropogenic activities is important because these features (1) influence estimates of aerosol radiative forcing and (2) can confound estimates of the historical response of climate to increases in greenhouse gases. Secondary organic aerosol (SOA), formed in the atmosphere by oxidation of organic gases, represents a major fraction of global submicron-sized atmospheric organic aerosol. Over the past decade, significant advances in understanding SOA properties and formation mechanisms have occurred through measurements, yet current climate models typically do not comprehensively include all important processes. This review summarizes some of the important developments during the past decade in understanding SOA formation. We highlight the importance of some processes that influence the growth of SOA particles to sizes relevant for clouds and radiative forcing, including formation of extremely low volatility organics in the gas phase, acid-catalyzed multiphase chemistry of isoprene epoxydiols, particle-phase oligomerization, and physical properties such as volatility and viscosity. Several SOA processes highlighted in this review are complex and interdependent and have nonlinear effects on the properties, formation, and evolution of SOA. Current global models neglect this complexity and nonlinearity and thus are less likely to accurately predict the climate forcing of SOA and project future climate sensitivity to greenhouse gases. Efforts are also needed to rank the most influential processes and nonlinear process-related interactions, so that these processes can be accurately represented in atmospheric chemistry-climate models.
Posted Content•
TL;DR: The white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.
Abstract: This white paper summarizes the workshop "U.S. Cosmic Visions: New Ideas in Dark Matter" held at University of Maryland on March 23-25, 2017.
TL;DR: FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs.
Abstract: Summary FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data. Availability and implementation FQC is implemented in Python 3 and Javascript, and is maintained under an MIT license. Documentation and source code is available at: https://github.com/pnnl/fqc . Contact joseph.brown@pnnl.gov.
TL;DR: In this paper, the authors present a critical overview of recent progress in conventional aqueous redox-flow batteries and next-generation flow batteries, highlighting the latest innovative alternative materials.
Abstract: Spatial separation of the electrolyte and electrode is the main characteristic of flow-battery technologies, which liberates them from the constraints of overall energy content and the energy/power ratio. The concept of a flowing electrolyte not only presents a cost-effective approach for large-scale energy storage, but has also recently been used to develop a wide range of new hybrid energy storage and conversion systems. The advent of flow-based lithium-ion, organic redox-active materials, metal–air cells and photoelectrochemical batteries promises new opportunities for advanced electrical energy-storage technologies. In this Review, we present a critical overview of recent progress in conventional aqueous redox-flow batteries and next-generation flow batteries, highlighting the latest innovative alternative materials. We outline their technical feasibility for use in long-term and large-scale electrical energy-storage devices, as well as the limitations that need to be overcome, providing our view of promising future research directions in the field of redox-flow batteries. Flow-battery technologies open a new age of large-scale electrical energy-storage systems. This Review highlights the latest innovative materials and their technical feasibility for next-generation flow batteries.
TL;DR: The first measurement of the tau lepton polarization P-tau(D*) in the decay (B) over bar -> D* tau(-) (v) over b (tau) as well as a new measurement of the ratio of the branching fractions was reported in this paper.
Abstract: We report the first measurement of the tau lepton polarization P-tau(D*) in the decay (B) over bar -> D* tau(-) (v) over bar (tau) as well as a newmeasurement of the ratio of the branching fractions R(D*) = B((B) over bar -> D* tau(-) (v) over bar (tau)) / B((B) over bar -> D* l(-) (v) over bar (l)), where l(-) denotes an electron or a muon, and the tau is reconstructed in the modes tau(-) -> pi(-) v(tau) and tau(-) -> rho(-) v(tau). We use the full data sample of 772 x 10(6) B (B) over bar pairs recorded with the Belle detector at the (KEKB) over bar electron-positron collider. Our results, P-tau(D*) = -0.38 +/- 0.51 (stat)(-0.16)(+0.21) (syst) and R(D*) = 0.270 +/- 0.035 (stat)(- 0.025)(+0.028) (syst), are consistent with the theoretical predictions of the standard model.
Pierre-and-Marie-Curie University1, Max Planck Society2, National Center for Atmospheric Research3, National Oceanic and Atmospheric Administration4, Princeton University5, Beijing Normal University6, Deutscher Wetterdienst7, Pacific Northwest National Laboratory8, University of Tokyo9, University of Exeter10
TL;DR: Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers.
Abstract: The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling with its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model...
TL;DR: In this article, a review of the recent progress and in depth understandings on the application of LMR cathode materials from a practical point of view is presented, focusing on addressing the fundamental problems of lithium and manganese-rich (LMR) cathodes while keeping practical considerations in mind.
Abstract: The lithium- and manganese-rich (LMR) layered structure cathodes exhibit one of the highest specific energies (≈900 W h kg−1) among all the cathode materials. However, the practical applications of LMR cathodes are still hindered by several significant challenges, including voltage fade, large initial capacity loss, poor rate capability and limited cycle life. Herein, we review the recent progress and in depth understandings on the application of LMR cathode materials from a practical point of view. Several key parameters of LMR cathodes that affect the LMR/graphite full-cell operation are systematically analyzed. These factors include the first-cycle capacity loss, voltage fade, powder tap density, and electrode density. New approaches to minimize the detrimental effects of these factors are highlighted in this work. We also provide perspectives for the future research on LMR cathode materials, focusing on addressing the fundamental problems of LMR cathodes while keeping practical considerations in mind.
Utrecht University1, United States Department of Energy2, National Autonomous University of Mexico3, National and Kapodistrian University of Athens4, University of Debrecen5, Leiden University6, Commonwealth Scientific and Industrial Research Organisation7, University of Göttingen8, Maynooth University9, University of Seville10, University of Natural Resources and Life Sciences, Vienna11, Broad Institute12, Huazhong Agricultural University13, State University of Campinas14, International Sleep Products Association15, Université libre de Bruxelles16, University of Nottingham17, Aix-Marseille University18, Pasteur Institute19, King Abdulaziz University20, Institut national de la recherche agronomique21, University of Helsinki22, University of Amsterdam23, University of St Andrews24, University of Ioannina25, Saint Petersburg State University26, Spanish National Research Council27, Federal University of São Carlos28, Swedish University of Agricultural Sciences29, Technical University of Berlin30, National Scientific and Technical Research Council31, Concordia University32, Kyungpook National University33, University of the Republic34, Karlsruhe Institute of Technology35, University of Sulaymaniyah36, University of Ljubljana37, Leibniz Association38, Stanford University39, Kansas State University40, Technical University of Denmark41, University of Wisconsin-Madison42, Pacific Northwest National Laboratory43, University of Jena44, University of São Paulo45, University of Kansas46, Imperial College London47, Université Paris-Saclay48, Vienna University of Technology49
TL;DR: In this article, a comparative genomics and experimental study of the aspergilli genus is presented, which allows for the first time a genus-wide view of the biological diversity of the Aspergillus and in many, but not all, cases linked genome differences to phenotype.
Abstract: Background: The fungal genus Aspergillus is of critical importance to humankind. Species include those with industrial applications, important pathogens of humans, animals and crops, a source of potent carcinogenic contaminants of food, and an important genetic model. The genome sequences of eight aspergilli have already been explored to investigate aspects of fungal biology, raising questions about evolution and specialization within this genus. Results: We have generated genome sequences for ten novel, highly diverse Aspergillus species and compared these in detail to sister and more distant genera. Comparative studies of key aspects of fungal biology, including primary and secondary metabolism, stress response, biomass degradation, and signal transduction, revealed both conservation and diversity among the species. Observed genomic differences were validated with experimental studies. This revealed several highlights, such as the potential for sex in asexual species, organic acid production genes being a key feature of black aspergilli, alternative approaches for degrading plant biomass, and indications for the genetic basis of stress response. A genome-wide phylogenetic analysis demonstrated in detail the relationship of the newly genome sequenced species with other aspergilli. Conclusions: Many aspects of biological differences between fungal species cannot be explained by current knowledge obtained from genome sequences. The comparative genomics and experimental study, presented here, allows for the first time a genus-wide view of the biological diversity of the aspergilli and in many, but not all, cases linked genome differences to phenotype. Insights gained could be exploited for biotechnological and medical applications of fungi.
TL;DR: MicroBooNE as discussed by the authors is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics.
Abstract: This paper describes the design and construction of the MicroBooNE liquid argon time projection chamber and associated systems. MicroBooNE is the first phase of the Short Baseline Neutrino program, located at Fermilab, and will utilize the capabilities of liquid argon detectors to examine a rich assortment of physics topics. In this document details of design specifications, assembly procedures, and acceptance tests are reported.
TL;DR: Detailed reaction kinetics are reported on low-temperature standard NH3-SCR, supplemented by DFT calculations, as strong evidence that the low-Temperature oxidation half-cycle occurs with the participation of two isolated CuI ions via formation of a transient [CuI(NH3)2]+-O2-[CuI (NH3]2]+ intermediate.
Abstract: Active centers in Cu/SSZ-13 selective catalytic reduction (SCR) catalysts have been recently identified as isolated Cu2+ and [CuII(OH)]+ ions. A redox reaction mechanism has also been established, where Cu ions cycle between CuI and CuII oxidation states during SCR reaction. While the mechanism for the reduction half-cycle (CuII → CuI) is reasonably well-understood, that for the oxidation half-cycle (CuI → CuII) remains an unsettled debate. Herein we report detailed reaction kinetics on low-temperature standard NH3-SCR, supplemented by DFT calculations, as strong evidence that the low-temperature oxidation half-cycle occurs with the participation of two isolated CuI ions via formation of a transient [CuI(NH3)2]+–O2–[CuI(NH3)2]+ intermediate. The feasibility of this reaction mechanism is confirmed from DFT calculations, and the simulated energy barrier and rate constants are consistent with experimental findings. Significantly, the low-temperature standard SCR mechanism proposed here provides full consiste...
TL;DR: The result is consistent with standard model (SM) expectations, where the largest discrepancy from a SM prediction is observed in the muon modes with a local significance of 2.6σ.
Abstract: We present a measurement of angular observables and a test of lepton flavor universality in the B -> K(+)l(+)l(-) decay, where l is either e or mu. The analysis is performed on a data sample corresponding to an integrated luminosity of 711 fb(-1) containing 772 x 10(6) B (B) over bar pairs, collected at the Upsilon(4S) resonance with the Belle detector at the asymmetric-energy e(+)e(-) collider KEKB. The result is consistent with standard model (SM) expectations, where the largest discrepancy from a SM prediction is observed in the muon modes with a local significance of 2.6 sigma.
TL;DR: In this paper, a cobalt-based bimetallic transition metal phosphide encapsulated in carbonized zeolitic imadazolate frameworks has been successfully synthesized and showed excellent activities toward both hydrogen evolution reaction (HER) and oxygen evolution reaction.
Abstract: Cobalt-based bimetallic phosphide encapsulated in carbonized zeolitic imadazolate frameworks has been successfully synthesized and showed excellent activities toward both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Density functional theory calculation and electrochemical measurements reveal that the electrical conductivity and electrochemical activity are closely associated with the Co2P/CoP mixed phase behaviors upon Cu metal doping. This relationship is found to be the decisive factor for enhanced electrocatalytic performance. Moreover, the precise control of Cu content in Co-host lattice effectively alters the Gibbs free energy for H* adsorption, which is favorable for facilitating reaction kinetics. Impressively, an optimized performance has been achieved with mild Cu doping in Cu0.3Co2.7P/nitrogen-doped carbon (NC) which exhibits an ultralow overpotential of 0.19 V at 10 mA cm–2 and satisfying stability for OER. Cu0.3Co2.7P/NC also shows excellent HER activity, affording a current density of 10 mA cm–2 at a low overpotential of 0.22 V. In addition, a homemade electrolyzer with Cu0.3Co2.7P/NC paired electrodes shows 60% larger current density than Pt/RuO2 couple at 1.74 V, along with negligible catalytic deactivation after 50 h operation. The manipulation of electronic structure by controlled incorporation of second metal sheds light on understanding and synthesizing bimetallic transition metal phosphides for electrolysis-based energy conversion.
TL;DR: An overview on the recent progress of high concentration electrolytes in different battery chemistries is provided and the formation mechanism and the nature of the SEI layers derived from concentrated electrolytes could be fundamentally distinct from those of the traditional SEI and thus enable unusual functions that cannot be realized using regular electrolytes.
Abstract: The electrolyte is an indispensable component in all electrochemical energy storage and conversion devices with batteries being a prime example. While most research efforts have been pursued on the materials side, the progress for the electrolyte is slow due to the decomposition of salts and solvents at low potentials, not to mention their complicated interactions with the electrode materials. The general properties of bulk electrolytes such as ionic conductivity, viscosity, and stability all affect the cell performance. However, for a specific electrochemical cell in which the cathode, anode, and electrolyte are optimized, it is the interface between the solid electrode and the liquid electrolyte, generally referred to as the solid electrolyte interphase (SEI), that dictates the rate of ion flow in the system. The commonly used electrolyte is within the range of 1-1.2 m based on the prior optimization experience, leaving the high concentration region insufficiently recognized. Recently, electrolytes with increased concentration (>1.0 m) have received intensive attention due to quite a few interesting discoveries in cells containing concentrated electrolytes. The formation mechanism and the nature of the SEI layers derived from concentrated electrolytes could be fundamentally distinct from those of the traditional SEI and thus enable unusual functions that cannot be realized using regular electrolytes. In this article, we provide an overview on the recent progress of high concentration electrolytes in different battery chemistries. The experimentally observed phenomena and their underlying fundamental mechanisms are discussed. New insights and perspectives are proposed to inspire more revolutionary solutions to address the interfacial challenges.
TL;DR: A global-scale analysis of future urban densities and associated energy use in the built environment under different urbanization scenarios and examining building energy use for heating and cooling finds that dense urban development leads to less urban energy use overall.
Abstract: Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios, we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7–40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas.
TL;DR: In this paper, the recent development of a variety of Redox-Active Organic Materials (ROMs) and associated battery designs in both aqueous and nonaqueous electrolytes are reviewed.
Abstract: Redox flow batteries (RFBs) are propitious stationary energy storage technologies with exceptional scalability and flexibility to improve the stability, efficiency, and sustainability of our power grid. The redox-active materials are the key component for RFBs with which to achieve high energy density and good cyclability. Traditional inorganic-based materials encounter critical technical and economic limitations such as low solubility, inferior electrochemical activity, and high cost. Redox-active organic materials (ROMs) are promising alternative “green” candidates to push the boundaries of energy storage because of the significant advantages of molecular diversity, structural tailorability, and natural abundance. Here, the recent development of a variety of ROMs and associated battery designs in both aqueous and nonaqueous electrolytes are reviewed. The critical challenges and potential research opportunities for developing practically relevant organic flow batteries are discussed.
TL;DR: In this article, a review of recent advances in 3D printing of electrochemical energy storage (EES) devices is presented, and a perspective on how to integrate the emerging 3D print technologies with existing technologies to create structures over multiple length scale from nano to macro for EES applications.
TL;DR: Improvements on the measurement accuracy of experimental parameters influencing IM separations provide standardized drift tube, nitrogen CCS values (DTCCSN2) for over 120 unique ion species with the lowest measurement uncertainty to date.
Abstract: Collision cross section (CCS) measurements resulting from ion mobility–mass spectrometry (IM-MS) experiments provide a promising orthogonal dimension of structural information in MS-based analytical separations. As with any molecular identifier, interlaboratory standardization must precede broad range integration into analytical workflows. In this study, we present a reference drift tube ion mobility mass spectrometer (DTIM-MS) where improvements on the measurement accuracy of experimental parameters influencing IM separations provide standardized drift tube, nitrogen CCS values (DTCCSN2) for over 120 unique ion species with the lowest measurement uncertainty to date. The reproducibility of these DTCCSN2 values are evaluated across three additional laboratories on a commercially available DTIM-MS instrument. The traditional stepped field CCS method performs with a relative standard deviation (RSD) of 0.29% for all ion species across the three additional laboratories. The calibrated single field CCS method...
01 Sep 2017
TL;DR: This paper proposed an attention mechanism which roughly identifies text regions via an automatically learned attentional map, which substantially suppresses background interference in the convolutional features, which is the key to producing accurate inference of words, particularly at extremely small sizes.
Abstract: We present a novel single-shot text detector that directly outputs word-level bounding boxes in a natural image. We propose an attention mechanism which roughly identifies text regions via an automatically learned attentional map. This substantially suppresses background interference in the convolutional features, which is the key to producing accurate inference of words, particularly at extremely small sizes. This results in a single model that essentially works in a coarse-to-fine manner. It departs from recent FCN-based text detectors which cascade multiple FCN models to achieve an accurate prediction. Furthermore, we develop a hierarchical inception module which efficiently aggregates multi-scale inception features. This enhances local details, and also encodes strong context information, allowing the detector to work reliably on multi-scale and multi-orientation text with single-scale images. Our text detector achieves an F-measure of 77% on the ICDAR 2015 benchmark, advancing the state-of-the-art results in [18, 28]. Demo is available at: http://sstd.whuang.org/.