Showing papers by "Pacific Northwest National Laboratory published in 2020"
University of Paderborn1, University of Zurich2, Lawrence Berkeley National Laboratory3, IBM4, McGill University5, ETH Zurich6, Victoria University, Australia7, Aalto University8, University of Regensburg9, University of Lincoln10, Intel11, Pacific Northwest National Laboratory12, University of Insubria13, Bosch14, Science and Technology Facilities Council15, Paul Scherrer Institute16
TL;DR: CP2K as discussed by the authors is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems, especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations.
Abstract: CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.
938 citations
National Center for Atmospheric Research1, University of Colorado Boulder2, Utrecht University3, Brown University4, Cooperative Institute for Research in Environmental Sciences5, University of Toronto6, University of Wisconsin–Milwaukee7, University of California, Irvine8, Columbia University9, Pacific Northwest National Laboratory10
TL;DR: The Community Earth System Model Version 2 (CESM2) as discussed by the authors is the most recent version of the Coupled Model Intercomparison Project (CMEI) coupled model.
Abstract: An overview of the Community Earth System Model Version 2 (CESM2) is provided, including a discussion of the challenges encountered during its development and how they were addressed. In addition, an evaluation of a pair of CESM2 long preindustrial control and historical ensemble simulations is presented. These simulations were performed using the nominal 1° horizontal resolution configuration of the coupled model with both the “low-top” (40 km, with limited chemistry) and “high-top” (130 km, with comprehensive chemistry) versions of the atmospheric component. CESM2 contains many substantial science and infrastructure improvements and new capabilities since its previous major release, CESM1, resulting in improved historical simulations in comparison to CESM1 and available observations. These include major reductions in low-latitude precipitation and shortwave cloud forcing biases; better representation of the Madden-Julian Oscillation; better El Nino-Southern Oscillation-related teleconnections; and a global land carbon accumulation trend that agrees well with observationally based estimates. Most tropospheric and surface features of the low- and high-top simulations are very similar to each other, so these improvements are present in both configurations. CESM2 has an equilibrium climate sensitivity of 5.1–5.3 °C, larger than in CESM1, primarily due to a combination of relatively small changes to cloud microphysics and boundary layer parameters. In contrast, CESM2's transient climate response of 1.9–2.0 °C is comparable to that of CESM1. The model outputs from these and many other simulations are available to the research community, and they represent CESM2's contributions to the Coupled Model Intercomparison Project Phase 6.
884 citations
TL;DR: The extent of the trait data compiled in TRY is evaluated and emerging patterns of data coverage and representativeness are analyzed to conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements.
Abstract: Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
882 citations
Graz University of Technology1, Université Paris-Saclay2, University of Waterloo3, Guizhou University4, European Food Information Council5, Institut national de la recherche agronomique6, Agricultural University of Athens7, University of Minnesota8, University of Minho9, University of Vienna10, Agriculture and Agri-Food Canada11, Rothamsted Research12, Pacific Northwest National Laboratory13, Austrian Institute of Technology14, CABI15, Tallinn University of Technology16, Wageningen University and Research Centre17, Pondicherry University18, State University of Campinas19, University of Sydney20, Teagasc21
TL;DR: A definition of microbiome is proposed based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings.
Abstract: The field of microbiome research has evolved rapidly over the past few decades and has become a topic of great scientific and public interest. As a result of this rapid growth in interest covering different fields, we are lacking a clear commonly agreed definition of the term “microbiome.” Moreover, a consensus on best practices in microbiome research is missing. Recently, a panel of international experts discussed the current gaps in the frame of the European-funded MicrobiomeSupport project. The meeting brought together about 40 leaders from diverse microbiome areas, while more than a hundred experts from all over the world took part in an online survey accompanying the workshop. This article excerpts the outcomes of the workshop and the corresponding online survey embedded in a short historical introduction and future outlook. We propose a definition of microbiome based on the compact, clear, and comprehensive description of the term provided by Whipps et al. in 1988, amended with a set of novel recommendations considering the latest technological developments and research findings. We clearly separate the terms microbiome and microbiota and provide a comprehensive discussion considering the composition of microbiota, the heterogeneity and dynamics of microbiomes in time and space, the stability and resilience of microbial networks, the definition of core microbiomes, and functionally relevant keystone species as well as co-evolutionary principles of microbe-host and inter-species interactions within the microbiome. These broad definitions together with the suggested unifying concepts will help to improve standardization of microbiome studies in the future, and could be the starting point for an integrated assessment of data resulting in a more rapid transfer of knowledge from basic science into practice. Furthermore, microbiome standards are important for solving new challenges associated with anthropogenic-driven changes in the field of planetary health, for which the understanding of microbiomes might play a key role.
733 citations
TL;DR: By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of climate impacts can be made.
Abstract: Recent decades have been characterized by increasing temperatures worldwide, resulting in an exponential climb in vapor pressure deficit (VPD). VPD has been identified as an increasingly important driver of plant functioning in terrestrial biomes and has been established as a major contributor in recent drought-induced plant mortality independent of other drivers associated with climate change. Despite this, few studies have isolated the physiological response of plant functioning to high VPD, thus limiting our understanding and ability to predict future impacts on terrestrial ecosystems. An abundance of evidence suggests that stomatal conductance declines under high VPD and transpiration increases in most species up until a given VPD threshold, leading to a cascade of subsequent impacts including reduced photosynthesis and growth, and higher risks of carbon starvation and hydraulic failure. Incorporation of photosynthetic and hydraulic traits in 'next-generation' land-surface models has the greatest potential for improved prediction of VPD responses at the plant- and global-scale, and will yield more mechanistic simulations of plant responses to a changing climate. By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of climate impacts can be made.
633 citations
University of Paderborn1, University of Zurich2, Lawrence Berkeley National Laboratory3, IBM4, McGill University5, ETH Zurich6, Victoria University, Australia7, Aalto University8, University of Regensburg9, University of Lincoln10, Intel11, Pacific Northwest National Laboratory12, University of Insubria13, Bosch14, Science and Technology Facilities Council15, Paul Scherrer Institute16
TL;DR: This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations and puts the emphasis on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.
Abstract: CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2k to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.
632 citations
Australian National University1, Argonne National Laboratory2, Scripps Health3, Iowa State University4, Western New England University5, Michigan State University6, National Institute of Advanced Industrial Science and Technology7, Microsoft8, University of Colorado Denver9, Oak Ridge National Laboratory10, Pacific Northwest National Laboratory11, University of Nebraska–Lincoln12, Nanjing University13, Sandia National Laboratories14, Moscow State University15, Kyocera16, Cray17, Purdue University18, Old Dominion University19, University of Rochester20
TL;DR: A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented, which include fragmentation methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory.
Abstract: A discussion of many of the recently implemented features of GAMESS (General Atomic and Molecular Electronic Structure System) and LibCChem (the C++ CPU/GPU library associated with GAMESS) is presented. These features include fragmentation methods such as the fragment molecular orbital, effective fragment potential and effective fragment molecular orbital methods, hybrid MPI/OpenMP approaches to Hartree-Fock, and resolution of the identity second order perturbation theory. Many new coupled cluster theory methods have been implemented in GAMESS, as have multiple levels of density functional/tight binding theory. The role of accelerators, especially graphical processing units, is discussed in the context of the new features of LibCChem, as it is the associated problem of power consumption as the power of computers increases dramatically. The process by which a complex program suite such as GAMESS is maintained and developed is considered. Future developments are briefly summarized.
575 citations
TL;DR: The current state of knowledge about the impacts of climate change on soil microorganisms in different climate-sensitive soil ecosystems, as well as potential ways that soil micro organisms can be harnessed to help mitigate the negative consequences of climatechange are explored.
Abstract: The soil microbiome governs biogeochemical cycling of macronutrients, micronutrients and other elements vital for the growth of plants and animal life. Understanding and predicting the impact of climate change on soil microbiomes and the ecosystem services they provide present a grand challenge and major opportunity as we direct our research efforts towards one of the most pressing problems facing our planet. In this Review, we explore the current state of knowledge about the impacts of climate change on soil microorganisms in different climate-sensitive soil ecosystems, as well as potential ways that soil microorganisms can be harnessed to help mitigate the negative consequences of climate change. In this Review, Jansson and Hofmockel explore the impacts of climate change on soil microorganisms in different climate-sensitive soil ecosystems and the potential ways that soil microorganisms can be harnessed to help mitigate the negative consequences of climate change.
545 citations
TL;DR: A machine learning design is developed to train a quantum circuit specialized in solving a classification problem and it is shown that the circuits perform reasonably well on classical benchmarks.
Abstract: A machine learning design is developed to train a quantum circuit specialized in solving a classification problem. In addition to discussing the training method and effect of noise, it is shown that the circuits perform reasonably well on classical benchmarks.
530 citations
Pacific Northwest National Laboratory1, Ajou University2, Hanyang University3, Bar-Ilan University4, University of Chicago5, Argonne National Laboratory6, University of Waterloo7, University of Nottingham8, University of Oxford9, Institute of Science and Technology Austria10, Graz University of Technology11
TL;DR: This review is to provide an objective, comprehensive, and authoritative assessment of the intensive work invested in nonaqueous rechargeable metal-air batteries over the past few years, which identified the key problems and guides directions to solve them.
Abstract: The goal of limiting global warming to 1.5 °C requires a drastic reduction in CO2 emissions across many sectors of the world economy. Batteries are vital to this endeavor, whether used in electric vehicles, to store renewable electricity, or in aviation. Present lithium-ion technologies are preparing the public for this inevitable change, but their maximum theoretical specific capacity presents a limitation. Their high cost is another concern for commercial viability. Metal-air batteries have the highest theoretical energy density of all possible secondary battery technologies and could yield step changes in energy storage, if their practical difficulties could be overcome. The scope of this review is to provide an objective, comprehensive, and authoritative assessment of the intensive work invested in nonaqueous rechargeable metal-air batteries over the past few years, which identified the key problems and guides directions to solve them. We focus primarily on the challenges and outlook for Li-O2 cells but include Na-O2, K-O2, and Mg-O2 cells for comparison. Our review highlights the interdisciplinary nature of this field that involves a combination of materials chemistry, electrochemistry, computation, microscopy, spectroscopy, and surface science. The mechanisms of O2 reduction and evolution are considered in the light of recent findings, along with developments in positive and negative electrodes, electrolytes, electrocatalysis on surfaces and in solution, and the degradative effect of singlet oxygen, which is typically formed in Li-O2 cells.
501 citations
Pacific Northwest National Laboratory1, United States Geological Survey2, Smithsonian Tropical Research Institute3, Smithsonian Conservation Biology Institute4, University of Minnesota5, Joint Global Change Research Institute6, University of Maryland, College Park7, Duke University8, Boston University9, Swiss Federal Institute for Forest, Snow and Landscape Research10, University of California, Berkeley11, Stanford University12, University of Florida13, Lawrence Berkeley National Laboratory14, Northern Arizona University15, Goddard Space Flight Center16, University of Birmingham17, Technische Universität München18, University of Natural Resources and Life Sciences, Vienna19, University of Wisconsin-Madison20, Columbia University21, Oak Ridge National Laboratory22, Los Alamos National Laboratory23
TL;DR: The authors show that shifts in forest dynamics are already occurring, and the emerging pattern is that global forests are tending toward younger stands with faster turnover as old-growth forest with stable dynamics are dwindling.
Abstract: Forest dynamics arise from the interplay of environmental drivers and disturbances with the demographic processes of recruitment, growth, and mortality, subsequently driving biomass and species composition. However, forest disturbances and subsequent recovery are shifting with global changes in climate and land use, altering these dynamics. Changes in environmental drivers, land use, and disturbance regimes are forcing forests toward younger, shorter stands. Rising carbon dioxide, acclimation, adaptation, and migration can influence these impacts. Recent developments in Earth system models support increasingly realistic simulations of vegetation dynamics. In parallel, emerging remote sensing datasets promise qualitatively new and more abundant data on the underlying processes and consequences for vegetation structure. When combined, these advances hold promise for improving the scientific understanding of changes in vegetation demographics and disturbances.
Emory University1, Johns Hopkins University2, National Institutes of Health3, Stanford University4, University of Pennsylvania5, Arizona State University6, Veterans Health Administration7, Icahn School of Medicine at Mount Sinai8, Mayo Clinic9, University of Florida10, Pacific Northwest National Laboratory11, NewYork–Presbyterian Hospital12, Rush University Medical Center13, Baylor College of Medicine14
TL;DR: Large-scale, comprehensive proteomic profiling of Alzheimer’s disease brain and cerebrospinal fluid reveals disease-associated protein coexpression modules and highlights the importance of glia and energy metabolism in disease pathogenesis.
Abstract: Our understanding of Alzheimer's disease (AD) pathophysiology remains incomplete. Here we used quantitative mass spectrometry and coexpression network analysis to conduct the largest proteomic study thus far on AD. A protein network module linked to sugar metabolism emerged as one of the modules most significantly associated with AD pathology and cognitive impairment. This module was enriched in AD genetic risk factors and in microglia and astrocyte protein markers associated with an anti-inflammatory state, suggesting that the biological functions it represents serve a protective role in AD. Proteins from this module were elevated in cerebrospinal fluid in early stages of the disease. In this study of >2,000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brains that may serve as therapeutic targets and fluid biomarkers for the disease.
TL;DR: In this article, the authors discuss the fundamental definition of Coulombic efficiency (CE) and unravel its true meaning in lithium-ion batteries and a few representative configurations of lithium metal batteries.
Abstract: Coulombic efficiency (CE) has been widely used in battery research as a quantifiable indicator for the reversibility of batteries While CE helps to predict the lifespan of a lithium-ion battery, the prediction is not necessarily accurate in a rechargeable lithium metal battery Here, we discuss the fundamental definition of CE and unravel its true meaning in lithium-ion batteries and a few representative configurations of lithium metal batteries Through examining the similarities and differences of CE in lithium-ion batteries and lithium metal batteries, we establish a CE measuring protocol with the aim of developing high-energy long-lasting practical lithium metal batteries The understanding of CE and the CE protocol are broadly applicable in other rechargeable metal batteries including Zn, Mg and Na batteries Coulombic efficiency (CE) has been frequently used to assess the cyclability of newly developed materials for lithium metal batteries The authors argue that caution must be exercised during the assessment of CE, and propose a CE testing protocol for the development of lithium metal batteries
TL;DR: It is theoretically proved that in the proposed method, gradient descent algorithms are not attracted to suboptimal critical points or local minima, and the proposed adaptive activation functions are shown to accelerate the minimization process of the loss values in standard deep learning benchmarks with and without data augmentation.
University of Waterloo1, National Technical University of Athens2, University of Alaska Fairbanks3, École Polytechnique Fédérale de Lausanne4, University of Kiel5, RMIT University6, University of St. Thomas (Minnesota)7, Nanyang Technological University8, Pacific Northwest National Laboratory9, Microsoft10, University of South Florida11, University of Chile12, South Dakota State University13
TL;DR: In this paper, definitions and classification of microgrid stability are presented and discussed, considering pertinent microgrid features such as voltage-frequency dependence, unbalancing, low inertia, and generation intermittency.
Abstract: This document is a summary of a report prepared by the IEEE PES Task Force (TF) on Microgrid Stability Definitions, Analysis, and Modeling, IEEE Power and Energy Society, Piscataway, NJ, USA, Tech. Rep. PES-TR66, Apr. 2018, which defines concepts and identifies relevant issues related to stability in microgrids. In this paper, definitions and classification of microgrid stability are presented and discussed, considering pertinent microgrid features such as voltage-frequency dependence, unbalancing, low inertia, and generation intermittency. A few examples are also presented, highlighting some of the stability classes defined in this paper. Further examples, along with discussions on microgrid components modeling and stability analysis tools can be found in the TF report.
TL;DR: The authors developed a diffusion-induced stress model to understand the origin of the planar gliding and propose ways to stabilize these nickel-rich cathodes in working batteries, providing clues to mitigate particle fracture from synthesis modifications.
Abstract: High-energy nickel (Ni)-rich cathode will play a key role in advanced lithium (Li)-ion batteries, but it suffers from moisture sensitivity, side reactions, and gas generation. Single-crystalline Ni-rich cathode has a great potential to address the challenges present in its polycrystalline counterpart by reducing phase boundaries and materials surfaces. However, synthesis of high-performance single-crystalline Ni-rich cathode is very challenging, notwithstanding a fundamental linkage between overpotential, microstructure, and electrochemical behaviors in single-crystalline Ni-rich cathodes. We observe reversible planar gliding and microcracking along the (003) plane in a single-crystalline Ni-rich cathode. The reversible formation of microstructure defects is correlated with the localized stresses induced by a concentration gradient of Li atoms in the lattice, providing clues to mitigate particle fracture from synthesis modifications.
TL;DR: In cPINN, locally adaptive activation functions are used, hence training the model faster compared to its fixed counterparts, and it efficiently lends itself to parallelized computation, where each sub-domain can be assigned to a different computational node.
Pacific Northwest National Laboratory1, Lawrence Berkeley National Laboratory2, National Center for Computational Sciences3, Brookhaven National Laboratory4, Argonne National Laboratory5, Intel6, University of Texas at Arlington7, State University of New York System8, Pennsylvania State University9, Oak Ridge National Laboratory10, Washington University in St. Louis11, Wellesley College12, Maria Curie-Skłodowska University13, Iowa State University14, Academy of Sciences of the Czech Republic15, University of Tennessee at Martin16, Université libre de Bruxelles17, Facebook18, Russian Academy of Sciences19, University of Minnesota20, University of Washington21, United States Naval Research Laboratory22, Georgia Institute of Technology23, University of St Andrews24, Universidad Autónoma Metropolitana25, University of California, San Diego26, Saarland University27, Sandia National Laboratories28, University of Illinois at Urbana–Champaign29, University of Iceland30, Australian National University31, Florida Institute of Technology32, University of Science and Technology of China33, Oswaldo Cruz Foundation34, Cardiff University35, Louisiana State University36, Chinese Academy of Sciences37, National Autonomous University of Mexico38, University of Florida39, Los Alamos National Laboratory40, University of Oviedo41, Prince of Songkla University42, Ames Laboratory43, University of Utah44, Northwestern University45, Universal Display Corporation46, Federal University of Pernambuco47, CD-adapco48, Cray49, Massachusetts Institute of Technology50, Nvidia51, University of Tennessee52, Shandong Normal University53, University of Cambridge54, Advanced Micro Devices55, Technische Universität München56, Stanford University57, Wuhan University of Technology58, Stony Brook University59
TL;DR: The NWChem computational chemistry suite is reviewed, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.
Abstract: Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.
Pacific Northwest National Laboratory1, Washington University in St. Louis2, University of Pittsburgh3, State University of New York System4, Oak Ridge National Laboratory5, Argonne National Laboratory6, Los Alamos National Laboratory7, Northern Illinois University8, Environmental Molecular Sciences Laboratory9
TL;DR: In this paper, an atomically dispersed Co and N co-doped carbon (CoN4C12) catalyst with porphyrin-like sites is reported with an improved activity and durability in PEM fuel cell conditions.
Abstract: The development of catalysts free of platinum-group metals and with both a high activity and durability for the oxygen reduction reaction in proton exchange membrane fuel cells is a grand challenge. Here we report an atomically dispersed Co and N co-doped carbon (Co–N–C) catalyst with a high catalytic oxygen reduction reaction activity comparable to that of a similarly synthesized Fe–N–C catalyst but with a four-time enhanced durability. The Co–N–C catalyst achieved a current density of 0.022 A cm−2 at 0.9 ViR-free (internal resistance-compensated voltage) and peak power density of 0.64 W cm−2 in 1.0 bar H2/O2 fuel cells, higher than that of non-iron platinum-group-metal-free catalysts reported in the literature. Importantly, we identified two main degradation mechanisms for metal (M)–N–C catalysts: catalyst oxidation by radicals and active-site demetallation. The enhanced durability of Co–N–C relative to Fe–N–C is attributed to the lower activity of Co ions for Fenton reactions that produce radicals from the main oxygen reduction reaction by-product, H2O2, and the significantly enhanced resistance to demetallation of Co–N–C. Platinum-group-metal-free, non-iron catalysts are highly desirable for the oxygen reduction reaction at proton exchange membrane (PEM) fuel cell cathodes, as they avoid the detrimental Fenton reactions. Now, a cobalt and nitrogen co-doped carbon catalyst with atomically dispersed porphyrin-like CoN4C12 sites is reported with an improved activity and durability in PEM fuel cell conditions.
TL;DR: In this article, a single-crystalline LiNi0.83Co0.11Mn0.06O2 (SC-NCM) with primary particles of 3-6-μm diameter is developed and comprehensively investigated, which exhibits superior cycling performance at both room temperature and elevated temperature (55 °C).
TL;DR: In this paper, the authors proposed a new composite neural network (NN) that can be trained based on multi-fidelity data, which is comprised of three NNs, with the first NN trained using the low fidelity data and coupled to two high fidelity NN, one with activation functions and another one without, in order to discover and exploit nonlinear and linear correlations, respectively, between the low-idelity and the high fidelity data.
Research Triangle Park1, Foundation for Research & Technology – Hellas2, University of Washington3, University of Michigan4, National Center for Atmospheric Research5, University of East Anglia6, Colorado State University7, University of Maryland, Baltimore County8, Leibniz Association9, University of Crete10, Columbia University11, University of Illinois at Urbana–Champaign12, Nankai University13, Georgia Institute of Technology14, Tsinghua University15, Pacific Northwest National Laboratory16, McGill University17
TL;DR: This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets, including recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale.
Abstract: . Acidity, defined as pH, is a central component of aqueous
chemistry. In the atmosphere, the acidity of condensed phases (aerosol
particles, cloud water, and fog droplets) governs the phase partitioning of
semivolatile gases such as HNO3 , NH3 , HCl, and organic acids and
bases as well as chemical reaction rates. It has implications for the
atmospheric lifetime of pollutants, deposition, and human health. Despite
its fundamental role in atmospheric processes, only recently has this field
seen a growth in the number of studies on particle acidity. Even with this
growth, many fine-particle pH estimates must be based on thermodynamic model
calculations since no operational techniques exist for direct measurements.
Current information indicates acidic fine particles are ubiquitous, but
observationally constrained pH estimates are limited in spatial and temporal
coverage. Clouds and fogs are also generally acidic, but to a lesser degree
than particles, and have a range of pH that is quite sensitive to
anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient
ammonia. Historical measurements indicate that cloud and fog droplet pH has
changed in recent decades in response to controls on anthropogenic
emissions, while the limited trend data for aerosol particles indicate
acidity may be relatively constant due to the semivolatile nature of the
key acids and bases and buffering in particles. This paper reviews and
synthesizes the current state of knowledge on the acidity of atmospheric
condensed phases, specifically particles and cloud droplets. It includes
recommendations for estimating acidity and pH, standard nomenclature, a
synthesis of current pH estimates based on observations, and new model
calculations on the local and global scale.
TL;DR: This review focuses on the recent progress on the stabilization of LMA with nonaqueous electrolytes and reveals the fundamental mechanisms behind this improved stability, which will lead to the large-scale application of LMBs.
Abstract: High-energy rechargeable lithium (Li) metal batteries (LMBs) with Li metal anode (LMA) were first developed in the 1970s, but their practical applications have been hindered by the safety and low-efficiency concerns related to LMA. Recently, a worldwide effort on LMA-based rechargeable LMBs has been revived to replace graphite-based, Li-ion batteries because of the much higher energy density that can be achieved with LMBs. This review focuses on the recent progress on the stabilization of LMA with nonaqueous electrolytes and reveals the fundamental mechanisms behind this improved stability. Various strategies that can enhance the stability of LMA in practical conditions and perspectives on the future development of LMA are also discussed. These strategies include the use of novel electrolytes such as superconcentrated electrolytes, localized high-concentration electrolytes, and highly fluorinated electrolytes, surface coatings that can form a solid electrolyte interphase with a high interfacial energy and self-healing capabilities, development of "anode-free" Li batteries to minimize the interaction between LMA and electrolyte, approaches to enable operation of LMA in practical conditions, etc. Combination of these strategies ultimately will lead us closer to the large-scale application of LMBs which often is called the "Holy Grail" of energy storage systems.
TL;DR: This paper provides a unified framework for model predictive building control technology with focus on the real-world applications and presents the essential components of a practical implementation of MPC such as different control architectures and nuances of communication infrastructures within supervisory control and data acquisition (SCADA) systems.
University of Washington1, Fermilab2, Lawrence Livermore National Laboratory3, Los Alamos National Laboratory4, National Radio Astronomy Observatory5, Pacific Northwest National Laboratory6, University of California, Berkeley7, University of Chicago8, University of Florida9, University of Göttingen10, University of Sheffield11, Washington University in St. Louis12
TL;DR: In this article, a cavity haloscope search for dark matter axions in the Galactic halo in the mass range 2.81-3.31 µeV was performed using low-noise Josephson parametric amplifier and a large-cavity haloscope.
Abstract: This Letter reports on a cavity haloscope search for dark matter axions in the Galactic halo in the mass range 2.81-3.31 μeV. This search utilizes the combination of a low-noise Josephson parametric amplifier and a large-cavity haloscope to achieve unprecedented sensitivity across this mass range. This search excludes the full range of axion-photon coupling values predicted in benchmark models of the invisible axion that solve the strong CP problem of quantum chromodynamics.
TL;DR: H hierarchical porous CNT@Si@C microspheres are constructed as anodes for Li-ion batteries, enabling both high electrochemical performance and excellent mechanical strength, and provides insights into the design of electrode materials for other batteries.
Abstract: Porous structured silicon has been regarded as a promising candidate to overcome pulverization of silicon-based anodes. However, poor mechanical strength of these porous particles has limited their volumetric energy density towards practical applications. Here we design and synthesize hierarchical carbon-nanotube@silicon@carbon microspheres with both high porosity and extraordinary mechanical strength (>200 MPa) and a low apparent particle expansion of ~40% upon full lithiation. The composite electrodes of carbon-nanotube@silicon@carbon-graphite with a practical loading (3 mAh cm−2) deliver ~750 mAh g−1 specific capacity, 92% capacity retention over 500 cycles. This work is a leap in silicon anode development and provides insights into the design of electrode materials for other batteries. The authors here construct hierarchical porous CNT@Si@C microspheres as anodes for Li-ion batteries, enabling both high electrochemical performance and excellent mechanical strength. The work highlights the importance of mechanical properties in developing battery materials for practical applications.
TL;DR: In this article, the authors compare and connect strategies to enable different multivalent and monovalent metal-ion battery anodes, including metal anodes and intercalation-based, alloy-based and conversion-reaction-based anodes.
Abstract: The inability of current battery technologies to keep up with the performance requirements of industry is pushing forward developments in electrochemistry. Specifically, the battery’s negative electrode, the anode, presents many unique chemical, physical and engineering challenges. Lithium-based battery technologies have dominated the past decade, but concerns about the limited supply of lithium in the Earth’s crust have led researchers to look towards alternative metal-ion technologies. Various alkali metals (such as sodium and potassium) and alkali earth metals (such as magnesium and calcium) have attracted significant research interest. In this Review, we analyse these technologies in a coherent manner, addressing the problems of each type of anode, rather than those of specific types of metal-ion batteries. Covering direct metal plating and stripping, intercalation-based, alloy-based and conversion-reaction-based anode technologies, this analysis will offer the reader a comprehensive understanding of the behaviour of different metal-ion anodes and of what can be learned by transferring knowledge between these different systems. Increasing demand for energy-storage systems will inevitably stress the Earth’s lithium supply; thus, the research focus is shifting towards other alkali and alkali earth metals. This Review compares and connects strategies to enable different multivalent and monovalent metal-ion battery anodes, including metal anodes and intercalation-based, alloy-based and conversion-reaction-based anodes.
TL;DR: An operando mass spectrometry technique is presented, along with molecular dynamics simulations, that unveils the evolution of the solid–electrolyte interphase chemistry and structure in lithium-ion batteries during the first cycle.
Abstract: The solid–electrolyte interphase (SEI) dictates the performance of most batteries, but the understanding of its chemistry and structure is limited by the lack of in situ experimental tools. In this work, we present a dynamic picture of the SEI formation in lithium-ion batteries using in operando liquid secondary ion mass spectrometry in combination with molecular dynamics simulations. We find that before any interphasial chemistry occurs (during the initial charging), an electric double layer forms at the electrode/electrolyte interface due to the self-assembly of solvent molecules. The formation of the double layer is directed by Li+ and the electrode surface potential. The structure of this double layer predicts the eventual interphasial chemistry; in particular, the negatively charged electrode surface repels salt anions from the inner layer and results in an inner SEI that is thin, dense and inorganic in nature. It is this dense layer that is responsible for conducting Li+ and insulating electrons, the main functions of the SEI. An electrolyte-permeable and organic-rich outer layer appears after the formation of the inner layer. In the presence of a highly concentrated, fluoride-rich electrolyte, the inner SEI layer has an elevated concentration of LiF due to the presence of anions in the double layer. These real-time nanoscale observations will be helpful in engineering better interphases for future batteries. An operando mass spectrometry technique, along with molecular dynamics simulations, unveils the evolution of the solid–electrolyte interphase chemistry and structure in lithium-ion batteries during the first cycle.
TL;DR: A comprehensive proteogenomic characterization of endometrial carcinomas revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways.
TL;DR: This work constitutes the most precise measurements of R(D) and R (D^{*}) performed to date as well as the first result for R( D) based on a semileptonic tagging method.
Abstract: The experimental results on the ratios of branching fractions $\mathcal{R}(D) = {\cal B}(\bar{B} \to D \tau^- \bar{
u}_{\tau})/{\cal B}(\bar{B} \to D \ell^- \bar{
u}_{\ell})$ and $\mathcal{R}(D^*) = {\cal B}(\bar{B} \to D^* \tau^- \bar{
u}_{\tau})/{\cal B}(\bar{B} \to D^* \ell^- \bar{
u}_{\ell})$, where $\ell$ denotes an electron or a muon, show a long-standing discrepancy with the Standard Model predictions, and might hint to a violation of lepton flavor universality. We report a new simultaneous measurement of $\mathcal{R}(D)$ and $\mathcal{R}(D^*)$, based on a data sample containing $772 \times 10^6$ $B\bar{B}$ events recorded at the $\Upsilon(4S)$ resonance with the Belle detector at the KEKB $e^+ e^-$ collider. In this analysis the tag-side $B$ meson is reconstructed in a semileptonic decay mode and the signal-side $\tau$ is reconstructed in a purely leptonic decay. The measured values are $\mathcal{R}(D)= 0.307 \pm 0.037 \pm 0.016$ and $\mathcal{R}(D^*) = 0.283 \pm 0.018 \pm 0.014$, where the first uncertainties are statistical and the second are systematic. These results are in agreement with the Standard Model predictions within $0.2$, $1.1$ and $0.8$ standard deviations for $\mathcal{R}(D)$, $\mathcal{R}(D^*)$ and their combination, respectively. This work constitutes the most precise measurements of $\mathcal{R}(D)$ and $\mathcal{R}(D^*)$ performed to date as well as the first result for $\mathcal{R}(D)$ based on a semileptonic tagging method.