Showing papers by "Lawrence Berkeley National Laboratory published in 2021"
University of Washington1, Harvard University2, University of Texas Southwestern Medical Center3, University of Cambridge4, Stanford University5, Lawrence Berkeley National Laboratory6, North-West University7, University of the Free State8, University of Graz9, Medical University of Graz10, University of Victoria11, University of British Columbia12, University of California, Berkeley13
TL;DR: In this article, a three-track network is proposed to combine information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level.
Abstract: DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.
1,907 citations
University of Edinburgh1, Autonomous University of Madrid2, Pierre-and-Marie-Curie University3, University of Portsmouth4, University of Wisconsin-Madison5, University of Cape Town6, New Mexico State University7, Moscow State University8, New York University9, University of Utah10, University of Toronto11, Université Paris-Saclay12, University of Waterloo13, Sejong University14, Stanford University15, Max Planck Society16, University College London17, Texas Christian University18, National Autonomous University of Mexico19, University of Barcelona20, Universidad de Guanajuato21, Consejo Nacional de Ciencia y Tecnología22, Liverpool John Moores University23, Lawrence Berkeley National Laboratory24, Ohio State University25, École Polytechnique Fédérale de Lausanne26, University of Wyoming27, Haverford College28, University of Oxford29, University of Pittsburgh30, Perimeter Institute for Theoretical Physics31, California Institute of Technology32, Ohio University33, Swinburne University of Technology34, Fermilab35, University of Washington36, Korea Astronomy and Space Science Institute37, Brookhaven National Laboratory38, University of St Andrews39, Durham University40
TL;DR: In this article, the authors present the cosmological implications from final measurements of clustering using galaxies, quasars, and Lyα forests from the completed SDSS lineage of experiments in large-scale structure.
Abstract: We present the cosmological implications from final measurements of clustering using galaxies, quasars, and Lyα forests from the completed Sloan Digital Sky Survey (SDSS) lineage of experiments in large-scale structure. These experiments, composed of data from SDSS, SDSS-II, BOSS, and eBOSS, offer independent measurements of baryon acoustic oscillation (BAO) measurements of angular-diameter distances and Hubble distances relative to the sound horizon, rd, from eight different samples and six measurements of the growth rate parameter, fσ8, from redshift-space distortions (RSD). This composite sample is the most constraining of its kind and allows us to perform a comprehensive assessment of the cosmological model after two decades of dedicated spectroscopic observation. We show that the BAO data alone are able to rule out dark-energy-free models at more than eight standard deviations in an extension to the flat, ΛCDM model that allows for curvature. When combined with Planck Cosmic Microwave Background (CMB) measurements of temperature and polarization, under the same model, the BAO data provide nearly an order of magnitude improvement on curvature constraints relative to primary CMB constraints alone. Independent of distance measurements, the SDSS RSD data complement weak lensing measurements from the Dark Energy Survey (DES) in demonstrating a preference for a flat ΛCDM cosmological model when combined with Planck measurements. The combined BAO and RSD measurements indicate σ8=0.85±0.03, implying a growth rate that is consistent with predictions from Planck temperature and polarization data and with General Relativity. When combining the results of SDSS BAO and RSD, Planck, Pantheon Type Ia supernovae (SNe Ia), and DES weak lensing and clustering measurements, all multiple-parameter extensions remain consistent with a ΛCDM model. Regardless of cosmological model, the precision on each of the three parameters, ωΛ, H0, and σ8, remains at roughly 1%, showing changes of less than 0.6% in the central values between models. In a model that allows for free curvature and a time-evolving equation of state for dark energy, the combined samples produce a constraint ωk=-0.0022±0.0022. The dark energy constraints lead to w0=-0.909±0.081 and wa=-0.49-0.30+0.35, corresponding to an equation of state of wp=-1.018±0.032 at a pivot redshift zp=0.29 and a Dark Energy Task Force Figure of Merit of 94. The inverse distance ladder measurement under this model yields H0=68.18±0.79 km s-1 Mpc-1, remaining in tension with several direct determination methods; the BAO data allow Hubble constant estimates that are robust against the assumption of the cosmological model. In addition, the BAO data allow estimates of H0 that are independent of the CMB data, with similar central values and precision under a ΛCDM model. Our most constraining combination of data gives the upper limit on the sum of neutrino masses at mν<0.115 eV (95% confidence). Finally, we consider the improvements in cosmology constraints over the last decade by comparing our results to a sample representative of the period 2000-2010. We compute the relative gain across the five dimensions spanned by w, ωk, mν, H0, and σ8 and find that the SDSS BAO and RSD data reduce the total posterior volume by a factor of 40 relative to the previous generation. Adding again the Planck, DES, and Pantheon SN Ia samples leads to an overall contraction in the five-dimensional posterior volume of 3 orders of magnitude.
575 citations
European Bioinformatics Institute1, Newcastle University2, Newcastle upon Tyne Hospitals NHS Foundation Trust3, Oregon Health & Science University4, University of Genoa5, Istituto Giannina Gaslini6, University of Western Australia7, King Edward Memorial Hospital8, American College of Medical Genetics9, Anschutz Medical Campus10, Johns Hopkins University11, Ludwig Maximilian University of Munich12, Children's Hospital of Philadelphia13, Austrian Academy of Sciences14, University of Connecticut15, French Institute of Health and Medical Research16, Lawrence Berkeley National Laboratory17, University of Michigan18, University of Freiburg19, University of Luxembourg20, Oregon State University21, Chestnut Hill College22, Medical University of Graz23, Queen Mary University of London24, Hebrew University of Jerusalem25, University of Pennsylvania26
TL;DR: Recent major extensions of the Human Phenotype Ontology for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas are presented and new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease are presented.
Abstract: The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.
503 citations
TL;DR: This work reports the development of an amplification-free CRISPR-Cas13a assay for direct detection of SARS-CoV-2 from nasal swab RNA that can be read with a mobile phone microscope and has the potential to enable rapid, low-cost, point-of-care screening for Sars-Cov-2.
501 citations
TL;DR: In this paper, the authors discuss the recent achievements, challenges, and opportunities of four important "beyond Li-ion" technologies: Na-ion batteries, K-ion, all-solid-state batteries, and multivalent batteries.
Abstract: The tremendous improvement in performance and cost of lithium-ion batteries (LIBs) have made them the technology of choice for electrical energy storage. While established battery chemistries and cell architectures for Li-ion batteries achieve good power and energy density, LIBs are unlikely to meet all the performance, cost, and scaling targets required for energy storage, in particular, in large-scale applications such as electrified transportation and grids. The demand to further reduce cost and/or increase energy density, as well as the growing concern related to natural resource needs for Li-ion have accelerated the investigation of so-called "beyond Li-ion" technologies. In this review, we will discuss the recent achievements, challenges, and opportunities of four important "beyond Li-ion" technologies: Na-ion batteries, K-ion batteries, all-solid-state batteries, and multivalent batteries. The fundamental science behind the challenges, and potential solutions toward the goals of a low-cost and/or high-energy-density future, are discussed in detail for each technology. While it is unlikely that any given new technology will fully replace Li-ion in the near future, "beyond Li-ion" technologies should be thought of as opportunities for energy storage to grow into mid/large-scale applications.
485 citations
TL;DR: The Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes, is presented, providing comprehensive resources for microbiome researchers.
Abstract: Comprehensive, high-quality reference genomes are required for functional characterization and taxonomic assignment of the human gut microbiota. We present the Unified Human Gastrointestinal Genome (UHGG) collection, comprising 204,938 nonredundant genomes from 4,644 gut prokaryotes. These genomes encode >170 million protein sequences, which we collated in the Unified Human Gastrointestinal Protein (UHGP) catalog. The UHGP more than doubles the number of gut proteins in comparison to those present in the Integrated Gene Catalog. More than 70% of the UHGG species lack cultured representatives, and 40% of the UHGP lack functional annotations. Intraspecies genomic variation analyses revealed a large reservoir of accessory genes and single-nucleotide variants, many of which are specific to individual human populations. The UHGG and UHGP collections will enable studies linking genotypes to phenotypes in the human gut microbiome.
485 citations
University of London1, University of Glasgow2, University of Edinburgh3, Lawrence Berkeley National Laboratory4, Memorial Sloan Kettering Cancer Center5, Cornell University6, University of Cambridge7, University of Lugano8, University of Zurich9, Maynooth University10, University of New South Wales11, ETH Zurich12, Boston Children's Hospital13, University of Liverpool14, National Institutes of Health15, Washington University in St. Louis16
TL;DR: In this paper, the authors demonstrate that the immunodominant SARS-CoV-2 spike (S) receptor binding motif (RBM) is a highly variable region of S and provide epidemiological, clinical, and molecular characterization of a prevalent, sentinel RBM mutation, N439K.
483 citations
Ludwig Maximilian University of Munich1, University of Cambridge2, University of Hyderabad3, Katholieke Universiteit Leuven4, Massachusetts Institute of Technology5, University of Antwerp6, Indian Institute of Science7, Yantai University8, University of Vigo9, King Abdullah University of Science and Technology10, Nanjing University of Science and Technology11, Lawrence Berkeley National Laboratory12, University of California, Berkeley13, Nanyang Technological University14, Soochow University (Suzhou)15, Technische Universität München16, ETH Zurich17, Lund University18, Hokkaido University19, University of California, Santa Cruz20, Chinese Academy of Sciences21, Beijing Institute of Technology22, City University of Hong Kong23, University of Texas at Austin24, Indian Association for the Cultivation of Science25, San Diego State University26, University of Washington27, Texas A&M University28, Bilkent University29, James I University30, Max Planck Society31, National Renewable Energy Laboratory32, University of Valencia33, Shanghai Jiao Tong University34, Istituto Italiano di Tecnologia35, Swiss Federal Laboratories for Materials Science and Technology36, University of Notre Dame37, Monash University, Clayton campus38, Imperial College London39
TL;DR: A comprehensive review of metal-halide perovskite nanocrystals can be found in this article, where researchers having expertise in different fields (chemistry, physics, and device engineering) have joined together to provide a state-of-the-art overview and future prospects of metalhalide nanocrystal research.
Abstract: Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.
471 citations
TL;DR: In this article, the authors examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities, and found that warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species.
Abstract: Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. These results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming. The authors examine the effect of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. They find warming increases network complexity, which is strongly correlated with network stability.
393 citations
North Carolina State University1, Ritsumeikan University2, Ohio State University3, University of California, Santa Barbara4, Institute of High Performance Computing Singapore5, Pohang University of Science and Technology6, University of California, Irvine7, University of California, Riverside8, Lawrence Berkeley National Laboratory9, Kyoto University10, Yanshan University11, Chinese Academy of Sciences12
Abstract: Heterostructured materials are an emerging class of materials with superior performances that are unattainable by their conventional homogeneous counterparts. They consist of heterogeneous zones wi...
392 citations
TL;DR: The utility of this collection of >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans is demonstrated for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses.
Abstract: The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.
TL;DR: CheckV as discussed by the authors is an automated pipeline for identifying closed closed viral genomes, estimating the completeness of genome fragments and removing flanking host regions from integrated proviruses, which significantly improves the accuracy of identification of auxiliary metabolic genes and interpretation of viral-encoded functions.
Abstract: Millions of new viral sequences have been identified from metagenomes, but the quality and completeness of these sequences vary considerably. Here we present CheckV, an automated pipeline for identifying closed viral genomes, estimating the completeness of genome fragments and removing flanking host regions from integrated proviruses. CheckV estimates completeness by comparing sequences with a large database of complete viral genomes, including 76,262 identified from a systematic search of publicly available metagenomes, metatranscriptomes and metaviromes. After validation on mock datasets and comparison to existing methods, we applied CheckV to large and diverse collections of metagenome-assembled viral sequences, including IMG/VR and the Global Ocean Virome. This revealed 44,652 high-quality viral genomes (that is, >90% complete), although the vast majority of sequences were small fragments, which highlights the challenge of assembling viral genomes from short-read metagenomes. Additionally, we found that removal of host contamination substantially improved the accurate identification of auxiliary metabolic genes and interpretation of viral-encoded functions. The quality of viral genomes assembled from metagenome data is assessed by CheckV.
Evgeny Epifanovsky, Andrew T.B. Gilbert1, Andrew T.B. Gilbert2, Xintian Feng3 +235 more•Institutions (54)
TL;DR: The Q-Chem quantum chemistry program package as discussed by the authors provides a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, and methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques.
Abstract: This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.
TL;DR: In this paper, the metal-induced gap states (MIGS) were suppressed and degenerate states in the metal dichalcogenides (TMDs) spontaneously formed in contact with bismuth.
Abstract: Advanced beyond-silicon electronic technology requires both channel materials and also ultralow-resistance contacts to be discovered1,2. Atomically thin two-dimensional semiconductors have great potential for realizing high-performance electronic devices1,3. However, owing to metal-induced gap states (MIGS)4–7, energy barriers at the metal–semiconductor interface—which fundamentally lead to high contact resistance and poor current-delivery capability—have constrained the improvement of two-dimensional semiconductor transistors so far2,8,9. Here we report ohmic contact between semimetallic bismuth and semiconducting monolayer transition metal dichalcogenides (TMDs) where the MIGS are sufficiently suppressed and degenerate states in the TMD are spontaneously formed in contact with bismuth. Through this approach, we achieve zero Schottky barrier height, a contact resistance of 123 ohm micrometres and an on-state current density of 1,135 microamps per micrometre on monolayer MoS2; these two values are, to the best of our knowledge, the lowest and highest yet recorded, respectively. We also demonstrate that excellent ohmic contacts can be formed on various monolayer semiconductors, including MoS2, WS2 and WSe2. Our reported contact resistances are a substantial improvement for two-dimensional semiconductors, and approach the quantum limit. This technology unveils the potential of high-performance monolayer transistors that are on par with state-of-the-art three-dimensional semiconductors, enabling further device downscaling and extending Moore’s law. Electric contacts of semimetallic bismuth on monolayer semiconductors are shown to suppress metal-induced gap states and thus have very low contact resistance and a zero Schottky barrier height.
TL;DR: Aghanim et al. as mentioned in this paper used the same data set to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
Abstract: Author(s): Aghanim, N; Akrami, Y; Ashdown, M; Aumont, J; Baccigalupi, C; Ballardini, M; Banday, AJ; Barreiro, RB; Bartolo, N; Basak, S; Battye, R; Benabed, K; Bernard, JP; Bersanelli, M; Bielewicz, P; Bock, JJ; Bond, JR; Borrill, J; Bouchet, FR; Boulanger, F; Bucher, M; Burigana, C; Butler, RC; Calabrese, E; Cardoso, JF; Carron, J; Challinor, A; Chiang, HC; Chluba, J; Colombo, LPL; Combet, C; Contreras, D; Crill, BP; Cuttaia, F; De Bernardis, P; De Zotti, G; Delabrouille, J; Delouis, JM; DI Valentino, E; DIego, JM; Dore, O; Douspis, M; Ducout, A; Dupac, X; Dusini, S; Efstathiou, G; Elsner, F; Enslin, TA; Eriksen, HK; Fantaye, Y; Farhang, M; Fergusson, J; Fernandez-Cobos, R; Finelli, F; Forastieri, F; Frailis, M; Fraisse, AA; Franceschi, E; Frolov, A; Galeotta, S; Galli, S; Ganga, K; Genova-Santos, RT; Gerbino, M; Ghosh, T; Gonzalez-Nuevo, J; Gorski, KM; Gratton, S; Gruppuso, A; Gudmundsson, JE; Hamann, J; Handley, W; Hansen, FK; Herranz, D; Hildebrandt, SR; Hivon, E; Huang, Z; Jaffe, AH; Jones, WC; Karakci, A; Keihanen, E; Keskitalo, R; Kiiveri, K; Kim, J; Kisner, TS | Abstract: In the original version, the bounds given in Eqs. (87a) and (87b) on the contribution to the early-time optical depth, (15,30), contained a numerical error in deriving the 95th percentile from the Monte Carlo samples. The corrected 95% upper bounds are: τ(15,30) l 0:018 (lowE, flat τ(15, 30), FlexKnot), (1) τ(15, 30) l 0:023 (lowE, flat knot, FlexKnot): (2) These bounds are a factor of 3 larger than the originally reported results. Consequently, the new bounds do not significantly improve upon previous results from Planck data presented in Millea a Bouchet (2018) as was stated, but are instead comparable. Equations (1) and (2) give results that are now similar to those of Heinrich a Hu (2021), who used the same Planck 2018 data to derive a 95% upper bound of 0.020 using the principal component analysis (PCA) model and uniform priors on the PCA mode amplitudes.
University of Manchester1, City University of New York2, Istanbul Technical University3, New York University4, Heidelberg University5, Niels Bohr Institute6, University of Edinburgh7, University of Bologna8, Academy of Athens9, Sapienza University of Rome10, University of Naples Federico II11, Stanford University12, Institut d'Astrophysique de Paris13, University of Portsmouth14, Cardiff University15, Universidade Federal do Espírito Santo16, University of Michigan17, Asia Pacific Center for Theoretical Physics18, University of New Mexico19, University of Barcelona20, University of St. Thomas (Minnesota)21, Princeton University22, National Autonomous University of Mexico23, California Institute of Technology24, INAF25, University of Chicago26, Michigan Technological University27, Lawrence Berkeley National Laboratory28, University of Cambridge29, Imperial College London30, Ruhr University Bochum31, University of Waterloo32, University of Oxford33, Johns Hopkins University34, University of Pennsylvania35, University of California, Davis36, Birla Institute of Technology and Science37, RWTH Aachen University38, Université libre de Bruxelles39, University of Padua40, Indian Institute of Technology Kharagpur41, Spanish National Research Council42, University of North Carolina at Chapel Hill43, University of Arizona44, University of Oslo45, Jamia Millia Islamia46, University of Southern Denmark47, National Institute for Space Research48, Fermilab49, Presidency University, Kolkata50, Université Paris-Saclay51, University of Montpellier52, University of Szczecin53, Korea Astronomy and Space Science Institute54, University of California, Los Angeles55, University of Paris56, Leiden University57, Swarthmore College58, University of Sheffield59, University of Amsterdam60, United College, Winnipeg61, Liaoning Normal University62
TL;DR: In this article, the authors focus on the 4.4σ tension between the Planck estimate of the Hubble constant H0 and the SH0ES collaboration measurements and discuss how the next decade's experiments will be crucial.
TL;DR: In this paper, the authors summarized the latest market outlooks and targets for truck, bus, locomotive, and marine applications and discussed the necessary improvements in fuel-cell materials and integration.
Abstract: The recent release of hydrogen economy roadmaps for several major countries emphasizes the need for accelerated worldwide investment in research and development activities for hydrogen production, storage, infrastructure and utilization in transportation, industry and the electrical grid. Due to the high gravimetric energy density of hydrogen, the focus of technologies that utilize this fuel has recently shifted from light-duty automotive to heavy-duty vehicle applications. Decades of development of cost-effective and durable polymer electrolyte membrane fuel cells must now be leveraged to meet the increased efficiency and durability requirements of the heavy-duty vehicle market. This Review summarizes the latest market outlooks and targets for truck, bus, locomotive and marine applications. Required changes to the fuel-cell system and operating conditions for meeting Class 8 long-haul truck targets are presented. The necessary improvements in fuel-cell materials and integration are also discussed against the benchmark of current passenger fuel-cell electric vehicles. Fuel cells are increasingly being considered for powertrains of heavy-duty transportation. Cullen et al. survey the technical challenges of fuel cells at both the system and materials level for transportation application and outline the roadmap for future development.
TL;DR: VirSorter2 as mentioned in this paper is a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection.
Abstract: Viruses are a significant player in many biosphere and human ecosystems, but most signals remain “hidden” in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools. Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2’s modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity. With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available (
https://bitbucket.org/MAVERICLab/virsorter2
), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse (
https://de.cyverse.org/de
).
Fred Hutchinson Cancer Research Center1, Washington University in St. Louis2, University of Washington3, Memorial Sloan Kettering Cancer Center4, Cornell University5, Rega Institute for Medical Research6, University of Cambridge7, Lawrence Berkeley National Laboratory8, University of Texas Southwestern Medical Center9, Howard Hughes Medical Institute10
TL;DR: In this paper, the authors comprehensively characterize escape, breadth and potency across a panel of SARS-CoV-2 antibodies targeting the receptor-binding domain (RBD).
Abstract: An ideal therapeutic anti-SARS-CoV-2 antibody would resist viral escape1–3, have activity against diverse sarbecoviruses4–7, and be highly protective through viral neutralization8–11 and effector functions12,13. Understanding how these properties relate to each other and vary across epitopes would aid the development of therapeutic antibodies and guide vaccine design. Here we comprehensively characterize escape, breadth and potency across a panel of SARS-CoV-2 antibodies targeting the receptor-binding domain (RBD). Despite a trade-off between in vitro neutralization potency and breadth of sarbecovirus binding, we identify neutralizing antibodies with exceptional sarbecovirus breadth and a corresponding resistance to SARS-CoV-2 escape. One of these antibodies, S2H97, binds with high affinity across all sarbecovirus clades to a cryptic epitope and prophylactically protects hamsters from viral challenge. Antibodies that target the angiotensin-converting enzyme 2 (ACE2) receptor-binding motif (RBM) typically have poor breadth and are readily escaped by mutations despite high neutralization potency. Nevertheless, we also characterize a potent RBM antibody (S2E128) with breadth across sarbecoviruses related to SARS-CoV-2 and a high barrier to viral escape. These data highlight principles underlying variation in escape, breadth and potency among antibodies that target the RBD, and identify epitopes and features to prioritize for therapeutic development against the current and potential future pandemics. A survey of SARS-CoV-2 RBD antibodies identifies those with activity against diverse SARS-CoV-2 variants and SARS-related coronaviruses, highlighting epitopes and features to prioritize in antibody and vaccine development.
TL;DR: IMG v 6.0 includes advanced search functions and a new tool for statistical analysis of mixed sets of genomes and metagenome bins, and the new IMG web user interface has a new Help page with additional documentation and webinar tutorials to help users better understand how to use various IMG functions and tools.
Abstract: The Integrated Microbial Genomes & Microbiomes system (IMG/M: https://img.jgi.doe.gov/m/) contains annotated isolate genome and metagenome datasets sequenced at the DOE's Joint Genome Institute (JGI), submitted by external users, or imported from public sources such as NCBI. IMG v 6.0 includes advanced search functions and a new tool for statistical analysis of mixed sets of genomes and metagenome bins. The new IMG web user interface also has a new Help page with additional documentation and webinar tutorials to help users better understand how to use various IMG functions and tools for their research. New datasets have been processed with the prokaryotic annotation pipeline v.5, which includes extended protein family assignments.
University of New South Wales1, Max Planck Society2, Netherlands Environmental Assessment Agency3, University of Natural Resources and Life Sciences, Vienna4, Technical University of Dortmund5, Imperial College London6, University of Bristol7, International Institute for Applied Systems Analysis8, Copenhagen Business School9, University of Groningen10, University of Maryland, College Park11, Federal University of Rio de Janeiro12, Lawrence Berkeley National Laboratory13, Great Zimbabwe University14, University of California, Irvine15, Peking University16, Asian Institute of Technology17, Chinese Academy of Sciences18, Shanghai Jiao Tong University19
TL;DR: In this paper, the authors present estimates of greenhouse gas emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions.
Abstract: Global greenhouse gas emissions can be traced to five economic sectors: energy, industry, buildings, transport and AFOLU (agriculture, forestry and other land uses). In this topical review we synthesize the literature to explain recent trends in global and regional emissions in each of these sectors. To contextualise our review, we present estimates of greenhouse gas emissions trends by sector from 1990 to 2018, describing the major sources of emissions growth, stability and decline across ten global regions. Both the literature and data emphasize limited progress towards reducing greenhouse gas emissions. The prominent global pattern is a continuation of underlying drivers with few signs of emerging limits to demand, nor of a deep shift towards the delivery of low and zero carbon services across sectors. We observe a moderate decarbonisation of energy systems in Europe and North America, driven by fuel switching and the increasing penetration of renewables. By contrast, in rapidly industrialising regions, fossil-based energy systems have continuously expanded, only very recently slowing down in their growth. Strong demand for materials, floor area, energy services and travel have driven emissions growth in the industry, buildings and transport sectors, particularly in Eastern Asia, Southern Asia and South-East Asia. An expansion of agriculture into carbon-dense tropical forest areas has driven recent increases in AFOLU emissions in Latin America, South-East Asia and Africa. Identifying, understanding, and tackling the most persistent and climate-damaging trends across sectors is a fundamental concern for research and policy as humanity treads deeper into the Anthropocene.
Oak Ridge National Laboratory1, University of New South Wales2, Ludwig Maximilian University of Munich3, University of Arizona4, Stanford University5, Scripps Institution of Oceanography6, Smithsonian Environmental Research Center7, University of Sydney8, Max Planck Society9, Smithsonian Conservation Biology Institute10, Smithsonian Tropical Research Institute11, Seconda Università degli Studi di Napoli12, University of Leeds13, Aix-Marseille University14, Swiss Federal Institute for Forest, Snow and Landscape Research15, University of California, Santa Barbara16, Commonwealth Scientific and Industrial Research Organisation17, Université Paris-Saclay18, Australian National University19, National University of Singapore20, ETH Zurich21, California Institute of Technology22, Imperial College London23, Northern Arizona University24, Oeschger Centre for Climate Change Research25, Lawrence Berkeley National Laboratory26, University of California, Berkeley27, University of Basel28, Auckland University of Technology29, Indiana University30, University of Oxford31, Spanish National Research Council32, Umeå University33, University of Exeter34, Lawrence Livermore National Laboratory35, University of California, Irvine36, United States Geological Survey37, State University of New York College of Environmental Science and Forestry38, Rutgers University39, Wageningen University and Research Centre40
TL;DR: A range of evidence supports a positive terrestrial carbon sink in response to iCO2, albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
Abstract: Atmospheric carbon dioxide concentration ([CO2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO2 ] increase and thus climate change. However, ecosystem CO2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO2 ] (iCO2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change.
TL;DR: In this paper, the authors used a suite of correlative operando scanning probe and X-ray microscopy techniques to establish a link between the oxygen evolution activity and the local operational chemical, physical and electronic nanoscale structure of single-crystalline β-Co(OH)2 platelet particles.
Abstract: Transition metal (oxy)hydroxides are promising electrocatalysts for the oxygen evolution reaction1–3. The properties of these materials evolve dynamically and heterogeneously4 with applied voltage through ion insertion redox reactions, converting materials that are inactive under open circuit conditions into active electrocatalysts during operation5. The catalytic state is thus inherently far from equilibrium, which complicates its direct observation. Here, using a suite of correlative operando scanning probe and X-ray microscopy techniques, we establish a link between the oxygen evolution activity and the local operational chemical, physical and electronic nanoscale structure of single-crystalline β-Co(OH)2 platelet particles. At pre-catalytic voltages, the particles swell to form an α-CoO2H1.5·0.5H2O-like structure—produced through hydroxide intercalation—in which the oxidation state of cobalt is +2.5. Upon increasing the voltage to drive oxygen evolution, interlayer water and protons de-intercalate to form contracted β-CoOOH particles that contain Co3+ species. Although these transformations manifest heterogeneously through the bulk of the particles, the electrochemical current is primarily restricted to their edge facets. The observed Tafel behaviour is correlated with the local concentration of Co3+ at these reactive edge sites, demonstrating the link between bulk ion-insertion and surface catalytic activity. Mapping the operational chemical, physical and electronic structure of an oxygen evolution electrocatalyst at the nanoscale links the properties of the material with the observed oxygen evolution activity.
TL;DR: It is shown here that the HE concept can lead to very substantial improvements in performance in battery cathodes, particularly in cation-disordered rocksalt-type cathodes for Li-ion batteries.
Abstract: High-entropy (HE) ceramics, by analogy with HE metallic alloys, are an emerging class of solid solutions composed of a large number of species. These materials offer the benefit of large compositional flexibility and can be used in a wide variety of applications, including thermoelectrics, catalysts, superionic conductors and battery electrodes. We show here that the HE concept can lead to very substantial improvements in performance in battery cathodes. Among lithium-ion cathodes, cation-disordered rocksalt (DRX)-type materials are an ideal platform within which to design HE materials because of their demonstrated chemical flexibility. By comparing a group of DRX cathodes containing two, four or six transition metal (TM) species, we show that short-range order systematically decreases, whereas energy density and rate capability systematically increase, as more TM cation species are mixed together, despite the total metal content remaining fixed. A DRX cathode with six TM species achieves 307 mAh g−1 (955 Wh kg−1) at a low rate (20 mA g−1), and retains more than 170 mAh g−1 when cycling at a high rate of 2,000 mA g−1. To facilitate further design in this HE DRX space, we also present a compatibility analysis of 23 different TM ions, and successfully synthesize a phase-pure HE DRX compound containing 12 TM species as a proof of concept. High-entropy ceramics are solid solutions offering compositional flexibility and wide variety of applicability. High-entropy concepts are shown to lead to substantial performance improvement in cation-disordered rocksalt-type cathodes for Li-ion batteries.
Stanford University1, Lawrence Livermore National Laboratory2, Indiana University3, Northern Arizona University4, Autonomous University of Barcelona5, Oak Ridge National Laboratory6, University of Exeter7, Lawrence Berkeley National Laboratory8, Swiss Federal Institute for Forest, Snow and Landscape Research9, ETH Zurich10, University of Cambridge11, University of Sydney12, Environmental Change Institute13, Washington State University14, University of California, Los Angeles15, California Institute of Technology16, University of Antwerp17
TL;DR: In this paper, the authors synthesize data from 108 eCO2 experiments and find that the effect of e CO2 on organic carbon stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by e CO 2, organic carbon storage declines; conversely, when biomass is weakly stimulated, SOC storage increases.
Abstract: Terrestrial ecosystems remove about 30 per cent of the carbon dioxide (CO2) emitted by human activities each year1, yet the persistence of this carbon sink depends partly on how plant biomass and soil organic carbon (SOC) stocks respond to future increases in atmospheric CO2 (refs. 2,3). Although plant biomass often increases in elevated CO2 (eCO2) experiments4–6, SOC has been observed to increase, remain unchanged or even decline7. The mechanisms that drive this variation across experiments remain poorly understood, creating uncertainty in climate projections8,9. Here we synthesized data from 108 eCO2 experiments and found that the effect of eCO2 on SOC stocks is best explained by a negative relationship with plant biomass: when plant biomass is strongly stimulated by eCO2, SOC storage declines; conversely, when biomass is weakly stimulated, SOC storage increases. This trade-off appears to be related to plant nutrient acquisition, in which plants increase their biomass by mining the soil for nutrients, which decreases SOC storage. We found that, overall, SOC stocks increase with eCO2 in grasslands (8 ± 2 per cent) but not in forests (0 ± 2 per cent), even though plant biomass in grasslands increase less (9 ± 3 per cent) than in forests (23 ± 2 per cent). Ecosystem models do not reproduce this trade-off, which implies that projections of SOC may need to be revised. A synthesis of elevated carbon dioxide experiments reveals that when plant biomass is strongly stimulated by elevated carbon dioxide levels, soil carbon storage declines, and where biomass is weakly stimulated, soil carbon accumulates.
01 Mar 2021
TL;DR: In this paper, a cationic redox-tuning method was proposed to modulate in situ catalyst leaching and to redirect the dynamic surface restructuring of layered LiCoO2−xClx (x = 0, 0.1 or 0.2), for the electrochemical oxygen evolution reaction (OER).
Abstract: Rationally manipulating the in situ formed catalytically active surface of catalysts remains a tremendous challenge for a highly efficient water electrolysis. Here we present a cationic redox-tuning method to modulate in situ catalyst leaching and to redirect the dynamic surface restructuring of layered LiCoO2–xClx (x = 0, 0.1 or 0.2), for the electrochemical oxygen evolution reaction (OER). Chlorine doping lowered the potential to trigger in situ cobalt oxidation and lithium leaching, which induced the surface of LiCoO1.8Cl0.2 to transform into a self-terminated amorphous (oxy)hydroxide phase during the OER. In contrast, Cl-free LiCoO2 required higher electrochemical potentials to initiate the in situ surface reconstruction to spinel-type Li1±xCo2O4 and longer cycles to stabilize it. Surface-restructured LiCoO1.8Cl0.2 outperformed many state-of-the-art OER catalysts and demonstrated remarkable stability. This work makes a stride in modulating surface restructuring and in designing superior OER electrocatalysts via manipulating the in situ catalyst leaching. Rationally manipulating the in-situ-formed catalytically active surface of catalysts is a challenging but promising endeavour. Now, the surface of LiCoO2 during water oxidation is engineered by Cl doping via a cationic redox-tuning method that modulates in situ leaching and redirects the dynamic surface restructuring.
TL;DR: The third version of IMG/VR is presented, composed of 18 373 cultivated and 2 314 329 uncultivated viral genomes (UViGs), nearly tripling the total number of sequences compared to the previous version, and annotated with a new standardized pipeline including genome quality estimation using CheckV and expanded host taxonomy prediction.
Abstract: Viruses are integral components of all ecosystems and microbiomes on Earth. Through pervasive infections of their cellular hosts, viruses can reshape microbial community structure and drive global nutrient cycling. Over the past decade, viral sequences identified from genomes and metagenomes have provided an unprecedented view of viral genome diversity in nature. Since 2016, the IMG/VR database has provided access to the largest collection of viral sequences obtained from (meta)genomes. Here, we present the third version of IMG/VR, composed of 18 373 cultivated and 2 314 329 uncultivated viral genomes (UViGs), nearly tripling the total number of sequences compared to the previous version. These clustered into 935 362 viral Operational Taxonomic Units (vOTUs), including 188 930 with two or more members. UViGs in IMG/VR are now reported as single viral contigs, integrated proviruses or genome bins, and are annotated with a new standardized pipeline including genome quality estimation using CheckV, taxonomic classification reflecting the latest ICTV update, and expanded host taxonomy prediction. The new IMG/VR interface enables users to efficiently browse, search, and select UViGs based on genome features and/or sequence similarity. IMG/VR v3 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.
TL;DR: In this article, it was shown that carbon-containing defects in hexagonal boron nitride (hBN) are carbon-related and that only carbon implantation creates single photon emitters in the visible spectral range.
Abstract: Single-photon emitters (SPEs) in hexagonal boron nitride (hBN) have garnered increasing attention over the last few years due to their superior optical properties. However, despite the vast range of experimental results and theoretical calculations, the defect structure responsible for the observed emission has remained elusive. Here, by controlling the incorporation of impurities into hBN via various bottom-up synthesis methods and directly through ion implantation, we provide direct evidence that the visible SPEs are carbon related. Room-temperature optically detected magnetic resonance is demonstrated on ensembles of these defects. We perform ion-implantation experiments and confirm that only carbon implantation creates SPEs in the visible spectral range. Computational analysis of the simplest 12 carbon-containing defect species suggest the negatively charged $${\rm{V}}_{\rm{B}}{\rm{C}}_{\rm{N}}^ -$$
defect as a viable candidate and predict that out-of-plane deformations make the defect environmentally sensitive. Our results resolve a long-standing debate about the origin of single emitters at the visible range in hBN and will be key to the deterministic engineering of these defects for quantum photonic devices. Comparison of hexagonal boron nitride samples grown with different techniques and with varying carbon-doping content provides evidence that the defects emitting single photons in the visible range are carbon related.
University of Arizona1, Max Planck Society2, University of California, Santa Barbara3, University of California, Irvine4, European Southern Observatory5, Carnegie Learning6, California Institute of Technology7, Lawrence Berkeley National Laboratory8, INAF9, Massachusetts Institute of Technology10, Peking University11, University of Michigan12
TL;DR: In this paper, the authors reported the discovery of a luminous quasar at $z=7.642, J0313$-$1806, the most distant quasar yet known.
Abstract: Distant quasars are unique tracers to study the formation of the earliest supermassive black holes (SMBHs) and the history of cosmic reionization. Despite extensive efforts, only two quasars have been found at $z\ge7.5$, due to a combination of their low spatial density and the high contamination rate in quasar selection. We report the discovery of a luminous quasar at $z=7.642$, J0313$-$1806, the most distant quasar yet known. This quasar has a bolometric luminosity of $3.6\times10^{13} L_\odot$. Deep spectroscopic observations reveal a SMBH with a mass of $(1.6\pm0.4) \times10^9M_\odot$ in this quasar. The existence of such a massive SMBH just $\sim$670 million years after the Big Bang challenges significantly theoretical models of SMBH growth. In addition, the quasar spectrum exhibits strong broad absorption line (BAL) features in CIV and SiIV, with a maximum velocity close to 20% of the speed of light. The relativistic BAL features, combined with a strongly blueshifted CIV emission line, indicate that there is a strong active galactic nucleus (AGN) driven outflow in this system. ALMA observations detect the dust continuum and [CII] emission from the quasar host galaxy, yielding an accurate redshift of $7.6423 \pm 0.0013$ and suggesting that the quasar is hosted by an intensely star-forming galaxy, with a star formation rate of $\rm\sim 200 ~M_\odot ~yr^{-1}$ and a dust mass of $\sim7\times10^7~M_\odot$. Followup observations of this reionization-era BAL quasar will provide a powerful probe of the effects of AGN feedback on the growth of the earliest massive galaxies.
TL;DR: This review critically analyze the most recent development in the dielectric polymers for high-temperature capacitive energy storage applications and focuses on the structural dependence of the high-field dielectrics and electrical properties and the capacitive performance, including discharged energy density, charge-discharge efficiency and cyclability, of dielectic polymers at high temperatures.
Abstract: Polymers are the preferred materials for dielectrics in high-energy-density capacitors. The electrification of transport and growing demand for advanced electronics require polymer dielectrics capable of operating efficiently at high temperatures. In this review, we critically analyze the most recent development in the dielectric polymers for high-temperature capacitive energy storage applications. While general design considerations are discussed, emphasis is placed on the elucidation of the structural dependence of the high-field dielectric and electrical properties and the capacitive performance, including discharged energy density, charge-discharge efficiency and cyclability, of dielectric polymers at high temperatures. Advantages and limitations of current approaches to high-temperature dielectric polymers are summarized. Challenges along with future research opportunities are highlighted at the end of this article.