Institution
Brookhaven National Laboratory
Facility•Upton, New York, United States•
About: Brookhaven National Laboratory is a facility organization based out in Upton, New York, United States. It is known for research contribution in the topics: Quantum chromodynamics & Scattering. The organization has 18828 authors who have published 39450 publications receiving 1782061 citations. The organization is also known as: BNL.
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors present a survey of the state-of-the-art marine science institutions in the United States, including the University of Alaska, Fairbanks, Alaska 99701, U.S.
399 citations
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TL;DR: In this article, the authors present a review of early eco-design tools and decision support as a key strategy for the future and provide a framework for ongoing research, as well as encourage research collaborations among the various communities interested in sustainable product realization.
Abstract: Product design is one of the most important sectors influencing global sustainability, as almost all the products consumed by people are outputs of the product development process. In particular, early design decisions can have a very significant impact on sustainability. These decisions not only relate to material and manufacturing choices but have a far-reaching effect on the product’s entire life cycle, including transportation, distribution, and end-of-life logistics. However, key challenges have to be overcome to enable eco-design methods to be applicable in early design stages. Lack of information models, semantic interoperability, methods to influence eco-design thinking in early stages, measurement science and uncertainty models in eco-decisions, and ability to balance business decisions and eco-design methodology are serious impediments to realizing sustainable products and services. Therefore, integrating downstream life cycle data into eco-design tools is essential to achieving true sustainable product development. Our review gives an overview of related research and positions early eco-design tools and decision support as a key strategy for the future. By merging sustainable thinking into traditional design methods, this review provides a framework for ongoing research, as well as encourages research collaborations among the various communities interested in sustainable product realization.
398 citations
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Institute of Cosmology and Gravitation, University of Portsmouth1, Chinese Academy of Sciences2, Leiden University3, University of Chicago4, Simon Fraser University5, University of Cambridge6, Apache Corporation7, Leibniz Institute for Astrophysics Potsdam8, Autonomous University of Madrid9, University of Córdoba (Spain)10, University of Barcelona11, Harvard University12, University of La Laguna13, Spanish National Research Council14, Korea Astronomy and Space Science Institute15, Aix-Marseille University16, Ohio State University17, Sejong University18, Max Planck Society19, New York University20, University of St Andrews21, Brookhaven National Laboratory22
TL;DR: In this article, the authors investigated whether these tensions can be interpreted as evidence for a non-constant dynamical dark energy and found that the tensions are relieved by an evolving dark energy model preferred at a 3.5σ significance level based on the improvement in the fit alone.
Abstract: A flat Friedmann–Robertson–Walker universe dominated by a cosmological constant (Λ) and cold dark matter (CDM) has been the working model preferred by cosmologists since the discovery of cosmic acceleration1,2. However, tensions of various degrees of significance are known to be present among existing datasets within the ΛCDM framework3,4,5,6,7,8,9,10,11. In particular, the Lyman-α forest measurement of the baryon acoustic oscillations (BAO) by the Baryon Oscillation Spectroscopic Survey3 prefers a smaller value of the matter density fraction Ω M than that preferred by cosmic microwave background (CMB). Also, the recently measured value of the Hubble constant, H 0 = 73.24 ± 1.74 km s−1 Mpc−1 (ref. 12), is 3.4σ higher than the 66.93 ± 0.62 km s−1 Mpc−1 inferred from the Planck CMB data7. In this work, we investigate whether these tensions can be interpreted as evidence for a non-constant dynamical dark energy. Using the Kullback–Leibler divergence13 to quantify the tension between datasets, we find that the tensions are relieved by an evolving dark energy, with the dynamical dark energy model preferred at a 3.5σ significance level based on the improvement in the fit alone. While, at present, the Bayesian evidence for the dynamical dark energy is insufficient to favour it over ΛCDM, we show that, if the current best-fit dark energy happened to be the true model, it would be decisively detected by the upcoming Dark Energy Spectroscopic Instrument survey14.
398 citations
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TL;DR: Density functional theory calculations indicate that the Au-CeOx interface is the active site for CO2 activation and the reduction to CO, where the synergy between Au and CeOx promotes the stability of key carboxyl intermediate (*COOH) and thus facilitates CO2RR.
Abstract: The electrochemical CO2 reduction reaction (CO2RR) typically uses transition metals as the catalysts. To improve the efficiency, tremendous efforts have been dedicated to tuning the morphology, size, and structure of metal catalysts and employing electrolytes that enhance the adsorption of CO2. We report here a strategy to enhance CO2RR by constructing the metal–oxide interface. We demonstrate that Au–CeOx shows much higher activity and Faradaic efficiency than Au or CeOx alone for CO2RR. In situ scanning tunneling microscopy and synchrotron-radiation photoemission spectroscopy show that the Au–CeOx interface is dominant in enhancing CO2 adsorption and activation, which can be further promoted by the presence of hydroxyl groups. Density functional theory calculations indicate that the Au–CeOx interface is the active site for CO2 activation and the reduction to CO, where the synergy between Au and CeOx promotes the stability of key carboxyl intermediate (*COOH) and thus facilitates CO2RR. Similar interface...
398 citations
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Laurentian University1, Queen's University2, University of Texas at Austin3, University of Pennsylvania4, Carleton University5, University of Alberta6, University of Guelph7, Lawrence Berkeley National Laboratory8, University of Oxford9, University of Washington10, Los Alamos National Laboratory11, Massachusetts Institute of Technology12, Louisiana State University13, Brookhaven National Laboratory14, University of British Columbia15, TRIUMF16
TL;DR: In this paper, a combined analysis of solar neutrino data from all phases of the Sudbury Neutrino Observatory was presented, which showed that particle identification information obtained from the proportional counters installed during the third phase improved background rejection in that phase of the experiment.
Abstract: We report results from a combined analysis of solar neutrino data from all phases of the Sudbury Neutrino Observatory. By exploiting particle identification information obtained from the proportional counters installed during the third phase, this analysis improved background rejection in that phase of the experiment. The combined analysis resulted in a total flux of active neutrino flavors from 8B decays in the Sun of (5.25 \pm 0.16(stat.)+0.11-0.13(syst.))\times10^6 cm^{-2}s^{-1}. A two-flavor neutrino oscillation analysis yielded \Deltam^2_{21} = (5.6^{+1.9}_{-1.4})\times10^{-5} eV^2 and tan^2{\theta}_{12}= 0.427^{+0.033}_{-0.029}. A three-flavor neutrino oscillation analysis combining this result with results of all other solar neutrino experiments and the KamLAND experiment yielded \Deltam^2_{21} = (7.41^{+0.21}_{-0.19})\times10^{-5} eV^2, tan^2{\theta}_{12} = 0.446^{+0.030}_{-0.029}, and sin^2{\theta}_{13} =(2.5^{+1.8}_{-1.5})\times10^{-2}. This implied an upper bound of sin^2{\theta}_{13} < 0.053 at the 95% confidence level (C.L.).
397 citations
Authors
Showing all 18948 results
Name | H-index | Papers | Citations |
---|---|---|---|
H. S. Chen | 179 | 2401 | 178529 |
Nora D. Volkow | 165 | 958 | 107463 |
David H. Adams | 155 | 1613 | 117783 |
Todd Adams | 154 | 1866 | 143110 |
Jay Roberts | 152 | 1562 | 120516 |
Jongmin Lee | 150 | 2257 | 134772 |
Andrew White | 149 | 1494 | 113874 |
Th. Müller | 144 | 1798 | 125843 |
Alexander Milov | 142 | 1143 | 93374 |
Alexander Belyaev | 142 | 1895 | 100796 |
Gunther Roland | 141 | 1471 | 100681 |
Mingshui Chen | 141 | 1543 | 125369 |
David Lynn | 139 | 1044 | 90913 |
Kaushik De | 139 | 1625 | 102058 |
Xin Chen | 139 | 1008 | 113088 |