ALBERT

Description: Author(s): N. D. Lepley and N. A. W. Holzwarth We present a general scheme to model an energy for analyzing interfaces between crystalline solids, quantitatively including the effects of varying configurations and lattice strain. This scheme is successfully applied to the modeling of likely interface geometries of several solid state battery mat… [Phys. Rev. B 92, 214201] Published Tue Dec 01, 2015

Description: The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Lejaeghere, Kurt -- Bihlmayer, Gustav -- Bjorkman, Torbjorn -- Blaha, Peter -- Blugel, Stefan -- Blum, Volker -- Caliste, Damien -- Castelli, Ivano E -- Clark, Stewart J -- Dal Corso, Andrea -- de Gironcoli, Stefano -- Deutsch, Thierry -- Dewhurst, John Kay -- Di Marco, Igor -- Draxl, Claudia -- Dulak, Marcin -- Eriksson, Olle -- Flores-Livas, Jose A -- Garrity, Kevin F -- Genovese, Luigi -- Giannozzi, Paolo -- Giantomassi, Matteo -- Goedecker, Stefan -- Gonze, Xavier -- Granas, Oscar -- Gross, E K U -- Gulans, Andris -- Gygi, Francois -- Hamann, D R -- Hasnip, Phil J -- Holzwarth, N A W -- Iusan, Diana -- Jochym, Dominik B -- Jollet, Francois -- Jones, Daniel -- Kresse, Georg -- Koepernik, Klaus -- Kucukbenli, Emine -- Kvashnin, Yaroslav O -- Locht, Inka L M -- Lubeck, Sven -- Marsman, Martijn -- Marzari, Nicola -- Nitzsche, Ulrike -- Nordstrom, Lars -- Ozaki, Taisuke -- Paulatto, Lorenzo -- Pickard, Chris J -- Poelmans, Ward -- Probert, Matt I J -- Refson, Keith -- Richter, Manuel -- Rignanese, Gian-Marco -- Saha, Santanu -- Scheffler, Matthias -- Schlipf, Martin -- Schwarz, Karlheinz -- Sharma, Sangeeta -- Tavazza, Francesca -- Thunstrom, Patrik -- Tkatchenko, Alexandre -- Torrent, Marc -- Vanderbilt, David -- van Setten, Michiel J -- Van Speybroeck, Veronique -- Wills, John M -- Yates, Jonathan R -- Zhang, Guo-Xu -- Cottenier, Stefaan -- New York, N.Y. -- Science. 2016 Mar 25;351(6280):aad3000. doi: 10.1126/science.aad3000.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Molecular Modeling, Ghent University, Technologiepark 903, BE-9052 Zwijnaarde, Belgium. ; Peter Grunberg Institute and Institute for Advanced Simulation, Forschungszentrum Julich and JARA (Julich Aachen Research Alliance), D-52425 Julich, Germany. ; Department of Physics, Abo Akademi, FI-20500 Turku, Finland. Centre of Excellence in Computational Nanoscience (COMP) and Department of Applied Physics, Aalto University School of Science, Post Office Box 11100, FI-00076 Aalto, Finland. ; Institute of Materials Chemistry, Vienna University of Technology, Getreidemarkt 9/165-TC, A-1060 Vienna, Austria. ; Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC 27708, USA. ; Universite Grenoble Alpes, Institut Nanosciences et Cryogenie-Modeling and Material Exploration Department (INAC-MEM), Laboratoire de Simulation Atomistique (L_Sim), F-38042 Grenoble, France. Commissariat a l'Energie Atomique et aux Energies Alternatives (CEA), INAC-MEM, L_Sim, F-38054 Grenoble, France. ; Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne, Switzerland. ; Department of Physics, University of Durham, Durham DH1 3LE, UK. ; International School for Advanced Studies (SISSA) and DEMOCRITOS, Consiglio Nazionale delle Ricerche-Istituto Officina dei Materiali (CNR-IOM), Via Bonomea 265, I-34136 Trieste, Italy. ; Max-Planck-Institut fur Mikrostrukturphysik, Weinberg 2, D-06120 Halle, Germany. ; Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Post Office Box 516, SE-75120 Uppsala, Sweden. ; Institut fur Physik and Integrative Research Institute for the Sciences (IRIS)-Adlershof, Humboldt-Universitat zu Berlin, Zum Grossen Windkanal 6, D-12489 Berlin, Germany. Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany. ; Center for Atomic-Scale Materials Design, Department of Physics, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark. ; Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8553, Gaithersburg, MD 20899, USA. ; Department of Mathematics, Computer Science, and Physics, University of Udine, Via delle Scienze 206, I-33100 Udine, Italy. ; Institute of Condensed Matter and Nanosciences-Nanoscopic Physics (NAPS), Universite Catholique de Louvain, Chemin des Etoiles 8, BE-1348 Louvain-la-Neuve, Belgium. ; Institut fur Physik, Universitat Basel, Klingelbergstrasse 82, CH-4056 Basel, Switzerland. ; Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Post Office Box 516, SE-75120 Uppsala, Sweden. School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA. ; Department of Computer Science, University of California-Davis, Davis, CA 95616, USA. ; Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854-8019, USA. Mat-Sim Research, Post Office Box 742, Murray Hill, NJ 07974, USA. ; Department of Physics, University of York, Heslington, York YO10 5DD, UK. ; Department of Physics, Wake Forest University, Winston-Salem, NC 27109, USA. ; Scientific Computing Department, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot OX11 0QX, UK. ; CEA, DAM, DIF, F-91297 Arpajon, France. ; Department of Materials, University of Oxford, 16 Parks Road, Oxford OX1 3PH, UK. ; Faculty of Physics and Center for Computational Materials Science, University of Vienna, Sensengasse 8/12, A-1090 Vienna, Austria. ; LeibnizInstitut fur Festkorper- und Werkstoffforschung (IFW) Dresden, Post Office Box 270 116, D-01171 Dresden, Germany. Dresden Center for Computational Materials Science (DCMS), Technische Universitat Dresden, D-01069 Dresden, Germany. ; Theory and Simulation of Materials (THEOS) and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), Ecole Polytechnique Federale de Lausanne, CH-1015 Lausanne, Switzerland. International School for Advanced Studies (SISSA) and DEMOCRITOS, Consiglio Nazionale delle Ricerche-Istituto Officina dei Materiali (CNR-IOM), Via Bonomea 265, I-34136 Trieste, Italy. ; Department of Physics and Astronomy, Division of Materials Theory, Uppsala University, Post Office Box 516, SE-75120 Uppsala, Sweden. Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, Netherlands. ; Institut fur Physik and Integrative Research Institute for the Sciences (IRIS)-Adlershof, Humboldt-Universitat zu Berlin, Zum Grossen Windkanal 6, D-12489 Berlin, Germany. ; LeibnizInstitut fur Festkorper- und Werkstoffforschung (IFW) Dresden, Post Office Box 270 116, D-01171 Dresden, Germany. ; Institute for Solid State Physics, The University of Tokyo, Kashiwa 277-8581, Japan. ; Institut de Mineralogie, de Physique des Materiaux, et de Cosmochimie (IMPMC), Sorbonne Universites-Pierre and Marie Curie University Paris 06, Centre National de la Recherche Scientifique (CNRS) Unite Mixte de Recherche (UMR) 7590, Museum National d'Histoire Naturelle, Institut de Recherche pour le Developpement (IRD) Unite de Recherche 206, 4 Place Jussieu, F-75005 Paris, France. ; Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, UK. ; Center for Molecular Modeling, Ghent University, Technologiepark 903, BE-9052 Zwijnaarde, Belgium. High Performance Computing Unit, Ghent University, Krijgslaan 281 S9, BE-9000 Ghent, Belgium. ; Department of Physics, Royal Holloway, University of London, Egham TW20 0EX, UK. ISIS Facility, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Didcot OX11 0QX, UK. ; Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany. Department of Chemistry and Biochemistry and Materials Department, University of California-Santa Barbara, Santa Barbara, CA 93106-5050, USA. ; Institute for Solid State Physics, Vienna University of Technology, A-1040 Vienna, Austria. ; Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg 4-6, D-14195 Berlin, Germany. Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg. ; Department of Physics and Astronomy, Rutgers University, Piscataway, NJ 08854-8019, USA. ; Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. ; Institute of Theoretical and Simulational Chemistry, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin 150001, People's Republic of China. ; Center for Molecular Modeling, Ghent University, Technologiepark 903, BE-9052 Zwijnaarde, Belgium. Department of Materials Science and Engineering, Ghent University, Technologiepark 903, BE-9052 Zwijnaarde, Belgium.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/27013736" target="_blank"〉PubMed〈/a〉

Description: Browsing of tree saplings by deer hampers forest regeneration in mixed forests across Europe and North America. It is well known that tree species are differentially affected by deer browsing, but little is known about how different facets of diversity, such as species richness, identity, and composition, affect browsing intensity at different spatial scales. Using forest inventory data from the Hainich National Park, a mixed deciduous forest in central Germany, we applied a hierarchical approach to model the browsing probability of patches (regional scale) as well as the species-specific proportion of saplings browsed within patches (patch scale). We found that, at the regional scale, the probability that a patch was browsed increased with certain species composition, namely with low abundance of European beech ( Fagus sylvatica L.) and high abundance of European ash ( Fraxinus excelsior L.), whereas at the patch scale, the proportion of saplings browsed per species was mainly determined by the species’ identity, providing a “preference ranking” of the 11 tree species under study. Interestingly, at the regional scale, species-rich patches were more likely to be browsed; however, at the patch scale, species-rich patches showed a lower proportion of saplings per species browsed. Presumably, diverse patches attract deer, but satisfy nutritional needs faster, such that fewer saplings need to be browsed. Some forest stand parameters, such as more open canopies, increased the browsing intensity at either scale. By showing the effects that various facets of diversity, as well as environmental parameters, exerted on browsing intensity at the regional as well as patch scale, our study advances the understanding of mammalian herbivore–plant interactions across scales. Our results also indicate which regeneration patches and species are (least) prone to browsing and show the importance of different facets of diversity for the prediction and management of browsing intensity and regeneration dynamics. Using forest inventory data, we examined how different facets of diversity, such as species richness, identity, and composition, affect browsing intensity at different spatial scales. We found that, at the regional scale, the browsing probability of a patch was mainly driven by species composition, whereas at the regional scale, the proportion of individual saplings browsed was mainly determined by the species’ identity, providing a “preference ranking” of the 11 tree species under study. Interestingly, at the regional scale, species-rich patches were more likely to be browsed; however, at the patch scale, species-rich patches had a lower proportion of saplings per species browsed, which shows that species richness can have opposing effects on mammalian browsing, depending on the scale of foraging decision.

Description: Nonphotochemical quenching (NPQ) is the process that protects the photosynthetic apparatus of plants and algae from photodamage by dissipating as heat the energy absorbed in excess. Studies on NPQ have almost exclusively focused on photosystem II (PSII), as it was believed that NPQ does not occur in photosystem I (PSI)....

Description: Context. Convective motions in the solar atmosphere cause spectral lines to become asymmetric and shifted in wavelength. For photospheric lines, this differential Doppler shift varies from the solar disk center to the limb. Aims. Precise and comprehensive observations of the convective blueshift and its center-to-limb variation improve our understanding of the atmospheric hydrodynamics and ensuing line formation, and provide the basis to refine 3D models of the solar atmosphere. Methods. We performed systematical spectroscopic measurements of the convective blueshift of the quiet Sun with the Laser Absolute Reference Spectrograph (LARS) at the German Vacuum Tower Telescope. The spatial scanning of the solar disk covered 11 heliocentric positions each along four radial (meridional and equatorial) axes. The high-resolution spectra of 26 photospheric to chromospheric lines in the visible range were calibrated with a laser frequency comb to absolute wavelengths at the 1 m s−1 accuracy. Applying ephemeris and reference corrections, the bisector analysis provided line asymmetries and Doppler shifts with an uncertainty of only few m s−1. To allow for a comparison with other observations, we convolved the results to lower spectral resolutions. Results. All spectral line bisectors exhibit a systematic center-to-limb variation. Typically, a blueshifted “C”-shaped curve at disk center transforms into a less blueshifted “”-shape toward the solar limb. The comparison of all lines reveals the systematic dependence of the convective blueshift on the line depth. The blueshift of the line minima describe a linear decrease with increasing line depths. The slope of the center-to-limb variation develops a reversal point at heliocentric positions between μ = 0.7 and 0.85, seen as the effect of horizontal granular flows in the mid photosphere. Line minima formed in the upper photosphere to chromosphere exhibit hardly any blueshift or even a slight redshift. Synthetic models yield considerable deviations from the observed center-to-limb variation. Conclusions. The obtained Doppler shifts of the quiet Sun can serve as an absolute reference for other observations, the relative calibration of Dopplergrams, and the necessary refinement of atmospheric models. Based on this, the development of high-precision models of stellar surface convection will advance the detection of (potentially habitable) exoplanets by radial velocity measurements.