High-temperature phase transitions in dense germanium.

Through a series of high-pressure x-ray diffraction experiments combined with in situ laser heating, we explore the pressure-temperature phase diagram of germanium (Ge) at pressures up to 110 GPa and temperatures exceeding 3000 K. In the pressure range of 64-90 GPa, we observe orthorhombic Ge-IV transforming above 1500 K to a previously unobserved high-temperature phase, which we denote as Ge-VIII. This high-temperature phase is characterized by a tetragonal crystal structure, space group I4/mmm. Density functional theory simulations confirm that Ge-IV becomes unstable at high temperatures and that Ge-VIII is highly competitive and dynamically stable at these conditions. The existence of Ge-VIII has profound implications for the pressure-temperature phase diagram, with melting conditions increasing to much higher temperatures than previous extrapolations would imply

High-temperature phase transitions in dense germanium.

Through a series of high-pressure x-ray diffraction experiments combined with in situ laser heating, we explore the pressure-temperature phase diagram of germanium (Ge) at pressures up to 110 GPa and temperatures exceeding 3000 K. In the pressure range of 64-90 GPa, we observe orthorhombic Ge-IV transforming above 1500 K to a previously unobserved high-temperature phase, which we denote as Ge-VIII. This high-temperature phase is characterized by a tetragonal crystal structure, space group I4/mmm. Density functional theory simulations confirm that Ge-IV becomes unstable at high temperatures and that Ge-VIII is highly competitive and dynamically stable at these conditions. The existence of Ge-VIII has profound implications for the pressure-temperature phase diagram, with melting conditions increasing to much higher temperatures than previous extrapolations would imply

Priming for self-esteem influences the monitoring of one’s own performance

Social cues have subtle effects on a person, often without them being aware. One explanation for this influence involves implicit priming of trait associations. To study this effect, we activated implicit associations in participants of ‘being Clever’ or ‘being Stupid’ that were task relevant, and studied its behavioural impact on an independent cognitive task (the n-back task). Activating a representation of ‘Clever’ caused participants to slow their reaction times after errors on the working memory task, while the reverse pattern was seen for associations to ‘Stupid’. Critically, these behavioural effects were absent in control conditions. Using functional magnetic resonance imaging, we show that the neural basis of this effect involves the anterior paracingulate cortex (area 32) where activity tracked the observed behavioural pattern, increasing its activity during error monitoring in the ‘Clever’ condition and decreasing in the ‘Stupid’ condition. The data provide a quantitative demonstration of how implicit cues, which specifically target a person’s self-concept, influences the way we react to our own behaviour and point to the anterior paracingulate cortex as a critical cortical locus for mediating these self-concept related behavioural regulations

NMR parameters in alkali, alkaline earth and rare earth fluorides from first principle calculations

19F isotropic chemical shifts for alkali, alkaline earth and rare earth of column 3 basic fluorides are measured and the corresponding isotropic chemical shieldings are calculated using the GIPAW method. When using PBE exchange correlation functional for the treatment of the cationic localized empty orbitals of Ca2+, Sc3+ (3d) and La3+ (4f), a correction is needed to accurately calculate 19F chemical shieldings. We show that the correlation between experimental isotropic chemical shifts and calculated isotropic chemical shieldings established for the studied compounds allows to predict 19F NMR spectra of crystalline compounds with a relatively good accuracy. In addition, we experimentally determine the quadrupolar parameters of 25Mg in MgF2 and calculate the electric field gradient of 25Mg in MgF2 and 139La in LaF3 using both PAW and LAPW methods. The orientation of the EFG components in the crystallographic frame, provided by DFT calculations, is analysed in term of electron densities. It is shown that consideration of the quadrupolar charge deformation is essential for the analysis of slightly distorted environments or highly irregular polyhedra.Comment: 18 pages, 8 figures, 4 tables and ES

A survey for variable young stars with small telescopes: II - mapping a protoplanetary disc with stable structures at 0.15 au

The HOYS citizen science project conducts long term, multifilter, high cadence monitoring of large YSO samples with a wide variety of professional and amateur telescopes. We present the analysis of the light curve of V1490 Cyg in the Pelican Nebula. We show that colour terms in the diverse photometric data can be calibrated out to achieve a median photometric accuracy of 0.02 mag in broadband filters, allowing detailed investigations into a variety of variability amplitudes over timescales from hours to several years. Using Gaia DR2 we estimate the distance to the Pelican Nebula to be 870 +70 −55 pc. V1490 Cyg is a quasi-periodic dipper with a period of 31.447 ± 0.011 d. The obscuring dust has homogeneous properties, and grains larger than those typical in the ISM. Larger variability on short timescales is observed in U and Rc−Hα, with U-amplitudes reaching 3 mag on timescales of hours, indicating the source is accreting. The Hα equivalent width and NIR/MIR colours place V1490 Cyg between CTTS/WTTS and transition disk objects. The material responsible for the dipping is located in a warped inner disk, about 0.15 AU from the star. This mass reservoir can be filled and emptied on time scales shorter than the period at a rate of up to 10−10 M�/yr, consistent with low levels of accretion in other T Tauri stars. Most likely the warp at this separation from the star is induced by a protoplanet in the inner accretion disk. However, we cannot fully rule out the possibility of an AA Tau-like warp, or occultations by the Hill sphere around a forming planet

Remote ischemic conditioning: from experimental observation to clinical application: report from the 8th Biennial Hatter Cardiovascular Institute Workshop

In 1993, Przyklenk and colleagues made the intriguing experimental observation that 'brief ischemia in one vascular bed also protects remote, virgin myocardium from subsequent sustained coronary artery occlusion' and that this effect '.... may be mediated by factor(s) activated, produced, or transported throughout the heart during brief ischemia/reperfusion'. This seminal study laid the foundation for the discovery of 'remote ischemic conditioning' (RIC), a phenomenon in which the heart is protected from the detrimental effects of acute ischemia/reperfusion injury (IRI), by applying cycles of brief ischemia and reperfusion to an organ or tissue remote from the heart. The concept of RIC quickly evolved to extend beyond the heart, encompassing inter-organ protection against acute IRI. The crucial discovery that the protective RIC stimulus could be applied non-invasively, by simply inflating and deflating a blood pressure cuff placed on the upper arm to induce cycles of brief ischemia and reperfusion, has facilitated the translation of RIC into the clinical setting. Despite intensive investigation over the last 20 years, the underlying mechanisms continue to elude researchers. In the 8th Biennial Hatter Cardiovascular Institute Workshop, recent developments in the field of RIC were discussed with a focus on new insights into the underlying mechanisms, the diversity of non-cardiac protection, new clinical applications, and large outcome studies. The scientific advances made in this field of research highlight the journey that RIC has made from being an intriguing experimental observation to a clinical application with patient benefit

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447

Report on the sixth blind test of organic crystal-structure prediction methods

The sixth blind test of organic crystal-structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal, and a bulky flexible molecule. This blind test has seen substantial growth in the number of submissions, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and "best practices" for performing CSP calculations. All of the targets, apart from a single potentially disordered Z` = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms