45 research outputs found
First-principles calculations of the crystal structure, electronic structure, and thermodynamic stability of Be(BH4)2
Alanates and boranates are intensively studied because of their potential use as hydrogen storage materials. In this paper, we present a first-principles study of the electronic structure and the energetics of beryllium boranate BeBH42. From total energy calculations, we show that—in contrast to the other boranates and alanates—hydrogen desorption directly to the elements is likely and is at least competitive with desorption to the elemental hydride BeH2. The formation enthalpy of BeBH42 is only −0.14 eV/H2 at T=0 K. This low value can be rationalized by the participation of all atoms in the covalent bonding, which is in contrast to the ionic bonding observed in other boranates. From calculations of thermodynamic properties at finite temperature, we estimate a decomposition temperature of 162 K at a pressure of 1 bar
Tunable Hydrogen Storage in Magnesium - Transition Metal Compounds
Magnesium dihydride (\mgh) stores 7.7 weight % hydrogen, but it suffers
from a high thermodynamic stability and slow (de)hydrogenation kinetics.
Alloying Mg with lightweight transition metals (TM = Sc, Ti, V, Cr) aims at
improving the thermodynamic and kinetic properties. We study the structure and
stability of MgTMH compounds, -1], by first-principles
calculations at the level of density functional theory. We find that the
experimentally observed sharp decrease in hydrogenation rates for
correlates with a phase transition of MgTMH from a fluorite to
a rutile phase. The stability of these compounds decreases along the series Sc,
Ti, V, Cr. Varying the transition metal (TM) and the composition , the
formation enthalpy of MgTMH can be tuned over the substantial
range 0-2 eV/f.u. Assuming however that the alloy MgTM does not
decompose upon dehydrogenation, the enthalpy associated with reversible
hydrogenation of compounds with a high magnesium content () is close to
that of pure Mg.Comment: 8 pages, 5 figure
Modeling the polymorphism of pentacene
Thin films of pentacene are known to crystallize in at least four different polymorphs. All polymorphs are layered structures that are characterized by their interlayer spacing d(001). We develop a model that rationalizes the size of the interlayer spacing in terms of intralayer shifts of the pentacene molecules along their long molecular axes. It explains the wide variety of interlayer spacings, without distorting the herringbone pattern that is characteristic of many acenes. Using two simple theoretical models, we attempt to relate the intralayer shifts with the dominant, although weak, interatomic interactions (van der Waals, weak electrostatic, and covalent). For two polymorphs, a consistent picture is found. A full understanding of the other two, substrate-induced, polymorphs probably requires consideration of interlayer interactions
Anisotropy of the Mobility of Pentacene from Frustration
The bandstructure of pentacene is calculated using first-principles density
functional theory. A large anisotropy of the hole and electron effective masses
within the molecular planes is found. The band dispersion of the HOMO and the
LUMO is analyzed with the help of a tight-binding fit. The anisotropy is shown
to be intimately related to the herringbone structure.Comment: Accepted for publication in Synthetic Metal
First principles modelling of magnesium titanium hydrides
Mixing Mg with Ti leads to a hydride Mg(x)Ti(1-x)H2 with markedly improved
(de)hydrogenation properties for x < 0.8, as compared to MgH2. Optically, thin
films of Mg(x)Ti(1-x)H2 have a black appearance, which is remarkable for a
hydride material. In this paper we study the structure and stability of
Mg(x)Ti(1-x)H2, x= 0-1 by first-principles calculations at the level of density
functional theory. We give evidence for a fluorite to rutile phase transition
at a critical composition x(c)= 0.8-0.9, which correlates with the
experimentally observed sharp decrease in (de)hydrogenation rates at this
composition. The densities of states of Mg(x)Ti(1-x)H2 have a peak at the Fermi
level, composed of Ti d states. Disorder in the positions of the Ti atoms
easily destroys the metallic plasma, however, which suppresses the optical
reflection. Interband transitions result in a featureless optical absorption
over a large energy range, causing the black appearance of Mg(x)Ti(1-x)H2.Comment: 22 pages, 9 figures, 4 table
A model for the formation energies of alanates and boranates
We develop a simple model for the formation energies (FEs) of alkali and
lkaline earth alanates and boranates, based upon ionic bonding between metal
cations and (AlH4)- or (BH4)- anions. The FEs agree well with values obtained
from first principles calculations and with experimental FEs. The model shows
that details of the crystal structure are relatively unimportant. The small
size of the (BH4)- anion causes a strong bonding in the crystal, which makes
boranates more stable than alanates. Smaller alkali or alkaline earth cations
do not give an increased FE. They involve a larger ionization potential that
compensates for the increased crystal bonding.Comment: 3 pages, 2 figure
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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
Chlorine on Si(001)-(2 x 1) : bridge versus terminal bonding
We present density functional calculations of the bonding structures and diffusion barriers for a Cl adatom on Si(001)-(2×1). Besides the stable adsorption site at the dangling bond (DB), a metastable bridge-bonded state breaking a surface dimer bond and ~1.1 eV higher in energy than the DB is found. The calculated properties of this state agree with recent ESDIAD and HREELS observations. This bridge-bonded site is not along the Cl intradimer diffusion pathway of lowest energy. For this path a transition state also having a bridging structure (but not breaking the dimer bond) and rather low in energy ( ~0.6 eV with respect to the DB) is determined. The low intradimer barrier is consistent with the facile switching of Cl recently observed in scanning tunneling microscopy experiments