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By including a fraction of exact exchange (EXX), hybrid functionals reduce the self-interaction error in semilocal density functional theory (DFT) and thereby furnish a more accurate and reliable d...

A comprehensive microscopic understanding of ambient liquid water is a major challenge for $ab$ $initio$ simulations as it simultaneously requires an accurate quantum mechanical description of the underlying potential energy surface (PES) as well as extensive sampling of configuration space. Due to the presence of light atoms (e.g., H or D), nuclear quantum fluctuations lead to observable changes in the structural properties of liquid water (e.g., isotope effects), and therefore provide yet another challenge for $ab$ $initio$ approaches. In this work, we demonstrate that the combination of dispersion-inclusive hybrid density functional theory (DFT), the Feynman discretized path-integral (PI) approach, and machine learning (ML) constitutes a versatile $ab$ $initio$ based framework that enables extensive sampling of both thermal and nuclear quantum fluctuations on a quite accurate underlying PES. In particular, we employ the recently developed deep potential molecular dynamics (DPMD) model---a neural-network representation of the $ab$ $initio$ PES---in conjunction with a PI approach based on the generalized Langevin equation (PIGLET) to investigate how isotope effects influence the structural properties of ambient liquid H$_2$O and D$_2$O. Through a detailed analysis of the interference differential cross sections as well as several radial and angular distribution functions, we demonstrate that this approach can furnish a semi-quantitative prediction of these subtle isotope effects., Comment: 19 pages, 5 figures, and 1 table

The photocatalytic activity of TiO2 for water splitting has been known for decades, yet the adsorption structure and hydrogen bonding of water at the interface with TiO2 have remained controversial. We investigate the prototypical aqueous interface with anatase TiO2 (101) using ab initio molecular dynamics (AIMD) with the strongly constrained and appropriately normed (SCAN) density functional, recently shown to provide an excellent description of the properties of bulk liquid water. We find that water forms a stable bilayer of intact molecules with ice-like dynamics and enhanced dipole moment and polarizability on the anatase surface. The orientational order and H-bond environment of interfacial water are reflected in the computed sum frequency generation (SFG) spectrum, which agrees well with recent measurements in the OH stretching frequency range (3000–3600 cm–1). Additional AIMD simulations for a model interface with 66% of dissociated water in the contact layer show that surface hydroxyls disrupt the...

In this work, an investigation of supercritical water is presented combining inelastic and deep inelastic neutron scattering experiments and molecular dynamics simulations based on a machine-learned potential of ab initio quality. The local hydrogen dynamics is investigated at 250 bar and in the temperature range of 553-823 K, covering the evolution from subcritical liquid to supercritical gas-like water. The evolution of libration, bending, and stretching motions in the vibrational density of states is studied, analyzing the spectral features by a mode decomposition. Moreover, the hydrogen nuclear momentum distribution is measured, and its anisotropy is probed experimentally. It is shown that hydrogen bonds survive up to the higher temperatures investigated, and we discuss our results in the framework of the coupling between intramolecular modes and intermolecular librations. Results show that the local potential affecting hydrogen becomes less anisotropic within the molecular plane in the supercritical phase, and we attribute this result to the presence of more distorted hydrogen bonds.

We carry out X-ray absorption spectroscopy experiment at oxygen K-edge in croconic acid (C5H2O5) crystal as a prototype of ferroelectric organic molecular solid, whose electric polarization is generated by proton transfer. The experimental spectrum is well reproduced by the electron-hole excitation theory simulations from configuration generated by ab initio molecular dynamics simulation. When inversion symmetry is broken in ferroelectric state, the hydrogen bonding environment on the two bonded molecules become inequivalent. Such a difference is sensitively probed by the bound excitation in the pre-edge, which are strongly localized on the excited molecules. Our analysis shows that a satellite peak in the pre-edge will emerge at higher excitation energy which serves as a clear signature of ferroelectricity in the material., Comment: 6 pages, 3 figures

We explore how anharmonicity, nuclear quantum effects (NQE), many-body dispersion interactions, and Pauli repulsion influence thermal properties of dispersion-bound molecular crystals. Accounting for anharmonicity with ab initio molecular dynamics yields cell parameters accurate to within $2%$ of experiment for a set of pyridinelike molecular crystals at finite temperatures and pressures. From the experimental thermal expansion curve, we find that pyridine-I has a Debye temperature just above its melting point, indicating sizable NQE across the entire crystalline range of stability. We find that NQE lead to a substantial volume increase in pyridine-I $(\ensuremath{\approx}40$% more than classical thermal expansion at 153 K) and attribute this to intermolecular Pauli repulsion promoted by intramolecular quantum fluctuations. When predicting delicate properties such as the thermal expansivity, we show that many-body dispersion interactions and more sophisticated density functional approximations improve the accuracy of the theoretical model.

We introduce a local order metric (LOM) that measures the degree of order in the neighborhood of an atomic or molecular site in a condensed medium. The LOM maximizes the overlap between the spatial distribution of sites belonging to that neighborhood and the corresponding distribution in a suitable reference system. The LOM takes a value tending to zero for completely disordered environments and tending to one for environments that perfectly match the reference. The site-averaged LOM and its standard deviation define two scalar order parameters, $S$ and $\ensuremath{\delta}S$, that characterize with excellent resolution crystals, liquids, and amorphous materials. We show with molecular dynamics simulations that $S$, $\ensuremath{\delta}S$, and the LOM provide very insightful information in the study of structural transformations, such as those occurring when ice spontaneously nucleates from supercooled water or when a supercooled water sample becomes amorphous upon progressive cooling.

We perform ab initio molecular dynamics (AIMD) simulation of liquid water in the canonical ensemble at ambient conditions using the strongly constrained and appropriately normed (SCAN) meta-generalized-gradient approximation (GGA) functional approximation and carry out systematic comparisons with the results obtained from the GGA-level Perdew-Burke-Ernzerhof (PBE) functional and Tkatchenko-Scheffler van der Waals (vdW) dispersion correction inclusive PBE functional. We analyze various properties of liquid water including radial distribution functions, oxygen-oxygen-oxygen triplet angular distribution, tetrahedrality, hydrogen bonds, diffusion coefficients, ring statistics, density of states, band gaps, and dipole moments. We find that the SCAN functional is generally more accurate than the other two functionals for liquid water by not only capturing the intermediate-range vdW interactions but also mitigating the overly strong hydrogen bonds prescribed in PBE simulations. We also compare the results of SCAN-based AIMD simulations in the canonical and isothermal-isobaric ensembles. Our results suggest that SCAN provides a reliable description for most structural, electronic, and dynamical properties in liquid water.

We have synthesized boron nitride nanotubes (BNNTs) in an arc in presence of boron and nitrogen species only, without transition metals. We find that BNNTs are often attached to pure boron nanoparticles, suggesting that root-growth is a likely mechanism for their formation. To gain further insight into this process we have studied key mechanisms for root growth of BNNTs on the surface of a liquid boron droplet by ab initio molecular dynamics simulations. We find that nitrogen atoms reside predominantly on the droplet surface where they organize to form boron nitride islands below 2400 K. To minimize contact with the liquid particle underneath, the islands assume non-planar configurations that are likely precursors for the thermal nucleation of cap structures. Once formed, the caps are stable and can easily incorporate nitrogen and boron atoms at their base, resulting in further growth. Our simulations support the root-growth mechanism of BNNTs and provide comprehensive evidence of the active role played by liquid boron., Comment: supporting inofrmation inlcuded

Quantum-mechanical calculations enable reliable computation of structures and stabilities for molecular crystal polymorphs., Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies to within 1 kJ/mol per molecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods. Specifically, we present a hierarchical energy ranking approach intended for the refinement of relative stabilities in the final stage of a crystal structure prediction procedure. Such a combined approach provides excellent stability rankings for all studied systems and can be applied to molecular crystals of pharmaceutical importance.

Quantum ESPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudo-potential and projector-augmented-wave approaches. Quantum ESPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement theirs ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software., Comment: Psi-k highlight September 2017: psi-k.net/dowlnload/highlights/Highlight_137.pdf; J. Phys.: Condens. Matter, accepted

Significance Water is vital to our everyday life, but its structure at a molecular level is still not fully understood from either experiment or theory. The latter is hampered by our inability to construct a purely predictive, first principles model. The difficulty in modeling water lies in capturing the delicate interplay among the many strong and weak forces that govern its behavior and phase diagram. Herein, molecular simulations with a recently proposed nonempirical quantum mechanical approach (the SCAN density functional) yield an excellent description of the structural, electronic, and dynamic properties of liquid water. SCAN (strongly constrained and appropriately normed)-based approaches, which describe diverse types of bonds in materials on an equal, accurate footing, will likely enable efficient and reliable modeling of aqueous phase chemistry.

Biological membranes are essential for cell life and hydration. Water provides the driving force for the assembly and stability of many cell components. Here, we study the structural properties of water in a phospholipid membrane. We characterize the local structures, inspecting the intermediate range order (IRO) and adopting a sensitive local order metric recently proposed by Martelli et al. that measures and grades the degree of overlap of the local environment with the structures of perfect ice. Close to the membrane, water acquires a high IRO and changes its dynamical properties; i.e., its translational and rotational degrees of freedom slow in a region that extends over ≃ 1 nm from the membrane interface. Surprisingly, we show that at distances as far as ≃ 2.5 nm from the interface, although the bulk-like dynamics are recovered, the IRO of water is still slightly higher than that in the bulk under the same thermodynamic conditions. Therefore, the water-membrane interface has a structural effect at ambient conditions that propagates further than the often-invoked 1-nm length scale. Consequently, this should be considered when analyzing experimental data of water confined by membranes and could help us to understand the role of water in biological systems.

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. Fil: Reilly, Anthony M.. Cambridge Crystallographic Data Centre; Fil: Cooper, Richard I.. Chemistry Research Laboratory; Fil: Adjiman, Claire S.. Imperial College London; Reino Unido Fil: Bhattacharya, Saswata. Fritz Haber Institute Of The Max Planck Society; Fil: Boese, A. Daniel. Karl-franzens-universitat Graz; Austria Fil: Brandenburg, Jan Gerit. Colegio Universitario de Londres; Reino Unido. Universitat Bonn; Alemania Fil: Bygrave, Peter J.. University of Southampton; Reino Unido Fil: Bylsma, Rita. Radboud Universiteit Nijmegen; Países Bajos Fil: Campbell, Josh E.. University of Southampton; Reino Unido Fil: Car, Roberto. University of Princeton; Estados Unidos Fil: Case, David H.. University of Southampton; Reino Unido Fil: Chadha, Renu. University Institute Of Pharmaceutical Sciences India; India Fil: Cole, Jason C.. Cambridge Crystallographic Data Centre; Fil: Cosburn, Katherine. University of Tulane; Estados Unidos. University of Toronto; Canadá Fil: Cuppen, Herma M.. Radboud Universiteit Nijmegen; Países Bajos Fil: Curtis, Farren. University of Tulane; Estados Unidos. University of Carnegie Mellon; Estados Unidos Fil: Day, Graeme M.. University of Southampton; Reino Unido Fil: DiStasio, Robert A.. University of Princeton; Estados Unidos. Cornell University; Estados Unidos Fil: Dzyabchenko, Alexander. Karpov Institute Of Physical Chemistry; Fil: Van Eijck, Bouke P.. University of Utrecht; Países Bajos. Utrecht University; Países Bajos Fil: Elking, Dennis M.. Openeye Scientific Software, Inc; Fil: Van Den Ende, Joost A.. Radboud Universiteit Nijmegen; Países Bajos Fil: Facelli, Julio C.. University of Utah; Estados Unidos Fil: Ferraro, Marta B.. Universidad de Buenos Aires; Argentina Fil: Fusti-Molnar, Laszlo. Openeye Scientific Software, Inc; Fil: Gatsiou, Christina-Anna. Imperial College London; Reino Unido Fil: Gee, Thomas S.. University of Southampton; Reino Unido Fil: De Gelder, René. Radboud Universiteit Nijmegen; Países Bajos Fil: Ghiringhelli, Luca M.. Fritz Haber Institute Of The Max Planck Society; Fil: Goto, Hitoshi. Toyohashi University Of Technology; Fil: Grimme, Stefan. Universitat Bonn; Alemania Fil: Guo, Rui. Colegio Universitario de Londres; Reino Unido Fil: Hofmann, Detlef W. M.. Flexcryst; . Polaris; Fil: Hoja, Johannes. Fritz Haber Institute Of The Max Planck Society; Fil: Hylton, Rebecca K.. Colegio Universitario de Londres; Reino Unido Fil: Iuzzolino, Luca. Colegio Universitario de Londres; Reino Unido Fil: Jankiewicz, Wojciech. University Of Silesia In Katowice; Fil: De Jong, Daniël T.. Radboud Universiteit Nijmegen; Países Bajos Fil: Kendrick, John. University Of Bradford; Fil: De Klerk, Niek J. J.. Radboud Universiteit Nijmegen; Países Bajos Fil: Ko, Hsin-Yu. University of Princeton; Estados Unidos Fil: Kuleshova, Liudmila N.. Flexcryst; Fil: Li, Xiayue. University of Tulane; Estados Unidos. Argonne National Laboratory; Estados Unidos Fil: Lohani, Sanjaya. University of Tulane; Estados Unidos Fil: Leusen, Frank J. J.. University Of Bradford; Fil: Lund, Albert M.. University of Utah; Estados Unidos. Openeye Scientific Software, Inc; Fil: Lv, Jian. Jilin University; China Fil: Ma, Yanming. Jilin University; China Fil: Marom, Noa. University of Carnegie Mellon; Estados Unidos. University of Tulane; Estados Unidos Fil: Masunov, Artëm E.. University Of Central Florida; . National Research Nuclear University Mephi; Fil: McCabe, Patrick. Cambridge Crystallographic Data Centre; Fil: McMahon, David P.. University of Southampton; Reino Unido Fil: Meekes, Hugo. Radboud Universiteit Nijmegen; Países Bajos Fil: Metz, Michael P.. University Of Delaware; Fil: Misquitta, Alston J.. Queen Mary, University Of London; Fil: Mohamed, Sharmarke. Khalifa University Of Science And Technology; Fil: Monserrat, Bartomeu. Rutgers, The State University Of New Jersey; . University of Cambridge; Estados Unidos Fil: Needs, Richard J.. University of Cambridge; Estados Unidos Fil: Neumann, Marcus A.. No especifica; Fil: Nyman, Jonas. University of Southampton; Reino Unido Fil: Obata, Shigeaki. Toyohashi University Of Technology; Fil: Oberhofer, Harald. Universitat Technical Zu Munich; Alemania Fil: Oganov, Artem R.. Northwestern Polytechnical University; China. Skolkovo Institute Of Science And Technology; . Moscow Institute Of Physics And Technology; . Stony Brook University; Fil: Orendt, Anita M.. University of Utah; Estados Unidos Fil: Pagola, Gabriel Ignacio. Universidad de Buenos Aires; Argentina Fil: Pantelides, Constantinos C.. Imperial College London; Reino Unido Fil: Pickard, Chris J.. University of Cambridge; Estados Unidos. Colegio Universitario de Londres; Reino Unido Fil: Podeszwa, Rafal. University Of Silesia In Katowice; Fil: Price, Louise S.. Colegio Universitario de Londres; Reino Unido Fil: Price, Sarah L.. Colegio Universitario de Londres; Reino Unido Fil: Pulido, Angeles. University of Southampton; Reino Unido Fil: Read, Murray G.. Cambridge Crystallographic Data Centre; Fil: Reuter, Karsten. Universitat Technical Zu Munich; Alemania Fil: Schneider, Elia. University of New York; Estados Unidos Fil: Schober, Christoph. Universitat Technical Zu Munich; Alemania Fil: Shields, Gregory P.. Cambridge Crystallographic Data Centre; Fil: Singh, Pawanpreet. University Institute Of Pharmaceutical Sciences India; India Fil: Sugden, Isaac J.. Imperial College London; Reino Unido Fil: Szalewicz, Krzysztof. University Of Delaware; Fil: Taylor, Christopher R.. University of Southampton; Reino Unido Fil: Tkatchenko, Alexandre. University Of Luxembourg; . Fritz Haber Institute Of The Max Planck Society; Fil: Tuckerman, Mark E.. University of New York; Estados Unidos. New York University Shanghai; China. Courant Institute Of Mathematical Sciences; Fil: Vacarro, Francesca. University of Tulane; Estados Unidos. Loyola University New Orleans; Fil: Vasileiadis, Manolis. Imperial College London; Reino Unido Fil: Vazquez-Mayagoitia, Alvaro. Argonne National Laboratory; Estados Unidos Fil: Vogt, Leslie. University of New York; Estados Unidos Fil: Wang, Yanchao. Jilin University; China Fil: Watson, Rona E.. Colegio Universitario de Londres; Reino Unido Fil: De Wijs, Gilles A.. Radboud Universiteit Nijmegen; Países Bajos Fil: Yang, Jack. University of Southampton; Reino Unido Fil: Zhu, Qiang. Stony Brook University; Fil: Groom, Colin R.. Cambridge Crystallographic Data Centre