Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

QUANTUM ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling, based on density-functional theory, plane waves, and pseudopotentials (norm-conserving, ultrasoft, and projector-augmented wave). The acronym ESPRESSO stands for opEn Source Package for Research in Electronic Structure, Simulation, and Optimization. It is freely available to researchers around the world under the terms of the GNU General Public License. QUANTUM ESPRESSO builds upon newly-restructured electronic-structure codes that have been developed and tested by some of the original authors of novel electronic-structure algorithms and applied in the last twenty years by some of the leading materials modeling groups worldwide. Innovation and efficiency are still its main focus, with special attention paid to massively parallel architectures, and a great effort being devoted to user friendliness. QUANTUM ESPRESSO is evolving towards a distribution of independent and interoperable codes in the spirit of an open-source project, where researchers active in the field of electronic-structure calculations are encouraged to participate in the project by contributing their own codes or by implementing their own ideas into existing codes.

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QUANTUM ESPRESSO: a modular and open-source software project for quantum simulations of materials

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

We present ab initio quantum-mechanical molecular-dynamics simulations of the liquid-metal--amorphous-semiconductor transition in Ge. Our simulations are based on (a) finite-temperature density-functional theory of the one-electron states, (b) exact energy minimization and hence calculation of the exact Hellmann-Feynman forces after each molecular-dynamics step using preconditioned conjugate-gradient techniques, (c) accurate nonlocal pseudopotentials, and (d) Nos\'e dynamics for generating a canonical ensemble. This method gives perfect control of the adiabaticity of the electron-ion ensemble and allows us to perform simulations over more than 30 ps. The computer-generated ensemble describes the structural, dynamic, and electronic properties of liquid and amorphous Ge in very good agreement with experiment. The simulation allows us to study in detail the changes in the structure-property relationship through the metal-semiconductor transition. We report a detailed analysis of the local structural properties and their changes induced by an annealing process. The geometrical, bonding, and spectral properties of defects in the disordered tetrahedral network are investigated and compared with experiment.

Ab initio molecular-dynamics simulation of the liquid-metal-amorphous-semiconductor transition in germanium.

The uncatalyzed edge growth of carbon nanotubes was investigated by first-principles molecular dynamics simulations. At experimental temperatures the open end of single-walled nanotubes closed spontaneously into a graphitic dome, which may explain why these nanotubes do not grow in the absence of transition metal catalysts. On the other hand, chemical bonding between the edges of adjacent coaxial tubes (“lip-lip” interactions) trapped the end of a double-walled nanotube in a metastable energy minimum, thus preventing dome closure. These calculations show that this end geometry exhibits a high degree of chemical activity and easily accommodates incoming carbon fragments, supporting a model of growth by chemisorption from the vapor phase.

Microscopic Growth Mechanisms for Carbon Nanotubes

We present results of ab-initio Molecular Dynamics simulations of the Si(111) surface. Pandey's 2 × 1 chain-geometry is obtained by simulated annealing, starting directly from the ideal bulk-terminated surface. The dynamical path followed during the reconstruction is described. The resulting 2 × 1 structure agrees well with Low Energy Electron Diffraction and Medium Energy Ion Scattering results. The phonon spectrum which is calculated ab-initio for the first time shows well defined surface modes at frequencies close to the measured values. The atomic motions and the dynamic effective charges of these modes are also analyzed.

Si(111): (2 × 1) reconstruction and surface phonons from ab-initio molecular dynamics

We present an ab initio molecular dynamics study of the structure and dynamics of a close-packed monolayer of Pb on the Ge(111) surface, with coverage FTHETA=4/3, at different temperatures. The room-temperature (\ensuremath{\surd}3 \ifmmode\times\else\texttimes\fi{} \ensuremath{\surd}3 ) structure is characterized by large in-plane fluctuations of the Pb adatoms, and agrees well with recent x-ray standing wave data. At T\ensuremath{\sim}800 K we observe a (1\ifmmode\times\else\texttimes\fi{}1) disordered structure showing in-plane diffusion of the Pb atoms. Disordering is confined to the plane of the overlayer. A strong correlation with the solid Ge substrate is present, leading to preferential residence sites and diffusion paths of the Pb atoms on the surface. The calculated local density of states for the high-temperature phase is found to agree with recent scanning tunnel microscope observations, which show a simply Pb-terminated (1\ifmmode\times\else\texttimes\fi{}1) surface with an apparent coverage FTHETA=1.

Low- and high-temperature phases of a Pb monolayer on Ge(111) from ab initio molecular dynamics

The forces derived from the Hellmann–Feynman theory, are calculated for a molecule, using the local density approximation and within the pseudopotential scheme. We show that, in contrast to the general result of all‐electrons calculations, the pseudopotential scheme allows us to obtain accurate and reliable forces with a small number of basis functions. Fast convergence in the basis set is crucial for calculations of large molecules. We apply our method to the Na2 molecule and discuss the convergence rate in detail.

Forces in pseudopotential molecular calculations

Ice Ih, the common form of ice in the biosphere, contains proton disorder. Its proton-ordered counterpart, ice XI, is thermodynamically stable below 72 K. However, even below this temperature the formation of ice XI is kinetically hindered and experimentally it is obtained by doping ice with KOH. Doping creates ionic defects that promote the migration of protons and the associated change in proton configuration. In this article, we mimic the effect of doping in molecular dynamics simulations using a bias potential that enhances the formation of ionic defects. The recombination of the ions thus formed proceeds through fast migration of the hydroxide and results in the jump of protons along a hydrogen bond loop. This provides a physical and expedite way to change the proton configuration, and to accelerate diffusion in proton configuration space. A key ingredient of this approach is a machine learning potential trained with density functional theory data and capable of modeling molecular dissociation. We exemplify the usefulness of this idea by studying the order-disorder transition using an appropriate order parameter to distinguish the proton environments in ice Ih and XI. We calculate the changes in free energy, enthalpy, and entropy associated with the transition. Our estimated entropy agrees with experiment within the error bars of our calculation.

Roberto Car

Papers

Microscopic Growth Mechanisms for Carbon Nanotubes

Si(111): (2 × 1) reconstruction and surface phonons from ab-initio molecular dynamics

Low- and high-temperature phases of a Pb monolayer on Ge(111) from ab initio molecular dynamics

Forces in pseudopotential molecular calculations

Enhancing the formation of ionic defects to study the ice Ih/XI transition with molecular dynamics simulations