Thousands Of Atoms Research Articles

SIMULATION AND 3D VISUALIZATION OF COMPLEX MOLECULAR STRUCTURE FOR STUDY OF PROTEIN AND NANO MATERIALS

Simulation and visualization of complex bio-molecules are gaining importance; this is because of the fact that functional properties of such molecules are more dependent on their 3D structures. One of the challenges of computational biology is prediction of structures of protein from amino sequence. Three dimensional visualization of molecular structure is also an important research goal in nano engineering. Such visualization, simulation and animation of reaction dynamics are essential for modern chemistry. Force field simulation of large number of atoms in complex molecular structure is computationally challenging. To find equilibrium of force fields and resultant dynamic structure of large atomic clusters which assembles to predictable molecules is one of the major goals of computational biology. In this paper we describe a simple but efficient algorithm (MoliSim3D) to simulate and dynamically visualize in 3D the assembly of atoms in presence of internal and external forces. It helps monitoring and measuring different bond angles, dimensions and displacements of selected portions from thousands of atoms forming target molecule. Pattern recognition, pattern error detection and reaction control are advance tools of virtual molecular assembly. The proposed system is basically intended as educational tool and to help researchers in understanding complex molecular dynamics and functionality with high degree of confidence in simulated environment.

Achieving linear scaling in computational cost for a fully polarizable MM/continuum embedding.

In this paper, we present a new, efficient implementation of a fully polarizable QM/MM/continuum model based on an induced-dipoles polarizable force field and on the Conductor-like Screening Model as a polarizable continuum in combination with a self-consistent field QM method. The paper focuses on the implementation of the MM/continuum embedding, where the two polarizable methods are fully coupled to take into account their mutual polarization. With respect to previous implementations, we achieve for the first time a linear scaling with respect to both the computational cost and the memory requirements without limitations on the molecular cavity shape. This is achieved thanks to the use of the recently developed ddCOSMO model for the continuum and the Fast Multipole Method for the force field, together with an efficient iterative procedure. Therefore, it becomes possible to include in the classical layer as much as several tens of thousands of atoms with a limited computational effort.

ChemInform Abstract: A Century of Powder Diffraction: A Brief History

AbstractReview: 155 refs.

Introduction to first-principles simulation package ABACUS based on systematically improvable atomic orbitals

With the rapid development of supercomputers and the advances of numerical algorithms, nowadays it is possible to study the electronic, structural and dynamical properties of complicated physical systems containing thousands of atoms using density functional theory (DFT). The numerical atomic orbitals are ideal basis sets for large-scale DFT calculations in terms of their small base size and localized characteristic, and can be mostly easily combined with linear scaling methods. Here we introduce a first-principles simulation package “Atomic-orbital Based Ab-initio Computation at UStc (ABACUS)”, developed at the Key Laboratory of Quantum Information, University of Science and Technology of China. This package provides a useful tool to study the electronic, structural and molecular dynamic properties of systems containing up to 1000 atoms. In this paper, we introduce briefly the main algorithms used in the package, including construction of the atomic orbital bases, construction of the Kohn-Sham Hamiltonian in the atomic basis sets, and some details of solving Kohn-Sham equations, including charge mixing, charge extrapolation, smearing etc. We then give some examples calculated using ABACUS: 1) the energy orders of B20 clusters; 2) the structure of bulk Ti with vacancies; 3) the density of states of a model protein; 4) the structure of a piece of DNA containing 12 base pairs, 788 atoms. All results show that the results obtained by ABACUS are in good agreement with either experimental results or results calculated using plane wave basis.

Accurate and efficient linear scaling DFT calculations with universal applicability.

Density functional theory calculations are computationally extremely expensive for systems containing many atoms due to their intrinsic cubic scaling. This fact has led to the development of so-called linear scaling algorithms during the last few decades. In this way it becomes possible to perform ab initio calculations for several tens of thousands of atoms within reasonable walltimes. However, even though the use of linear scaling algorithms is physically well justified, their implementation often introduces some small errors. Consequently most implementations offering such a linear complexity either yield only a limited accuracy or, if one wants to go beyond this restriction, require a tedious fine tuning of many parameters. In our linear scaling approach within the BigDFT package, we were able to overcome this restriction. Using an ansatz based on localized support functions expressed in an underlying Daubechies wavelet basis - which offers ideal properties for accurate linear scaling calculations - we obtain an amazingly high accuracy and a universal applicability while still keeping the possibility of simulating large system with linear scaling walltimes requiring only a moderate demand of computing resources. We prove the effectiveness of our method on a wide variety of systems with different boundary conditions, for single-point calculations as well as for geometry optimizations and molecular dynamics.

希ガス同位体質量分析の温故知新

Because noble gases are chemically inert, scarce in the earth and meteorite (except 40Ar in the earth’s atmosphere), and highly volatile, their isotope ratios have provided important insights in research fields of earth, planetary, and environmental sciences. The progress of noble gas geochemistry and cosmochemistry has been paced by the rate of developments in mass spectrometry. In this contribution, the history and basic principles of noble gas mass spectrometry and general techniques used in most modern laboratories are overviewed. The noble gas mass spectrometry has developed with inventions of various techniques—Nier type electron ionization (EI) source, static mode operation under ultrahigh-vacuum, adequately high resolution to distinguish very minor noble gas isotopes from interferences, and numerous small tips accumulated in laboratories—to attain increasingly greater precision to distinguish the often subtle variations in isotopic compositions, higher sensitivity to measure the low abundances found in many materials, and lower blanks to remove interference from atmospheric gases. New technologies recently exploited, such as simultaneous detection of noble gas isotopes with multicollector detection system, high-transmission EI source, resonance ionization, compression EI source, post-ionization of sputtered noble gases by focused ion beam, which enable us to detect quite small amount of noble gases down to several thousands of atoms, are opening new era of noble gas mass spectrometry. The highly-sensitive noble gas mass spectrometry can be applied to continuous monitoring of activity of volcanoes or active faults and to detect trace amount of noble-gas producing elements upon neutron irradiation, such as halogens, potassium, calcium, uranium, etc.

Thermally-induced chemical-order transitions in medium–large alloy nanoparticles predicted using a coarse-grained layer model

A new coarse-grained layer model (CGLM) for efficient computation of axially symmetric elemental equilibrium configurations in alloy nanoparticles (NPs) is introduced and applied to chemical-order transitions in Pt-Ir truncated octahedra (TOs) comprising up to tens of thousands of atoms. The model is based on adaptation of the free energy concentration expansion method (FCEM) using coordination-dependent bond-energy variations (CBEV) as input extracted from DFT-computed elemental bulk and surface energies. Thermally induced quite sharp transitions from low-T asymmetric quasi-Janus and quasi ball-and-cup configurations to symmetric multi-shells furnish unparalleled nanophase composite diagrams for 1289-, 2406- and 4033-atom NPs. At even higher temperatures entropic atomic mixing in the multi-shells gradually intensifies, as reflected in broad heat-capacity Schottky humps, which become sharper for much larger TOs (e.g., ∼10 nm, ∼30,000 atoms), due to transformation to solid-solution-like cores.

Electronic structure and aromaticity of large-scale hexagonal graphene nanoflakes.

With the help of the recently developed SIESTA-pole (Spanish Initiative for Electronic Simulations with Thousands of Atoms) - PEXSI (pole expansion and selected inversion) method [L. Lin, A. García, G. Huhs, and C. Yang, J. Phys.: Condens. Matter 26, 305503 (2014)], we perform Kohn-Sham density functional theory calculations to study the stability and electronic structure of hydrogen passivated hexagonal graphene nanoflakes (GNFs) with up to 11,700 atoms. We find the electronic properties of GNFs, including their cohesive energy, edge formation energy, highest occupied molecular orbital-lowest unoccupied molecular orbital energy gap, edge states, and aromaticity, depend sensitively on the type of edges (armchair graphene nanoflakes (ACGNFs) and zigzag graphene nanoflakes (ZZGNFs)), size and the number of electrons. We observe that, due to the edge-induced strain effect in ACGNFs, large-scale ACGNFs' edge formation energy decreases as their size increases. This trend does not hold for ZZGNFs due to the presence of many edge states in ZZGNFs. We find that the energy gaps E(g) of GNFs all decay with respect to 1/L, where L is the size of the GNF, in a linear fashion. But as their size increases, ZZGNFs exhibit more localized edge states. We believe the presence of these states makes their gap decrease more rapidly. In particular, when L is larger than 6.40 nm, we find that ZZGNFs exhibit metallic characteristics. Furthermore, we find that the aromatic structures of GNFs appear to depend only on whether the system has 4N or 4N + 2 electrons, where N is an integer.

A Century of Powder Diffraction: a Brief History

AbstractAlmost a century has passed since the pioneering work of Debye, Scherrer, and Hull and their first powder X‐ray diffraction experiments in 1916/17. Although these pioneers and many others discovered most of the fundamental concepts in the field of powder diffraction within the first few years, nobody at that time could foresee the development of the computer and its calculating power in the 21st century. The general availability of computing power changed the field of powder diffraction, as Hugo Rietveld showed with his computer‐assisted whole powder pattern fitting concept around fifty years after the first powder diffraction patterns were observed. Nowadays, much more complex algorithms are used to solve and identify crystal structures from powders. The intention of this historical review is to show some of the most important developments from the viewpoint of the authors in the field of powder diffraction in the last century, from the beginnings of the first transmission experiments and the determination of simple cubic crystal structures to the techniques of today allowing for the refinement of thousands of atoms within one unit cell.

Expanding the Scope of Density Derived Electrostatic and Chemical Charge Partitioning to Thousands of Atoms.

The density derived electrostatic and chemical (DDEC/c3) method is implemented into the onetep program to compute net atomic charges (NACs), as well as higher-order atomic multipole moments, of molecules, dense solids, nanoclusters, liquids, and biomolecules using linear-scaling density functional theory (DFT) in a distributed memory parallel computing environment. For a >1000 atom model of the oxygenated myoglobin protein, the DDEC/c3 net charge of the adsorbed oxygen molecule is approximately -1e (in agreement with the Weiss model) using a dynamical mean field theory treatment of the iron atom, but much smaller in magnitude when using the generalized gradient approximation. For GaAs semiconducting nanorods, the system dipole moment using the DDEC/c3 NACs is about 5% higher in magnitude than the dipole computed directly from the quantum mechanical electron density distribution, and the DDEC/c3 NACs reproduce the electrostatic potential to within approximately 0.1 V on the nanorod's solvent-accessible surface. As examples of conducting materials, we study (i) a 55-atom Pt cluster with an adsorbed CO molecule and (ii) the dense solids Mo2C and Pd3V. Our results for solid Mo2C and Pd3V confirm the necessity of a constraint enforcing exponentially decaying electron density in the tails of buried atoms.

Dynamical heterogeneity in the supercooled liquid state of the phase change material GeTe.

A contending technology for nonvolatile memories of the next generation is based on a remarkable property of chalcogenide alloys known as phase change materials, namely their ability to undergo a fast and reversible transition between the amorphous and crystalline phases upon heating. The fast crystallization has been ascribed to the persistence of a high atomic mobility in the supercooled liquid phase, down to temperatures close to the glass transition. In this work we unravel the atomistic, structural origin of this feature in the supercooled liquid state of GeTe, a prototypical phase change compound, by means of molecular dynamic simulations. To this end, we employed an interatomic potential based on a neural network framework, which allows simulating thousands of atoms for tens of ns by keeping an accuracy close to that of the underlying first-principles framework. Our findings demonstrate that the high atomic mobility is related to the presence of clusters of slow and fast moving atoms. The latter contain a large fraction of chains of homopolar Ge-Ge bonds, which at low temperatures have a tendency to move by discontinuous cage-jump rearrangements. This structural fingerprint of dynamical heterogeneity provides an explanation of the breakdown of the Stokes-Einstein relation in GeTe, which is the ultimate origin of the fast crystallization of phase change materials exploited in the devices.

Triangulating molecular surfaces over a LAN of GPU-enabled computers

The first multi-GPU marching cubes algorithm using a distributed OpenMPI-OpenMP-CUDA architecture.Triangulating and rendering of molecules with a large number of atoms (millions of atoms).A scalable solution to triangulate and render very-large datasets of molecules over a LAN populated with GPUs. Standalone GPU-enabled computers are adequate to triangulate and rendering molecular datasets with some tens of thousands of atoms at most. But, a standalone GPU-enabled computer has a limited capacity to host programable graphics cards, which in turn have also their constraints in terms of memory space. Thus, in spite of the huge memory space made available and the tremendous processing power of the current GPU-based graphics cards, there remains a scalability problem when it is necessary to triangulate and render big molecules with hundreds of thousands to millions of atoms. In order to overcome this scalability problem we use an OpenMPI-OpenMP-CUDA solution that runs on a loosely-coupled GPU cluster over a LAN (Local Area Network). More specifically, we propose a fast, scalable, parallel triangulation algorithm for molecular surfaces that takes advantage of multicore processors of CPUs and GPUs available over a local network, with each CPU core working as the master of a single GPU. The main contribution of this paper is that likely introduces the first marching cubes algorithm that triangulates molecular surfaces on CUDA devices over a network of GPU-enabled computers.

A grouping approach to homotop global optimization in alloy nanoparticles.

We propose an approach to accelerate the computational exploration and the prediction of the preferred chemical ordering in alloy nanoparticles. This approach, named Grouping Global Optimization (GGO), is based on grouping atoms into equivalence sets constrained to be occupied by the same elemental species, with a consequent significant reduction in the compositional degrees of freedom of the system. The equivalence sets are defined on the basis of point group symmetry or in general of any given order parameter, thus leaving the user a great freedom in the implementation to each specific system. The GGO approach can be used within both systematic and stochastic sampling algorithms as demonstrated by tests conducted on prototypical nanoalloys, namely on Pd-Pt and Ag-Cu binary pairs, as representative of high- or low-miscibility alloys, respectively, and on particles of two different sizes, i.e., truncated octahedra composed of 586 and 4033 atoms. It is found that GGO enables an extremely quick scan of the chemical ordering in nanoalloys containing thousands of atoms and to predict low-energy chemical ordering patterns as a function of size and composition with a modest computational effort even for the larger and symmetry-broken particles. The strategy here proposed should be applicable equally well in other fields than that of nanoalloys.

Accuracy and transferability of Gaussian approximation potential models for tungsten

We introduce interatomic potentials for tungsten in the bcc crystal phase and its defects within the Gaussian approximation potential framework, fitted to a database of first-principles density functional theory calculations. We investigate the performance of a sequence of models based on databases of increasing coverage in configuration space and showcase our strategy of choosing representative small unit cells to train models that predict properties observable only using thousands of atoms. The most comprehensive model is then used to calculate properties of the screw dislocation, including its structure, the Peierls barrier and the energetics of the vacancy-dislocation interaction. All software and raw data are available at www.libatoms.org.

FT-Raman and FTIR spectra of photoactive aminobenzazole derivatives in the solid state: A combined experimental and theoretical study

This study reports the experimental investigation of two photoactive aminobenzazole derivatives in the solid state by FT-Raman and Infrared Spectroscopies (FTIR) and its comparison with theoretical models. The optimized molecular structure, vibrational frequencies, and corresponding vibrational assignments of these compounds have been investigated experimentally and theoretically using Spanish Initiative for Electronic Simulations with Thousands of Atoms (SIESTA) and Gaussian03 Software Package. The FT-Raman and FTIR spectra were acquired with high resolution and emission frequencies identified by simulating the vibrational modes. The most intense peak observed in the FT-Raman spectra is the in-plane deformation vibrational of O–H bond that could be related to the vibrational region responsible for the stabilization of the enol conformer in the ground state which undergoes ESIPT to form a keto tautomer in the excited state. Additionally, the position of the amino group played an important role on the vibrational characteristics of the studied compounds. Also, the simulations proved to be a good approach in undertaking the FTIR and FT-Raman experiments. The use of graphic correlations helps us to determine the method and basis that best fit the experimental results.

The new phase GdFe0690Si1940as a structural intermediate of GdSi2and GdFe2Si2

Intermetallic phases are solid state compounds formed between metals that exhibit a wide structural variety and a myriad of important properties such as magnetism, catalysis, and superconductivity. Developing their properties requires an ability to control or guide their crystal structures, which can be wildly elaborate, involving thousands of atoms per unit cell. One principle for approaching this problem is the recognition that many of the most complex phases encountered in intermetallics can be understood in terms of fragments of simpler structures. The challenge of tailoring of intermetallics then lies in understanding the driving forces for the insertion of interfaces into simple structures to build complexity. We present the synthesis and the crystal structure of a new phase that sheds light on this issue, GdFe0690Si1940. It shares structural motifs with two neighboring phases in the Gd-Fe-Si system with common structure types, GdSi2(AlB2-type) and GdFe2Si2(ThCr2Si2-type). GdFe0690Si1940arises as the hexagonal nets of GdSi2are cut perpendicular to the a axis by square nets, forming distinct slabs. The surroundings of the Fe square nets locally resemble slabs of the GdFe2Si2structure, but the Fe content of the nets varies, depending on the presence of an Fe/Si mixed site. GdFe0690Si1940thus represents an intermediate point between the GdSi2and GdFe2Si2phases. This viewpoint offers the possibility of a series of crystal structures linking GdSi2and GdFe2Si2, representing a continuum of GdFexSi2phases with varying degrees of Fe incorporation, which we are now exploring synthetically.

Lattice dynamics and macroscopic properties in complex metallic alloys

Complex metallic alloys are long-range ordered materials, characterized by large unit cells, comprising several tens to thousands of atoms [1]. These complex alloys often consist of characteristic, cluster building blocks, which in many cases show icosahedral symmetry. Numerous complex phases are known, that can be described in a rather simple way as the periodic or quasi-periodic packing of such atomic clusters. The lattice dynamics of CMAs has been the subject of both theoretical and experimental investigations in view of their interesting macroscopic properties such as low thermal conductivity. In aperiodic crystals in the higher wave-vector regime, theory predicts that the lattice modes are critical: they are neither extended as in simple crystals nor localized as in disordered systems [2]. Experimentally phonons have been studied in different CMAs systems like clathrates, approximant-crystals and quasicrystals. For all of them, acoustic modes are well-defined for wave-vectors close to Brillouin zone centres, but then broaden rapidly as the result of coupling with other excitations [3]. We will present a combined experimental and atomistic simulation study of the lattice dynamics of the complex metallic alloy Al13Co4 phase [4], which is a periodic approximant of the decagonal phase. Particular attention will be paid to the differences between the periodic and `quasiperiodic' directions. Inelastic neutron scattering measurements carried out on a large, single grain on a triple-axis spectrometer will be compared to simulations, focussing on the dispersion relations and the intensity distribution of the S(Q,ω) scattering function, which is a very sensitive test of the model [3]. Simulations are performed with DFT methods and empirical, oscillating, pair potentials [5]. In addition, thermal conductivity calculations, based on the Green-Kubo method, will be compared with measurements, which show a weak anisotropy [6-7]. In this way, the structure-dynamics-properties relation for CMAs is thoroughly explored.

Multiexciton Generation in Seeded Nanorods.

The stochastic formulation of multiexciton generation (MEG) rates is extended to provide access to MEG efficiencies in nanostructures containing thousands of atoms. The formalism is applied to a series of CdSe/CdS seeded nanorod heterostructures with different core and shell dimensions. At energies above 3Eg (where Eg is the band gap), the MEG yield increases with decreasing core size, as expected for spherical nanocrystals. Surprisingly, this behavior is reversed for energies below this value, and is explained by the dependence of the density of states near the valence band edge, which increases with the core diameter. Our predictions indicate that the onset of MEG can be shifted to lower energies by manipulating the density of states in complex nanostructure geometries.

Augmented Lagrangian formulation of orbital-free density functional theory

We present an Augmented Lagrangian formulation and its real-space implementation for non-periodic Orbital-Free Density Functional Theory (OF-DFT) calculations. In particular, we rewrite the constrained minimization problem of OF-DFT as a sequence of minimization problems without any constraint, thereby making it amenable to powerful unconstrained optimization algorithms. Further, we develop a parallel implementation of this approach for the Thomas–Fermi–von Weizsacker (TFW) kinetic energy functional in the framework of higher-order finite-differences and the conjugate gradient method. With this implementation, we establish that the Augmented Lagrangian approach is highly competitive compared to the penalty and Lagrange multiplier methods. Additionally, we show that higher-order finite-differences represent a computationally efficient discretization for performing OF-DFT simulations. Overall, we demonstrate that the proposed formulation and implementation are both efficient and robust by studying selected examples, including systems consisting of thousands of atoms. We validate the accuracy of the computed energies and forces by comparing them with those obtained by existing plane-wave methods.

Next generation interatomic potentials for condensed systems

The computer simulation of condensed systems is a challenging task. While electronic structure methods like density-functional theory (DFT) usually provide a good compromise between accuracy and efficiency, they are computationally very demanding and thus applicable only to systems containing up to a few hundred atoms. Unfortunately, many interesting problems require simulations to be performed on much larger systems involving thousands of atoms or more. Consequently, more efficient methods are urgently needed, and a lot of effort has been spent on the development of a large variety of potentials enabling simulations with significantly extended time and length scales. Most commonly, these potentials are based on physically motivated functional forms and thus perform very well for the applications they have been designed for. On the other hand, they are often highly system-specific and thus cannot easily be transferred from one system to another. Moreover, their numerical accuracy is restricted by the intrinsic limitations of the imposed functional forms. In recent years, several novel types of potentials have emerged, which are not based on physical considerations. Instead, they aim to reproduce a set of reference electronic structure data as accurately as possible by using very general and flexible functional forms. In this review we will survey a number of these methods. While they differ in the choice of the employed mathematical functions, they all have in common that they provide high-quality potential-energy surfaces, while the efficiency is comparable to conventional empirical potentials. It has been demonstrated that in many cases these potentials now offer a very interesting new approach to study complex systems with hitherto unreached accuracy.