Thousands Of Atoms Research Articles

LDA + U Study of Induced Half Metallicity in Cr-Doped GaN

Half-metallic ferromagnetism in the Ga1 − xCrxN compound at different concentrations, x = 25, 12.5 and 6.25 %, have been investigated using density functional theory as implemented in code Spanish Initiative for Electronic Simulations with Thousands of Atoms (SIESTA) using LDA + U as exchange-correlation (XC) potential, to find out the possibility of new diluted DMSs. The outcomes reveal that transition metal atom (Cr) doping in GaN induces ferromagnetism. The 3d levels of the TM ion originate a half-metallic gap at the Fermi level in the majority spin channel for all concentrations. Moreover, diluted magnetic semiconductor compounds retain the half-metallic nature at all concentrations, i.e., x = 0.25, 0.125 and 0.0625, with 100 % spin polarization at the Fermi level (EF). The total magnetic moment of these compounds is due to Cr-3d states, and the existence of a small magnetic moment on Ga and N, non-magnetic atoms, for all doping concentrations is a consequence of p-d hybridization of Cr-d and N-p states. The calculated values of s-d exchange constant N α and p-d exchange constant N βconfirm the ferromagnetic character of the Cr-doped GaN compound.

Detailing Protein Landscapes under Pressure

Natural protein molecules are remarkable physical objects. Despite the astronomical number of competing structural forms, these systems self-organize into beautiful structural ensembles in biologically short timescales, puzzling out the feat of specifically bringing together thousands of atoms interacting by a myriad of weak forces. Moreover, most protein domains appear to fold with ease in a deceptively simple two-state manner, populating either the fully folded or fully unfolded ensembles. This is certainly not a property of random amino acid chains…how do proteins do it?

Self-consistent implementation of meta-GGA functionals for the ONETEP linear-scaling electronic structure package.

Accurate and computationally efficient exchange-correlation functionals are critical to the successful application of linear-scaling density functional theory (DFT). Local and semi-local functionals of the density are naturally compatible with linear-scaling approaches, having a general form which assumes the locality of electronic interactions and which can be efficiently evaluated by numerical quadrature. Presently, the most sophisticated and flexible semi-local functionals are members of the meta-generalized-gradient approximation (meta-GGA) family, and depend upon the kinetic energy density, τ, in addition to the charge density and its gradient. In order to extend the theoretical and computational advantages of τ-dependent meta-GGA functionals to large-scale DFT calculations on thousands of atoms, we have implemented support for τ-dependent meta-GGA functionals in the ONETEP program. In this paper we lay out the theoretical innovations necessary to implement τ-dependent meta-GGA functionals within ONETEP's linear-scaling formalism. We present expressions for the gradient of the τ-dependent exchange-correlation energy, necessary for direct energy minimization. We also derive the forms of the τ-dependent exchange-correlation potential and kinetic energy density in terms of the strictly localized, self-consistently optimized orbitals used by ONETEP. To validate the numerical accuracy of our self-consistent meta-GGA implementation, we performed calculations using the B97M-V and PKZB meta-GGAs on a variety of small molecules. Using only a minimal basis set of self-consistently optimized local orbitals, we obtain energies in excellent agreement with large basis set calculations performed using other codes. Finally, to establish the linear-scaling computational cost and applicability of our approach to large-scale calculations, we present the outcome of self-consistent meta-GGA calculations on amyloid fibrils of increasing size, up to tens of thousands of atoms.

The young person's guide to the PDB.

The Protein Data Bank (PDB), created in 1971 when merely seven protein crystal structures were known, today holds over 120, 000 experimentally-determined three-dimensional models of macromolecules, including gigantic structures comprised of hundreds of thousands of atoms, such as ribosomes and viruses. Most of the deposits come from X-ray crystallography experiments, with important contributions also made by NMR spectroscopy and, recently, by the fast growing Cryo-Electron Microscopy. Although the determination of a macromolecular crystal structure is now facilitated by advanced experimental tools and by sophisticated software, it is still a highly complicated research process requiring specialized training, skill, experience and a bit of luck. Understanding the plethora of structural information provided by the PDB requires that its users (consumers) have at least a rudimentary initiation. This is the purpose of this educational overview.

Polyyne electronic and vibrational properties under environmental interactions

Recently the novel system of linear carbon chains inside double-walled carbon nanotubes has extended the length of $s{p}^{1}$ hybridized carbon chains from 44 to thousands of atoms [Shi et al., Nat. Mater. 15, 634 (2016)]. The optoelectronic properties of these ultralong chains are poorly described by current theoretical models, which are based on short chain experimental data and assume a constant environment. As such, a physical understanding of the system in terms of charge transfer and van der Waals interactions is widely missing. We provide a reference for the intrinsic Raman frequency of polyynes in vacuo and explicitly describe the interactions between polyynes and carbon nanotubes. We find that van der Waals interactions strongly shift this frequency, which has been neither expected nor described for other intramolecular C-C stretching vibrations. As a consequence of charge transfer from the tube to the chain, the Raman response of long chains is qualitatively different from the known phonon dispersion of polymers close to the $\mathrm{\ensuremath{\Gamma}}$ point. Based on these findings we show how to correctly interpret the Raman data, considering the nanotube's properties. This is essential for its use as an analytical tool to optimize the growth process for future applications.

Linear-scaling density functional theory using the projector augmented wave method

Quantum mechanical simulation of realistic models of nanostructured systems, such as nanocrystals and crystalline interfaces, demands computational methods combining high-accuracy with low-order scaling with system size. Blöchl’s projector augmented wave (PAW) approach enables all-electron (AE) calculations with the efficiency and systematic accuracy of plane-wave pseudopotential calculations. Meanwhile, linear-scaling (LS) approaches to density functional theory (DFT) allow for simulation of thousands of atoms in feasible computational effort. This article describes an adaptation of PAW for use in the LS-DFT framework provided by the ONETEP LS-DFT package. ONETEP uses optimisation of the density matrix through in situ-optimised local orbitals rather than the direct calculation of eigenstates as in traditional PAW approaches. The method is shown to be comparably accurate to both PAW and AE approaches and to exhibit improved convergence properties compared to norm-conserving pseudopotential methods.

O(NlogN) scaling method to evaluate the ion-electron potential of crystalline solids.

We propose a simple O(NlogN) scaling expression in reciprocal space for evaluating the ion-electron potential of crystalline solids. The expression replaces the long-range ion-electron potential with an equivalent localized charge distribution and corresponding boundary conditions on the unit cell. Given that no quadratic scaling structure factor is required-as used in traditional methods-the expression shows the inherent O(NlogN) behavior, and is well suited to simulating large-scale systems within orbital-free density functional theory. The scheme is implemented in the ATLAS software package and benchmarked by using a solid Mg body-centered cubic lattice containing tens of thousands of atoms in the unit cell. The test results show that the method can efficiently simulate large scale crystals with high computational accuracy.

Lattice thermal conductivity of boron nitride nanoribbon from molecular dynamics simulation

The lattice thermal conductivity of boron nitride nanoribbon(BNNR) is calculated by using equilibrium molecular dynamics (EMD) simulation method. The Green–Kubo relation derived from linear response theory is used to acquire the thermal conductivity from heat current auto-correlation function (HCACF). HCACF of the selected BNNR system shows a tendency of a very fast decay and then be followed by a very slow decay process, finally, approaching zero approximately within 3 ps. The convergence of lattice thermal conductivity demonstrates that the thermal conductivity of BNNR can be simulated by EMD simulation using several thousands of atoms with periodic boundary conditions. The results show that BNNR exhibit lower thermal conductivity than that of boron nitride(BN) monolayer, which indicates that phonons boundary scatting significantly suppresses the phonons transport in BNNR. Vacancies in BNNR greatly affect the lattice thermal conductivity, in detail, only 1% concentration of vacancies in BNNR induce a 60% reduction of the lattice thermal conductivity at room temperature.

Challenges in large scale quantum mechanical calculations

During the past decades, quantum mechanical methods have undergone an amazing transition from pioneering investigations of experts into a wide range of practical applications, made by a vast community of researchers. First principles calculations of systems containing up to a few hundred atoms have become a standard in many branches of science. The sizes of the systems which can be simulated have increased even further during recent years, and quantum‐mechanical calculations of systems up to many thousands of atoms are nowadays possible. This opens up new appealing possibilities, in particular for interdisciplinary work, bridging together communities of different needs and sensibilities. In this review we will present the current status of this topic, and will also give an outlook on the vast multitude of applications, challenges, and opportunities stimulated by electronic structure calculations, making this field an important working tool and bringing together researchers of many different domains. WIREs Comput Mol Sci 2017, 7:e1290. doi: 10.1002/wcms.1290This article is categorized under: Structure and Mechanism > Computational Materials Science Electronic Structure Theory > Ab Initio Electronic Structure Methods Electronic Structure Theory > Density Functional Theory

Entanglement depth for symmetric states

Entanglement depth characterizes the minimal number of particles in a system that are mutually entangled. For symmetric states, we show that there is a dichotomy for entanglement depth: an $N$-particle symmetric state is either fully separable, or fully entangled---the entanglement depth is either $1$ or $N$. This property is even stable under non-symmetric noise. We propose an experimentally accessible method to detect entanglement depth in atomic ensembles based on a bound on the particle number population of Dicke states, and demonstrate that the entanglement depth of some Dicke states, for example the twin Fock state, is very stable even under a large arbitrary noise. Our observation can be applied to atomic Bose-Einstein condensates to infer that these systems can be highly entangled with the entanglement depth that is of the order of the system size (i.e. several thousands of atoms).

Effective passivant pseudopotentials for semiconductors: Beyond the spherical approximation

A new type of atomic pseudopotential for passivation of semiconductors surfaces is presented. These pseudopotentials are intended to be used with empirical or effective pseudopotentials methods, where the main goal is to address nanostructures composed of thousands of atoms, but at low computational costs in comparison to density functional theory (DFT). It is shown that the spherical approximation, which is currently used for these potentials, is not suitable for describing passivants and that, instead, they have to be regarded as complex quantities in reciprocal space. A methodology to extract and implement the new pseudopotentials are described here based on an analytic formulation. Passivants for six different semiconductor compounds (GaAs, AlAs, Si, Ge, CdSe and ZnO) are generated, and their accuracy and high transferability are demonstrated by the calculation of the electronic states of different kinds of surfaces and structures and comparison to DFT calculations. The results show that the DFT results can be reproduced with high fidelity with the passivant potentials here presented.

Interactive Musical Display of Quantum Dot Emission Spectra

Quantum dots (QDs) are zero-dimensional semiconductor nanostructures composed of thousands of atoms. QDs are often referred to as artificial atoms because their small structure results in unique, atom-like behavior; like atoms, QDs have optical emission at discrete wavelengths. Here the authors describe a novel method to interactively learn about the spectral properties of QDs using musical intuitions. They transform spectral information from selected Indum Arsenide (InAs) QDs into musical information, including both pitch and rhythm. Thus, they generate a multisensory experience of spectral information allowing users to learn about the range of frequencies of QDs as well as their unique spectral properties resulting from coulombic interactions.

Averaging the intensity of many-layered structures for accurate stacking-fault analysis using Rietveld refinement

Many technologically important synthetic and natural materials display stacking faults which lead to complex peak broadenings, asymmetries and shifts in their powder diffraction patterns. The patterns can be described using an enlarged unit cell (called a supercell) containing an explicit description of the layers. Since the supercell can contain hundreds of thousands of atoms with hundreds of thousands ofhklreflections, a Rietveld approach has been too computationally demanding for all but the simplest systems. This article describes the implementation of the speed-ups necessary to allow Rietveld refinement in the computer programTOPASVersion 6 (Bruker AXS, Karlsruhe, Germany). Techniques implemented include: a peaks buffer that allows hundreds of thousands ofhkl-dependent peak shapes to be automatically approximated by a few hundred peaks; an averaging process for hundreds of large supercells with minimum impact on computational time; a smoothing technique that allows for the use of small supercells which approximate supercells ten to 20 times larger; and efficient algorithms for stacking sequence generation. The result is Rietveld refinement of supercells operating at speeds several thousand times faster than traditional Rietveld refinements. This allows quantitative and simultaneous analysis of structure and microstructure in complex stacking-faulted samples.

Equilibrium Born-Oppenheimer molecular-dynamics exploration of the lattice thermal conductivity of silicon clathrates

Thermal conductivity plays a critical rôle in determining the performance of a thermoelectric material. However, the computation of thermal conductivity from first principles is a challenging and laborious process, with pitfalls galore. Here, we present results on the calculation of the lattice thermal conductivities of silicon clathrates using a very efficient scheme based on the Einstein relationship for the energy moment, sampled from ab initio Born-Oppenheimer molecular dynamics employing linear-scaling Density Functional Theory. Both sI and sII silicon clathrates were studied using systems consisting of up to thousands of atoms. Instead of more glass-like behaviour reported for an empty sII clathrate, the present accurate first-principles calculations predict a thermal-conductivity temperature dependence more in keeping with that of a normal crystal for both clathrates polymorphs, essentially in agreement with a previous theoretical study on sI clathrate. Over the temperature range from 50 to 600K at ambient pressure, it is found that the sI-structure thermal conductivity is somewhat lower than sII, due probably to the greater proportion of larger tetrakaidecahedral 51262 cavities (vis-à-vis smaller dodecahedral 512 cages) therein leading to more substantial dissipation of heat-carrying acoustic phonons. However, the absolute conductivity of sII clathrate is itself limited due to the larger number of atoms per unit cell (136 versus 46 for sI) leading to significant zone-edge damping of acoustic phonons.

Single-electron induced surface plasmons on a topological nanoparticle.

It is rarely the case that a single electron affects the behaviour of several hundred thousands of atoms. Here we demonstrate a phenomenon where this happens. The key role is played by topological insulators—materials that have surface states protected by time-reversal symmetry. Such states are delocalized over the surface and are immune to its imperfections in contrast to ordinary insulators. For topological insulators, the effects of these surface states will be more strongly pronounced in the case of nanoparticles. Here we show that under the influence of light a single electron in a topologically protected surface state creates a surface charge density similar to a plasmon in a metallic nanoparticle. Such an electron can act as a screening layer, which suppresses absorption inside the particle. In addition, it can couple phonons and light, giving rise to a previously unreported topological particle polariton mode. These effects may be useful in the areas of plasmonics, cavity electrodynamics and quantum information.

Single-Slice Nanoworlds Online

Although general multi-slice calculations remain too slow, web-browsers on many platforms now make possible real-time single-slice (strong phase/amplitude object) simulation, with live image, diffraction, image power-spectrum, and darkfield-image modes, including specimen rotation e.g. for atomic-resolution images with specimens having several tens of thousands of atoms. Moreover, a wide range of qualitative phenomena emerge that include diffraction-contrast effects associated with thickness, orientation changes, and defect strain. Hence students with no math background can get a visceral feel for the way 2-D lattice-projections, diffraction-patterns, image power-spectra, aperture size/position, and darkfield images relate to a specimen's structure & orientation, as well as microscope contrast-transfer, well before access to a real electron microscope is available.

Direct Atom Imaging by Chemical-Sensitive Holography.

In order to understand the physical and chemical properties of advanced materials, functional molecular adsorbates, and protein structures, a detailed knowledge of the atomic arrangement is essential. Up to now, if subsurface structures are under investigation, only indirect methods revealed reliable results of the atoms' spatial arrangement. An alternative and direct method is three-dimensional imaging by means of holography. Holography was in fact proposed for electron waves, because of the electrons' short wavelength at easily accessible energies. Further, electron waves are ideal structure probes on an atomic length scale, because electrons have a high scattering probability even for light elements. However, holographic reconstructions of electron diffraction patterns have in the past contained severe image artifacts and were limited to at most a few tens of atoms. Here, we present a general reconstruction algorithm that leads to high-quality atomic images showing thousands of atoms. Additionally, we show that different elements can be identified by electron holography for the example of FeS2.

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning.

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.

Density functional theory based simulations of silicon nanowire field effect transistors

First-principles density functional theory (DFT) based, atomistic, self-consistent device simulations are performed for realistically sized Si nanowire field effect transistors (NW FETs) having tens of thousands of atoms. Through mode space transformation, DFT Hamiltonian and overlap matrices are reduced in size from a few thousands to around one hundred. Ultra-efficient quantum-mechanical transport calculations in the non-equilibrium Green's function formalism in a non-orthogonal basis are therefore made possible. The n-type and p-type Si NW FETs are simulated and found to exhibit similar device performance in the nanoscale regime.

Hybrid Hamiltonian and Green's Function Approach for Studying Native Point Defect Levels in Semiconductor Compounds and Superlattices

We have developed a hybrid method that can be applied to study isolated defects in semiconductor compounds and superlattices. The method is a combination of (1) a long-range tight-binding (TB) Hamiltonian, (2) a first-principles Hamiltonian, and (3) a Green’s function (GF) formalism. The calculation of the GF requires accurate energy band structure, wave functions, and defect potentials. The TB Hamiltonian with sp3 orbitals basis ensures accurate band gaps and band masses while providing the functional form for the wave functions. We calculated the band gaps of InAs/GaSb and InAs/InAsSb strained-layer superlattices and found them to agree well with measurements. The change in potentials caused by native point defects (NPDs) was obtained from a first-principles method using Spanish Initiative for Electronic Simulations with Thousands of Atoms, which also uses sp3 basis. We describe the method of calculating NPD energy levels in compounds and superlattices, obtain some defect levels in GaAs, InAs, InSb, and GaSb compounds, and provide details of the NPD-level calculations.