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We examine the interactions between polyelectrolytes (PEs) and uncharged substrates under conditions corresponding to a dielectric discontinuity between the aqueous solution and the substrate. To this end, we vary the relevant system characteristics, in particular the substrate dielectric constant ɛs under different salt conditions. We employ coarse-grained molecular dynamics simulations with rodlike PEs in salt solutions with explicit ions and implicit water solvent with dielectric constant ɛw = 80. As expected, at low salt concentrations, PEs are repelled from the substrates with ɛs < ɛw but are attracted to substrates with a high dielectric constant due to image charges. This attraction considerably weakens for high salt and multivalent counterions due to enhanced screening. Furthermore, for monovalent salt, screening enhances adsorption for weakly charged PEs, but weakens it for strongly charged ones. Meanwhile, multivalent counterions have little effect on weakly charged PEs, but prevent adsorption of highly charged PEs, even at low salt concentrations. We also find that correlation-induced charge inversion of a PE is enhanced close to the low dielectric constant substrates, but suppressed when the dielectric constant is high. To explore the possibility of a PE monolayer formation, we examine the interaction of a pair of like-charged PEs aligned parallel to a high dielectric constant substrate with ɛs = 8000. Our main conclusion is that monolayer formation is possible only for weakly charged PEs at high salt concentrations of both monovalent and multivalent counterions. Finally, we also consider the energetics of a PE approaching the substrate perpendicular to it, in analogy to polymer translocation. Our results highlight the complex interplay between electrostatic and steric interactions and contribute to a deeper understanding of PE-substrate interactions and adsorption at substrate interfaces with varying dielectric discontinuities from solution, ubiquitous in biointerfaces, PE coating applications, and designing adsorption setups., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Machine learned potentials (MLPs) have been widely employed in molecular dynamics simulations to study thermal transport. However, the literature results indicate that MLPs generally underestimate the lattice thermal conductivity (LTC) of typical solids. Here, we quantitatively analyze this underestimation in the context of the neuroevolution potential (NEP), which is a representative MLP that balances efficiency and accuracy. Taking crystalline silicon, gallium arsenide, graphene, and lead telluride as examples, we reveal that the fitting errors in the machine-learned forces against the reference ones are responsible for the underestimated LTC as they constitute external perturbations to the interatomic forces. Since the force errors of a NEP model and the random forces in the Langevin thermostat both follow a Gaussian distribution, we propose an approach to correcting the LTC by intentionally introducing different levels of force noises via the Langevin thermostat and then extrapolating to the limit of zero force error. Excellent agreement with experiments is obtained by using this correction for all the prototypical materials over a wide range of temperatures. Based on spectral analyses, we find that the LTC underestimation mainly arises from increased phonon scatterings in the low-frequency region caused by the random force errors., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

We review the GPAW open-source Python package for electronic structure calculations. GPAW is based on the projector-augmented wave method and can solve the self-consistent density functional theory (DFT) equations using three different wave-function representations, namely real-space grids, plane waves, and numerical atomic orbitals. The three representations are complementary and mutually independent and can be connected by transformations via the real-space grid. This multi-basis feature renders GPAW highly versatile and unique among similar codes. By virtue of its modular structure, the GPAW code constitutes an ideal platform for the implementation of new features and methodologies. Moreover, it is well integrated with the Atomic Simulation Environment (ASE), providing a flexible and dynamic user interface. In addition to ground-state DFT calculations, GPAW supports many-body GW band structures, optical excitations from the Bethe-Salpeter Equation, variational calculations of excited states in molecules and solids via direct optimization, and real-time propagation of the Kohn-Sham equations within time-dependent DFT. A range of more advanced methods to describe magnetic excitations and non-collinear magnetism in solids are also now available. In addition, GPAW can calculate non-linear optical tensors of solids, charged crystal point defects, and much more. Recently, support for graphics processing unit (GPU) acceleration has been achieved with minor modifications to the GPAW code thanks to the CuPy library. We end the review with an outlook, describing some future plans for GPAW., (© 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).)

Finding low-energy structures of ligand-protected clusters is challenging due to the enormous conformational space and the high computational cost of accurate quantum chemical methods for determining the structures and energies of conformers. Here, we adopted and utilized a kernel rigid regression based machine learning method to accelerate the search for low-energy structures of ligand-protected clusters. We chose the Au25(Cys)18 (Cys: cysteine) cluster as a model system to test and demonstrate our method. We found that the low-energy structures of the cluster are characterized by a specific hydrogen bond type in the cysteine. The different configurations of the ligand layer influence the structural and electronic properties of clusters., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Four-center two-electron Coulomb integrals routinely appear in electronic structure algorithms. The resolution-of-the-identity (RI) is a popular technique to reduce the computational cost for the numerical evaluation of these integrals in localized basis-sets codes. Recently, Duchemin and Blase proposed a separable RI scheme [J. Chem. Phys. 150, 174120 (2019)], which preserves the accuracy of the standard global RI method with the Coulomb metric and permits the formulation of cubic-scaling random phase approximation (RPA) and GW approaches. Here, we present the implementation of a separable RI scheme within an all-electron numeric atom-centered orbital framework. We present comprehensive benchmark results using the Thiel and the GW100 test set. Our benchmarks include atomization energies from Hartree-Fock, second-order Møller-Plesset (MP2), coupled-cluster singles and doubles, RPA, and renormalized second-order perturbation theory, as well as quasiparticle energies from GW. We found that the separable RI approach reproduces RI-free HF calculations within 9 meV and MP2 calculations within 1 meV. We have confirmed that the separable RI error is independent of the system size by including disordered carbon clusters up to 116 atoms in our benchmarks., (© 2024 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).)

We present an update of the DScribe package, a Python library for atomistic descriptors. The update extends DScribe's descriptor selection with the Valle-Oganov materials fingerprint and provides descriptor derivatives to enable more advanced machine learning tasks, such as force prediction and structure optimization. For all descriptors, numeric derivatives are now available in DScribe. For the many-body tensor representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), we have also implemented analytic derivatives. We demonstrate the effectiveness of the descriptor derivatives for machine learning models of Cu clusters and perovskite alloys., (© 2023 Author(s). Published under an exclusive license by AIP Publishing.)

Recently, great progress has been made in the field of ultrasensitive microwave detectors, reaching even the threshold for utilization in circuit quantum electrodynamics. However, cryogenic sensors lack the compatibility with broad-band metrologically traceable power absorption measurements at ultralow powers, which restricts their range of applications. Here, we demonstrate such measurements using an ultralow-noise nanobolometer, which we extend by an additional direct-current (dc) heater input. The tracing of the absorbed power relies on comparing the response of the bolometer between radio frequency and dc-heating powers traced to the Josephson voltage and quantum Hall resistance. To illustrate this technique, we demonstrate two different methods of dc-substitution to calibrate the power that is delivered to the base temperature stage of a dilution refrigerator using our in situ power sensor. As an example, we demonstrate the ability to accurately measure the attenuation of a coaxial input line between the frequencies of 50 MHz and 7 GHz with an uncertainty down to 0.1 dB at a typical input power of -114 dBm., (© 2023 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).)

We present our latest advancements of machine-learned potentials (MLPs) based on the neuroevolution potential (NEP) framework introduced in Fan et al. [Phys. Rev. B 104, 104309 (2021)] and their implementation in the open-source package gpumd. We increase the accuracy of NEP models both by improving the radial functions in the atomic-environment descriptor using a linear combination of Chebyshev basis functions and by extending the angular descriptor with some four-body and five-body contributions as in the atomic cluster expansion approach. We also detail our efficient implementation of the NEP approach in graphics processing units as well as our workflow for the construction of NEP models and demonstrate their application in large-scale atomistic simulations. By comparing to state-of-the-art MLPs, we show that the NEP approach not only achieves above-average accuracy but also is far more computationally efficient. These results demonstrate that the gpumd package is a promising tool for solving challenging problems requiring highly accurate, large-scale atomistic simulations. To enable the construction of MLPs using a minimal training set, we propose an active-learning scheme based on the latent space of a pre-trained NEP model. Finally, we introduce three separate Python packages, viz., gpyumd, calorine, and pynep, that enable the integration of gpumd into Python workflows.

We present a soft-potential-enhanced Poisson-Boltzmann (SPB) theory to efficiently capture ion distributions and electrostatic potential around rodlike charged macromolecules. The SPB model is calibrated with a coarse-grained particle-based model for polyelectrolytes (PEs) in monovalent salt solutions as well as compared to a full atomistic molecular dynamics simulation with the explicit solvent. We demonstrate that our modification enables the SPB theory to accurately predict monovalent ion distributions around a rodlike PE in a wide range of ion and charge distribution conditions in the weak-coupling regime. These include excess salt concentrations up to 1M and ion sizes ranging from small ions, such as Na + or Cl - , to softer and larger ions with a size comparable to the PE diameter. The work provides a simple way to implement an enhancement that effectively captures the influence of ion size and species into the PB theory in the context of PEs in aqueous salt solutions.

Self-assembly in natural and synthetic molecular systems can create complex aggregates or materials whose properties and functionalities rise from their internal structure and molecular arrangement. The key microscopic features that control such assemblies remain poorly understood, nevertheless. Using classical density functional theory, we demonstrate how the intrinsic length scales and their interplay in terms of interspecies molecular interactions can be used to tune soft matter self-assembly. We apply our strategy to two different soft binary mixtures to create guidelines for tuning intermolecular interactions that lead to transitions from a fully miscible, liquid-like uniform state to formation of simple and core-shell aggregates and mixed aggregate structures. Furthermore, we demonstrate how the interspecies interactions and system composition can be used to control concentration gradients of component species within these assemblies. The insight generated by this work contributes toward understanding and controlling soft multi-component self-assembly systems. Additionally, our results aid in understanding complex biological assemblies and their function and provide tools to engineer molecular interactions in order to control polymeric and protein-based materials, pharmaceutical formulations, and nanoparticle assemblies.

A poloidal array of scintillator-based Fast-Ion Loss Detectors (FILDs) has been installed in the ASDEX Upgrade (AUG) tokamak. While all AUG FILD systems are mounted on reciprocating arms driven externally by servomotors, the reciprocating system of the FILD probe located just below the midplane is based on a magnetic coil that is energized in real-time by the AUG discharge control system. This novel reciprocating system allows, for the first time, real-time control of the FILD position including infrared measurements of its probe head temperature to avoid overheating. This considerably expands the diagnostic operational window, enabling unprecedented radial measurements of fast-ion losses. Fast collimator-slit sweeping (up to 0.2 mm/ms) is used to obtain radially resolved velocity-space measurements along 8 cm within the scrape-off layer. This provides a direct evaluation of the neutral beam deposition profiles via first-orbit losses. Moreover, the light-ion beam probe (LIBP) technique is used to infer radial profiles of fast-ion orbit deflection. This radial-LIBP technique is applied to trapped orbits (exploring both the plasma core and the FILD stroke near the wall), enabling radial localization of internal plasma fluctuations (neoclassical tearing modes). This is quantitatively compared against electron cyclotron emission measurements, showing excellent agreement. For the first time, radial profiles of fast-ion losses in MHD quiescent plasmas as well as in the presence of magnetic islands and edge localized modes are presented.

Electronic circular dichroism (ECD) is a powerful spectroscopy method for investigating chiral properties at the molecular level. ECD calculations with the commonly used linear-response time-dependent density functional theory (LR-TDDFT) framework can be prohibitively costly for large systems. To alleviate this problem, we present here an ECD implementation within the projector augmented-wave method in a real-time-propagation TDDFT framework in the open-source GPAW code. Our implementation supports both local atomic basis sets and real-space finite-difference representations of wave functions. We benchmark our implementation against an existing LR-TDDFT implementation in GPAW for small chiral molecules. We then demonstrate the efficiency of our local atomic basis set implementation for a large hybrid nanocluster and discuss the chiroptical properties of the cluster.

Strong light-matter interactions facilitate not only emerging applications in quantum and non-linear optics but also modifications of properties of materials. In particular, the latter possibility has spurred the development of advanced theoretical techniques that can accurately capture both quantum optical and quantum chemical degrees of freedom. These methods are, however, computationally very demanding, which limits their application range. Here, we demonstrate that the optical spectra of nanoparticle-molecule assemblies, including strong coupling effects, can be predicted with good accuracy using a subsystem approach, in which the response functions of different units are coupled only at the dipolar level. We demonstrate this approach by comparison with previous time-dependent density functional theory calculations for fully coupled systems of Al nanoparticles and benzene molecules. While the present study only considers few-particle systems, the approach can be readily extended to much larger systems and to include explicit optical-cavity modes.

The (001) surface of the emerging photovoltaic material cesium lead triiodide (CsPbI 3 ) is studied. Using first-principles methods, we investigate the atomic and electronic structure of cubic (α) and orthorhombic (γ) CsPbI 3 . For both phases, we find that CsI-termination is more stable than PbI 2 -termination. For the CsI-terminated surface, we then compute and analyze the surface phase diagram. We observe that surfaces with added or removed units of nonpolar CsI and PbI 2 are most stable. The corresponding band structures reveal that the α phase exhibits surface states that derive from the conduction band. The surface reconstructions do not introduce new states in the bandgap of CsPbI 3 , but for the α phase, we find additional surface states at the conduction band edge.

We present a relativistic correction scheme to improve the accuracy of 1s core-level binding energies calculated from Green's function theory in the GW approximation, which does not add computational overhead. An element-specific corrective term is derived as the difference between the 1s eigenvalues obtained from the self-consistent solutions to the non- or scalar-relativistic Kohn-Sham equations and the four-component Dirac-Kohn-Sham equations for a free neutral atom. We examine the dependence of this corrective term on the molecular environment and the amount of exact exchange in hybrid exchange-correlation functionals. This corrective term is then added as a perturbation to the quasiparticle energies from partially self-consistent and single-shot GW calculations. We show that this element-specific relativistic correction, when applied to a previously reported benchmark set of 65 core-state excitations [D. Golze et al., J. Phys. Chem. Lett. 11, 1840-1847 (2020)], reduces the mean absolute error (MAE) with respect to the experiment from 0.55 eV to 0.30 eV and eliminates the species dependence of the MAE, which otherwise increases with the atomic number. The relativistic corrections also reduce the species dependence for the optimal amount of exact exchange in the hybrid functional used as a starting point for the single-shot G 0 W 0 calculations. Our correction scheme can be transferred to other methods, which we demonstrate for the delta self-consistent field (ΔSCF) approach based on density functional theory.

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension.

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

We present density functional theory (DFT) calculations of atomic ionization potentials and lattice constants of simple solids from low atomic numbers Z to the large-Z limit. We compare different kinetic energy functional approximations [Kohn-Sham (KS) vs simple orbital-free functionals] and, in the case of orbital free, also different methods for including the nuclear potential (all-electron with the projector augmented wave method vs local pseudopotentials). For both ionization potentials and lattice constants, all-electron orbital-free DFT does yield the general trend of KS DFT for moderate values of the atomic number Z. For large values of Z, all-electron orbital-free DFT deviates from the KS DFT results. Local pseudopotentials give a better qualitative description by adding shell oscillations to the orbital-free DFT model. We show that both all-electron orbital-free DFT and KS DFT have a finite value for nonrelativistic lattice constants in the large-Z limit.

Nonequilibrium molecular dynamics (NEMD) has been extensively used to study thermal transport at various length scales in many materials. In this method, two local thermostats at different temperatures are used to generate a nonequilibrium steady state with a constant heat flux. Conventionally, the thermal conductivity of a finite system is calculated as the ratio between the heat flux and the temperature gradient extracted from the linear part of the temperature profile away from the local thermostats. Here, we show that, with a proper choice of the thermostat, the nonlinear part of the temperature profile should actually not be excluded in thermal transport calculations. We compare NEMD results against those from the atomistic Green's function method in the ballistic regime and those from the homogeneous nonequilibrium molecular dynamics method in the ballistic-to-diffusive regime. These comparisons suggest that in all the transport regimes, one should directly calculate the thermal conductance from the temperature difference between the heat source and sink and, if needed, convert it into the thermal conductivity by multiplying it with the system length. Furthermore, we find that the Langevin thermostat outperforms the Nosé-Hoover (chain) thermostat in NEMD simulations because of its stochastic and local nature. We show that this is particularly important for studying asymmetric carbon-based nanostructures, for which the Nosé-Hoover thermostat can produce artifacts leading to unphysical thermal rectification.

Instant machine learning predictions of molecular properties are desirable for materials design, but the predictive power of the methodology is mainly tested on well-known benchmark datasets. Here, we investigate the performance of machine learning with kernel ridge regression (KRR) for the prediction of molecular orbital energies on three large datasets: the standard QM9 small organic molecules set, amino acid and dipeptide conformers, and organic crystal-forming molecules extracted from the Cambridge Structural Database. We focus on the prediction of highest occupied molecular orbital (HOMO) energies, computed at the density-functional level of theory. Two different representations that encode the molecular structure are compared: the Coulomb matrix (CM) and the many-body tensor representation (MBTR). We find that KRR performance depends significantly on the chemistry of the underlying dataset and that the MBTR is superior to the CM, predicting HOMO energies with a mean absolute error as low as 0.09 eV. To demonstrate the power of our machine learning method, we apply our model to structures of 10k previously unseen molecules. We gain instant energy predictions that allow us to identify interesting molecules for future applications.

Ray-tracing techniques are applied to filtered divertor imaging, a diagnostic that has long suffered from artifacts due to the polluting effect of reflected light in metal walled fusion machines. Physically realistic surface reflections were modeled using a Cook-Torrance micro-facet bi-directional reflection distribution function applied to a high resolution mesh of the vessel geometry. In the absence of gonioreflectometer measurements, a technique was developed to fit the free parameters of the Cook-Torrance model against images of the JET in-vessel light sources. By coupling this model with high fidelity plasma fluid simulations, photo-realistic renderings of a number of tokamak plasma emission scenarios were generated. Finally, a sensitivity matrix describing the optical coupling of a JET divertor camera and the emission profile of the plasma was obtained, including full reflection effects. These matrices are used to perform inversions on measured data and shown to reduce the level of artifacts in inverted emission profiles.

While doping is widely used for tuning physical properties of perovskites in experiments, it remains a challenge to exactly know how doping achieves the desired effects. Here, we propose an empirical and computationally tractable model to understand the effects of doping with Fe-doped BaTiO 3 as an example. This model assumes that the lattice sites occupied by a Fe ion and its nearest six neighbors lose their ability to polarize, giving rise to a small cluster of defective dipoles. Employing this model in Monte Carlo simulations, many important features such as reduced polarization and the convergence of phase transition temperatures, which have been observed experimentally in acceptor doped systems, are successfully obtained. Based on microscopic information of dipole configurations, we provide insights into the driving forces behind doping effects and propose that active dipoles, which exist in proximity to the defective dipoles, can account for experimentally observed phenomena. Close attention to these dipoles is necessary to understand and predict doping effects.

Our manuscript investigates a self-consistent solution of the statistical atom model proposed by Berthold-Georg Englert and Julian Schwinger (the ES model) and benchmarks it against atomic Kohn-Sham and two orbital-free models of the Thomas-Fermi-Dirac (TFD)-λvW family. Results show that the ES model generally offers the same accuracy as the well-known TFD-15vW model; however, the ES model corrects the failure in the Pauli potential near-nucleus region. We also point to the inability of describing low-Z atoms as the foremost concern in improving the present model.

We explore different schemes for improved accuracy of entropy calculations in aqueous liquid mixtures from molecular dynamics (MD) simulations. We build upon the two-phase thermodynamic (2PT) model of Lin et al. [J. Chem. Phys. 119, 11792 (2003)] and explore new ways to obtain the partition between the gas-like and solid-like parts of the density of states, as well as the effect of the chosen ideal "combinatorial" entropy of mixing, both of which have a large impact on the results. We also propose a first-order correction to the issue of kinetic energy transfer between degrees of freedom (DoF). This problem arises when the effective temperatures of translational, rotational, and vibrational DoF are not equal, either due to poor equilibration or reduced system size/time sampling, which are typical problems for ab initio MD. The new scheme enables improved convergence of the results with respect to configurational sampling, by up to one order of magnitude, for short MD runs. To ensure a meaningful assessment, we perform MD simulations of liquid mixtures of water with several other molecules of varying sizes: methanol, acetonitrile, N, N-dimethylformamide, and n-butanol. Our analysis shows that results in excellent agreement with experiment can be obtained with little computational effort for some systems. However, the ability of the 2PT method to succeed in these calculations is strongly influenced by the choice of force field, the fluidicity (hard-sphere) formalism employed to obtain the solid/gas partition, and the assumed combinatorial entropy of mixing. We tested two popular force fields, GAFF and OPLS with SPC/E water. For the mixtures studied, the GAFF force field seems to perform as a slightly better "all-around" force field when compared to OPLS+SPC/E.

We present a microwave correlation measurement system based on two low-cost USB-connected software defined radio dongles modified to operate as coherent receivers by using a common local oscillator. Existing software is used to obtain I/Q samples from both dongles simultaneously at a software tunable frequency. To achieve low noise, we introduce an easy low-noise solution for cryogenic amplification at 600-900 MHz based on single discrete HEMT with 21 dB gain and 7 K noise temperature. In addition, we discuss the quantization effects in a digital correlation measurement and determination of optimal integration time by applying Allan deviation analysis.

The recrossing correction to the transition state theory estimate of a thermal rate can be difficult to calculate when the energy barrier is flat. This problem arises, for example, in polymer escape if the polymer is long enough to stretch between the initial and final state energy wells while the polymer beads undergo diffusive motion back and forth over the barrier. We present an efficient method for evaluating the correction factor by constructing a sequence of hyperplanes starting at the transition state and calculating the probability that the system advances from one hyperplane to another towards the product. This is analogous to what is done in forward flux sampling except that there the hyperplane sequence starts at the initial state. The method is applied to the escape of polymers with up to 64 beads from a potential well. For high temperature, the results are compared with direct Langevin dynamics simulations as well as forward flux sampling and excellent agreement between the three rate estimates is found. The use of a sequence of hyperplanes in the evaluation of the recrossing correction speeds up the calculation by an order of magnitude as compared with the traditional approach. As the temperature is lowered, the direct Langevin dynamics simulations as well as the forward flux simulations become computationally too demanding, while the harmonic transition state theory estimate corrected for recrossings can be calculated without significant increase in the computational effort.

Previous studies have demonstrated that when experimental conditions generate non-adiabatic dynamics that prevents highly efficient population transfer between states of an isolated system by stimulated Raman adiabatic passage (STIRAP), the addition of an auxiliary counter-diabatic field (CDF) can restore most or all of that efficiency. This paper examines whether that strategy is also successful in a non-isolated system in which the energies of the states fluctuate, e.g., when a solute is subject to collisions with solvent. We study population transfer in two model systems: (i) the three-state system used by Demirplak and Rice [J. Chem. Phys. 116, 8028 (2002)] and (ii) a four-state system, derived from the simulation studies of Demirplak and Rice [J. Chem. Phys. 125, 194517 (2006)], that mimics HCl in liquid Ar. Simulation studies of the vibrational manifold of HCl in dense fluid Ar show that the collision induced vibrational energy level fluctuations have asymmetric distributions. Representations of these asymmetric energy level fluctuation distributions are used in both models (i) and (ii). We identify three sources of degradation of the efficiency of STIRAP generated selective population transfer in model (ii): too small pulse areas of the laser fields, unwanted interference arising from use of strong fields, and the vibrational detuning. For both models (i) and (ii), our examination of the efficiency of STIRAP + CDF population transfer under the influence of the asymmetric distribution of the vibrational energy fluctuations shows that there is a range of field strengths and pulse durations under which STIRAP + CDF control of population transfer has greater efficiency than does STIRAP generated population transfer.

The behaviour of sheared colloidal suspensions with full hydrodynamic interactions (HIs) is numerically studied. To this end, we use the hybrid stochastic rotation dynamics-molecular dynamics (SRD-MD) method. The shear viscosity of colloidal suspensions is computed for different volume fractions, both for dilute and concentrated cases. We verify that HIs help in the collisions and the streaming of colloidal particles, thereby increasing the overall shear viscosity of the suspension. Our results show a good agreement with known experimental, theoretical, and numerical studies. This work demonstrates the ability of SRD-MD to successfully simulate transport coefficients that require correct modelling of HIs.

We present an approach for generating local numerical basis sets of improving accuracy for first-principles nanoplasmonics simulations within time-dependent density functional theory. The method is demonstrated for copper, silver, and gold nanoparticles that are of experimental interest but computationally demanding due to the semi-core d-electrons that affect their plasmonic response. The basis sets are constructed by augmenting numerical atomic orbital basis sets by truncated Gaussian-type orbitals generated by the completeness-optimization scheme, which is applied to the photoabsorption spectra of homoatomic metal atom dimers. We obtain basis sets of improving accuracy up to the complete basis set limit and demonstrate that the performance of the basis sets transfers to simulations of larger nanoparticles and nanoalloys as well as to calculations with various exchange-correlation functionals. This work promotes the use of the local basis set approach of controllable accuracy in first-principles nanoplasmonics simulations and beyond.

The conductivity of carbon nanotube thin films is mainly determined by carbon nanotube junctions, the resistance of which can be reduced by several different methods. We investigate electronic transport through carbon nanotube junctions in a four-terminal configuration, where two metallic single-wall carbon nanotubes are linked by a group 6 transition metal atom. The transport calculations are based on the Green's function method combined with the density-functional theory. The transition metal atom is found to enhance the transport through the junction near the Fermi level. However, the size of the nanotube affects the improvement in the conductivity. The enhancement is related to the hybridization of chromium and carbon atom orbitals, which is clearly reflected in the character of eigenstates near the Fermi level. The effects of chromium atoms and precursor molecules remaining adsorbed on the nanotubes outside the junctions are also examined.

We present a computational scheme for orbital-free density functional theory (OFDFT) that simultaneously provides access to all-electron values and preserves the OFDFT linear scaling as a function of the system size. Using the projector augmented-wave method (PAW) in combination with real-space methods, we overcome some obstacles faced by other available implementation schemes. Specifically, the advantages of using the PAW method are twofold. First, PAW reproduces all-electron values offering freedom in adjusting the convergence parameters and the atomic setups allow tuning the numerical accuracy per element. Second, PAW can provide a solution to some of the convergence problems exhibited in other OFDFT implementations based on Kohn-Sham (KS) codes. Using PAW and real-space methods, our orbital-free results agree with the reference all-electron values with a mean absolute error of 10 meV and the number of iterations required by the self-consistent cycle is comparable to the KS method. The comparison of all-electron and pseudopotential bulk modulus and lattice constant reveal an enormous difference, demonstrating that in order to assess the performance of OFDFT functionals it is necessary to use implementations that obtain all-electron values. The proposed combination of methods is the most promising route currently available. We finally show that a parametrized kinetic energy functional can give lattice constants and bulk moduli comparable in accuracy to those obtained by the KS PBE method, exemplified with the case of diamond.

Six recently developed exchange functionals for pairing with two different versions of van der Waals density functionals (vdW-DF) are tested for weakly bonded solids. The test, using 26 layered weakly bonded compounds, benchmarks the lattice constants against experimental data and the interlayer binding energies against reference data from the random-phase approximation (RPA). The investigated functionals tend to give interlayer binding energies higher than the RPA benchmark, and the overall performance for lattice constants is good. The exchange functionals optB86b and cx13 paired with the original vdW-DF and the B86R functional paired with vdW-DF2 are found to give particularly good results for equilibrium geometries.

We study the driven transport of polymers in a periodically patterned channel using Langevin dynamics simulations in two dimensions. The channel walls are patterned with periodically alternating patches of attractive and non-attractive particles that act as trapping sites for the polymer. We find that the system shows rich dynamical behavior, observing giant diffusion, negative differential mobility, and several different transition mechanisms between the attractive patches. We also show that the channel can act as an efficient high-pass filter for polymers longer than a threshold length Nthr, which can be tuned by adjusting the length of the attractive patches and the driving force. Our findings suggest the possibility of fabricating polymer filtration devices based on patterned nanochannels.

I analyze the fluid-fluid phase separation of nonadditive hard sphere fluid mixture absorbed in random porous media. An equation of state is derived by using the perturbation theory to this complex system with quenched disorders. The results of this theory are in good agreement with those obtained from semi-grand canonical ensemble Monte Carlo simulations. The contact value of the fluid-fluid radial distribution functions of the reference which is the key point of the perturbation process is derived as well, the comparison against Monte Carlo simulations shows that it has an excellent accuracy.

We determine the orientation-resolved interfacial free energy between a body-centered-cubic (bcc) crystal and the coexisting fluid for a many-particle system interacting via a Yukawa pair potential. For two different screening strengths, we compare results from molecular dynamics computer simulations, density functional theory, and a phase-field-crystal approach. Simulations predict an almost orientationally isotropic interfacial free energy of 0.12k(B)T/a(2) (with k(B)T denoting the thermal energy and a the mean interparticle spacing), which is independent of the screening strength. This value is in reasonable agreement with our Ramakrishnan-Yussouff density functional calculations, while a high-order fitted phase-field-crystal approach gives about 2-3 times higher interfacial free energies for the Yukawa system. Both field theory approaches also give a considerable anisotropy of the interfacial free energy. Our result implies that, in the Yukawa system, bcc crystal-fluid free energies are a factor of about 3 smaller than face-centered-cubic crystal-fluid free energies.

We study the influence of spherical, triangular, and rod-like nanoparticles on the mechanical properties of a polymer nanocomposite (PNC), via coarse-grained molecular dynamics simulations. We focus on how the nanoparticle size, loading, mass, and shape influence the PNC's elastic modulus, stress at failure and resistance against cavity formation and growth, under external stress. We find that in the regime of strong polymer-nanoparticle interactions, the formation of a polymer network via temporary polymer-nanoparticle crosslinks has a predominant role on the PNC reinforcement. Spherical nanoparticles, whose size is comparable to that of the polymer monomers, are more effective at toughening the PNC than larger spherical particles. When comparing particles of spherical, triangular, and rod-like geometries, the rod-like nanoparticles emerge as the best PNC toughening agents.

We study the driven translocation of polymers under time-dependent driving forces using N-particle Langevin dynamics simulations. We consider the force to be either sinusoidally oscillating in time or dichotomic noise with exponential correlation time, to mimic both plausible experimental setups and naturally occurring biological conditions. In addition, we consider both the case of purely repulsive polymer-pore interactions and the case with additional attractive polymer-pore interactions, typically occurring inside biological pores. We find that the nature of the interaction fundamentally affects the translocation dynamics. For the non-attractive pore, the translocation time crosses over to a fast translocation regime as the frequency of the driving force decreases. In the attractive pore case, because of a free energy well induced inside the pore, the translocation time can be a minimum at the optimal frequency of the force, the so-called resonant activation. In the latter case, we examine the effect of various physical parameters on the resonant activation, and explain our observations using simple theoretical arguments.

We derive equations for nonadiabatic Ehrenfest molecular dynamics within the projector augmented-wave (PAW) formalism. The discretization of the electrons is time-dependent as the augmentation functions depend on the positions of the nuclei. We describe the implementation of the Ehrenfest molecular dynamics equations within the real-space PAW method. We demonstrate the applicability of our method by studying the vibration of NaCl, the torsional rotation of H(2)C=NH(2)(+) in both the adiabatic and the nonadiabatic regimes, and the hydrogen bombardment of C(40)H(16).

We present an all-electron method for time-dependent density functional theory which employs hierarchical nonuniform finite-element bases and the time-propagation approach. The method is capable of treating linear and nonlinear response of valence and core electrons to an external field. We also introduce (i) a preconditioner for the propagation equation, (ii) a stable way to implement absorbing boundary conditions, and (iii) a new kind of absorbing boundary condition inspired by perfectly matched layers., (© 2011 American Institute of Physics)

Domain wall dynamics in thin magnetic films with perpendicular and in-plane anisotropy is studied using a novel magneto-optical Kerr effect susceptometery method. The method allows for measurements of domain wall motion under ac field excitation and the analysis of dynamic modes as a function of driving frequency and magnetic field amplitude. Domain wall dynamics in the perpendicular anisotropy system, a Co/Pt multilayer, is characterized by thermally activated creep motion. For this dynamic mode, a polydispersivity exponent of β = 0.50 ± 0.03 is derived at small excitation energy, which is in excellent agreement with theoretical models. The dynamics of the other system, a Co wire with transverse uniaxial anisotropy, is dominated by viscous slide motion in a regular magnetic stripe pattern. Analytical expressions are derived for this magnetic configuration and by using these expressions, accurate values for the depinning field and the domain wall mobility are extracted from the susceptibility measurements.

We develop and test numerically a lattice-Boltzmann (LB) model for nonideal fluids that incorporates thermal fluctuations. The fluid model is a momentum-conserving thermostat, for which we demonstrate how the temperature can be made equal at all length scales present in the system by having noise both locally in the stress tensor and by shaking the whole system in accord with the local temperature. The validity of the model is extended to a broad range of sound velocities. Our model features a consistent coupling scheme between the fluid and solid molecular dynamics objects, allowing us to use the LB fluid as a heat bath for solutes evolving in time without external Langevin noise added to the solute. This property expands the applicability of LB models to dense, strongly correlated systems with thermal fluctuations and potentially nonideal equations of state. Tests on the fluid itself and on static and dynamic properties of a coarse-grained polymer chain under strong hydrodynamic interactions are used to benchmark the model. The model produces results for single-chain diffusion that are in quantitative agreement with theory.

We have calculated the absorption characteristics of different hybrid systems consisting of Ag, Ag(2), or Ag(3) atomic clusters and poly(methacrylic acid) using the time-dependent density-functional theory. The polymer is found to have an extensive structural-dependency on the spectral patterns of the hybrid systems relative to the bare clusters. The absorption spectrum can be "tuned" to the visible range for hybrid systems with an odd number of electrons per silver cluster, whereas for hybrid systems comprising an even number of electrons per silver cluster, the leading absorption edge can be shifted up to approximately 4.5 eV. The results give theoretical support to the experimental observations on the absorption in the visible range in metal cluster-polymer hybrid structures.