Fast, scalable and accurate finite-element based ab initio calculations using mixed precision computing: 46 PFLOPS simulation of a metallic dislocation system
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The mechanical stability and physical properties of Co{sub 2}V{sub 1−x}Zr{sub x}Ga (x = 0, 0.25, 0.50, 0.75, 1) have been predicted by using ab initio calculations based on density functional theory. The exchange-correlation potentials are treated within the generalized gradient approximation-Perdew-Burke and Ernzerhhof (GGA-PBE) and Hubbard coefficient (GGA+U). The investigated minimum lattice parameter of Co{sub 2}VGa is 5.8030 Å, which is in excellent agreement with available experimental and theoretical data and for Co{sub 2}V{sub 1−x}Zr{sub x}Ga (x = 0.25, 0.50, 0.75, 1) are 5.9026, 5.9625, 6.0060 and 6.0021 Å, respectively, which are predicted for the very first time. The total magnetic moments decrease with increasing concentration of x in Co{sub 2}V{sub 1−x}Zr{sub x}Ga, in agreement with the Slater-Pauling rule. Band structure and density of states calculations show that the minority spin channel exhibits band gaps of 0.43, 0.46, 0.52, 0.54 and 1.01 eV for GGA+U scheme around the Fermi level confirming that all the studied composites are half-metallic in nature. In this study, we also studied the elastic constant and it is established that all the materials are mechanically stable and ductile in nature. The Co{sub 2}VGa is stiffer than other materials and all the studied composites have anisotropic behaviour. Moreover, by using a quasi-harmonic Debye model and calculated elastic constant, the Debye temperature and temperature-dependent constant volume heat capacity have been investigated.
Collisional energy transfer plays a pivotal role in a-priori calculations of the pressure-dependent rate constants obtained from a master equation. However, accurate determinations of collisional energy transfer parameters are rare and so most kinetic studies rely on best-fits of these parameters to experimental measurements (if available) or estimates guided from literature studies. In this work, we have quantified the effect of the uncertainty in energy transfer parameters on the thermal and prompt dissociation kinetics of a resonance stabilized radical, 1-methyl allyl (1MA), of relevance to the combustion of 1- and 2-butene isomers. Simulations using literature kinetics models were performed to assess the impact of these uncertainties on flame propagation and speciation data in laminar flames of 1- and 2-butene. Analyses of the uncertainty propagated by the energy transfer parameters for 1MA dissociation to the flame simulations, in particular the laminar flame speed, indicate an intricate coupling between the kinetics of 1MA dissociation (chain propagation) and its reaction with H-atoms (chain-termination). Ab-initio based theoretical calculations were also performed to obtain pressure-dependent kinetics for the reaction of 1MA with H-atoms. Lastly, theoretically calculated energy transfer parameters were used to best characterize the kinetics and branching between the chain propagating 1MA dissociation and the chain-terminating reaction 1MA + H.
Close-packed assemblies of ligand-passivated colloidal nanocrystals can exhibit enhanced photoluminescent stability, but the origin of this effect is unclear. Here, we use experiment, simulation, and ab initio computation to examine the influence of interparticle interactions on the photoluminescent stability of silicon nanocrystal aggregates. The time-dependent photoluminescence emitted by structures ranging in size from a single quantum dot to agglomerates of more than a thousand is compared with Monte Carlo simulations of noninteracting ensembles using measured single-particle blinking data as input. In contrast to the behavior typically exhibited by the metal chalcogenides, the measured photoluminescent stability shows an enhancement with respect to the noninteracting scenario with increasing aggregate size. We model this behavior using time-dependent density functional theory calculations of energy transfer between neighboring nanocrystals as a function of nanocrystal size, separation, and the presence of charge and/or surface-passivation defects. In conclusion, our results suggest that rapid exciton transfer from “bright” nanocrystals to surface trap states in nearest-neighbors can efficiently fill such traps and enhance the stability of emission by promoting the radiative recombination of slowly diffusing excited electrons.
Heavy atomic nuclei have an excess of neutrons over protons, which leads to the formation of a neutron skin whose thickness is sensitive to details of the nuclear force. This links atomic nuclei to properties of neutron stars, thereby relating objects that differ in size by orders of magnitude. The nucleus 208 Pb is of particular interest because it exhibits a simple structure and is experimentally accessible. However, computing such a heavy nucleus has been out of reach for ab initio theory. By combining advances in quantum many-body methods, statistical tools and emulator technology, we make quantitative predictions for the properties of 208 Pb starting from nuclear forces that are consistent with symmetries of low-energy quantum chromodynamics. We explore 10 9 different nuclear force parameterizations via history matching, confront them with data in select light nuclei and arrive at an importance-weighted ensemble of interactions. We accurately reproduce bulk properties of 208 Pb and determine the neutron skin thickness, which is smaller and more precise than a recent extraction from parity-violating electron scattering but in agreement with other experimental probes. This work demonstrates how realistic two- and three-nucleon forces act in a heavy nucleus and allows us to make quantitative predictions across the nuclear landscape.
A six-dimensional potential energy hypersurface (PES) for two interacting rigid ethylene oxide (C{sub 2}H{sub 4}O) molecules was determined from high-level quantum-chemical ab initio calculations. The counterpoise-corrected supermolecular approach at the MP2 and CCSD(T) levels of theory was utilized to determine interaction energies for 10178 configurations of two molecules. An analytical site-site potential function with 19 sites per ethylene oxide molecule was fitted to the interaction energies and fine tuned to agree with data for the second acoustic virial coefficient from accurate speed of sound measurements. The PES was validated by computing the second virial coefficient, shear viscosity, and thermal conductivity. The values of these properties are substantiated by the best experimental data as they tend to fall within the uncertainty intervals and also obey the experimental temperature functions, except for viscosity, where experimental data are insufficient. Due to the lack of reliable data, especially for the transport properties, our calculated values are currently the most accurate estimates for these properties of ethylene oxide.
We report ab-initio molecular dynamics simulations of dense liquid/solid sodium for a pressure range from 0 to 100 GPa. The simulations have been performed with the orbital free ab-initio molecular dynamics method which, by using the electron density as the basic variable, allows to perform simulations with large samples and for long runs. The calculated melting curve shows a maximum at a pressure ≈ 30 GPa and it is followed by a long, steep decrease. These features are in good agreement with the experimental data. For various pressures along the melting curve, we have calculated several liquid static properties (pair distribution functions, static structure factors and short-range order parameters) in order to analyze the structural effects of pressure.
Abstract—The phonon spectrum of CdGa{sub 2}S{sub 4} has been experimentally investigated by Raman spectroscopy and theoretically analyzed using the density functional theory (DFT). Eleven active Raman modes (at 83, 135, 165, 219, 243, 260, 310, 322, 352, 361, and 392 cm{sup –1}) have been detected and identified. The identification of all vibrational modes is based on consideration of the point symmetry group. The results are compared with the existing experimental IR spectroscopy and Raman scattering data.
The spin-vibronic energy levels of the chloroacetylene cation up to 4000 cm{sup −1} above the ground state have been measured using the one-photon zero-kinetic energy photoelectron spectroscopic method. The spin-vibronic energy levels have also been calculated using a diabatic model, in which the potential energy surfaces are expressed by expansions of internal coordinates, and the Hamiltonian matrix equation is solved using a variational method with harmonic basis functions. The calculated spin-vibronic energy levels are in good agreement with the experimental data. The Renner-Teller (RT) parameters describing the vibronic coupling for the H—C≡C bending mode (ε{sub 4}), Cl—C≡C bending mode (ε{sub 5}), the cross-mode vibronic coupling (ε{sub 45}) of the two bending vibrations, and their vibrational frequencies (ω{sub 4} and ω{sub 5}) have also been determined using an effective Hamiltonian matrix treatment. In comparison with the spin-orbit interaction, the RT effect in the H—C≡C bending (ε{sub 4}) mode is strong, while the RT effect in the Cl—C≡C bending mode is weak. There is a strong cross-mode vibronic coupling of the two bending vibrations, which may be due to a vibronic resonance between the two bending vibrations. The spin-orbit energy splitting of the ground state has been determined for the first time and is found to be 209 ± 2 cm{sup −1}.
We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme based on the kernel method and Bayesian linear regression, with the training data generated from the Kohn–Sham density functional theory (DFT) using the Gauss spectral quadrature method, within which we calculate energies, atomic forces, and stresses. We verify the accuracy of the formalism by comparing the predicted properties of warm dense carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that ab initio MD simulations of WDM can be accelerated by up to three orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the diffusion coefficients and shear viscosity of CH at a density of 1 g/cm3 and temperatures in the range of 75 000–750 000 K. We find that the self- and inter-diffusion coefficients and the viscosity obey a power law with temperature, and that the diffusion coefficient results suggest a weak coupling between C and H in CH. In addition, we find agreement within standard deviation with previous results for C and CH but disagreement for H, demonstrating the need for ab initio calculations as presented here.
Direct reaction experiments exhibit a powerful tool to probe the structure of neutron-rich nuclei like beryllium-11. We use halo effective field theory to calculate the cross section of the deuteron-induced neutron transfer reaction 10 Be(d, p) 11 Be. The effective theory contains dynamical fields for the beryllium-10 core, the neutron, and the proton. In contrast, the deuteron and the beryllium-11 halo nucleus are generated dynamically from contact interactions using experimental and ab initio input. Breakup contributions are then included by construction. The reaction amplitude is constructed up to next-to-leading order in an expansion in the ratio of the length scales characterizing the core and the halo. The Coulomb repulsion between core and proton is treated perturbatively. Lastly, we compare our results to cross-section data and other calculations.
The continued development of plasma-assisted processing techniques requires a fundamental understanding of plasma-surface interactions. Molecular dynamics (MD) simulations have been employed to complement experimental studies and better understand the properties of such systems. Recently, machine learning (ML) methods have enabled the development of ab initio-based interatomic potentials, which can be generalized to complex combinations of multiple atom types. In this work, we use ML potentials developed using the Deep Potential Molecular Dynamics (DeepMD) framework to provide a model of ion-enhanced etching of Si by Cl atoms. We demonstrate the importance of proper selection of the training data set to the accuracy of the DeepMD model and compare our results to MD results using empirical potentials, as well as to experimental measurements. Exposure of undoped Si at 300 K to thermal Cl atoms yields a steady-state Cl coverage of 1.25 monolayers, which is slightly lower than the value obtained in previous experimental studies. Predictions of Si etch yields by simultaneous Cl atom and Ar + ion impacts as a function of ion energy, neutral to ion flux ratio, and angle of incidence of the ions are in reasonably good agreement with classical MD results and experimental measurements. Finally, etch yields and SiCl x mixed layer thicknesses during simultaneous bombardment of the Si(100) surface by Cl atoms and Cl + ions are in good agreement with experimental data. In conclusion, the present work is a necessary condition for the extension of the DeepMD procedure to more complex systems of interest in plasma-surface interactions.
The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.
Recently, we presented ab initio quantum Monte Carlo calculations of magnetic moments and M1 transitions in A?10 nuclei, which include two-body meson-exchange currents' contributions of one- and two-pion range, derived from chiral effective field. These corrections are found to always improve the theoretical predictions, leading to a very good agreement with the experimental data. Here, we report on a study, carried out within the same framework, of M1 transitions in low-lying states of 8Be. We also present a number of E2 transition calculations, evaluated in impulse approximation, with emphasis on transitions involving the 8Be resonant excited states at ?3 MeV and ?11 MeV.
Recently, we presented ab initio quantum Monte Carlo calculations of magnetic moments and M1 transitions in A <= 10 nuclei, which include two-body meson-exchange currents' contributions of one- and two-pion range, derived from chiral effective field. These corrections are found to always improve the theoretical predictions, leading to a very good agreement with the experimental data. Here, we report on a study, carried out within the same framework, of M1 transitions in low-lying states of 8Be. We also present a number of E2 transition calculations, evaluated in impulse approximation, with emphasis on transitions involving the 8Be resonant excited states at ~ 3 MeV and ~ 11 MeV.
Abstract It is well-known that the atomic-scale and nano-scale configuration of dopants can play a crucial role in determining the electronic properties of materials. However, predicting such effects is challenging due to the large range of atomic configurations that are possible. Here, we present a case study of how deep learning algorithms can enable bandgap prediction in hybridized boron–nitrogen graphene with arbitrary supercell configurations. A material descriptor that enables correlation of structure and bandgap was developed for convolutional neural networks. Bandgaps calculated by ab initio calculations, and corresponding structures, were used as training datasets. The trained networks were then used to predict bandgaps of systems with various configurations. For 4 × 4 and 5 × 5 supercells they accurately predict bandgaps, with a R 2 of >90% and root-mean-square error of ~0.1 eV. The transfer learning was performed by leveraging data generated from small supercells to improve the prediction accuracy for 6 × 6 supercells. This work will pave a route to future investigation of configurationally hybridized graphene and other 2D materials. Moreover, given the ubiquitous existence of configurations in materials, this work may stimulate interest in applying deep learning algorithms for the configurational design of materials across different length scales.
A realistic description of halo nuclei, characterized by low-lying breakup thresholds, requires a proper treatment of continuum effects. We have developed an ab initio approach, the No-Core Shell Model with Continuum (NCSMC), capable of describing both bound and unbound states in light nuclei in a unified way. With chiral two- and three-nucleon interactions as the only input, we can predict the structure and dynamics of halo and other light nuclei and, by comparing to available experimental data, test the quality of chiral nuclear forces. We review NCSMC calculations of weakly bound states and resonances of the exotic halo nuclei 6He, 8B, 11Be, and 15C. For the latter, we discuss its production in the capture reaction 14C(n,𝛾 )15C. We highlight the challenges of a description of 6He as a Borromean n-n-4He system. Finally, we present our calculations of excited states in 10Be exhibiting a one-neutron halo structure and a large scale No-Core Shell Model investigation of 11Li as a precursor of a full n-n-9Li NCSMC study.
The spectrum of CrH has been reinvestigated in the 9000-15000/cm region using the Fourier transform spectrometer of the National Solar Observatory. The 1-0 and 1-1 bands of the A6Sigma+ - X6Sigma+ transition have been measured and improved spectroscopic constants have been determined. A value for the 2-0 band origin has been obtained from the band head using estimated spectroscopic constants. These data provide a set of much improved equilibrium vibrational and rotational constants for the A6Sigma+ state. An accurate description of the A-X transition has been obtained using a multi-reference configuration interaction approach. The inclusion of both scalar relativity and Cr 3s3p correlation are required to obtain a good description of both states. The ab initio computed Einstein coefficients and radiative lifetimes are reported.