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DOE OSTI2014

Precise Lifetime Measurements in Light Nuclei for Benchmarking Modern Ab-initio Nuclear Structure Models

A new generation of ab-initio calculations, based on realistic two- and three-body forces, is having a profound impact on our view of how nuclei work. To improve the numerical methods, and the parameterization of 3-body forces, new precise data are needed. Electromagnetic transitions are very sensitive to the dynamics which drive mixing between configurations. We have made a series of precise (< 3%) measurements of electromagnetic transitions in the A=10 nuclei {sup 10}C and {sup 10}Be by using the Doppler Shift Attenuation method carefully. Many interesting features can be reproduced including the strong α clustering. New measurements on {sup 8}Be and {sup 12}Be highlight the interplay between the alpha clusters and their valence neutrons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

An interatomic potential for the Al–Tb alloy around the composition of Al 90 Tb 10 is developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for the Al–Tb alloy. Here we show that the obtained DNN model can well reproduce the energies and forces calculated by AIMD simulations. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of the Al 90 Tb 10 liquid, such as partial pair correlation functions (PPCFs) and bond angle distributions, in comparison with the results from AIMD simulations. Furthermore, the developed DNN interatomic potential predicts the formation energies of the crystalline phases of the Al–Tb system with an accuracy comparable to ab initio calculations. The structure factors of the Al 90 Tb 10 metallic liquid and glass obtained by MD simulations using the developed DNN interatomic potential are also in good agreement with the experimental X-ray diffraction data. The development of short-range order (SRO) in the Al 90 Tb 10 liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered ‘3661’ and ‘15551’ clusters, respectively, are identified.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Study of the thermodynamic properties of CeO{sub 2} from ab initio calculations: The effect of phonon-phonon interaction

The thermodynamic properties of CeO{sub 2} have been reevaluated by a simple but accurate scheme. All our calculations are based on the self-consistent ab initio lattice dynamical (SCAILD) method that goes beyond the quasiharmonic approximation. Through this method, the effects of phonon-phonon interactions are included. The obtained thermodynamic properties and phonon dispersion relations are in good agreement with experimental data when considering the correction of phonon-phonon interaction. We find that the correction of phonon-phonon interaction is equally important and should not be neglected. At last, by comparing with quasiharmonic approximation, the present scheme based on SCAILD method is probably more suitable for high temperature systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Time-dependent density-functional theory of high-order harmonic generation from noble-gas atoms driven by orthogonally polarized two-color laser fields

An orthogonally polarized two-color (OTC) field of frequency ratio 1 : 2 is known to generate both odd and even harmonic spectra in the mutually orthogonal directions of the fundamental and the second-harmonic fields, respectively. Recollision angles of an ionized electron driven back to its parent ion by an OTC field are inferred from the intensity ratio of odd and even harmonics, where the relative phase delays between the two-color fields can be used in time-resolved measurements on a subcycle time scale. Here, we present the ab initio, many-electron calculation of time-resolved recollision angles of noble-gas atoms driven by an OTC field, based on the time-dependent density-functional theory. Our results agree well with experimental data by Shafir et al. in Nat. Phys. 5, 412 (2009) of helium atom and New J. Phys. 12, 073032 (2010) of neon atom.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Development of a deep potential model for F and CF 2 etching of Si and SiO 2

An understanding of plasma-surface interactions at increasingly smaller scales is invaluable for the development of novel technologies and processing techniques. Molecular dynamics (MD) simulations can provide insights into atomic-scale interactions, though they are restricted by the availability of interatomic potentials. Machine learning methods, such as Deep Potential Molecular Dynamics (DeepMD), provide a systematic framework for the development of accurate and flexible ab initio-based models. In this work, we develop DeepMD models for the ion-enhanced etching of Si and SiO 2 by F and CF 2 radicals. We employ an active learning process to expand the data set on which the model is trained and demonstrate its effect on the model accuracy. The DeepMD results are compared to data from classical MD simulations and experiments. Physical sputtering yields of SiO 2 by Ar + ions show good agreement with previous simulation results using conventional interatomic potentials, though the predicted depth profiles are different. Etching yields are calculated as a function of ion energy and neutral to ion flux ratio for the Ar + ion-enhanced etching of SiO 2 and Si by F atoms, as well as for etching of SiO 2 by CF 2 radicals, showing reasonable agreement with experimental data. Finally, an ion-enhanced surface kinetic model is fitted to the DeepMD etch yields, and the fitted parameters are compared to quantities computed directly from DeepMD simulations. This study illustrates how molecular dynamics simulations using machine learning potentials can provide an accurate model of etching processes relevant to device manufacturing.

Kounis-Melas, Andreas [Princeton Univ., NJ (United↗

NASA NTRS1985

Molecular orbital predictions of the vibrational frequencies of some molecular ions

The initial detections of IR vibration-rotation bands in polyatomic molecular ions by recent spectroscopic advances were guided by ab initio prediction of vibrational frequencies. The present calculations predict the vibrational frequencies of additional ions which are candidates for laboratory analysis. Neutral molecule vibrational frequencies were computed at three levels of theory and then compared with experimental data; the effect of scaling was also investigated, in order to determine how accurately vibrational frequencies could be predicted. For 92 percent of the frequencies examined, the relatively simple HF/6-31G theory's vibrational frequencies were within 100/cm of experimental values, with a mean absolute error of 49/cm. On this basis, the frequencies of 30 molecular ions (many possessing astrophysical significance) were computed.

Defrees, D. J.↗

NASA NTRS1987

(2 + 1) resonant enhanced multiphoton ionization of H2 via the E,F 1Sigma(+)g state

In this paper, the results of ab initio calculations of photoelectron angular distributions and vibrational branching ratios for the (2 + 1) resonant enhanced multiphoton ionization (REMPI) of H2 via the E,F 1Sigma(+)g state are reported, and these are compared with the experimental data of Anderson et al. (1984). These results show that the observed non-Franck-Condon behavior is predominantly due to the R dependence of the transition matrix elements, and to a lesser degree to the energy dependence. This work presents the first molecular REMPI study employing a correlated wave function to describe the Rydberg-valence mixing in the resonant intermediate state.

Rudolph, H.↗

DOE OSTI2016

Ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes

Here, we present an efficient methodology for computing solute-induced changes in lattice parameters and elastic stiffness coefficients Cij of single crystals using density functional theory. We also introduce a solute strain misfit tensor that quantifies how solutes change lattice parameters due to the stress they induce in the host crystal. Solutes modify the elastic stiffness coefficients through volumetric changes and by altering chemical bonds. We compute each of these contributions to the elastic stiffness coefficients separately, and verify that their sum agrees with changes in the elastic stiffness coefficients computed directly using fully optimized supercells containing solutes. Computing the two elastic stiffness contributions separately is more computationally efficient and provides more information on solute effects than the direct calculations. We compute the solute dependence of polycrystalline averaged shear and Young's moduli from the solute dependence of the single-crystal Cij. We then apply this methodology to substitutional Al, B, Cu, Mn, Si solutes and octahedral interstitial C and N solutes in bcc Fe. Comparison with experimental data indicates that our approach accurately predicts solute-induced changes in the lattice parameter and elastic coefficients. The computed data can be used to quantify solute-induced changes in mechanical properties such as strength and ductility, and can be incorporated into mesoscale models to improve their predictive capabilities.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Hyperfine and quadrupole interactions for Dy isotopes in DyPc 2 molecules

Nuclear spin levels play a vital role in understanding magnetization dynamics and implementation and control of quantum bits in lanthanide-based single-molecule magnets. We investigate the hyperfine and nuclear quadrupole interactions for 161 Dy and 163 Dy nuclei in anionic DyPc 2 (Pc=phthalocyanine) single-molecule magnets, using multiconfigurational ab initio methods (beyond density-functional theory) including spin–orbit interaction. The two isotopes of Dy are chosen because the others have zero nuclear spin. Both isotopes have the nuclear spin I =5/2, although the magnitude and sign of the nuclear magnetic moment differ from each other. The large energy gap between the electronic ground and first-excited Kramers doublets, allows us to map the microscopic hyperfine and quadrupole interaction Hamiltonian onto an effective Hamiltonian with an electronic pseudo-spin that corresponds to the ground Kramers doublet. Our ab initio calculations illustrate that the coupling between the nuclear spin and electronic orbital angular momentum contributes the most to the hyperfine interaction and that both the hyperfine and nuclear quadrupole interactions for 161 Dy and 163 Dy nuclei are much smaller than those for the 159 Tb nucleus in TbPc 2 single-molecule magnets. The calculated separations of the electronic-nuclear levels are comparable to experimental data reported for 163 DyPc 2 . We demonstrate that hyperfine interaction for the Dy Kramers ion leads to tunnel splitting (or quantum tunneling of magnetization) at zero field. This effect does not occur for TbPc 2 single-molecule magnets. The magnetic field values of the avoided level crossings for 161 DyPc 2 and 163 DyPc 2 are found to be noticeably different, which can be observed from the experiment.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Crystal structure of the $τ_{11}$ Al 4 Fe 1.7 Si phase from neutron diffraction and ab initio calculations

The intermetallic τ 11 Al 4 Fe 1.7 Si phase is of interest for high-temperature structural application due to its combination of low density and high strength. We determine the crystal structure of the τ 11 phase through a combination of powder neutron diffraction and density functional theory calculations. Using Pawley and Rietveld refinements of the neutron diffraction data provides an initial crystal structure model. Since Al and Si have nearly identical neutron scattering lengths, we use density-functional calculations to determine their preferred site occupations. The τ 11 phase exhibits a hexagonal crystal structure with space group P6 3 /mmc and lattice parameters of a = 7.478 Å and c = 7.472 Å. The structure comprises five Wyckoff positions; Al occupies the 6h and 12k sites, Fe the 2a and 6h sites, and Si the 2a sites. Here we observe site disorder and partial occupancies on all sites with a large fraction of 80% Fe vacancies on the 2d sites, indicating an entropic stabilization of the τ 11 phase at high temperature.

36 MATERIALS SCIENCE↗

NASA NTRS1995

A Correlated Ab Initio Study of Linear Carbon-Chain Radicals C(sub n)H (n=2-7)

Linear carbon-chain radicals C(sub n) H for n = 2-7 have been studied with correlation consistent valence and core-valence basis sets and the coupled cluster method RCCSD(T). Equilibrium structures, rotational constants, and dipole moments are reported and compared with available experimental data. The ground state of the even-n series changes from 2Sigma(+) to 2Pi as the chain is extended. For C4H, the 2Sigma(+) state was found to lie only 72 cm(exp -1) below the 2Pi state in the estimated complete basis set limit for valence correlation. The C2H(-) and C3H(-) anions have also been characterized.

Woon, David E.↗

DOE OSTI2015

Experimental and ab initio studies on sub-lattice ordering and magnetism in Co{sub 2}Fe(Ge{sub 1−x}Si{sub x}) alloys

Crystallographic and magnetic properties of bulk Co{sub 2}Fe(Ge{sub 1−x}Si{sub x}) alloys with 0 ≤ x ≤ 1, synthesized by arc melting method, have been studied. Co{sub 2}FeSi alloy has been found to crystallize with L2{sub 1} structure, but the super-lattice peaks are absent in the X-ray diffraction patterns of alloys containing high Ge concentration. Unit cell volume of this series of alloys decreased from 185.2 to 178.5 Å{sup 3} as Si content was increased from 0 to 1.00. All alloy compositions exhibit ferromagnetic behavior with a high Curie temperature (T{sub C}). T{sub C} showed a systematic variation with x. A comparison between the values of saturation magnetization (M{sub s}) and effective moment per magnetic atom p{sub c} estimated from the temperature dependent susceptibility data above T{sub C}, shows that the alloys have half-metallic character. The alloy with x = 0 follows Slater-Pauling (S-P) rule with M{sub s} of 5.99μ{sub B}. However, M{sub s} for the alloy with x = 1.00 was found to be 5.42μ{sub B}, which is lower than the value of 6.0μ{sub B} predicted by S-P rule. Since atomic disorder is known to affect the M{sub s} and electronic structure of these alloys, ab initio calculations were carried out to explain the deviation in observed M{sub s} from S-P rule prediction and the half-metallic character of the alloys. Ab initio calculations reveal that alloys with L2{sub 1} structure have M{sub s} value as predicted by S-P rule. However, introduction of 12.5% DO{sub 3} disorder, which occurs due to swapping of Co and Fe atoms in the unit cell, decreases M{sub s} of alloys with x > 0 from the S-P prediction to values obtained experimentally. The results analyzed from the view point of electronic structure of the alloys in different ordered states bring out the influence of disorder on the observed magnetic properties of these technologically important alloys.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Structure of the Bastnäsite (001) Surface by Crystal Truncation Rod X-ray Diffraction and Ab Initio Molecular Dynamics: Implications for Separations of a Rare Earth Ore Mineral

Bastnäsite ((Ce,La)FCO 3 ) is the primary mineral source of light rare earth elements, but its surface structure is not well understood. This presents a major challenge in improving beneficiation strategies. In this work, a synergistic combination of X-ray scattering and ab initio molecular dynamics (AIMD) was used to gain atomistic insight into the interfacial structure of bastnäsite. Surface X-ray scattering was used to measure crystal truncation rods (CTRs) of the bastnäsite (001) surface, a significant crystal face with a previously unknown termination. The best-fit atomic-scale model of the CTR data features a carbonate layer at the surface, which is stabilized by the relaxation of carbonate groups from their bulk structural positions. AIMD simulations predict similar surface relaxations, which are shown to be influenced by the protonation of oxygen atoms at the surface. Evidence of ordered water at the interface is also observed in the best-fit model and AIMD simulations. Further, the presence of a carbonate layer at this dominant crystal surface is significant for improving separation technologies because most commonly used ligands utilize anionic functional groups to chelate metal cations at particle surfaces. Without modification, anionic ligands are expected to have poor affinity for the carbonate-terminated (001) surface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Machine Learning a Simple Interpretable Short-Range Potential for Silica

A wide array of models, spanning from computationally expensive ab initio methods to a spectrum of force-field approaches, have been developed and employed to probe silica polymorphs and understand growth processes and atomic-level dynamical transitions in silica. However, the quest for a model capable of making accurate predictions with high computational efficiency for various silica polymorphs is still ongoing. Recent developments in short-range machine-learned models, such as GAP and NNPScan, have shown promise in providing reasonable descriptions of silica, but their computational cost remains high compared to force fields such as BKS which are based on simple interpretable functional forms. Here, in this study, we build on the recent success of our reinforcement learning (RL) workflow to derive a new set of optimal parameters for a promising short-range BKS-based model proposed by Soules. We use RL to navigate the eight-dimensional parameter space of the Soules potential using an experimental training data set that includes both local and global structural features from approximately 21 experimentally realized silica polymorphs, including high density phases and porous zeolites. We compare the performance of our machine-learned ML-Soules model with other high quality models including our recent machine-learned parametrization of BKS (ML-BKS), a machine-learned potential (GAP), as well as predictions of ab initio calculations with the highly fidelity SCAN functional. The ML-Soules accurately captures the relative energetic ordering of various polymorphs as well as their structural features at a significantly reduced computational expense. The ML-Soules model also reasonably captures the structure, density, and elastic constants of quartz, as well as metastable silica polymorphs. We further discuss the limitations of the Soules functional form and propose potential enhancements, including the incorporation of additional three-body terms and/or the utilization of different short-ranged functional forms to achieve greater accuracy for both global and local features in the modeling of silica while retaining low computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1986

Ab initio study of the alkali and alkaline-earth monohydroxides

A systematic study of the structures and dissociation energies of all the alkali and alkaline-earth monohydroxides is conducted. A theoretical model for determining accurate dissociation energies of ionic molecules is discussed. The obtained theoretical structures and dissociation energies of the alkali and alkaline-earth monohydroxides, respectively, are compared with experimental data. It is found that the theoretical studies of the bending potentials of BeOH, MgOH, and CaOH reveal the different admixture of covalent character in these systems. The BeOH molecule with the largest degree of covalent character is found to be bent (theta equals 147 deg). The MgOH is also linear. The theoretical dissociation energies for the alkali and akaline-earth hydroxides are thought to be accurate to 0.1 eV.

Bauschlicher, C. W., Jr.↗

DOE OSTI2021

First principles molecular dynamics maps out complete mineral surface acidity landscape

In “Interfacial structures and acidity constants (pKa) of goethite from first principles molecular dynamics simulations,” authors Y. Zhang, X. Lui, J. Cheng, and X. Lu apply First Principles molecular dynamics (FPMD, also called Density Functional Theory MD, DFT/MD, or ab initio MD, AIMD), to evaluable the complete set of acidity constants (pK a ) of the hydroxyl groups on the most prominent goethite crystal facets. The pK a of these OH and OH$^+_2$ groups are compared with available data from the multisite complexation (MUSIC) model traditionally used to estimate pK a on mineral surfaces. The authors have presented eloquent rationale for the importance and implications of understanding goethite acidity constants in room temperature geochemistry settings. In this paper, I focus on the computational aspects, the strengths of FPMD, and its possibilities.

58 GEOSCIENCES↗

NASA NTRS2021

What it Takes to Compute Highly Accurate Rovibrational Line Lists for Use in Astrochemistry

We review the Best Theory + Reliable High-resolution Experiment (BTRHE) strategy for obtaining highly accurate molecular rovibrational line lists with InfraRed (IR) intensities. The need for highly accurate molecular rovibrational line lists is two-fold: a) assignment of the many rovibrational lines for common stable molecules especially those that exhibit a large amplitude motion, such as NH3, or have a high density of states such as SO2; and b) characterization of the atmospheres of exoplanets which will be one of the main areas of research in astronomy in the coming decades. The first motivation arises due to the need to eliminate lines due to common molecules in an astronomical observation in order to identify lines from new molecules, while the second motivation arises due to the need to obtain accurate molecular opacities in order to characterize the atmosphere of an exoplanet. The BTRHE strategy first consists of using high quality ab initio quantum chemical methods to obtain a global potential energy surface (PES) and dipole moment surface (DMS) that contains the proper physics. The global PES is then refined using a subset of the reliable high-resolution experimental data. The refined PES then gives energy level predictions to an accuracy similar to the reproduction accuracy of the experimental data used in the refinement step in the interpolation region (i.e., within the range of the experimental data used in the refinement step). The accuracy of the energy levels will slowly degrade as they are extrapolated to spectral regions beyond the high-resolution experimental data used in the refinement step. However, because the degradation is slow, the predicted energy levels can be used to assign new high-resolution experiments, and the data from these can then be used in a subsequent refinement step. In this way, the global PES eventually can yield highly accurate energy levels for all desired spectral regions including to very high energies and high J values. We show that IR intensities computed with the BTRHE rovibrational wavefunctions and the DMS can be very accurate provided one has minimized the fitting error of the DMS and tested the completeness of the DMS. Some examples of our work on NH3, CO2, and SO2 are given to highlight the usefulness of the BTRHE strategy and to provide ideas on how to further improve its predictive power in the future. In particular, it is shown how successive refinement steps, once new high-resolution data is available, can lead to PESs that yield highly accurate transition energies to larger spectral regions. The importance of including non-adiabatic corrections to reduce the J-dependence of errors for H-containing molecules is shown with work on NH3. Another very important aspect of the BTRHE approach is the consistency across isotopologues, which allows for highly accurate line lists for any isotopologue once one is obtained for the main isotopologue (which has more high-resolution data available for refinement).

Xinchuan Huang↗