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At least 145 records · Page 8

A potential-energy surface study of the 2A1 and low-lying dissociative states of the methoxy radical

Accurate, ab initio quantum chemical techniques are applied in the present study of low lying bound and dissociative states of the methoxy radical at C3nu conformations, using a double zeta quality basis set that is augmented with polarization and diffuse functions. Excitation energy estimates are obtained for vertical excitation, vertical deexcitation, and system origin. The rate of methoxy photolysis is estimated to be too small to warrant its inclusion in atmospheric models.

Jackels, C. F.↗

Theoretical study of collinear Be + FH/nu1/ yields BeF/nu2/ + H

The potential energy surface for collinear Be + FH yields BeF + H was studied at various levels of ab initio approximation. A final surface was obtained from a first order configuration interaction wave function, using the iterative orbital method and a medium-sized basis of Slater atomic functions. The exothermicity is computed to be 6 kcal/mole; the barrier height is predicted to be about 28 kcal/mole at a geometry where both internuclear separations are extended by about 0.4 bohr from their asymptotic equilibrium values. This surface differs qualitatively from simple LEPS models.

Schor, H.↗

Rototranslational absorption spectra of H2-H2 pairs in the far infrared

On the basis of ab initio induced dipole components and a well-tested isotropic potential, the collision-induced absorption rototranslational profiles of hydrogen have been determined using an exact wave-mechanical theory. The main induction mechanisms, particularly the quadrupole-induced 0223,2023 components, are found to be consistent with observations. It is demonstrated that the present theory can be used to predict spectra at temperatures where no measurements exist, as is needed for the modeling of planetary and stellar atmospheres.

Meyer, Wilfried↗

Quenching of Excited Na due to He Collisions

The quenching and elastic scattering of excited Sodium by collisions with Helium have been investigated for energies between 10(exp -13) eV and 10 eV. With the ab initio adiabatic potentials and nonadiabatic radial and rotational couplings obtained from multireference single- and double-excitation configuration interaction approach, we carried out scattering calculations by the quantum-mechanical molecular-orbital close-coupling method. Cross sections for quenching reactions and elastic collisions are presented. Quenching and elastic collisional rate coefficients as a function of temperature between 1 micro-K and 10,000 K are also obtained. The results are relevant to modeling non-LTE effects on Na D absorption lines in extrasolar planets and brown dwarfs.

Lin, C. Y.↗

Theoretical Study of the Electronic Spectra of a Polycyclic Aromatic Hydrocarbon, Naphthalene, and its Derivatives

In order to preselect possible candidates for the origin of diffuse interstellar bands observed, semiempirical quantum mechanical method INDO/S was applied to the optical spectra of neutral, cationic, and anionic states of naphthalene and its hydrogen abstraction and addition derivatives. Comparison with experiment shows that the spectra of naphthalene and its ions were reliably predicted. The configuration interaction calculations with single-electron excitations provided reasonable excited state wavefunctions compared to ab initio calculations that included higher excitations. The degree of similarity of the predicted spectra of the hydrogen abstraction and derivatives to those of naphthalene and ions depends largely on the similarity of the it electron configurations. For the hydrogen addition derivatives, very little resemblance of the predicted spectra to naphthalene was found because of the disruption of the aromatic conjugation system. The relevance of these calculations to astrophysical issues is discussed within the context of these polycyclic aromatic hydrocarbon models. Comparing the calculated electronic energies to the Diffuse Interstellar Bands (DIBs), a list of possible candidates of naphthalene derivatives is established which provides selected candidates for a definitive test through laboratory studies.

Du, Ping↗

Rototranslational collision-induced absorption by H2-H2 pairs at temperatures from 600 to 7000 K

The computation of the far-infrared, rototranslational (RT) collision-induced absorption (CIA) spectra of H2-H2 pairs is presented at temperatures from 600 to 7000 K for the first time. Theoretical results are based on the quantum mechanical and semiclassical, three lowest translational spectral moments obtained for H2 pairs. The effective, isotropic H2-H2 interaction potential, suitable for the high-temperature computations, and the ab initio induced dipoles, have been used as input. Special effort has been made to account for the rotational and vibrational states dependence of the dipoles, since it was found to be relevant at the high temperatures employed. The computations of the entire RT band account for all populated vibrational states of hydrogen molecule and include vibrational transitions v tends towards v-prime = v, with v = 0, 1, 2 and 3. The described method makes use of the adequately selected model line shapes with the temperature-dependent parameters. The presented model is useful for the 'model atmospheres' of zero- and low-metallicity, cool and dense stellar atmospheres, where CIA is known to be imporatnt.

Zheng, Chunguang↗

Ab initio characterization of ClOOH - Implications for atmospheric chemistry

The equilibrium structure, dipole moment, harmonic vibrational frequencies, and infrared intensities of ClOOH are determined using the CCSD(T) (singles and doubles coupled-cluster theory plus a perturbational estimate of the effects of connected triple excitations) electronic structure method in conjunction with a TZ2P (triple xi plus double polarization) basis set. The heat of formation of CIOOH is determined (using two different isodesmic reactions) to be +1.5 +/- 1 kcal/mol at 0 K or +0.2 +/- 1 kcal/mol at 298.15 K. Using the computed heat of formation, we examined the stability of ClOOH with respect to the ClO + OH, ClOO + H, and HOO + Cl dissociation limits. Since ClOOH is found to be quite stable, it is argued that the chemistry of ClOOH should be included in any accurate modeling of the stratosphere.

Lee, Timothy J.↗

Theoretical Studies of the Extra-terrestrial Chemistry of Biogenic Elements and Compounds

Results are presented on the following:(A) Ab initio quantum chemical studies of reactions in astrophysical ices.Theoretical electronic structure calculations were used to investigate reactions between formaldehyde (H2CO) and both hydrogen cyanide (HCN) and isocyanide (HNC) in search of other favorable reactions such as ammonia-formaldehyde addition, which was found in a recent theoretical study to be strongly enhanced when it occurs within cold ices.The present study examines further reactions between this product and H2CO in ices.(B) Heterogeneous hydrogenation of CO and H2CO on icy grain mantles.Formaldehyde (H2CO) and methanol (CH30H) are thought to be produced in the interstellar medium by the successive hydrogenation of carbon monoxide (CO) on grain surfaces. In the gas phase, the steps in which H adds to CO and H2CO possess modest barriers and are too inefficient to account for the observed abundances. Recent laboratory work has confirmed that formaldehyde and methanol are formed when H atoms are deposited on CO ice at 12 K. The present study employed ab initio quantum chemical calculations to investigate the impact of water ice on the sequential hydrogenation of CO.(C) Ice-bound condensed-phase reactions involving formic acid (HCOOH), methylenimine (CH2NH), hydrogen cyanide (HCN), hydrogen isocyanide (HNC), and ammonia ( 3) were investigated in order to characterize possible pathways to larger organic species that are efficient at the cold temperatures prevalent in cometary nuclei and the interstellar medium. (D) Pathways to glycine and other amino acids in ultraviolet-irradiated ices determined via quantum chemical modeling.(E) Photoionization in ultraviolet processing of astrophysical ice analogs at cryogenic temperatures.

Woon, David E.↗

Electrostatic Properties of PE and PTFE Subjected to Atmospheric Pressure Plasma Treatment; Correlation of Experimental Results with Atomistic Modeling

The use of an atmospheric pressure glow discharge (APGD) plasma was used at KSC to increase the hydrophilicity of spaceport materials to enhance their surface charge dissipation and prevent possible ESD in spaceport operations. Significant decreases in charge decay times were observed after tribocharging the materials using the standard KSC tribocharging test. The polarity and amount of charge transferred was dependent upon the effective work function differences between the respective materials. In this study, polyethylene (PE) and polytetrafluoroethylene (PTFE) were exposed to a He+O2 APGD. The pre and post treatment surface chemistry was analyzed by X-ray photoelectron spectroscopy and contact angle measurements. Semi-empirical and ab initio calculations were performed to correlate the experimental results with some plausible molecular and electronic structure features of the oxidation process. For the PE, significant surface oxidation was observed, as indicated by XPS showing C-O, C=O, and O-C=O bonding, and a decrease in the surface contact angle from 98.9 deg to 61.2 deg. For the PTFE, no C-O bonding appeared and the surface contact angle increased indicating the APGD only succeeded in cleaning the PTFE surface without affecting the surface structure. The calculations using the PM3 and DFT methods were performed on single and multiple oligomers to simulate a wide variety of oxidation scenarios. Calculated work function results suggest that regardless of oxidation mechanism, e.g. -OH, =0 or a combination thereof, the experimentally observed levels of surface oxidation are unlikely to lead to a significant change in the electronic structure of PE and that its increased hydrophilic properties are the primary reason for the observed changes in its electrostatic behavior. The calculations for PTFE argue strongly against significant oxidation of that material, as confirmed by the XPS results.

Trigwell, Steve↗

Collisional Dissociation of CO: ab initio Potential Energy Surfaces and Quasiclassical Trajectory Rate Coefficients

We have generated accurate global potential energy surfaces for CO+Ar and CO+O that correlate with atom-diatom pairs in their ground electronic states based on extensive ab initio electronic structure calculations and used these potentials in quasi-classical trajectory nuclear dynamics calculations to predict the thermal dissociation rate coefficients over 5000- 35000 K. Our results are not compatible with the 20-45 year old experimental results. For CO + Ar we obtain fairly good agreement with the experimental rate coefficients of Appleton et al. (1970) and Mick and Roth (1993), but our computed rate coefficients exhibit a stronger temperature dependence. For CO + O our dissociation rate coefficient is in close agreement with the value from the Park model, which is an empirical adjustment of older experimental results. However, we find the rate coefficient for CO + O is only 1.5 to 3.3 times larger than CO + Ar over the temperature range of the shock tube experiments (8000-15,000 K). The previously accepted value for this rate coefficient ratio is 15, independent of temperature. We also computed the rate coefficient for the CO + O ex- change reaction which forms C + O2. We find this reaction is much faster than previously believed and is the dominant process in the removal of CO at temperatures up to 16,000 K. As a result, the dissociation of CO is accomplished in two steps (react to form C+O2 and then O2 dissociates) that are endothermic by 6.1 and 5.1 eV, instead of one step that requires 11.2 eV to break the CO bond.

exchange rate coefficient↗

Theoretical dissociation energies for ionic molecules

Ab initio calculations at the self-consistent-field and singles plus doubles configuration-interaction level are used to determine accurate spectroscopic parameters for most of the alkali and alkaline-earth fluorides, chlorides, oxides, sulfides, hydroxides, and isocyanides. Numerical Hartree-Fock (NHF) calculations are performed on selected systems to ensure that the extended Slater basis sets employed for the diatomic systems are near the Hartree-Fock limit. Extended Gaussian basis sets of at least triple-zeta plus double polarization equality are employed for the triatomic system. With this model, correlation effects are relatively small, but invariably increase the theoretical dissociation energies. The importance of correlating the electrons on both the anion and the metal is discussed. The theoretical dissociation energies are critically compared with the literature to rule out disparate experimental values. Theoretical (sup 2)Pi - (sup 2)Sigma (sup +) energy separations are presented for the alkali oxides and sulfides.

Langhoff, S. R.↗

High-Throughput Screening of Li Solid-State Electrolytes With Bond Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Screening of Li-Based Solid Electrolytes Using Bond-Valence Methods and Graph Neural Networks

Li-based solid-state electrolyte (Li-SSE) materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. We present a high-throughput screening approach for Li-SSE materials using a combination of bond-valence methods and graph neural networks. We demonstrate the screening approach with a dataset containing tens of thousands of Li-containing compounds. Furthermore, we combine the machine-learning screening procedure with an isovalent substitution scheme to generate and screen additional Li SSE candidates beyond existing databases. Finally, we discuss relative importances of geometric and bond-valence quantities in the training of graph neural networks, providing insight for future modeling of ionic conductivity in Li-SSE materials.

Materials discovery↗

Accurate Infrared Line Lists for 20 Isotopologues of CS 2 at Room Temperature

To facilitate atmospheric and spectroscopic studies of carbon disulfide, or CS 2 , in both planetary and exoplanetary atmospheres, we adopt the “Best Theory + Reliable High-resolution Experiment” algorithm to generate semiempirical IR line lists for the 20 most abundant CS 2 isotopologues, denoted as Ames-296K. The IR lists are computed using the Ames-1 potential energy surface, refined using the experimental transition set and an ab initio dipole moment surface fitted from CCSD(T)/aug-cc-pV(T/Q/5+d)Z dipoles extrapolated to a one-particle basis set limit. The IR lists cover the range of 0–10,000 cm -1 , with an S 296K cutoff at 10 -31 cm -1 /molecule·cm -2 (abundance included). A “natural” IR line list at 296 K includes about 10 million lines of the 20 isotopologues, with their intensities scaled by the corresponding abundances. The zero-point energy, partition functions, and abundances are reported for each isotopologue. The energy levels in the global effective Hamiltonian model for 12 C 32 S 2 are adopted to improve the line position accuracy. This new IR list for the main isotopologue is denoted as A+I.296K. Reliable HITRAN2020 line positions are also utilized to improve the accuracy of the 32 S 12 C 34 S, 32 S 12 C 33 S, and 32 S 13 C 32 S isotopologue line lists. The final composite line list is validated against Pacific Northwest National Laboratory experimental cross sections, showing excellent agreement. The agreement supports the quality of the composite line list and the power of synergy between experiment and theory. The new data are proposed for use in updating and expanding the CS 2 data in HITRAN and other high-resolution IR databases. Supplementary files are available in Zenodo and AHED.

Exoplanet atmospheric composition↗

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗

Molecular processes in a high temperature shock layer

Models of the shock layer encountered by an Aeroassisted Orbital Transfer Vehicle require as input accurate cross sections and rate constants for the atomic and molecular processes that characterize the shock radiation. From the estimated atomic and molecular densities in the shock layer and the expected residence time of 1 m/s, it can be expected that electron-ion collision processes will be important in the shock model. Electron capture by molecular ions followed by dissociation, e.g., O2(+) + e(-) yields 0 + 0, can be expected to be of major importance since these processes are known to have high rates (e.g., 10 to the -7th power cu/cm/sec) at room temperature. However, there have been no experimental measurements of dissociative recombination (DR) at temperatures ( 12000K) that are expected to characterize the shock layer. Indeed, even at room temperature, it is often difficult to perform experiments that determine the dependence of the translational energy and quantum yields of the product atoms on the electronic and vibrational state of the reactant molecular ions. Presented are ab initio quantum chemical studies of DR for molecular ions that are likely to be important in the atmospheric shock layer.

Guberman, S. L.↗

Constraints on Triple Oxygen Isotope Kinetics

Triple oxygen isotope methods (e.g., using δ 18 O, and Δ′ 17 O) have been used to classify meteorites, to constrain atmospheric chemistry, and to estimate primary productivity, among other uses. Such utility relies on the mass dependency of most chemical reactions: δ 17 O is proportional to δ 18 O by roughly a factor of 0.5. However, in detail, mass-dependency factors vary. While constraints on mass dependency are well established for equilibrium isotope effects, similar constraints for kinetic isotope effects are lacking. Using an ab initio Monte Carlo approach (see envelopes in Figure 1), we find the range of kinetic isotope effects (i.e., resulting from unidirectional chemical reactions) contains and exceeds the range of accessible equilibrium isotope effects for the 16 O 17 O 18 O system (Hayles and Killingsworth, 2022). Accessible kinetic isotope effects can yield Δ′ 17 O variations as large 0.8 ‰ from a single kinetic fractionation step. Reactions that yield the largest deviations from equilibrium are those with the largest molecular mass difference between decomposition fragments, typically the two products such as a gas and solid generated from the thermal decomposition of an initial solid. Comparison of DFT transition state model results against previously published experiments on the thermal decomposition of calcite (CaCO 3 ) (Miller et al., 2002) and dehydroxylation of brucite (Mg(OH) 2 ) (Clayton and Mayeda, 2009) show they are matched with mass-dependent kinetic isotope effects. This approach can be applied to any system with more than two isotopes.

Oxygen isotopes↗

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗