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Results for “Potential energy surfaces”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Internal conversion and intersystem crossing dynamics based on coupled potential energy surfaces with full geometry-dependent spin–orbit and derivative couplings. Nonadiabatic photodissociation dynamics of NH 3 (A) leading to the NH(X 3 Σ – , a 1 Δ) + H 2 channel

Here we simulate the photodissociation of NH 3 originating from its first excited singlet state S 1 into the NH 2 + H (radical) and NH + H 2 (molecular) channels. The states considered are the ground singlet state S 0 , the first excited singlet state S 1 and the lowest-lying triplet state T 1 , which permit for the first time a uniform treatment of the internal conversion and intersystem crossing. The simulations are based on a diabatic potential energy matrix (DPEM) of S 0 , S 1 coupled by a conical intersection seam, as well as a potential energy surface (PES) for T 1 coupled by spin-orbit coupling (SOC) to the two singlet states. The DPEM and PES are fitted to ab initio electronic structure data (ESD) including energies, energy gradients, and derivative couplings. The DPEM also defines an adiabatic to diabatic state (AtD) transformation, which is used to transform the singular adiabatic SOC into a smooth function of the nuclear coordinates in the diabatic representation, allowing the diabatic SOC to be fit to an analytical functional form. ESD and SOC data obtained from these surfaces can serve as input for either quantum or semi-classical characterization of the nonadiabatic dynamics. Using the SHARC suite of programs, nonadiabatic simulations based on over 40 000 semi-classical trajectories assess the convergence of our results. The production of NH + H 2 is not direct, but is only achieved through a quasi-statistical dissociation mechanism after internal conversion to the ground electronic state. This leads to a much lower yield comparing with the main NH 2 + H channel. The NH(X 3 Σ_) radical produced through the intersystem crossing from S 0 to T 1 is rare (~0.2%) compared to NH(a 1 Δ) due to the process being spin forbidden.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ab initio quantum scattering calculations and a new potential energy surface for the HCl( X 1Σ+)–O2(X3Σg−) system: Collision-induced line shape parameters for O2-perturbed R(0) 0–0 line in H35Cl

The remote sensing of abundance and properties of HCl—the main atmospheric reservoir of Cl atoms that directly participate in ozone depletion—is important for monitoring the partitioning of chlorine between “ozone-depleting” and “reservoir” species. Such remote studies require knowledge of the shapes of molecular resonances of HCl, which are perturbed by collisions with the molecules of the surrounding air. In this work, we report the first fully quantum calculations of collisional perturbations of the shape of a pure rotational line in H35Cl perturbed by an air-relevant molecule [as the first model system we choose the R(0) line in HCl perturbed by O2]. The calculations are performed on our new highly accurate HCl(X1Σ+)–O2(X3Σg−) potential energy surface. In addition to pressure broadening and shift, we also determine their speed dependencies and the complex Dicke parameter. This gives important input to the community discussion on the physical meaning of the complex Dicke parameter and its relevance for atmospheric spectra (previously, the complex Dicke parameter for such systems was mainly determined from phenomenological fits to experimental spectra and the physical meaning of its value in that context is questionable). We also calculate the temperature dependence of the line shape parameters and obtain agreement with the available experimental data. We estimate the total combined uncertainties of our calculations at 2% relative root-mean-square error in the simulated line shape at 296 K. This result constitutes an important step toward computational population of spectroscopic databases with accurate ab initio line shape parameters for molecular systems of terrestrial atmospheric importance.

Chemistry↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Quantum scattering of HC 5 N and para -H 2 on a new potential energy surface

In the interstellar medium (ISM), non-local thermodynamic equilibrium situations are common due to low density, and one needs to consider the effect of molecular collisions in order to interpret the observations. Among the species detected in the ISM, cyanopolyynes, with the general molecular formula HC 2n+1 N (n = 1, 2, …), are characterized by large dipole moments and small rotational constants and constitute an indispensable class of candidates for the sensitive tracers of local density and temperature. We present a study of the collisional (de-) excitation of HC 5 N by para -H 2 (p-H 2 ) in its ground rotational state, namely HC 5 N ( j 1 ) + H 2 ( j 2 = 0) → HC 5 N (j$_1^′$) + H2 (j$_2^′$ = 0), where j 1 (or j$_1^′$) and j 2 (or j$_2^′$) denote the initial (or final) rotational quantum numbers of HC 5 N and H 2 , respectively. We performed the quantum scattering calculations at low collision energy using a new four-dimensional ab initio potential energy surface. In the regime where p-H 2 remains in its rotational ground state, converged cross sections did not require including excited rotational states of p-H 2 in the rotational basis. State-to-state cross sections were computed by means of the quantum-mechanical close-coupling (CC) method and the coupled states (CS) approximation, and rate coefficients for the first 61 levels of HC 5 N were computed for the first time up to 20 K with the CC approach and up to 50 K with the CS method. CC and CS results were found to agree well at temperatures up to 20 K. Finally, these data should allow a more accurate derivation of the HC 5 N abundance in molecular clouds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine learning potential assisted exploration of complex defect potential energy surfaces

Abstract Atomic-scale defects generated in materials under both equilibrium and irradiation conditions can significantly impact their physical and mechanical properties. Unraveling the energetically most favorable ground-state configurations of these defects is an important step towards the fundamental understanding of their influence on the performance of materials ranging from photovoltaics to advanced nuclear fuels. Here, using fluorite-structured thorium dioxide (ThO 2 ) as an exemplar, we demonstrate how density functional theory and machine learning interatomic potential can be synergistically combined into a powerful tool that enables exhaustive exploration of the large configuration spaces of small point defect clusters. Our study leads to several unexpected discoveries, including defect polymorphism and ground-state structures that defy our physical intuitions. Possible physical origins of these unexpected findings are elucidated using a local cluster expansion model developed in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Automated Reaction Kinetics of Gas-Phase Organic Species over Multiwell Potential Energy Surfaces

Automation of rate-coefficient calculations for gas-phase organic species became possible in recent years and has transformed how we explore these complicated systems computationally. Kinetics workflow tools bring rigor and speed and eliminate a large fraction of manual labor and related error sources. In this paper we give an overview of this quickly evolving field and illustrate, through five detailed examples, the capabilities of our own automated tool, KinBot. Here we bring examples from combustion and atmospheric chemistry of C-, H-, O-, and N-atom-containing species that are relevant to molecular weight growth and autoxidation processes. The examples shed light on the capabilities of automation and also highlight particular challenges associated with the various chemical systems that need to be addressed in future work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Proper orthogonal descriptors for efficient and accurate interatomic potentials

Here, we present the proper orthogonal descriptors for efficient and accuracy representation of the potential energy surface. The potential energy surface is represented as a many-body expansion of parametrized potentials in which the potentials are functions of atom positions and parameters. The proper orthogonal decomposition is employed to decompose the parametrized potentials into a set of proper orthogonal descriptors (PODs). Because of the rapid convergence of the proper orthogonal decomposition, relevant snapshots can be sampled exhaustively to represent the atomic neighborhood environment accurately with a small number of descriptors. The proper orthogonal descriptors are used to develop interatomic potentials by using a linear expansion of the descriptors and determining the expansion coefficients from a weighted least-squares regression against a density functional theory (DFT) training set. We present a comprehensive evaluation of the POD potentials on previously published DFT data sets comprising Li, Mo, Cu, Ni, Si, Ge, and Ta elements. The data sets represent a diverse pool of metals, transition metals, and semiconductors. The accuracy of the POD potentials are comparable to that of state-of-the-art machine learning potentials such as the spectral neighbor analysis potential (SNAP) and the atomic cluster expansion (ACE).

97 MATHEMATICS AND COMPUTING↗