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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

On the Nature of Extra-Framework Aluminum Species and Improved Catalytic Properties in Steamed Zeolites

Steamed zeolites exhibit improved catalytic properties for hydrocarbon activation (alkane cracking and dehydrogenation). The nature of this practically important phenomenon has remained a mystery for the last six decades and was suggested to be related to the increased strength of zeolitic Bronsted acid sites after dealumination. We now utilize state-of-the-art infrared spectroscopy measurements and prove that during steaming, aluminum oxide clusters evolve (due to hydrolysis of Al out of framework positions with the following clustering) in the zeolitic micropores with properties very similar to (nano) facets of hydroxylated transition alumina surfaces. The Bronsted acidity of the zeolite does not increase and the total number of Bronsted acid sites decreases during steaming. O 5 Al(VI)-OH surface sites of alumina clusters dehydroxylate at elevated temperatures to form penta-coordinate Al 1 O 5 sites that are capable of initiating alkane cracking by breaking the first C-H bond very effectively with much lower barriers (at lower temperatures) than for protolytic C-H bond activation, with the following reaction steps catalyzed by nearby zeolitic Bronsted acid sites. This explains the underlying mechanism behind the improved alkane cracking and alkane dehydrogenation activity of steamed zeolites: heterolytic C-H bond breaking occurs on Al-O sites of aluminum oxide clusters confined in zeolitic pores. Our findings explain the origin of enhanced activity of steamed zeolites at the molecular level and provide the missing understanding of the nature of extra-framework Al species formed in steamed/dealuminated zeolites.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Uncertainty-aware molecular dynamics from Bayesian active learning for phase transformations and thermal transport in SiC

Abstract Machine learning interatomic force fields are promising for combining high computational efficiency and accuracy in modeling quantum interactions and simulating atomistic dynamics. Active learning methods have been recently developed to train force fields efficiently and automatically. Among them, Bayesian active learning utilizes principled uncertainty quantification to make data acquisition decisions. In this work, we present a general Bayesian active learning workflow, where the force field is constructed from a sparse Gaussian process regression model based on atomic cluster expansion descriptors. To circumvent the high computational cost of the sparse Gaussian process uncertainty calculation, we formulate a high-performance approximate mapping of the uncertainty and demonstrate a speedup of several orders of magnitude. We demonstrate the autonomous active learning workflow by training a Bayesian force field model for silicon carbide (SiC) polymorphs in only a few days of computer time and show that pressure-induced phase transformations are accurately captured. The resulting model exhibits close agreement with both ab initio calculations and experimental measurements, and outperforms existing empirical models on vibrational and thermal properties. The active learning workflow readily generalizes to a wide range of material systems and accelerates their computational understanding.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Highly Active Hydrogen Evolution Reaction (HER) Catalysts Formed by Energetic Pt n Cluster Deposition: Deposition Dynamics and the HER Mechanism

Mass-selected Pt n + (n ≤ 7) were deposited at variable energies on highly oriented pyrolytic graphite (HOPG), creating highly active hydrogen evolution reaction (HER) electrocatalysts. HER mass activities were ~2 to >10 times higher than those for the surface atoms in bulk Pt and for Pt n deposited on several other supports. Thus, high activity reflects the Pt-C structures formed by energetic Pt n -HOPG impacts, in addition to high Pt surface availability. The Pt n /HOPG electrodes were probed by X-ray photoelectron spectroscopy, low energy ion scattering, and electron microscopy. Born-Oppenheimer molecular dynamics (BOMD) was used to simulate Pt n - HOPG impacts, revealing the types of structures formed at different energies, then DFT was used to probe their most important HER pathways. For low deposition energies, the Pt n deposit onto the HOPG surface with sub-unit sticking probability, aggregating at defects. With increasing deposition energy, the sticking probability initially decreases, then rises to unity as subplantation and defect creation allow formation of strongly bonded platinum-carbon structures. Barriers for HER on these structures were found to be low and weakly dependent on Pt n size, consistent with experiment. The activities were highest for small covalently-bonded Pt-C structures created at high deposition energies. The larger aggregated structures formed at low energies were less active, but still substantially better than the bulk Pt surface monolayer. The catalysts were stable in repeated potential cycling at reducing potentials, but electrodes containing subplanted Pt became more active when scanned to oxidizing potentials, due to emergence of subplanted Pt onto the surface.

08 HYDROGEN↗
DOE OSTI2022

Understanding Proton Movement in [Fe-Fe] Hydrogenases

Nature uses specialized metalloenzymes to carry out small molecule activation reactions, including CO 2 fixation, O 2 activation, and proton reduction, with unparalleled efficiency, rates, and selectivity. The latter reactions are performed by hydrogenases, protein metallo-complexes that interconverts H 2 to protons and electrons (H 2 oxidation) and the reverse reaction (H 2 production) with incredibly low energy input and amazingly fast kinetics. Reproducing both the activity and efficiency of metalloenzymes in sustainable anthropogenic systems remains one of the “holy grails” of inorganic chemistry. However, identifying the precise molecular components responsible for these desirable properties has been challenging in the natural metalloenzymes, hindering efforts to develop analogous processes in synthetic compounds. Considering the inherent complexity of a metalloenzyme and the many interactions, both strong and weak, that contribute to the function of an enzyme, we have elected to model natural metalloenzymes on a biochemical platform. Towards this end, we have a developed structural, functional, and mechanistic mimic of the [Ni-Fe] hydrogenases within a robust protein scaffold, rubredoxin, to understand the influence of the secondary coordination environment on the metal center. This involved preparing a series of three rubredoxin constructs containing a single point mutation at Val positions and making the NMR chemical shift assignments for the paramagnetic (nickel-substituted) and non-paramagnetic (zinc-substituted) form. These physical studies were complemented with in silico molecular dynamic studies on proteins with [Fe-S] clusters to engineer new proton channels to test in vitro . To assist our search for new natural metalloprotein scaffolds within the vast number of sequenced genomes, we created a neural network-based program to identify proteins with specific metal-binding sites. These computational and physical studies with metalloenzymes provide direct insight into the fundamental chemical principles driving the natural systems and offer design principles for developing catalysts that utilize analogous principles.

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

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Defect Production and Microstructural Feature Impact for Radiation Damage in Additively Manufactured 316 Stainless Steel

This milestone presents multi-scale modeling research results for additively manufactured 316 stainless steel. A combination of phase field, cluster dynamics, molecular dynamics, and density functional theory with machine learning is used, allowing for predictions of radiation-driven microstructural evolution in additively manufactured 316 stainless steel over a range of temperatures, damage rates, neutron spectra, and microstructures, and supporting the development of combined ion and neutron irradiation for material qualification. Informed by ion irradiation and neutron irradiation results across the Advanced Materials and Manufacturing Technologies program, we investigate the unique aspects of radiation-driven microstructure evolution in additively manufactured 316 stainless steel. In particular, we focus on understanding the impact of carbon concentration (varying, for example, between the 316L and 316H standards) on void formation; radiation-induced segregation at dislocation cells and grain boundaries; and the evolution of dislocation loops and network dislocation populations. We find that the unique characteristics of the additively manufactured microstructures must be accounted for in understanding the evolution of dislocation populations under thermal and irradiation conditions, such as the variation in sink strengths arising due to the variation in dislocation density. We also find that the radiation-induced segregation of Cr and Ni to grain boundaries and cell walls differs due to the differences in their defect sink biases. We also find that increasing the Ni content can slow vacancy diffusion, which may provide a mechanism for the observed reduction in transient swelling rate for austenitic Fe-Cr-Ni alloys with increasing Ni content. In addition, ion irradiations have shown that increasing carbon content in 316 SS results in a larger population of smaller voids, suggesting reduced vacancy diffusion. Our results show that the carbon content of additively manufactured 316 SS has a significant impact on the migration rate of defect clusters. The presence of carbon atoms results in carbon-vacancy trapping, significantly reducing the diffusion rate of vacancies. Carbon atoms may also be trapped near the surface of a void, which may reduce void growth by trapping vacancies that diffuse toward the void.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes

Electrolyte anions are pivotal for lithium battery performance, yet their fundamental electronic structural properties are not well understood. In this work, we employ a combination of negative-ion photoelectron spectroscopy (NIPES), ab initio calculations, and molecular dynamics (MD) simulations to investigate the electronic structures of three representative electrolyte anions. This multiscale approach enables us to elucidate how their intrinsic electronic properties govern anion–solvent interactions in gas-phase clusters, as well as lithium-ion (Li + ) solvation structures and ion transport behavior in the condensed phase. NIPES reveals that difluoro(oxalato)borate (DFOB – ), bis(fluorosulfonyl)imide (FSI – ), and bis(oxalato)borate (BOB – ) all exhibit high electron binding energies, with vertical/adiabatic detachment energies increasing from DFOB – (6.09/5.70 eV) to FSI – (6.80/6.10 eV) to BOB – (6.82/6.40 eV), correlating with enhanced oxidation stability. Ab initio calculations reveal that DFOB – /FSI – –solvent complexes bind Li + ∼ 10 kcal/mol stronger than BOB – series, aligning with the strength of a Li + –anion model. DFOB – exhibits pronounced charge localization on both oxygen and fluorine atoms, enabling their involvement in Li + coordination. In contrast, fluorine atoms in FSI – are largely electron-depleted and remain excluded from direct Li + binding. MD simulations further demonstrate that LiDFOB and LiFSI systems exhibit Li + diffusion coefficients three and five times higher than those of LiBOB across four common solvents. Notably, LiFSI salt in acetonitrile (AN) exhibits the fastest Li + diffusion among 12 electrolyte systems, highlighting the synergistic effect of FSI – and AN in promoting ion mobility. In conclusion, these findings provide a molecular-level understanding of the critical roles of anion and its microsolvation in optimizing Li + diffusion dynamics, once again emphasizing the positioning of FSI – and DFOB – as prime candidates for next-generation electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2025

Supercooling of Alaskan Beetle Larvae as a Winter Survival Strategy

Insects are able to survive subfreezing temperatures by either limiting ice crystal formation in their bodies or through freeze avoidance. Beetle larvae are able to avoid freezing in winter by dehydrating in the fall months and replacing their body water content with high concentrations of glycerol. This enables the body fluid of the insect to supercool, and even vitrify, recovering unharmed when the temperature warms in the spring. Using nondestructive, high‐energy X‐ray synchrotron diffraction experiments, direct insight into how cryopreservation occurs at the atomic level within the beetle larvae has been obtained. The results shed light on the molecular‐level interactions associated with the mechanism responsible for surviving freezing temperatures. The molecular models of severely dehydrated Alaskan beetle larvae, based on glycerol‐water mixtures, yield a total of 4.2 ± 1.2 intermolecular hydrogen bonds per glycerol molecule at 275 K, in good agreement with existing molecular dynamics simulations. Most importantly, they show that if just over half the body fluid content is water, the water clusters are too small to form ice crystals that cause cellular damage.

Benmore, Chris J. [X‐Ray Science Division Advanced↗
DOE OSTI2023

Excited-State Dynamics during Primary C–I Homolysis in Acetyl Iodide Revealed by Ultrafast Core-Level Spectroscopy

In typical carbonyl-containing molecules, bond dissociation events follow initial excitation to $nπ_{C=O}$$^*$ states. However, in acetyl iodide, the iodine atom gives rise to electronic states with mixed $nπ_{C=O}$$^*$ and $nπ_{C–I}$$^*$ character, leading to complex excited-state dynamics, ultimately resulting in dissociation. Using ultrafast extreme ultraviolet (XUV) transient absorption spectroscopy and quantum chemical calculations, we present an investigation of the primary photodissociation dynamics of acetyl iodide via time-resolved spectroscopy of core-to-valence transitions of the I atom after 266 nm excitation. The probed I 4d-to-valence transitions show features that evolve on sub-100-fs time scales, reporting on excited-state wavepacket evolution during dissociation. These features subsequently evolve to yield spectral signatures corresponding to free iodine atoms in their spin–orbit ground and excited states with a branching ratio of 1.1:1 following dissociation of the C–I bond. Calculations of the valence excitation spectrum via equation-of-motion coupled cluster with single and double substitutions (EOM-CCSD) show that initial excited states are of spin-mixed character. From the initially pumped spin-mixed state, we use a combination of time-dependent density functional theory (TDDFT)-driven nonadiabatic ab initio molecular dynamics and EOM-CCSD calculations of the N$_{4,5}$ edge to reveal a sharp inflection point in the transient XUV signal that corresponds to rapid C–I homolysis. Here, by examining the molecular orbitals involved in the core-level excitations at and around this inflection point, we are able to piece together a detailed picture of C–I bond photolysis in which d → σ* transitions give way to d → p excitations as the bond dissociates. We also report theoretical predictions of short-lived, weak 4d → 5d transitions in acetyl iodide, validated by weak bleaching in the experimental transient XUV spectra. This joint experimental–theoretical effort has thus unraveled the detailed electronic structure and dynamics of a strongly spin–orbit coupled system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multifunctional Catalysts for the Tandem Reactions of Oxygenates

Industrially-relevant catalytic reactions rarely consist of a simple sequence of elementary steps. Moreover, kinetic coupling of multiple reactions on a catalyst surface is highly desired for process intensification and improved energy efficiency for large scale chemical transformations. The shifting landscape of hydrocarbon chemical feedstocks in the US also motivates research on the selective conversion of more complex molecules. One desirable type of catalytic reaction is the reduction of carboxylic acids that are produced from biomass feedstocks to their corresponding alcohols. The proposed research explores the fundamental importance of hydrogen spillover on a multifunctional catalyst for carboxylic acid reduction with H 2 composed of metal particles coupled to metal oxide particles. Recent work has demonstrated the excellent performance of supported tungsten oxide clusters for carboxylic acid reduction, but only after they are promoted with a late transition metal such as palladium. Elucidating the active state of the catalyst and the associated reaction mechanism for acid reduction on that active state are the overall goals of the proposed project and successful completion will enable future design of efficient multifunctional catalysts. The critically important role of the metal promoter is hypothesized to be its ability to dissociate H2 and spillover atomic H to the support. Although hydrogen spillover is a well-recognized phenomenon in catalysis, its role in both catalyst activation and catalytic turnover are still unresolved. The study combined materials synthesis, characterization, reactivity testing, and molecular simulations, to explore the effect of hydrogen chemical potential on the formation of the active catalytic sites and on the steady state catalytic reduction of carboxylic acid. Varying the hydrogen chemical potential through modification of the gas conditions, support composition, and metal loading to modulated the structure and catalytic performance of the reducible metal oxide. Dual function catalysts containing supported Pd and WO x species co-located on a non-reducible carrier (silica) and a reducible carrier (titania) were synthesized and characterized by electron microscopy, temperature-programmed reduction, and chemisorption. Spectroscopic methods such as X-ray absorption and UV-vis were also used to evaluate the catalysts, which were used in the reduction of propionic acid to aldehyde and alcohol. Quantum chemical calculations, including ab initio phase diagrams provided molecular insights into the H spillover phenomenon.

09 BIOMASS FUELS↗
DOE OSTI2023

Two excited-state datasets for quantum chemical UV-vis spectra of organic molecules

Abstract We present two open-source datasets that provide time-dependent density-functional tight-binding (TD-DFTB) electronic excitation spectra of organic molecules. These datasets represent predictions of UV-vis absorption spectra performed on optimized geometries of the molecules in their electronic ground state. The GDB-9-Ex dataset contains a subset of 96,766 organic molecules from the original open-source GDB-9 dataset. The ORNL_AISD-Ex dataset consists of 10,502,904 organic molecules that contain between 5 and 71 non-hydrogen atoms. The data reveals the close correlation between the magnitude of the gaps between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and the excitation energy of the lowest singlet excited state energies quantitatively. The chemical variability of the large number of molecules was examined with a topological fingerprint estimation based on extended-connectivity fingerprints (ECFPs) followed by uniform manifold approximation and projection (UMAP) for dimension reduction. Both datasets were generated using the DFTB+ software on the “Andes” cluster of the Oak Ridge Leadership Computing Facility (OLCF).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Ferroelectric phase transition in group-IV monochalcogenides from an equivariant machine learned force field

Group-IV monochalcogenides are a class of layered ferroelectric semiconductors that have demonstrated spontaneous intrinsic polarization above room temperature. Here, in this study, we use the multi-atomic cluster expansion (MACE) machine learning architecture to train and test a force field capable of modeling the structural properties and second-order ferroelectric-to-paraelectric phase transition in a Group-IV monochalcogenide, GeSe. The model captures the double-well potential energy surface associated with the onset of macroscopic polarization in bulk GeSe within 12.5 meV/atom, as well as near-equilibrium properties like the phonon dispersion. The development of this quantitatively accurate force field enables long-time molecular dynamics simulations, which predict the critical temperature of the ferroelectric-to-paraelectric phase transition in bulk GeSe to be T c = 600 K. This study demonstrates the capabilities of equivariant force-fields to accurately describe phenomena associated with structural symmetry breaking.

ferroelectricity↗
DOE OSTI2026

Co-Design of Charge Transport Superhighways to Connect Catalytic Sites in Soft Photoelectrochemical Systems

Efficient photon-to-electron-to-molecule conversion requires multi-length scale control over charge transport pathways, where electronic charges are delivered to catalytic sites under high mass transport flux. A fundamental question is how can we co-design charge transport pathways to promote efficient charge transfer to/from catalytic sites in complex three-dimensional architectures? Soft conducting polymer systems offer exceptional promise to provide three-dimensional charge transport networks, where electrolyte (ion and solvent) can interdiffuse to promote long-lived charge carriers and the molecular nature allows for strategic synthetic design of catalytic sites. Herein we combine theoretical and experimental approaches to investigate the earliest stages of photoelectrochemical deposition of near-surface catalytic sites (Pt) on soft bulk heterojunction polymeric semiconductors composed of a prototype donor (PTB7-Th) and a prototype acceptor (N2200) as a model system towards better understanding molecular catalyst-polymer site interactions. We focus initially on photoelectrochemical deposition of low Pt loadings, nanoparticle sizes (formed by progressive nucleation) below 20 nm, for both density functional theory (DFT) modeling studies and for spectroscopic characterization using surface-sensitive X-ray and UV-photoemission (XPS/UPS). DFT modeling of “n-type” N2200 slabs reveal for the first time that sulfur atoms in the thiophene units serve as the lowest-energy adsorption sites for single Pt atoms, while larger Pt clusters engage more complexly with both thiophene and naphthalene diimide (NDI) core sites. Changes in chemical composition observed by X-ray photoelectron spectroscopy (XPS) support the DFT predictions, and the angle-resolved measurements reveal that Pt nucleation initiates at subsurface sites which appear to be localized active domains that promote charge transport/transfer and enable vertical growth toward the surface. These results suggest that light-activated Pt nanoparticle deposition decorates energetically distinct sites, where photoactivity is dictated by the local energetics of those sites, and the fact that they represent the termini of charge transport “super-highways” – a small percentage of the total volume of the donor/acceptor polymeric active layer which carries most of the photocurrent generated during both Pt deposition and photoelectrochemical HER. We posit that these initial studies provide a foundational strategy for design of catalytic sites in the near surface regions of complex polymeric materials and advancing soft semiconductor-based photoelectrochemical systems. Achieving a nanometer-scale understanding of catalyst deposition and the impact of local composition and energetics on that placement, should ultimately provide the design guidelines (co-design) for a broad array of catalysts at sites that optimize that efficiency and maximize platform durability.

14 SOLAR ENERGY↗
DOE OSTI2024

Anion photoelectron spectroscopy and chemical bonding of ThS 2 – and ThSO –

Anion photoelectron spectra of ThSO – and ThS 2 – were recorded using the third (355 nm) harmonic of an Nd-YAG laser; these provided the measured vertical detachment energies of each anion. The experiments are supported by extensive coupled cluster calculations on ThSO, ThSO – , ThS 2 , and ThS 2 – , as well as the oxygen congeners ThO 2 and ThO 2 – . The ab initio calculations, which included complete basis set extrapolations, spin–orbit effects using four-component coupled cluster, and higher-order correlation contributions through CCSDT(Q), yielded an adiabatic electron affinity for ThO 2 – that was within 0.02 eV of the previously determined experimental value. The singly occupied molecular orbital (SOMO) in all three anions corresponds primarily to the 7s orbital on Th. Successive substitution of S for each O in ThO 2 leads to larger electron affinities and smaller bond angles in the neutral molecules, but larger angles in the anions. As demonstrated by Franck–Condon simulations of the spectra using the CCSD(T) spectroscopic constants, substitution of O by S significantly complicates the resulting detachment spectra due to the lower vibrational frequencies in the sulfur species. Altogether the calculated vertical detachment energies are in very good agreement with the experiment. In addition to the adiabatic electron affinities of each species, atomization energies and heats of formation have also been determined via the FPD approach with expected uncertainties of 1–2 kcal/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Solution and Interface Structure and Dynamics in Geochemistry: Gateway to Link Elementary Processes to Mineral Nucleation and Growth

Our understanding of the process of mineral nucleation is starting to evolve from the solely thermodynamical aspects in classical nucleation theory toward a mechanistic study of reactions influenced by solvation structures of ions and their dynamics. A knowledge of how these atomic and molecular interactions respond to changing solution composition and/or the nature of an interface will form a fundamental foundation to understand rate-limiting reactions and processes for nucleation and growth. Here, we review recent advances from multidisciplinary experimental and computational approaches of the structure and dynamics of aqueous solutions and mineral–liquid interfaces that will influence rates of nucleation (and growth behavior) both homogeneously in aqueous solutions and heterogeneously at mineral–liquid interfaces. Furthermore, these processes include structure (and extent) of solute clustering, solvent degrees of freedom, and the presence of noninnocent charge-balancing ions, all of which can drive the selectivity and exert control over nucleation mechanisms. Similar controlling reactions can also occur at interfaces with the added complexities of how solute ions interact with and assemble on surface sites and use different mechanisms from bulk solutes, such as lateral solvent exchanges between distinct surface sites. To gain a predictive understanding of nucleation chemistry, we emphasize several key knowledge gaps that will need to be addressed in this field and highlight the importance of combining computations and experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Performance of an atomic mean-field spin–orbit approach within exact two-component theory for perturbative treatment of spin–orbit coupling

The paper reports development of an atomic mean-field (AMF) spin–orbit approach within the spin-free exact two-component theory in its one-electron variant (SFX2C-1e), a new relativistic quantum-chemical method for treating spin-orbit coupling in molecules. The effective one-electron spin–orbit integral matrix in the four-component representation is assembled as a direct sum of one-centre spin–orbit integral matrices with the mean-field two-electron contributions evaluated using atomic SFX2C-1e Hartree–Fock density matrices. It is then transformed into two-component representation using analytic SFX2C-1e energy derivative formulation. The resulting two-component spin–orbit integral matrix is by design suitable for use in perturbative calculations of spin–orbit coupling, treating SFX2C-1e wavefunctions as unperturbed states. The accuracy of the present AMF approach has been demonstrated using benchmark calculations of spin–orbit splittings for representative diatomic radicals at the equation-of-motion coupled-cluster singles and doubles level. In conclusion, to demonstrate the applicability and accuracy of the present perturbative spin–orbit scheme in calculations of challenging heavy-element containing systems, a thorough computational investigation of six low-lying electronic states of ThO+ is reported.

74 ATOMIC AND MOLECULAR PHYSICS↗