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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Unimolecular and bimolecular formic acid decomposition routes on dispersed Cu nanoparticles

The elementary steps and site requirements in formic acid (HCOOH) dehydrogenation on Cu surfaces remain of keen interest because formate species act as intermediates or spectators in methanol synthesis and water–gas shift reactions. Steady-state and transient kinetic data, isotopic effects, infrared spectra during catalytic and stoichiometric reactions, and theoretical treatments based on density functional theory (DFT) provide evidence for bimolecular reactions, in which saturated bidentate formate (*HCOO*) adlayers, present at 0.25 ML (0.25 *HCOO* per surface Cu atom), react with undissociated species (HCOOH$^\square$) bound at interstices within formate adlayers ($^\square$) to form H-bonded bimolecular HCOOH$^\square$-*HCOO* adducts. The co-existence of vicinal HCOOH$^\square$ and *HCOO* moieties is evident from antisymmetric infrared bands for *HCOO* that become stronger as a result of their H-bonding that perturbs the induced dipole moment of *HCOO* upon vibration, consistent with DFT-derived vibrational frequencies and intensities for such perturbed species. The *HCOO* moiety in this complex undergoes C-H activation via a transition state that is preferentially stabilized through H-bonding with the vicinal HCOOH$^\square$ relative to its *HCOO* precursor. DFT-derived HCOOH dehydrogenation activation barriers and those determined from the evolution of CO 2 from pre-adsorbed *HCOO* species are about 10 kJ mol -1 smaller in the presence of gaseous HCOOH reactants (because of HCOOH$^\square$-*HCOO* interactions) than those for the unimolecular decomposition of bound *HCOO* species. Such bimolecular routes are consistent with measured effects of HCOOH, H 2 , and CO pressures and of H/D isotopic substitution on dehydrogenation turnover rates and represent the predominant channel for the formation of CO 2 and H 2 during catalytic HCOOH dehydrogenation on Cu nanoparticles. A saturated *HCOO* adlayer that retains binding interstices and the presence of HCOOH(g) enable a sequence of elementary steps unavailable for *HCOO* species, thus circumventing unassisted unimolecular routes that exhibit higher activation barriers.

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

Analysis and prediction of reaction kinetics using the degree of rate control

“Degree of rate control” (DRC) analysis provides a quantitative approach for analysing the kinetics of multi-step reaction mechanisms that has been widely applied to both heterogeneous and homogeneous catalysis research, as well as electrocatalysis. The DRC of any given transition state or intermediate is defined as a partial derivative such that it approximately equals the fractional increase in net rate to the product of interest per differential decrease in its standard-state free energy for that species (÷RT), holding constant the standard-state free energies of all other transition states and intermediates. Even very complex mechanisms usually have only a few species with non-zero DRCs and are thus the species whose interactions with the catalyst most strongly affect the net rate. These key DRC values thus offer a simple and intuitive route to optimize catalyst materials, especially with the assistance of computational methods like density functional theory (DFT). These high-DRC species are also the species whose energetics must be most accurately measured or calculated to achieve an accurate kinetic model for any reaction mechanism. In simple cases with a single “rate-determining step”, the DRC for its transition state (TS) is + 1. Catalyst-bound intermediates, on the other hand, often have negative DRCs equal to a small integer times their fractional occupancy of catalyst sites. The apparent activation energy equals a weighted average of the standard-state enthalpies (relative to reactants) of all the species (intermediates, transition states and products) in the reaction mechanism, each weighted by its DRC (+RT). It has been shown that the apparent transfer coefficient in electrocatalysis, an inverted form of the Tafel slope, is a weighted average of the number of electrons transferred to generate each intermediate or product species in the mechanism, weighted again by the DRC. Quantitative analysis of kinetic isotope effects (KIEs, or the ratio of net rates for different reactant isotopes) in complex mechanisms has shown that the logarithm of the KIE equals the weighted average over all species in the mechanism of the difference between the two isotopes in their standard-state free energies (÷RT), again weighted by the DRC. The reaction orders with respect to fluid-phase concentrations of reactants, products and intermediates have also been proven to be directly related to DRCs. Thus, there are numerous experimental observables which equate to short linear combinations of DRCs, so that combinations of experimental measurements might provide access to DRC values. Since its invention for transition states in 1994 and its generalization to include intermediates in 2009, the DRC has thus far mainly been calculated for microkinetic models based either entirely on DFT or on DFT with the key energies (i.e., those for high-DRC species) being fine-tuned to match experiments. The relationships summarized in this work provide new opportunities for using experiments earlier in the development and optimization of microkinetic models that require input from computational catalysis.

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

Understanding the dynamic evolution of atomically dispersed Cu catalyst for CO 2 electrochemical conversion using integrated XANES analysis and mechanistic studies

Direct electrochemical conversion of CO 2 to ethanol (CH 3 CH 2 OH) offers a promising strategy to lower CO 2 emission while storing energy from renewable electricity. Our recent study reported a carbon-supported atomically dispersed Cu catalyst that achieved the highest reported selectivity for CH 3 CH 2 OH formation (91%) at a relatively low potential (-0.6 V), however, the active site structure that is responsible for such high activity and selectivity has yet to be understood. Here, in this paper, we demonstrate a computational investigation combining X-ray absorption near edge structure (XANES) simulations and a mechanistic study via density functional theory (DFT) to understand the catalyst structures of this Cu catalyst during electrocatalysis and the corresponding reaction mechanisms of the key products. An integrated computational and experimental XANES analysis depicted the dynamic evolution of the catalytic site during electrocatalysis. The as-prepared, atomically dispersed Cu catalyst aggregates and forms metallic clusters/nanoparticles under electrochemical condition, which then break down to smaller oxidized clusters after electrocatalysis. The formed Cu clusters/nanoparticles showed distinct catalytic activity and selectivity as a function of particle size based on the mechanistic investigation using DFT, which is consistent with experimental observations for catalyst samples with different Cu loadings. This comprehensive study which combines experimental and computational XANES investigation, mechanistic study via DFT calculations, and experimental performance of the catalysts, provides unprecedented dynamic and mechanistic insights into the supported atomically dispersed metal catalysts for CO 2 reduction. Such strategy and details gained can further guide discovery of novel catalyst materials for CO 2 electrochemical reduction.

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

Spectroscopic and computational investigations of organometallic complexation of group 12 transition metals by methanobactins from Methylocystis sp. SB2

Methanotrophic bacteria catalyze the aerobic oxidation of methane to methanol using Cu-containing enzymes, thereby exerting a modulating influence on the global methane cycle. To facilitate the acquisition of Cu ions, some methanotrophic bacteria secrete small modified peptides known as “methanobactins,” which strongly bind Cu and function as an extracellular Cu recruitment relay, analogous to siderophores and Fe. In addition to Cu, methanobactins form complexes with other late transition metals, including the Group 12 transition metals Zn, Cd, and Hg, although the interplay among solution-phase configurations, metal interactions, and the spectroscopic signatures of methanobactin-metal complexes remains ambiguous. In this study, the complexation of Zn, Cd, and Hg by methanobactin from Methylocystis sp. strain SB2 was studied using a combination of absorbance, fluorescence, extended x-ray absorption fine structure (EXAFS) spectroscopy, and time-dependent density functional theory (TD-DFT) calculations. We report changes in sample absorbance and fluorescence spectral dynamics, which occur on a wide range of experimental timescales and characterize a clear stoichiometric complexation dependence. Mercury L3-edge EXAFS and TD-DFT calculations suggest a linear model for Hg--S coordination, and TD-DFT suggests a tetrahedral model for Zn 2+ and Cd 2+ . We observed an enhancement in the fluorescence of methanobactin upon interaction with transition metals and propose a mechanism of complexation-hindered isomerization drawing inspiration from the wild-type Green Fluorescent Protein active site. Collectively, our results represent the first combined computational and experimental spectroscopy study of methanobactins and shed new light on molecular interactions and dynamics that characterize complexes of methanobactins with Group 12 transition metals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development and application of a uranium mononitride (UN) potential: Thermomechanical properties and Xe diffusion

We report that atomic-scale modeling of thermophysical and defect properties of uranium mononitride (UN) plays an important role in establishing a better understanding and improved models of UN fuel performance. Having an accurate interatomic potential is crucial for generating reliable data at finite temperatures using molecular dynamic simulations. We report a new interatomic potential for UN, based on a combination of many-body and pairwise interactions, a simple form that we later show could be easily adapted to include Xe-U and Xe-N interactions, i.e., generating a U-N-Xe interatomic potential. The potential was fitted to experimental thermal expansion and single crystal elastic constants, as well as Frenkel, Schottky, anti-Schottky, and antisite pair reaction energies from density functional theory (DFT) calculations. Using the potential, we successfully reproduced experimental lattice parameters, thermal expansion, single crystal elastic constants, and temperature dependent heat capacity. The potential also performs reasonably well in reproducing the energy of the aforementioned stoichiometric defect reactions and defect migration barriers calculated using DFT. However, the potential underestimates the energy difference between the tetrahedral and dumbbell uranium interstitials, and a more complex potential form might be needed to overcome this issue. The potential was also used to predict UN single crystal elastic constants and elastic properties at different temperatures, showing that UN becomes softer and more compressible with increasing temperature. We also compare our potential against literature data from previous empirical potentials, demonstrating similar or better behavior depending on the property of interest. To enable the simulation of Xe in UN a Buckingham potential has been fitted to DFT-derived Xe incorporation energies. The potential was then used to determine the activation energy for Xe diffusion due to various Xe-containing defects, with {XeU : VU} exhibiting the lowest activation energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Engineering defect energy landscape of CoCrFeNi high-entropy alloys by the introduction of additional dopants

The concept of high-entropy alloys (HEAs) focusing on tuning the overall chemical complexity represents a novel alloy design strategy. In contrast, alloying of a metallic matrix with minor doping elements with limited and localized tunability has been a common practice to improve material performance. Combining the idea of globally engineering defect energy landscape in HEAs and the localized doping strategy in dilute alloys, in this work, we explore doping effects of minor elements in a HEA matrix to further enhance the overall and localized chemical tunability, aiming to improve its irradiation resistance. Specifically, we study the influence of minor Al, Cu, Ti, and Pd substitutional doping elements on defect energetics in a CoCrFeNi model HEA based on density-functional theory (DFT) calculations. The DFT results indicate that the formation and migration energies of vacancies can be strongly influenced when a dopant is introduced at the first nearest neighbor shells around a vacancy. On the other hand, interstitial energetics are only slightly affected. Among the four elements, Ti and Pd generally decrease vacancy formation energies and increase vacancy migration energies more significantly than Al and Cu. The doping effects become more pronounced when the concentration of the substitutional dopants increases. Based on the energy distributions obtained from DFT, we build a kinetic Monte Carlo (kMC) model to assess the impact of dopants on vacancy-mediated diffusivity in the doped HEAs. Our results suggest that Ti and Pd can lower the tracer diffusivity in the considered HEAs and act as trapping sites, whereas Cu may enhance the atomic transport. This work indicates that substitutional doping in HEAs is an effective strategy in metallurgy to further tune the defect and transport properties of complex alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Hydrogen motion in near stoichiometric yttrium dihydride at elevated temperatures

The high-temperature motion of hydrogen in near stoichiometric yttrium dihydride (YH x , x = 1.62 and 1.87 at.%) was investigated using incoherent quasi-elastic neutron scattering and Density Functional Theory (DFT) calculations as a function of hydrogen stoichiometry. Translational motion (diffusivity) of hydrogen in yttrium dihydride was only observed in a temperature range of 1073–1173 K under vacuum environment. Here, the hydrogen motion was found to be limited to the tetrahedral sublattice, and diffusivity of hydrogen was observed to increase with decreasing hydrogen stoichiometry. The same behavior was also supported with DFT calculations. The DFT results also indicated that certain migration paths with smaller energy barriers favored H jump resulting in higher diffusivities.

08 HYDROGEN↗
DOE OSTI2024

First-principles investigation of lanthanides diffusion in HCP zirconium via vacancy-mediated transport

The diffusion of lanthanide fission products plays an important role in the growth of the fuel-cladding chemical interaction (FCCI) region in metallic fuels. The use of a Zr interdiffusion barrier may mitigate the transport of lanthanides from the fuel to the cladding, but the efficacy of such a liner is not yet known. In this paper, the stability and vacancy-mediated diffusion of La, Ce, Pr, and Nd in hexagonal close-packed (HCP) Zr is investigated via density functional theory (DFT) calculations and self-consistent mean field (SCMF) analysis. DFT is used to calculate the formation, binding, and migration energies of vacancies and vacancy-solute pairs. The DFT energetics are used in the KineCluE code to calculate the Onsager transport coefficients. La is found to be the fastest diffusing species in HCP Zr and experiences an almost isotropic diffusion behavior. The other three species (Ce, Pr, and Nd) demonstrate anisotropic diffusion where the diffusion in the basal planes is significantly faster than that along the c-axis. Further, the calculated lanthanide diffusivities in HCP Zr are fitted to an Arrhenius relation and the activation energies and prefactors are reported for the first time. Furthermore, the vacancy drag and the segregation tendencies were analyzed using the calculated off-diagonal transport coefficients. According to our vacancy-mediated diffusion model, lanthanides are expected to be enriched at vacancy sinks at low temperatures, while at high temperatures, lanthanides are depleted at sinks and will preferably diffuse into the bulk. The enrichment/depletion transition temperature depends on the diffusion direction (basal or axial) and hence will be controlled by the grain texture and orientation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Density functional theory calculations of the mixing enthalpy of ternary uranium carbide compounds

The high melting point of uranium-zirconium carbides (U,Zr)C makes them an ideal fuel for nuclear thermal propulsion (NTP) reactors. Gaps remain in the current understanding of the U-Zr-C system due to the difficulty of conducting thermodynamic experiments at NTP operation conditions. Density functional theory calculations using the Hubbard U model (DFT+U) were performed using orbital matrix occupation (OMC) to obtain the mixing enthalpy for UC and ZrC for (U,Zr)C ternary compounds. Similarly, DFT+U calculations were also carried out for the (U,Nb)C and (U,Ta)C systems. In conclusion, the DFT results are envisioned to be used in thermodynamic assessments of the uranium carbide systems based on the CALPHAD approach to supplement the lack of experimental data for the mixing thermodynamics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Charge-density based convolutional neural networks for stacking fault energy prediction in concentrated alloys

A descriptor-less machine learning (ML) model based only on charge density images extracted from density functional theory (DFT) is developed to predict stacking fault energies (SFE) in concentrated alloys. The model is based on convolutional neural networks (CNNs) as one of the promising ML techniques for dealing with complex images and data. Identification of correct descriptors is a key bottleneck to develop ML models for predicting materials properties. Often, in most ML models, textbook physical descriptors such as atomic radius, valence charge and electronegativity are used as descriptors which have limitations because these properties change in concentrated alloys when multiple elements are mixed to form a solid solution. Here, we illustrate that, within the scope of DFT, the search for descriptors can be circumvented by electronic charge density, which is the backbone of the Kohn-Sham DFT and describes the system completely. The performance of our model is demonstrated by predicting SFE of concentrated alloys with an RMSE and R 2 of 6.18 mJ/m 2 and 0.87, respectively, validating the accuracy of the proposed approach.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gas-phase ion-molecule interactions in a collision reaction cell with triple quadrupole-inductively coupled plasma mass spectrometry: Investigations with N 2 O as the reaction gas

Nitrous oxide (N 2 O) was used as a reaction gas to investigate the gas phase ion-molecule interactions using the Agilent 8900 QQQ-ICP-MS. A multi-element standard containing 45 elements with masses ranging from 9 to 208 u was measured in the presence and absence of N 2 O. The main product ion species observed were oxides and nitrides. Comparison of the N 2 O reaction results with similar measurements conducted with O 2 revealed that N 2 O was more effective at forming oxides in general: the elements Cd and Pb were shown to produce oxides with N 2 O where the reaction did not occur with O 2 . Nitrous oxide was also shown to produce a significant amount of nitride species in a few cases. The general reactivity was shown to be consistent with density functional theory (DFT)-predicted reaction enthalpies, such that all predicted exothermic reactions produced product ions at levels at least 1% of the unreacted ion. Our results show that reaction enthalpy is a reasonable predictor of reactivity with N2O on the timescales of the interactions in non-thermal ICP-MS/MS systems. Our work demonstrates the utility of two relatively new platforms (commercial elemental ICP-MS/MS and EMSL Arrows interface to the NWChem program suite), which allows for the study of a large number of elements within a short period. While DFT with the basis sets utilized here is not the most accurate computational method, it is also not computationally expensive and is shown to be suitable for predicting gas phase reactivity in the QQQ-ICP-MS for the majority of ions studied. Here, the ease and rapidity of data collection and DFT calculations has the potential to be very impactful for the identification of targeted reaction chemistries to be leveraged for analytical method development, such as for the inline separation of isobaric interferences from analytes of interest.

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

Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design

Conspectus The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and catalysts but also challenges conventional computational modeling tools. Here, tailoring ligand chemistry can alter preferred spin or oxidation states as well as electronic structure properties and reactivity, creating vast regions of chemical space to explore when designing new materials atom by atom. Although first-principles density functional theory (DFT) remains the workhorse of computational chemistry in mechanism deduction and property prediction, it is of limited use here. DFT is both far too computationally costly for widespread exploration of transition-metal chemical space and also prone to inaccuracies that limit its predictive performance for localized d electrons in transition-metal complexes. These challenges starkly contrast with the well-trodden regions of small-organic-molecule chemical space, where the analytical forms of molecular mechanics force fields and semiempirical theories have for decades accelerated the discovery of new molecules, accurate DFT functional performance has been demonstrated, and gold-standard methods from correlated wavefunction theory can predict experimental results to chemical accuracy. The combined promise of transition-metal chemical space exploration and lack of established tools has mandated a distinct approach. In this Account, we outline the path we charted in exploration of transition-metal chemical space starting from the first machine learning (ML) models (i.e., artificial neural network and kernel ridge regression) and representations for the prediction of open-shell transition-metal complex properties. The distinct importance of the immediate coordination environment of the metal center as well as the lack of low-level methods to accurately predict structural properties in this coordination environment first motivated and then benefited from these ML models and representations. Once developed, the recipe for prediction of geometric, spin state, and redox potential properties was straightforwardly extended to a diverse range of other properties, including in catalysis, computational “feasibility”, and the gas separation properties of periodic metal–organic frameworks. Interpretation of selected features most important for model prediction revealed new ways to encapsulate design rules and confirmed that models were robustly mapping essential structure–property relationships. Encountering the special challenge of ensuring that good model performance could generalize to new discovery targets motivated investigation of how to best carry out model uncertainty quantification. Distance-based approaches, whether in model latent space or in carefully engineered feature space, provided intuitive measures of the domain of applicability. With all of these pieces together, ML can be harnessed as an engine to tackle the large-scale exploration of transition-metal chemical space needed to satisfy multiple objectives using efficient global optimization methods. In practical terms, bringing these artificial intelligence tools to bear on the problems of transition-metal chemical space exploration has resulted in ML-model assessments of large, multimillion compound spaces in minutes and validated new design leads in weeks instead of decades.

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

Identifying Order and Disorder in Double Four-Membered Rings via Raman Spectroscopy during Crystallization of LTA Zeolite

Fluoride (F – ) has been essential for the synthesis of low-defect siliceous zeolites. It has been hypothesized that F – balances the positive charges from organic structure-directing agents (OSDAs) and stabilizes key building units during zeolite crystallization such as the double four-membered ring (D4R). However, due to the lack of characterization techniques for investigating medium-range structures, including rings and cages formed during zeolite crystallization, the roles of F – in stabilizing building units and maintaining local charge balance during zeolite assembly are not yet fully understood. Here, the crystallization of siliceous Linde type A (LTA) zeolite in the presence of F – was investigated using Raman spectroscopy and periodic density functional theory (DFT) calculations. We have discovered that the F – -filled double four-membered ring (F – /D4R) and the empty D4R exhibit rather distinct Raman features. Both the F – /D4R and empty D4R are formed in the LTA zeolite synthesized in the presence of F – using 1,2-dimethyl-3-(4-methylbenzyl) imidazolium as the OSDA. Observed Raman bands of the F – /D4R and empty D4R, along with predictive DFT calculations on LTA supercells, reveal an ordered distribution of these two D4R units in the final as-made LTA zeolite. The discovery of these distinct Raman signatures of F – /D4R and empty D4R units opens an interesting new window for studying defects in the D4R during zeolite formation. In particular, we have observed variation in Raman intensities of F – /D4R and empty D4R bands during LTA crystallization; periodic DFT calculations indicate that the observed Raman behavior is consistent with empty D4R units containing one or two Si vacancies surrounded by Q 3 Si—consistent also with solid-state nuclear magnetic resonance measurement. These defects appear to heal during further crystallization, leading to the formation of defect-free LTA zeolite crystals. Altogether, our results provide deeper understanding on the roles of F – in charge balancing and stabilizing intact D4R units during zeolite formation.

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

The Intermetallic Reactivity Database: Compiling Chemical Pressure and Electronic Metrics toward Materials Design and Discovery

Here, the advent of high-throughput Density Functional Theory (DFT) calculations has supported the creation of large databases containing the quantitative output necessary for constructing theoretical phase diagrams and predicting physical properties. In this Article, we present a complementary resource, the Intermetallic Reactivity Database (IRD), focused on the chemical bonding features of solid-state structures and indicators of potential structural transformations. Each IRD entry augments common features, such as band structures and density of states (DOS) distributions, with chemically motivated information including DFT-Chemical Pressure (CP) schemes and visualizable representations of the atomic charges. Together, these data types enable the rationalization and prediction of potential structural phenomena encountered in intermetallic chemistry, as we illustrate with four examples: the origins of the Y 2 Ni 2 Mg structure in terms of CP features of its parent structures, the anticipation of intergrowth phases from the net atomic CPs collected in Al-containing binary phases, the correlation between trends in the CP schemes of CaCu 5 -type phases and experimentally observed structural variations, and finally, the development of theoretical methodology with the testing of a streamlined method generating DFT-CP schemes. Altogether, these examples highlight how the IRD supports the creation of models of structural chemistry that extend beyond the bounds of its entries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Radiation Effects on Uranyl Tetrachloro Coordination Compounds: Impact of Lattice Water

Nuclear materials, such as uranium-bearing solids, are exposed to high levels of ionizing radiation throughout the nuclear fuel cycle; thus, it is important to develop a molecular-level understanding of how these materials behave and degrade in the presence of gamma (γ) irradiation. In the current study, three U(VI) tetrachloride complexes, M 2 [UO 2 Cl 4 ]·xH 2 O (where M = K + , Rb + , or Cs + and x = 0 or 2), and their respective chloride salts were exposed to 1–50 kGy of γ radiation using a 60 Co source. Irradiated materials were evaluated by using electron paramagnetic resonance (EPR) and Raman spectroscopy and were further explored by using density functional theory (DFT) methods. EPR spectra of the irradiated materials suggest the formation of a Cl-based radical for both the alkali salts and the uranyl tetrachloride compounds, and DFT calculations provide evidence that the Cl 2 –• radical is formed within these materials. The presence of water in the K + and Rb + compounds leads to additional spectroscopic signatures that could be traced back to water radiolysis and the formation of peroxide and superoxide species. DFT results support the formation of HO 2 • in the lattice and potentially the formation of a [UO 2 Cl 3 (O 2 )] 3– species, highlighting the impact of water within the hydrated material to alter U(VI) speciation by radiolysis.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spectroscopic and Theoretical Studies of Ruthenium Complexes with a Noninnocent N 2 S 2 Ligand in Different Redox States

Herein we report an electronic structure investigation of neutral and oxidized Ru complexes containing a redox noninnocent N 2 S 2 ligand derived from o-phenylenediamide (L1). UV–vis spectroelectrochemistry (SEC) studies were conducted on the square pyramidal complex [Ru I I(L1)(PPh 3 )] (1) and the six-coordinate complexes [Ru I I(μ-BH 3 )(L1)(PPh 3 )] (2) – which has BH 3 bound in a metal–ligand cooperative (MLC) fashion across Ru and L1 – and [Ru II (L1)(PPh 3 )(MeCN)] (3). The SEC results yielded spectra assigned to singly and doubly oxidized 1 and 3, revealing electronic structure changes as a function of oxidation state and in response to the presence and absence of bound MeCN. By contrast, the SEC results of 2 showed that it rapidly loses MLC-bound BH 3 upon oxidation. The SEC results for 1 and 3 were compared to single-crystal XRD data and UV–vis, EPR, and P K-edge, S K-edge, and Ru L 3 -edge X-ray absorption spectroscopy (XAS) data collected on isolated samples of chemically oxidized 3. The data revealed that the first two oxidations are primarily localized on the ligand, which was supported by DFT and TDDFT calculations. DFT calculations for the doubly oxidized species revealed a singlet ground state with a singlet–triplet gap of 8.9 kcal/mol. CASPT2 calculations corroborated the DFT calculations and further revealed that the singlet ground state is multiconfigurational with 21% radical character. Collectively, the results establish redox formalisms and the underlying electronic structure of Ru complexes containing a noninnocent tetradentate ligand in different oxidation states.

electronic structure↗
DOE OSTI2024

Ligand Many-Body Expansion as a General Approach for Accelerating Transition Metal Complex Discovery

Methods that accelerate the evaluation of molecular properties are essential for chemical discovery. While some degree of ligand additivity has been established for transition metal complexes, it is underutilized in asymmetric complexes, such as the square pyramidal coordination geometries highly relevant to catalysis. To develop predictive methods beyond simple additivity, we apply a many-body expansion to octahedral and square pyramidal complexes and introduce a correction based on adjacent ligands (i.e., the cis interaction model). We first test the cis interaction model on adiabatic spin-splitting energies of octahedral Fe(II) complexes, predicting DFT-calculated values of unseen binary complexes to within an average of 1.4 kcal/mol. Uncertainty analysis reveals the optimal basis, comprising the homoleptic and mer symmetric complexes. We next show that the cis model (i.e., the cis interaction model solved for the optimal basis) infers both DFT- and CCSD(T)-calculated model catalytic reaction energies to within 1 kcal/mol on average. The cis model predicts low-symmetry complexes with reaction energies outside the range of binary complex reaction energies. We observe that trans interactions are unnecessary for most monodentate systems but can be important for some combinations of ligands, such as complexes containing a mixture of bidentate and monodentate ligands. Lastly, we demonstrate that the cis model may be combined with Δ-learning to predict CCSD(T) reaction energies from exhaustively calculated DFT reaction energies and the same fraction of CCSD(T) reaction energies needed for the cis model, achieving around 30% of the error from using the CCSD(T) reaction energies in the cis model alone.

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

Screened Range-Separated Hybrid Functional with Polarizable Continuum Model Overcomes Challenges in Describing Triplet Excitations in the Condensed Phase Using TDDFT

Long range-corrected (LRC) or range-separated hybrid (RSH) functionals where the long-range (LR) limit of electronic interactions is set to the exact exchange have been shown to correct the tendency of traditional density functional theory (DFT) to underestimate the frontier orbital gap. Consequently, the use of such functionals in calculating electronic excited states using linear response based time-dependent DFT (TDDFT) has been successful in correcting the tendency for underestimating the energies of charge transfer states by DFT-based calculations. More recently formulations of functionals that attenuate the LR limit to address condensed-phase effects to polarize the electronic density have been reported. In particular screened RSH (SRSH) combined with polarizable continuum model (PCM) was benchmarked successfully in reproducing the fundamental gap and charge transfer state energies of molecular systems in the condensed phase. Here we use SRSH-PCM to address triplet excited states, and show its success in obtaining correspondence of the low-lying triplet states to the singlet–triplet gap in a similar way that the fundamental orbital gap corresponds to electron removal and addition energies. Importantly, the accuracy of the SRSH-PCM in calculating triplet excitations stands on the polarization consistent framework in addressing the scalar dielectric constant and without affecting the optimal tuning by triplet energies. Finally, the prospect of even further improving the SRSH-PCM accuracy in calculating triplet states can be achieved by optimal tuning on the basis of the spin multiplicity gap.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗