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DOE OSTI2026

Experimental evaluation of the vapor box divertor concept with an open vapor box module in Magnum-PSI

A promising approach to handle the intense plasma heat flux in the divertor region of a tokamak is the Vapor Box Divertor (VBD). Here plasma-lithium interaction creates a dense lithium vapor cloud which interacts with the incoming plasma, effectively shielding the tungsten surface beneath, therefore preventing overheating and sputtering of the tungsten and increasing the component’s lifetime. Two key steps must be addressed to validate this concept: investigating plasma-Li interactions and the transport mechanism of the latter in the presence of plasma. To explore this, a Vapor Box Module (VBM) has been designed for use with the linear plasma generator Magnum-PSI. The VBM consists of a series of three cylindrical boxes, with Li being evaporated at a controlled temperature in the central box (CB). Divertor-like plasma enters the VBM from an upstream aperture, interacts with the Li vapor cloud and exits through a downstream aperture ultimately impacting a target equipped with a calorimetry system. Optical diagnostics Thomson scattering, Filtered fast camera Imaging and optical emission spectroscopy provided information on plasma parameters in terms of electron density n e , temperature T e and plasma composition before and after this interaction. A significant reduction in plasma power was observed upon the establishment of lithium vaporization determined via cooling water calorimetry and embedded thermocouples at the downstream target. This resulted in a drop of the target temperature from ∼800 °C to ∼350 °C (57%) at the highest applied power (11.1 MW m −2 ) and CB temperature (∼700 °C). Lithium condensation at the side boxes of the VBM in combination with strong plasma momentum transfer effectively prevented upstream migration of lithium, while enhancing Li transport toward the target. The achievement of the two main goals of reducing plasma power and confining the Li in the VBM, are consistent with earlier published preliminary SOLPS-ITER simulations. This study shows that the presence of lithium in a VBD-like configuration can result in a strong reduction of power to the target surface, while at the same time the lithium vapor is effectively confined by the VBM, aided by the incoming plasma, preventing its escape from the VBM geometry. This represents a valuable step toward validating the feasibility of the VBD configuration in future fusion reactors.

Magnum-PSI↗

DOE OSTI2023

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

DOE OSTI2021

Physical Background, Computations and Practical Issues of the Magnetohydrodynamic Pressure Drop in a Fusion Liquid Metal Blanket

In blankets of a fusion power reactor, liquid metal (LM) breeders, such as pure lithium or lead-lithium alloy, circulate in complex shape blanket conduits for power conversion and tritium breeding in the presence of a strong plasma-confining magnetic field. The interaction of the magnetic field with induced electric currents in the breeder results in various magnetohydrodynamic (MHD) effects on the flow. Of them, high MHD pressure losses in the LM breeder flows is one of the most important feasibility issues. To design new feasible LM breeding blankets or to improve the existing blanket concepts and designs, one needs to identify and characterize sources of high MHD pressure drop, to understand the underlying physics of MHD flows and to eventually define ways of mitigating high MHD pressure drop in the entire blanket and its sub-components. This article is a comprehensive review of earlier and recent studies of MHD pressure drop in LM blankets with a special focus on: (1) physics of LM MHD flows in typical blanket configurations, (2) development and testing of computational tools for LM MHD flows, (3) practical aspects associated with pumping of a conducting liquid breeder through a strong magnetic field, and (4) approaches to mitigation of the MHD pressure drop in a LM blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

A Simple and Flexible Infusion Platform for Automated Native Mass Spectrometry Analysis

High throughput native mass spectrometry analysis of proteins and protein complexes has been enabled by recent development of infusion and liquid chromatography (LC) systems, which often include complete LC pumps without fully utilizing their gradient flows. We demonstrated a lower-cost infusion cart for native mass spectrometry applications using a single isocratic solvent pump that can operate at both nano- and high-flow configurations (0.05-150 $μ$L/min) for both infusion and online buffer exchange experiments. In conclusion, the platform is controlled via open-source software and can potentially be expanded for customized experimental designs, offering a lower cost alternative to laboratories with limited budgets and/or needs in student training.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

DOE OSTI2026

A two-stage optical fusion framework for wildfire severity mapping across the conterminous United States

Accurate wildfire severity mapping (WSM) is essential for post-fire recovery planning, erosion risk assessment, ecosystem monitoring, and disaster risk reduction. Although Landsat and Sentinel optical imagery have been widely used for burn severity assessment, the added value of fusing multiple optical sensors has not been sufficiently quantified across diverse fire events, particularly since the launch of Landsat-9. This study evaluates whether multisensor optical fusion improves wildfire severity mapping relative to single-sensor baselines using Sentinel-2, Landsat-8, and Landsat-9 imagery across 40 wildfire events in the conterminous United States. We tested a two-stage fusion framework that combines feature-level fusion with pixel-level dimensionality reduction. First, feature-level fused datasets were created through early fusion by combining standardized post-fire bands from each sensor into a single predictor stack. Both raw reflectance bands and pairwise spectral transforms were retained to capture within- and cross-sensor spectral interactions. Second, Linear Discriminant Analysis was applied to both single-sensor and fused datasets to produce comparable low-dimensional feature spaces. Six machine-learning classifiers were then used to benchmark model performance with repeated spatially buffered train–test splits. Results show that Landsat-9 was the strongest single-sensor baseline. Among the fusion strategies, Sentinel-2 + Landsat-9 produced the most consistent improvement and reduced performance variability. Landscape-condition analysis further showed that this fusion was most beneficial in shrubland-dominated and high-terrain fires, where it achieved the highest overall mean accuracy and the fewest failures. In contrast, its benefits were less reliable in evergreen forests, mixed vegetation, and low- to moderate-elevation terrain. In operational settings, the Sentinel-2 + Landsat-9 configuration offers a practical solution for post-fire recovery planning, erosion-risk assessment, watershed management, and ecological monitoring when field observations are available and timely satellite-based information is needed.

Landsat↗

DOE OSTI2022

Three-dimensional inhomogeneity of electron-temperature-gradient turbulence in the edge of tokamak plasmas

Nonlinear multiscale gyrokinetic simulations of a Joint European Torus edge pedestal are used to show that electron-temperature-gradient (ETG) turbulence has a rich three-dimensional structure, varying strongly according to the local magnetic-field configuration. In the plane normal to the magnetic field, the steep pedestal electron temperature gradient gives rise to anisotropic turbulence with a radial (normal) wavelength much shorter than in the binormal direction. In the parallel direction, the location and parallel extent of the turbulence are determined by the variation in the magnetic drifts and finite-Larmor-radius (FLR) effects. The magnetic drift and FLR topographies have a perpendicular-wavelength dependence, which permits turbulence intensity maxima near the flux-surface top and bottom at longer binormal scales, but constrains turbulence to the outboard midplane at shorter electron-gyroradius binormal scales. Here our simulations show that long-wavelength ETG turbulence does not transport heat efficiently, and significantly decreases overall ETG transport—in our case by ~40%—through multiscale interactions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Impacts of Experimentally Obtained Harmonic Spectrums of Residential Appliances on Distribution Feeder: Preprint

This paper focuses on the harmonic load flow study for a set of residential loads and the impacts of the harmonic contents on the distribution feeder. Owing to the increased use of the power electronic based appliances and energy efficient home equipment like the lighting loads, the percentage of non-linear loads has increased in the distribution system which can impact the system performance, loss, and stability. Thus a comprehensive knowledge of their power quality and harmonic analysis is essential to improve the load models, voltage stability assessment, determining possible interactions at harmonic frequencies, protection planning, and the effect of the system impedance. For this study, the household appliances include the lighting, power electronics, resistive, and motor loads with a nominal supply voltage of 120 V single-phase or 240 V split-phase at a nominal frequency of 60 Hz. The harmonic spectrum as obtained from the experimental data is used to solve the harmonic load flow for a detailed secondary network including the distribution transformer extracted from a real distribution feeder's model. Additionally, the impact of the voltage harmonic on a three phase test load is presented through experimental results. The harmonic data of the transformer terminal voltage as obtained from the former load flow study is scaled to generate the source voltage for the three phase configuration of the grid simulator to make the test setup very similar to a real scenario.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

High-Spin and Reactive Fe 13 Cluster with Exposed Metal Sites

We report atomically defined large metal clusters have applications in new reaction development and preparation of materials with tailored properties. Expanding the synthetic toolbox for reactive high nuclearity metal complexes, we report a new class of Fe clusters, Tp* 4 W 4 Fe 13 S 12 , displaying a Fe 13 core with M-M bonds that has precedent only in main group and late metal chemistry. M 13 clusters with closed shell electron configurations can show significant stability and have been classified as superatoms. In contrast, Tp* 4 W 4 Fe 13 S 12 displays a large spin ground state of S=13. This compound performs small molecule activations involving the transfer of up to 12 electrons resulting in significant cluster rearrangements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Giant Nonreciprocity and Gyration through Modulation-Induced Hatano-Nelson Coupling in Integrated Photonics

Asymmetric energy exchange interactions, also known as Hatano-Nelson type couplings, enable the study of non-Hermitian physics and associated phenomena like the non-Hermitian skin effect and exceptional points (EPs). Since these interactions are by definition nonreciprocal, there have been very few options for implementations in integrated photonics. Here, in this work, we show that asymmetric couplings are readily achievable in integrated photonic systems through time-domain dynamic modulation. We experimentally study this concept using a two-resonator photonic molecule produced in a lithium niobate on insulator platform that is electro-optically modulated by rf stimuli. We demonstrate the dynamic tuning of the Hatano-Nelson coupling between the resonators, surpassing the asymmetry that has been achieved in previous work, to reach an EP for the first time. We are additionally able to flip the relative sign of the couplings for opposite directions by going past the EP. Using this capability, we show that the through-chain transport can be configured to exhibit both giant (~60 dB) optical contrast as well as photonic gyration or nonreciprocal π phase contrast.

42 ENGINEERING↗

DOE OSTI2026

The presence of Ru metal modifies the behavior of deuterium bound to pyridinic nitrogen in doped graphene-like materials

We used a combination of x-ray photoelectron spectroscopy (XPS) and density functional theory (DFT) to investigate how the presence of a ruthenium (Ru) metal substrate modifies the N-D bond strength of the pyridinic nitrogen species in nitrogen (N)-doped graphene (Gr) on Ru(0001) compared to metal-free highly-oriented pyrolytic graphite (HOPG) substrate. The N-dopants were introduced through low-energy N+/N2+ irradiation. N is embedded in the carbon materials in two predominant configurations: as graphitic N (GN: N substituted in the hexagonal C lattice) and pyridinic N (PN: substitutional N adjacent to a C vacancy). XPS data showed that upon atomic deuterium (D) exposure at 220 K, the PN peak shifted to a higher binding energy by +1.2 eV for HOPG and +1.0 eV for N-doped graphene on Ru(0001), while the GN peak remained unchanged, indicating that the D atoms bound solely to pyridinic N. 85% of PN sites on HOPG can be saturated with D atoms, whereas only ~30% of pyridinic N sites are able to bind D atoms in N-doped Gr/Ru(0001). Our DFT analysis shows that this difference is due to the coordination of PN to Ru atoms, which necessitates bond cleavage of the N-Ru interaction prior to D atom adsorption. D begins desorbing from N-HOPG at ~573 K and is fully desorbed by ~973 K, whereas desorption from N-doped graphene on Ru(0001) begins at ~290 K, with complete desorption observed at ~700 K, indicating that the Ru metal weakens the N-D bond strength. We also studied a high-surface-area, layered, and porous N-doped carbon material, internally labeled NC900, which was synthesized by pyrolysis of glucose and graphitic carbon nitride (g-C3N4) at 1173 K. D exposure caused a +1.1 eV PN peak shift in NC900, with no change in the GN peak. Moreover, the NC900 exhibited the same desorption behavior as HOPG, demonstrating that well-defined model systems can effectively capture the behavior of more complex N-doped carbon materials.

Alupothe Gedara, Buddhika S.↗

DOE OSTI2026

Hydration structure and energetics of iron-exchanged montmorillonite

The interaction between iron released from corroded steel canisters and bentonite is a key process influencing the long-term performance of nuclear waste repositories. In particular, the migration of Fe²⁺ into montmorillonite (Mnt) interlayers may alter its hydration, swelling, and ion-transport properties. In the present study, molecular dynamics simulations were performed to investigate the hydration behavior, structural response, and transport properties of Fe-exchanged montmorillonite (Fe-Mnt) under varying hydration states. The simulations focus on short- to intermediate-time-scale Fe 2+ and Fe 3+ interlayer exchange and hydration effects, and do not consider long-term structural substitution, Fe-bearing clay phase stabilization, or secondary iron mineral precipitation. Systems containing Na + -, Fe 2+ -, and Fe 3+ -Mnt were examined using both periodic and edge-exposed configurations to evaluate interlayer structure, ion exchange, and free energy of Fe intercalation. The results show that Fe ions influence the interlayer spacing primarily at low water contents (<1 bilayer), where Fe-Mnt exhibits a d-spacing 1–2 Å larger than Na-Mnt due to stronger hydration. The calculated hydration energies follow the order Fe 2+ $<$Fe 3+ $<$Na + . Both water and ion diffusion coefficients decrease upon Fe ion intercalation, with Fe 2+ ions diffusing an order of magnitude more slowly than those of Na + . Free energy profiles further confirm that Fe 2+ and Fe 3+ ions are thermodynamically favored in the interlayer, with Fe 3+ being the most stable. In conclusion, these findings provide molecular-scale insights into the mechanisms of Fe–Na exchange and their implications for bentonite alteration in repository environments.

clay↗

DOE OSTI2026

Prediction and Experimental Verification of Electrolyte Solvation Structure from an OMol25-Trained Interatomic Potential

A molecular-level understanding of electrolyte solvation structure and ion–ion correlations is critical to developing next-generation battery chemistries. Atomistic simulation capabilities with sufficient accuracy, speed, and transferability to deliver reliable structural insights while avoiding arduous system-specific reparameterization are thus highly desirable. Machine learning interatomic potentials (MLIPs) trained on large, chemically diverse data sets are revolutionizing computational chemistry, enabling molecular dynamics simulations of battery electrolytes with near-DFT accuracy over 10,000× faster than DFT. While previous MLIP training data sets with suitable elemental coverage for electrolytes have been based on inorganic materials, the Open Molecules 2025 (OMol25) data set provides large-scale molecular DFT MLIP training data with broad elemental coverage and specifically samples tens of millions of electrolyte configurations. Here, we integrate computational modeling with experimental validation to systematically assess the ability of large-scale MLIPs pretrained on materials data or on OMol25 to accurately resolve nanoscale structural organization and ion-solvation characteristics in Na-ion battery electrolytes across diverse physicochemical conditions and compositional regimes. We find that the OMol25-trained Universal Model of Atoms (UMA-OMol) predicts experimentally measured densities and X-ray structure factors in substantially better agreement compared to state-of-the-art models trained only on inorganic materials data. Using UMA-OMol, we further analyze systematic trends in solvation structure as a function of cation identity, anion chemistry, salt concentration, and solvent topology. We observe that increasing system temperature amplifies the heterogeneity within the solvation environment, perturbing cation–solvent interactions and promoting the formation of contact ion pairs (CIPs). Moreover, subtle variations in the solvent topology of glyme-based electrolytes cause pronounced changes in ion correlations and solvation structure. The experimental agreement and microscopic insights shown here position OMol25-trained MLIPs as a practical route to predictive, high-throughput electrolyte simulations beyond the limits of classical force fields and direct DFT molecular dynamics, serving as a powerful tool for accelerating the design of next-generation Na-ion battery electrolytes and beyond.

MLIPs↗

DOE OSTI2024

Impacts of Topography-Based Subgrid Scheme and Downscaling of Atmospheric Forcing on Modeling Land Surface Processes in the Conterminous US

The effects of small-scale topography-induced land surface heterogeneity are not well represented in current Earth System Models (ESMs). In this study, a new topography-based subgrid structure referred to as topographic units (TGU) designed to better capture subgrid topographic effects, and methods to downscale atmospheric forcing to the land TGUs have been implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM). Effects of the subgrid scheme and downscaling methods on ELM simulated land surface processes are evaluated over the conterminous United States (CONUS). For this purpose, ELM simulations are performed using two configurations without (NoD ELM) and with (D ELM) downscaling, both using TGUs derived for the 0.5-degree grids and the same land surface parameters. Simulations using the two ELM configurations are compared over the CONUS domain, regional levels, and at observational sites (e.g., SNOTEL). The CONUS-level results suggest that D ELM simulates more snowfall and snow water equivalent (SWE), higher runoff, and less ET during spring and summer. Regional-level results suggest more pronounced impacts of downscaling over regions dominated by higher elevation TGUs and regions with maximum precipitation occurring during cool seasons. Results at the SNOTEL sites suggest that D ELM has superior capability of reproducing the observed SWE at 83% of the sites, with more pronounced performance over topographically heterogeneous TGUs with their maximum precipitation occurring during cool seasons. The results highlight the importance of improving representation of small-scale surface heterogeneity in ESMs and motivate future research to understand their effects on land-atmosphere interactions, streamflow, and water resources management over mountainous regions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Random singlet-like state in the dimer-based triangular antiferromagnet Ba 6 Y 2 Rh 2 Ti 2 O 17 − δ

We present the magnetic, thermodynamic, and muon spin relaxation ( μ SR ) results of the dimer-based triangular antiferromagnet Ba 6 Y 2 Rh 2 Ti 2 O 17 − δ . The magnetic susceptibility data show the sub-Curie-Weiss behavior χ ( T ) ∝ T − α χ below 100 K, suggesting random magnetism. The isothermal magnetization results reveal the presence of weakly interacting structural orphan spins about 6.1 % at 2 K, arising from the oxygen deficiency. The comprehensive μ SR experiments exhibit the coexisting relaxing and nonrelaxing components along with the thermally activated behavior in the muon spin relaxation rate, reflecting the fluctuating orphan spins in the dimer singlet background. In addition, we observe the scaling behavior of M ( H , T ) in H / T and P z ( t ) in t / H LF with the scaling exponents α χ = α M = 0.75 and α μ = 0.72 , respectively, but not for the magnetic specific heat data. The failure of the scaling relation in C m ( H , T ) / T implies low-energy excitations dressed by the conventional orphan spins. Based on these observations, we find that the magnetic ground state resembles random singlets and discuss the possible configurations of the spin dimer unit Rh 2 O 9 . Our results shed light on the role of quenched disorder in the dimer-based frustrated magnets. Published by the American Physical Society 2024

Lee, Wonjun (ORCID:000000034848852X)↗

DOE OSTI2025

Energy-relaxation pathways in finite-sized artificial square-ice structures

The energy-relaxation pathway in artificial spin ice structures refers to the series of individual moment reorientations the system undergoes as it relaxes from an initial state to a final low-energy state. The probability of the artificial spin ice structure reaching a ground state depends on the energy of the intermediate states as approximated by an Arrhenius-type relation. In this work, we report that by modifying the geometry of artificial square-ice structures, we can influence the probability of observing the ground state in different configurations. Furthermore, our findings are supported by dipolar energy calculations for various energy-relaxation pathways and the corresponding experimental data obtained by magnetic force microscopy.

Analog computation↗

DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Interaction of Th with H 0/–/+ : Combined Experimental and Theoretical Thermodynamic Properties

In this work, high-level electronic structure calculations of the lowlying energy electronic states for ThH, ThH – , and ThH + are reported and compared to experimental measurements. The inclusion of spin–orbit coupling is critical to predict the ground-state ordering as inclusion of spin–orbit switches the coupled-cluster CCSD(T) ordering of the two lowest energy states for ThH and ThH + . At the multireference spin–orbit SO-CASPT2 level, the ground states of ThH, ThH – , and ThH + are predicted to be the 2 Δ 3/2 , 3 Φ 2 , and 3 Δ 1 states, respectively. The adiabatic electron affinity is calculated to be 0.820 eV, and the vertical detachment energy is calculated to be 0.832 eV in comparison to an experimental value of 0.87 ± 0.02 eV. The observed ThH – photoelectron spectrum has many transitions, which approximately correlate with excitations of Th + and/or Th. The adiabatic ionization energy of ThH including spin–orbit corrections is calculated to be 6.181 eV. The natural bond orbital results are consistent with a significant contribution of the Th + H – ionic configuration to the bonding in ThH. The bond dissociation energies for ThH, ThH – , and ThH + using the Feller–Peterson–Dixon approach were calculated to be similar for all three molecules and lie between 259 and 280 kJ/mol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗