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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding and modeling current and future coastal wetland methane dynamics (Final Report)

The coastal terrestrial-aquatic interface (TAI) is a highly dynamic component of the Earth system that plays a critical role in biogeochemical cycling. Due to its dynamic nature, the processes that regulate decomposition and methane (CH 4 ) emissions are of greater significance at the TAI than in upland systems. Despite this, we have limited mechanistic understanding of how climate stressors interact to regulate the electron acceptors and donors that determine decomposition pathways within TAIs, including the generation of hot spots and hot moments. Accurately modeling these processes is critical for incorporating the coastal TAI into Earth systems models, such as DOE’s E3SM. With previous DOE support, we adapted an aerobic terrestrial representation of decomposition using PFLOTRAN, a reactive flow and transport model, and added anerobic decomposition pathways, salinity, and oxygen (O 2 ) that fluctuates independently of water table level. However, because this model (PFLOTRAN TAI ) is based on decomposition rates and organic matter carbon to nitrogen ratios from terrestrial systems, its performance in TAI systems is currently limited by the lack of empirical data to properly parameterize variables. In addition, while PFLOTRAN TAI can simulate movement of O 2 into sediments, it is not currently capable of tracking the movement of CH 4 gas through plant tissues due to both current model structure and lack of available data. Our overall objective of the project was the increase our mechanistic understanding of CH 4 dynamics in response to environmental change, such that we can improve the representation of these dynamics in PFLOTRAN. We installed automated flux chambers in a new field-scale active soil warming experiment and set up marsh organs (mesocosms) to test effects of warming, flooding, and salinity. This resulted in a new dataset consisting of chamber-level CH 4 flux measurements across multiple sites, ecological conditions, and timeframes, as well as corresponding measurements on porewater chemistry, soil carbon quality, plant biomass, and redox reaction rates. Using these data, we improved PFLOTRAN TAI to more accurately model CH 4 dynamics and successfully tested our hypotheses. This grant contributed to the professional development of 3 postdocs, 4 undergraduate interns, 4 teacher interns, 17 technicians, and 15 participatory scientists. The automated chamber technology designed for this grant has also been shared with multiple new projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Mathematical Modeling of the Potential and Time Dependence of Ir Dissolution from Hydrous Ir Oxide Oxygen Evolution Catalysts

One of the main degradation mechanisms of hydrous iridium oxide acidic oxygen evolution reaction (OER) catalysts is dissolution and loss into the acidic membrane. While degradation models have been proposed, there is a gap in understanding the potential and time dependence of the iridium dissolution reaction and its mechanistic underpinnings. In this work, Ir dissolution rates measured as a function of time and potential via time-resolved inductively-coupled plasma mass spectrometry (ICP-MS) in aqueous acidic electrolyte are used to establish a mathematical model for Ir dissolution. The mathematical model is generated using proposed formation and dissolution reactions for Ir species. Through comparison with the ICP-MS data and existing information on the potential-dependent Ir phase, we find that the potential and time-dependence of dissolution can be modeled as dissolution of an oxide phase, here represented as IrO 2 , with potential dependent kinetics and formation of a passivating species, a process with a rate-limiting step that is not potential dependent. This understanding of the potential dependence of dissolution and passivation kinetics using aqueous electrolyte half-cell measurements can be used to predict the degradation of Ir oxide in operating energy conversion devices relying on the OER, such as proton-exchange membrane water electrolyzers.

Kariuki, Nancy N. [Argonne National Laboratory (AN↗
NASA NTRS2024

Influence of More Mechanistic Representation of Particle Dry Deposition on 1850–2000 Changes in Global Aerosol Burdens and Radiative Forcing

Robust estimates of historical changes in aerosols are key for accurate constraints on climate sensitivity. Dry deposition is a primary sink of aerosols from the atmosphere. However, most global climate models do not accurately represent observed strong dependencies of dry deposition following turbulent transport on aerosol size. It is unclear whether there is a substantial impact of mischaracterized aerosol deposition velocities on historical aerosol changes. Here we describe improved mechanistic representation of aerosol dry deposition in the NASA Goddard Institute for Space Studies (GISS) global climate model, ModelE, and illustrate the impact on 1850–2000 changes in global aerosol burdens as well as aerosol direct and cloud albedo effects using a set of 1850 and 2000 time slice simulations. We employ two aerosol configurations of ModelE (a “bulk” mass-based configuration and a configuration that more explicitly represents aerosol size distributions, internal mixing, and microphysics) to explore how model structural differences in aerosol representation alter the response to representation of dry deposition. Both configurations show larger historical increases in the global burdens of non-dust aerosols with the new dry deposition scheme, by 11% in the simpler mass-based configuration and 23% in the more complex microphysical configuration. Historical radiative forcing responses, which vary in magnitude from 5% to 12% as well as sign, depend on the aerosol configuration.

aerosol↗
DOE OSTI2024

Anthropogenic extremely low volatility organics (ELVOCs) Govern the Growth of Molecular Clusters over the Southern Great Plains during the Springtime

New particle formation (NPF) and growth govern cloud condensation nuclei (CCN) concentrations in many regions. The mechanisms governing the nucleation of molecular clusters vary substantially in different regions of the atmosphere. Additionally, the growth of these clusters from ~2 to 20 nm sizes is often governed by the availability of extremely low volatility organic vapours (ELVOCs). While the pathways to ELVOC formation from the oxidation of biogenic monoterpenes with ozone is better understood, the chemical and mechanistic pathways for ELVOC formation from oxidation of anthropogenic organics are not well understood. We integrate measurements and three-dimensional regional model simulations with the Weather Research and Forecasting Model coupled to chemistry (WRF-Chem) to understand the processes governing new particle formation and growth and secondary organic aerosol (SOA) formation during the Holistic Interactions of Shallow Clouds, Aerosols and Land Ecosystems (HI-SCALE) field campaign at the Southern Great Plains (SGP) observatory in Oklahoma, and contrast it with a site within the Bankhead National Forest (BNF), Alabama in Southeast USA, where 5-year long measurements will begin in 2024. Simulations show that nucleation rates are at least an order of magnitude higher at SGP compared to BNF during the springtime days (April 28 and May 14, 2016), largely due to lower H2SO4 concentrations at BNF, which are needed for nucleation. In addition, the larger CS at BNF (compared to SGP) increase the loss of molecular clusters by coagulation to pre-existing particles. Among the 8 different nucleation mechanisms in WRF-Chem, we find that the amine+H2SO4 nucleation mechanism dominates at the SGP site, while the pure organic ion induced nucleation mechanism dominates over BNF. Through various WRF-Chem sensitivity simulations, we find that anthropogenic ELVOCs are critical for explaining the growth of newly formed particles and the resulting number size distribution observed near the surface at the SGP site during the daytime. In addition, we show that treating organic particles as semisolid, with strong diffusion-limited uptake of organic vapours, brings model predictions into closer agreement with the observed evolution of particle size distribution. Simulations also predict that anthropogenic SOA, formed by the oxidation of aromatic volatile organic compounds (VOCs), is the dominant organic aerosol component at SGP, while biogenic SOA dominates particle composition at the BNF site in Southeast USA on these days.

Shrivastava, ManishKumar B.↗
DOE OSTI2025

Mechanistic Insights into Visible-Light-Induced ATRA Reactions Powered by the Symbiotic Relationship between Cu(II)/Cu(I) Phenanthroline Complexes

As photoredox catalysis continues to yield promising chemical transformations, there is an increased need to understand how specific photocatalysts function to improve reaction efficiencies while expanding their scope. Copper-phenanthroline-based photocatalysts such as Cu II (dap)Cl 2 (dap = 2,9-di(p-anisyl)-1,10-phenanthroline) and [Cu I (dap) 2 ]Cl were both found to be equally capable of olefin activation through electrophilic atom transfer radical addition (ATRA) reactions. Although these molecular catalysts have proven successful, many intermediates suggested in the proposed catalytic cycles have never been detected. One undetermined aspect in this chemistry is related to how one equivalent of Cu II (dap)Cl 2 generates half of an equivalent of [Cu I (dap) 2 ] + during the photocatalytic sequence. To this end, we initially used more synthetically accessible model systems, namely, [Cu I (dpp) 2 ]Cl and Cu II (dpp)Cl 2 (dpp = 2,9-diphenyl-1,10-phenanthroline), to glean detailed mechanistic insights into this unusual symbiotic relationship. We directly detected several intermediates involved in the ATRA photocatalytic cycle using these model chromophores in conjunction with electronic spectroscopy, infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry, electronic structure calculations, EPR spin-trap experiments, and 1 H NMR spectroscopy. We found that the unique ligand lability and coordinating properties of acetonitrile enable both the in situ oxidation of [Cu I (dpp) 2 ] + by tosyl chloride into Cu II (dpp)Cl 2 and the visible-light-induced homolysis of the Cu II –Cl bond, which initiates the conversion to the Cu I species [Cu I (dpp) 2 ][Cu I Cl 2 ]. Here, the combined findings from the present study of the catalytic cycle demonstrate that the symbiotic relationship between Cu II (dpp)Cl 2 and [Cu I (dpp) 2 ] + , as well as between Cu II (dap)Cl 2 and [Cu I (dap) 2 ] + , is the critical factor enabling the ATRA photoreaction by departing from either photocatalyst.

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

Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics

Data-driven constitutive modeling with neural networks has received increased interest in recent years due to its ability to easily incorporate physical and mechanistic constraints and to overcome the challenging and time-consuming task of formulating phenomenological constitutive laws that can accurately capture the observed material response. However, even though neural network-based constitutive laws have been shown to generalize proficiently, the generated representations are not easily interpretable due to their high number of trainable parameters. Sparse regression approaches exist that allow for obtaining interpretable expressions, but the user is tasked with creating a library of model forms which by construction limits their expressiveness to the functional forms provided in the libraries. Here, in this work, we propose to train regularized physics-augmented neural network-based constitutive models utilizing a smoothed version of $L^0$-regularization. This aims to maintain the trustworthiness inherited by the physical constraints, but also enables interpretability which has not been possible thus far on any type of machine learning-based constitutive model where model forms were not assumed a priori but were actually discovered. During the training process, the network simultaneously fits the training data and penalizes the number of active parameters, while also ensuring constitutive constraints such as thermodynamic consistency. We show that the method can reliably obtain interpretable and trustworthy constitutive models for compressible and incompressible hyperelasticity, yield functions, and hardening models for elastoplasticity, using synthetic and experimental data. This work aims to set a new paradigm for interpretable machine learning models in the broad area of solid mechanics where low and limited data is available along with prior knowledge of physical constraints that the learned maps need to obey. This paradigm can potentially be extended to a broader spectrum of scientific exploration.

Data-driven constitutive models↗
NASA NTRS2010

Microstructure Modeling of Third Generation Disk Alloys

The objective of this program was to model, validate, and predict the precipitation microstructure evolution, using PrecipiCalc (QuesTek Innovations LLC) software, for 3rd generation Ni-based gas turbine disc superalloys during processing and service, with a set of logical and consistent experiments and characterizations. Furthermore, within this program, the originally research-oriented microstructure simulation tool was to be further improved and implemented to be a useful and user-friendly engineering tool. In this report, the key accomplishments achieved during the third year (2009) of the program are summarized. The activities of this year included: Further development of multistep precipitation simulation framework for gamma prime microstructure evolution during heat treatment; Calibration and validation of gamma prime microstructure modeling with supersolvus heat treated LSHR; Modeling of the microstructure evolution of the minor phases, particularly carbides, during isothermal aging, representing the long term microstructure stability during thermal exposure; and the implementation of software tools. During the research and development efforts to extend the precipitation microstructure modeling and prediction capability in this 3-year program, we identified a hurdle, related to slow gamma prime coarsening rate, with no satisfactory scientific explanation currently available. It is desirable to raise this issue to the Ni-based superalloys research community, with hope that in future there will be a mechanistic understanding and physics-based treatment to overcome the hurdle. In the mean time, an empirical correction factor was developed in this modeling effort to capture the experimental observations.

Jou, Herng-Jeng↗
DOE OSTI2025

Control of Two Solid Electrolyte Interphases at the Negative Electrode of an Anode‐Free All Solid‐State Battery based on Argyrodite Electrolyte

Abstract Anode‐free all solid‐state batteries (AF‐ASSBs) employ “empty” current collector with three active interfaces that determine electrochemical stability; lithium metal – Solid electrolyte (SE) interphase (SEI‐1), lithium – current collector interface, and collector – SE interphase (SEI‐2). Argyrodite Li 6 PS 5 Cl (LPSCl) solid electrolyte (SE) displays SEI‐2 containing copper sulfides, formed even at open circuit. Bilayer of 140 nm magnesium/30 nm tungsten (Mg/W‐Cu) controls the three interfaces and allows for state‐of‐the‐art electrochemical performance in half‐cells and fullcells. AF‐ASSB with NMC811 cathode achieves 150 cycles with Coulombic efficiency (CE) above 99.8%. With high mass‐loading cathode (8.6 mAh cm −2 ), AF‐ASSB retains 86.5% capacity after 45 cycles at 0.2C. During electrodeposition of Li, gradient Li‐Mg solid solution is formed, which reverses upon electrodissolution. This promotes conformal wetting/dewetting by Li and stabilizes SEI‐1 by lowering thermodynamic driving force for SE reduction. Inert refractory W underlayer is required to prevent ongoing formation of SEI‐2 that also drives electrochemical degradation. Inert Mo and Nb layers likewise protect Cu from corroding, while Li‐alloying layers (Mg, Sn) are less effective due to ongoing volume changes and associated pulverization. Mechanistic explanation for observed Li segregation within alloying Li x Mg layer is provided through mesoscale modelling, considering opposing roles of diffusivity differences and interfacial stresses.

Wang, Yixian [Materials Science and Engineering Pr↗
DOE OSTI2026

Light-Driven Iodine Loss and Photoluminescence Homogenization in Mixed-Halide Perovskite Semiconductors

Carrier-induced instabilities in lead halide perovskites are often investigated as either transient phenomena, e.g., photoinduced halide segregation or permanent performance changes, e.g., photodegradation, while the mechanistic links between them remain unclear. Here, we aim to connect these observations by studying a model mixed-halide system, MAPb(Br x I 1–x ) 3 . By combining grazing-incidence X-ray diffraction, photothermal deflection spectroscopy, and photoluminescence measurements with hyperspectral microscopy, we investigate the role of mobile halide defects and local chemistry on reversible and long-term instabilities in these materials. Our results show that mixed-halide perovskites are uniquely susceptible to photoinduced changes with illumination driving initial iodide redistribution (i.e., halide segregation), eventual selective iodine expulsion, and subsequent changes in photoinduced halide segregation behavior. By quantifying structural and compositional changes, we estimate an approximately 3–5% iodine loss in our mixed-halide samples after only 24 h of illumination. Further, using microscale measurements, we identify pre-existing iodide-rich domains as key contributors to both the observed transient photostability and permanent iodine loss in MAPbBrI 2 , and see evidence that extended light soaking results in iodide redistribution that improves optoelectronic homogeneity. Overall, our results emphasize the importance of carrier-induced halide oxidation in creating a dynamic defect landscape in mixed-halide perovskites and provide a framework for interpreting apparent light-driven changes in optoelectronic behavior through the lens of permanent compositional changes.

electrical conductivity↗
NASA NTRS1993

Monte Carlo modeling of atomic oxygen attack of polymers with protective coatings on LDEF

Characterization of the behavior of atomic oxygen interaction with materials on the Long Duration Exposure Facility (LDEF) assists in understanding of the mechanisms involved. Thus the reliability of predicting in-space durability of materials based on ground laboratory testing should be improved. A computational model which simulates atomic oxygen interaction with protected polymers was developed using Monte Carlo techniques. Through the use of an assumed mechanistic behavior of atomic oxygen interaction based on in-space atomic oxygen erosion of unprotected polymers and ground laboratory atomic oxygen interaction with protected polymers, prediction of atomic oxygen interaction with protected polymers on LDEF was accomplished. However, the results of these predictions are not consistent with the observed LDEF results at defect sites in protected polymers. Improved agreement between observed LDEF results and predicted Monte Carlo modeling can be achieved by modifying of the atomic oxygen interactive assumptions used in the model. LDEF atomic oxygen undercutting results, modeling assumptions, and implications are presented.

Banks, Bruce A.↗
DOE OSTI2026

From viruses to protists: temperature response of the neglected components of microbial controls on peatland nutrient cycling

The response of plant-associated microbial communities to rising temperatures likely plays a key role in global Carbon (C) and Nitrogen (N) biogeochemical cycles. Mosses of the genus Sphagnum, in particular, sequester 25% of all terrestrial C as recalcitrant peat. However, their ability to sequester C is mediated by interactions with microbes that fix N and pass it to the moss to grow in otherwise oligotrophic systems. Two important biotic controls on this processes are likely to respond to rising temperatures –predation by protists and infections by viruses– but whether and how this might occur is not well understood. This proposal addressed these questions using a combination of genomics and mathematical modeling with both field data from whole-ecosystem warming experiments, and laboratory-based microcosm experiments. We have discovered 1) mechanistic links between cell traits and thermal performance in protists, which 2) enabled predictions from populations to ecosystems, 3) we have identified eco-phenotypic feedbacks that determine protist–bacterial predator–prey dynamics, 4) have documented concomitant compositional and trait shifts in protist communities with warming in the field, 5) revealed consistent interactive effects of temperature and nutrients on bacterial and protist communities; 6) characterized the Sphagnum virome, and 7) made modeling predictions on its implications for thermal responses of microbial communities in peatlands globally. This award also substantially strengthened U.S. scientific capacity and workforce development.

Gibert, Jean Philippe [Duke University]↗
NASA NTRS2001

Radiation breakage of DNA: a model based on random-walk chromatin structure

Monte Carlo computer software, called DNAbreak, has recently been developed to analyze observed non-random clustering of DNA double strand breaks in chromatin after exposure to densely ionizing radiation. The software models coarse-grained configurations of chromatin and radiation tracks, small-scale details being suppressed in order to obtain statistical results for larger scales, up to the size of a whole chromosome. We here give an analytic counterpart of the numerical model, useful for benchmarks, for elucidating the numerical results, for analyzing the assumptions of a more general but less mechanistic "randomly-located-clusters" formalism, and, potentially, for speeding up the calculations. The equations characterize multi-track DNA fragment-size distributions in terms of one-track action; an important step in extrapolating high-dose laboratory results to the much lower doses of main interest in environmental or occupational risk estimation. The approach can utilize the experimental information on DNA fragment-size distributions to draw inferences about large-scale chromatin geometry during cell-cycle interphase.

Chromatin/radiation effects↗
DOE OSTI2024

Gas-Phase Oxidation Mechanisms of Nitrogen-Containing Organic Compounds

Nitrogen-containing organic molecules play essential roles in nearly every aspect of chemistry. The importance of these species within gas-phase chemistry has increased in recent years, due to their emissions from wildfires, crude biofuels, ammonia combustion, and CO 2 capture facilities. However, there is a lack of detailed relevant mechanistic and kinetic studies of N-compounds, resulting in poor representation of these pathways within chemical models. In this report, we detail our exploration of the gas-phase oxidation mechanisms of pyrrole, imidazole, pyrrolidine, methylamine, and dimethylamine, done by employing multiplexed VUV photoionization mass spectrometry coupled with KinBot, a computational tool that automatically explores multi-well potential energy surfaces. Overall, we vastly expanded the known gas-phase oxidation mechanisms and chemical kinetics of these species. This work will improve the accuracy and completeness of atmospheric and combustion chemistry models, ultimately leading to better-informed decision-makers in the energy and environmental sectors.

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

Development of a machine learning model for polyethylene pyrolysis using a detailed reaction mechanism

Waste plastics have recently received significant attention as the issue of waste generation continues to increase. Thermal conversion processes, such as pyrolysis and gasification, are attractive potential technologies for utilizing waste plastics and reducing overall waste generation. Efficient utilization of plastics requires a detailed understanding of the conversion process such as pyrolysis and gasification. However, a mechanistic understanding of these processes lead to large and complex kinetic schemes that are not suited for large-scale and long-time simulation methods. Currently, most modeling approaches for pyrolysis and gasification rely on globally lumped, simplified kinetic schemes that provide results that are classified by their product type and not individual species, which limit the level of fidelity achieved via modeling. A machine learning (ML) model has been developed for the primary reactions of high-density polyethylene (HDPE) in an attempt to increase computational efficiency while still maintaining a high level of detail and accuracy. The ML model is trained on a detailed reaction mechanism containing 42 total species and 737 chemical reactions. A DeepONet branch and trunk architecture was adopted to train the model using time-steps relevant to computational fluid dynamics simulations. The ML used physics-informed loss functions to ensure mass conservation. The surrogate model has been deployed in simple MFiX CFD simulations, single particle and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗
DOE OSTI2026

Mechanistic Insights for Plasma-Catalytic CO 2 Reduction over TiO 2 in a Dielectric Barrier Discharge Reactor

Reaction kinetics experiments coupled with phenomenological kinetic modeling and parameter estimation are used to elicit insights into the mechanism and active sites for the plasma-catalytic dissociation of CO 2 on TiO 2 . Experimental and model insights showed that gas-phase reactions contribute at least two-thirds of the overall product formation at explored conditions; weak temperature dependence, strong sensitivity to specific energy input (SEI), apparent first order in CO 2 , and positive influence of cofed argon (Ar) and oxygen (O 2 ) for the gas-phase contributions all suggest that expected plasma reaction steps such as electron-impact and high-energy collisions are the dominant modes for CO 2 dissociation. The Arrhenius-like expression for gas contributions resulted in a preexponential of 4.40 × 10 –3 s –1 , an E SEI,g of 7.90 × 10 –4 mol/kJ, and an E a,g of 1.00 × 10 –3 J/mol. For surface contributions, the small apparent barrier of 16.3 kJ/mol, relatively weaker dependence on SEI, first-order dependence on CO 2 , and insensitivity to cofed Ar and O 2 all point to CO 2 dissociation on TiO 2 surface facets without vacancies and aided by plasma (leading to vibrationally excited CO 2 and/or a reactive surface with significant surface charge accumulation). The Arrhenius-like expression resulted in a preexponential of 7.81 × 10 –2 s –1 , an E SEI,s of 1.90 × 10 –3 mol/kJ, and an E a,s of 1.63 × 10 4 J/mol. The derived kinetic model further enabled a systematic evaluation of the effect of inputs (plasma power, flow rate, CO 2 inlet concentration, and temperature) to identify process trends and optimal operating conditions.

catalyst↗
DOE OSTI2024

Investigating Mountain Watershed Headwater‐To‐Groundwater Connections, Water Sources, and Storage Selection Behavior With Dynamic‐Flux Particle Tracking

Abstract Climate change will impact mountain watershed streamflow both directly—with changing precipitation amounts and variability—and indirectly—through temperature shifts altering snowpack, melt, and evapotranspiration. To understand how these complex processes will affect ecosystem functioning and water resources, we need tools to distinguish connections between water sources (rain/snowmelt), groundwater storage, and exit fluxes (streamflow/evapotranspiration), and to determine how these connections change seasonally and as climate shifts. Here, we develop novel watershed‐scale approaches to understand water source, storage, and exit flux connections using a dynamic‐flux particle tracking model (EcoSLIM) applied in California's Cosumnes Watershed, which connects the Sierra Nevada and Central Valley. This work develops new visualizations and applications to provide mechanistic understanding that underpins the interpretation of isotopic field data at watershed scales to distinguish sources, flow paths, residence times, and storage selection. In our simulations, streamflow comes primarily from snow‐derived water while evapotranspiration generally comes from rain. Most streamflow starts above 1,000 m while evapotranspiration is sourced relatively evenly across the watershed and is generally younger than streamflow. Modeled streamflow consists primarily of water sourced from precipitation in the previous 5 years but before the current water year, while ET consists primarily of water from precipitation in the current water year. ET, and to a lesser extent streamflow, are both younger than water in groundwater storage. However, snowmelt‐derived streamflow preferentially discharges older water from snow‐derived storage. Dynamic‐flux particle tracking and new approaches presented here enable novel model‐tracer comparisons in large‐scale watersheds to better understand watershed behavior in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Direct Imaging of Hydrogen‐Driven Dislocation and Strain Field Evolution in a Stainless Steel Grain

Hydrogen embrittlement (HE) poses a significant challenge to the durability of materials used in hydrogen production and utilization. Disentangling the competing nanoscale mechanisms driving HE often relies on simulations and electron-transparent sample techniques, limiting experimental insights into hydrogen-induced dislocation behavior in bulk materials. This study employs in situ Bragg coherent X-ray diffraction imaging to track three-dimensional (3D) dislocation and strain field evolution during hydrogen charging in a bulk grain of austenitic 316 stainless steel. Tracking a single dislocation reveals hydrogen-enhanced mobility and relaxation, consistent with dislocation dynamics simulations. Subsequent observations reveal dislocation unpinning and climb processes, likely driven by osmotic forces. Additionally, nanoscale strain analysis around the dislocation core directly measures hydrogen-induced elastic shielding. These findings experimentally validate theoretical predictions and offer mechanistic insights into hydrogen-driven dislocation behavior. The quantified nanoscale phenomena serve as critical inputs for multiscale modeling frameworks to predict bulk material responses and accelerate the development of HE-resistant alloys.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Covalency-Driven Differences in the Hydrogenation Chemistry of Lanthanide- and Actinide-Based Frustrated Lewis Pairs

The electronic organization of Frustrated Lewis Pairs (FLPs) allows them to activate strong bonds in mechanisms that are usually free of redox events at the Lewis acidic site. The unique 6d/5f manifold of uranium could serve as an interesting FLP acceptor site, but to date FLP-like catalysis with actinide ions is unknown. In this paper, the catalytic, FLP-like hydrogenation reactivity of trivalent uranium complexes is explored in the presence of base-stabilized silylenes. Comparison to isoelectronic, isostructural lanthanide and thorium complexes lends insight into the electronic factors governing dihydrogen activation. Mechanistic studies of the uranium- and lanthanide-catalyzed hydrogenations are presented, including discussion of likely intermediates. Computational modeling of the f-element complexes, combined with experimental comparison to p-block Lewis acids, elucidates the relevance of steric hindrance to productive reactivity with dihydrogen. As a result, consideration of the complete experimental and theoretical evidence provides a clear picture of the electronic and steric factors governing dihydrogen activation by these FLPs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗