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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 145 records · Page 8

Cesium exhibits different mesoscale segregation and ion pairing than lithium, sodium, or potassium in concentrated alkaline aqueous nitrite solutions

Understanding ion pairing in concentrated alkaline electrolytes facilitates the prediction and control of chemical processes in nuclear waste. While sodium is the dominant alkali metal in such systems, cesium often exhibits distinct bulk behavior relative to lighter alkali cations. Aqueous mixtures of cesium hydroxide and sodium nitrite were compared to alkali hydroxide analogs using small-angle x-ray scattering, revealing that cesium disrupts the sodium nitrite electrolyte structure, forming cesium-rich domains. This mesoscale segregation contrasts with the near-ideal mixing observed in other mixed hydroxide–nitrite systems. Raman spectroscopy indicates cesium–nitrite ion pairing, evidenced by vibrational shifts distinct from those associated with sodium. Multinuclear magnetic resonance spectroscopy further supports cesium–nitrite and cesium–hydroxide association, revealing a distinct local environment for nitrite in cesium-containing solutions. Together, these findings show that cesium promotes a unique solution structure dominated by specific ion pairing within segregated domains. This structural organization may influence radical generation pathways in high-ionic-strength alkaline media relevant to nuclear waste processing and management.

Nienhuis, Emily T. [Pacific Northwest National Lab↗

Gapless dispersive continuum in a modulated quantum kagome antiferromagnet

The pursuit of quantum spin liquid (QSL) states in condensed matter physics has drawn attention to kagome antiferromagnets (AFM) where a two-dimensional corner-sharing network of triangles frustrates conventional magnetic orders. While quantum kagome AFMs based on Cu 2+ (3d 9 , s = 1/2) ions have been extensively studied, there is so far little work beyond copper-based systems. Here we present our bulk magnetization, specific heat and neutron scattering studies on single crystals of a new titanium fluorides Cs 8 RbK 3 Ti 12 F 48 where Ti 3+ (3d 1 , s = 1/2) ions form a modulated quantum kagome antiferromagnet that does not order magnetically down to 1.5 K. Our comprehensive map of the dynamic response function $S$($Q$,$\hslash$$\omega$) acquired at 1.5 K where the heat capacity is T-linear reveals a dispersive continuum emanating from soft lines that extend along (100). The data indicate fractionalized spinon-like excitations with quasi-one-dimensional dispersion within a quasi-two-dimensional spin system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Insights into controlling bacterial cellulose nanofiber film properties through balancing thermodynamic interactions and colloidal dynamics

In recent years, nanocellulose has emerged as a sustainable and environmentally friendly alternative to traditional petroleum-derived structural polymers. Sourced either from plants, algae, or bacteria, nanocellulose can be processed into colloid, gel, film and fiber forms. However, the required fundamental understanding of process parameters that govern the morphology and structure–property relationships of nanocellulose systems, from colloidal suspensions to bulk materials, has not been developed and generalized for all forms of cellulose. This further hinders the more widespread adoption of this biopolymer in applications. Our study investigates the dispersion of cellulose nanofibers (CNFs) produced by a bacterial–yeast co-culture, in solvents, highlighting the role of thermodynamic interactions in influencing their colloidal behavior. By adjusting Hansen solubility parameters, we controlled the thermodynamic relationship between CNFs and solvents across various concentrations, studying the dilute to semi-dilute regimes. Rheological measurements revealed that the threshold at which a concentration-based regime transition occurs is distinctly solvent-dependent. Complementing rheological analysis with small angle X-ray scattering and zeta potential measurements, our findings reveal that enhancing CNF–solvent interactions increases excluded volume in the dilute regime, emphasizing the importance of the balance between fiber–fiber and fiber–solvent interactions. Moreover, we investigated the transition from colloidal to solid state by creating films from dispersions with varying interaction parameters in semi-dilute regimes. Through mechanical testing and scanning electron microscopy imaging of the fracture surfaces, we highlight the significance of electrokinetic effects in such transitions, as dispersions with higher electrokinetic stabilization gave rise to stronger and tougher films despite having less favorable thermodynamic interaction parameters. Finally, our work provides insights into the thermodynamic and electrokinetic interplay that governs bacterial CNF dispersion, offering a foundation for future application and a deeper understanding of nanocellulose's colloidal and structure-property relationships.

59 BASIC BIOLOGICAL SCIENCES↗

Barium ion sensing with IPG K + molecular probes

Fluorophores covalently bound to azacrown ether ionophores can be assembled into sensitive turn-on chemosensors. The size specificity and electron-rich nature of the ionophore's binding domain contribute to both selectivity and strong turn-on fluorescence sensing by various mechanisms when properly constructed. Aza-18-crown-6 ethers are quite selective for binding to K + and Ba 2+ , yet the more electron-withdrawing dicationic nature of barium imposes a larger electronic effect on turn-on fluorescent sensors. Barium chemosensors can be important for measuring soluble Ba 2+ in drinking water and have gained recent attention for their potential to enhance the detection of rare events in xenon decay. Here we quantify the capability of three chemosensors, marketed for biologically useful K + sensing, as effective probes for Ba 2+ ions. Here, we present measurements from bulk spectrofluorometry to characterize the system in aqueous solutions and demonstrate the usefulness of these species for low-background single-ion fluorescence microscopy, revealing new candidates for Ba 2+ sensing.

Miller, R. L. [Department of Chemistry and Biochem↗

Putting error bars on density functional theory dataset

This dataset contains submission files and raw output files from high-throughput DFT simulations to analyze the systemic errors in lattice constant, bulk moduli and formation energy predictions for a range of binary and ternary oxides using four exchange correlation functionals (LDA, PBE, PBEsol and vdW-DF-C09). This data was then used as the basis for employing materials informatics methods to predict the expected errors in the lattice constants of the studied compounds. Predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide “error bars” for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

36 MATERIALS SCIENCE↗

IMS Rapid Response 2024 Summary Report: A Machine Learning Potential for the Periodic Table

Stockpile stewardship and nuclear waste remediation are inherently chemically complex, involving practically the full diversity of the periodic table, but existing methods are too expensive or not functional for a large diversity of atom types. Overall, the field of machine learning interatomic potentials (MLIPs) has advanced dramatically in 2024 with large high-accuracy datasets existing for bulk, surface, and organic chemical systems and new online leaderboards for diverse chemistry. To participate in, and bring LANL interests into this ecosystem, here, we have built upon existing technologies created by LANL to create a framework capable of creating machine learning interatomic potentials (MLIPs) for over 90 atom types. Our results have created a massively diverse coordination complex training dataset more than 3 times the size of existing datasets, parallelized MLIP training over multiple GPUs, enabling the training of an MLIP spanning the periodic table at 20 times the speed of prior training on 32 GPUs. These advances are substantial towards creation on foundational MLIPs for LANL-specific application areas.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗

Topological modes and spectral flows in inhomogeneous PT-symmetric continuous media

In classical Hermitian continuous media, the spectral-flow index of topological modes is linked to the bulk topology via index theorem. However, the interface between two bulks is usually non-Hermitian due to the inhomogeneities of system parameters. We show that the connection between topological modes and bulk topology still exists despite the non-Hermiticity at the interface if the system is endowed with PT symmetry. The theoretical framework developed is applied to the Hall magnetohydrodynamic model to identify a topological mode called topological Alfvén sound wave in magnetized plasmas. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Intermittent oxidation kinetics and metal/oxide interfacial undulation

The phenomenon of oxygen-adsorption-induced surface restructuring is widespread across various metal-oxygen systems, yet its impact on initiating bulk oxide formation remains largely unexplored. In this study, through in-situ atomic-resolution electron microscopy observations of surface oxidation of Cu(110) and Cu 85 Au 15 (110), we unveil intermittent oxide-film growth modulated by oxygen-induced surface restructuring. This modulation is evidenced by repeated pinning of Cu 2 O growth front at isolated Cu columns of the c(6×2)-O reconstruction, owing to required long-range diffusion of Cu and O atoms to the Cu 2 O growth front. We reveal that Cu vacancies, generated at the Cu 2 O growth front, are injected into the Cu 2 O/Cu interface, inducing hill-and-valley undulation of the Cu 2 O film. In contrast, atomic vacancies produced during the Cu 85 Au 15 (110) oxidation preferentially migrate into interfaces between Au-rich and Au-poor regions in the bulk, resulting in a flat and adherent Cu 2 O film. These findings demonstrate the critical role of oxygen-induced surface restructuring in modulating oxide-film-growth kinetics and manipulability of the fate of injected vacancies by alloying, thereby offering insights applicable to a broader range of metal-oxygen systems for fine-tuning oxidation kinetics and enhancing oxide/metal interfacial adhesion.

25 ENERGY STORAGE↗

A Semi-Empirical Density Law for Ternary, Homogeneous PuCl 3 /HCl/H 2 O Solutions

Nuclear material operations pose unique hazards that are not encountered in other chemical, energy, or manufacturing industries. One of these hazards is the potential for a nuclear criticality accident when handling fissile isotopes such as 235 U and 239 Pu. These hazards are particularly high when fissile material is dissolved in solution as the neutron behaviors of the system can change rapidly with the physical and chemical changes accessible in solution. Current estimates of solution density used for criticality safety are outdated and hinder fissile material handling. Developing new estimates for these safety calculations requires experimental characterization and the derivation of empirical density models. We have derived a density law describing PuCl 3 /HCl/H 2 O solutions from experimental data characterizing solution density. Density data was treated using a Pitzer-derived eight-parameter equation, defining density as a function of analyte concentrations, temperature, and interactions between these variables. The model is predictive across the concentration and temperature ranges from which it was derived. The potential effects of varying oxidation states of plutonium, which are easily accessible in aqueous media, on the bulk solution density of the ternary system were also investigated. The resulting Pitzer-derived density law was applied to a nuclear criticality safety model, and the impact of the experimental characterization of solution density relative to previous estimates was demonstrated to be significant and suggest that the current approach to estimating density in nuclear criticality safety calculations may lead to overly conservative controls.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗

Thin film combinatorial sputtering of TaTiHfZr refractory compositionally complex alloys for rapid materials discovery

Many applications from advanced nuclear reactors to aerospace and automotive industries require materials to operate in extreme environments. In search of new materials that can operate in these extremes, the present work explores this space whereby: (1) guided by atomistic and thermodynamic calculations we utilize thin film combinatorial synthesis to rapidly explore mechanical and thermal properties in a broad range of refractory compositionally complex alloys, and (2) observe transformation induced plasticity via oscillations in the thin film nanoindentation load depth curves that are attributed to, (3) a stress-induced HCP-to-BCC phase transformation in the resulting nanogranular microstructure, which to our knowledge has not been observed before in this alloy system; and finally (4) scale to bulk materials to compare the thin film results.

36 MATERIALS SCIENCE↗

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗

Size-dependent femtosecond proton transfer in protonated methanol clusters

Methanol clusters (CH 3 OH) n are prototypical hydrogen-bonded systems that bridge isolated molecules and bulk liquid methanol. Strong-field ionization of these clusters can trigger ultrafast charge migration, proton transfer, and isomerization; however, the onset timescales of these pathways remain largely unexplored despite extensive steady-state mass-spectrometric evidence for protonation and chemical rearrangement. Here we use femtosecond time-resolved strong-field ionization and disruptive probing to directly track the early-time dynamics of methanol clusters. Transient mass spectra yield size-dependent timescales for the formation of protonated clusters H + (CH 3 OH) n (n = 1–3) and an associated CHO˙ + radical cation. We find that both proton-transfer and subsequent stabilization become markedly faster with increasing cluster size. These measurements establish methanol clusters as a complementary benchmark to water for understanding ionization-initiated proton motion and chemical reorganization in hydrogen-bonded liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Republished: Colossal density-driven resistance response in the negative charge transfer insulator MnS 2

The Mn chalcogenides show a remarkable variation in structural and physical properties with density. In MnS 2 we observe a pronounced difference with the effects of varying hydrostaticity with pressure inducing a structural transition at 300 K. Within the pyrite phase, a colossal electrical resistance drop of 10 8 Ohms is observed by 12 GPa of nonhydrostatic compression at 300 K. DFT simulations reveal the metallization to be unexpectedly driven by previously unoccupied S$^{2-}_2$ σ$^*_{3p}$ antibonding states crossing the Fermi level. This is a seldom seen variant of the charge transfer insulator to metal transition for negative charge transfer insulators which have anions with an unsaturated valence. Finally, by 36 GPa of nonhydrostatic compression, the single presence of the low-spin insulating arsenopyrite (P2 1 /c) phase is confirmed, and the bulk metallicity is broken with the system returning to an insulative electronic state.

36 MATERIALS SCIENCE↗

Incorporating the molecular-scale into a hydrodynamic description of confined aqueous systems

Hydrodynamics provides a continuum-level description of fluid motion, but its applicability at the nanoscale becomes uncertain due to the emerging importance of molecular-level effects such as spatial heterogeneity. Hydrodynamic boundary conditions that incorporate molecular details allow us to partition the system into a near-wall region and a bulk fluid region. We identify a hydrodynamic wall located inside the fluid that determines where slip begins. By extending the hydrodynamic wall with the slip length, the position of the extrapolated wall is established. This offers a unified description of both slip and stagnant flow behaviors, with wall hydrophobicity characterized by the relative location of the extrapolated wall with respect to the physical wall. Employing this concept in analyses of equilibrium molecular dynamics (MD) and non-equilibrium MD simulations of Couette and Poiseuille flows, our results demonstrate consistency between equilibrium and non-equilibrium approaches across different flow types and confinement levels. This demonstrates the robust nature of linear response theory. We then explore the effects of fluid-wall and bulk fluid interactions on the hydrodynamic properties. These findings enhance the effectiveness of molecular-based simulations for investigating complex confined systems in nanofluidics, biology, and colloidal science, offering a complementary molecular-scale perspective to traditional continuum approaches.

flow simulations↗

Bulk synthesis of radiation resistant W – Ti – Cr – V compositionally complex alloys

Refractory compositionally complex alloys are candidate material systems for next generation advanced nuclear reactors. This work showcases the first successful bulk synthesis of low activation W–Ti based refractory compositionally complex alloys using arc melting and provides insights on using additive manufacturing for these compositions using directed energy deposition. Both techniques produce equiaxed grains composed of a tungsten matrix with Ti–V–Cr dendritic boundaries. The arc melted specimen possesses a multi-modal grain size distribution, while the directed energy deposition specimen possesses a more gaussian distribution of grain size. Both arc melted and directed energy deposition specimens demonstrate high thermal stability up to 900 °C, as well as promising radiation resistance with low loop formation and the presence of homogeneously distributed helium cavities maintaining small diameters at ≥10 dpa under simultaneous light (helium) and heavy (krypton) ion irradiation at 900 °C.

Arc melting (AM)↗

Topological Phenomena in Artificial Quantum Materials Revealed by Local Chern Markers

A striking example of frustration in physics is Hofstadter’s butterfly, a fractal structure that emerges from the competition between a crystal’s lattice periodicity and the magnetic length of an applied field. Current methods for predicting the topological invariants associated with Hofstadter’s butterfly are challenging or impossible to apply to a range of materials, including those that are disordered or lack a bulk spectral gap. Here, in this work, we demonstrate a framework for predicting a material’s local Chern markers using its position-space description and validate it against experimental observations of quantum transport in artificial graphene in a semiconductor heterostructure, inherently accounting for fabrication disorder strong enough to close the bulk spectral gap. By resolving local changes in the system’s topology, we reveal the topological origins of antidot-localized states that appear in artificial graphene in the presence of a magnetic field. Moreover, we show the breadth of this framework by simulating how Hofstadter’s butterfly emerges from an initially unpatterned 2D electron gas as the system’s potential strength is increased and predict that artificial graphene becomes a topological insulator at the critical magnetic field. Overall, we anticipate that a position-space approach to determine a material’s Chern invariant without requiring prior knowledge of its occupied states or bulk spectral gaps will enable a broad array of fundamental inquiries and provide a novel route to material discovery, especially in metallic, aperiodic, and disordered systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗