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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Electromagnetic waves in an optical photonic lattice

Laser light propagation in a photonic lattice consisting of two parallel waveguide arrays is theoretically studied using the coupled mode method, with the interaction of each waveguide with the nearest neighbours and between the waveguides of the arrays being taken into account. Analytical expressions are obtained that make it possible to accurately predict the presence of localisation of light depending on the coupling constants. Particular solutions of a system of coupled waves are found, which describe strongly localised light propagating without transverse diffraction along the entire lattice at certain values of the coupling constants. The emergence of spatially limited transverse diffraction of light is predicted. (integral optics)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Navigating Uncertainty: Challenges in Visualizing Ensemble Data and Surrogate Models for Decision Systems

Uncertainty visualization plays a critical role in transforming ensemble simulation data into actionable insights by effectively communicating various dimensions of uncertainty within a system. The emergence of artificial intelligence-driven surrogate models trained on multirun ensemble data offers a transformative opportunity to replace computationally intensive simulations with fast estimates, enabling users to explore data spaces with unprecedented depth and interactivity. However, integrating ensemble data and surrogate models into decision-making workflows and tools introduces novel challenges for uncertainty visualization. These include reconciling and clearly communicating the unique uncertainties associated with ensembles and their surrogate model estimates, and leveraging these approximations to inform actionable decisions. This work explores these challenges in the context of high-dimensional data visualization, bridging discrete datasets with their continuous representations and addressing the complexities of systems that support iterative navigation between input and output spaces. We evaluate the role of uncertainty visualization in fostering intuitive, actionable interactions and identify critical hurdles in advancing this frontier of computational simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

$T\overline{T}$ deformations and the width of fundamental particles

We provide a simple geometric meaning for deformations of so-called $T\overline{T}$ type in relativistic and non-relativistic systems. Deformations by the cross products of energy and momentum currents in integrable quantum field theories are known to modify the thermodynamic Bethe ansatz equations by a “CDD factor”. In turn, CDD factors may be interpreted as additional, fixed shifts incurred in scattering processes: a finite width added to the fundamental particles (or, if negative, to the free space between them). We suggest that this physical effect is a universal way of understanding $T\overline{T}$ deformations, both in classical and quantum systems. We first show this in non-relativistic systems, with particle conservation and translation invariance, using the deformation formed out of the densities and currents of particles and momentum. This holds at the level of the equations of motion, and for any interaction potential, integrable or not. We then argue, and show by similar techniques in free relativistic particle systems, that $T\overline{T}$ deformations of relativistic systems produce the equivalent phenomenon, accounting for length contractions. We also show that, in both the relativistic and non-relativistic cases, the width of particles is equivalent to a state-dependent change of metric, where the distance function discounts the particles’ widths, or counts the additional free space. This generalises and explains the known field-dependent coordinate change describing $T\overline{T}$ deformations. The results connect such deformations with generalised hydrodynamics, where the relations between scattering shifts, widths of particles and state-dependent changes of metric have been established.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Decay rates of almost strong modes in Floquet spin chains beyond Fermi's Golden Rule

The stability and dynamics of almost strong zero and π modes in weakly nonintegrable Floquet spin chains are investigated. Such modes can also be viewed as localized Majorana modes at the edge of a topological superconductor. Perturbation theory in the strength of integrability breaking interaction J z is employed to estimate the decay rates of these modes, and compared to decay rates obtained from exact diagonalization. Here, the structure of the perturbation theory and thus the lifetime of the modes is governed by the conservation of quasienergy modulo 2π/T, where T is the period of the Floquet system. If there are 4n – 1 bulk excitations whose quasienergies add up to zero (or π/T for a π mode), one obtains a decay channel of the Majorana mode with a decay rate proportional to $J$$^{2n}_{z}$. Thus the lifetime is sensitively controlled by the width of the single-particle Floquet bands. For regimes where the decay rates are quadratic in J z , an analytic expression for the decay rate in terms of an infinite temperature autocorrelation function of the integrable model is derived, and shown to agree well with exact diagonalization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Path integral approach to quantum anomalies in interacting models

The prediction and subsequent discovery of topological semimetal phases of matter in solid state systems has instigated a surge of activity investigating the exotic properties of these unusual materials. Among these are transport signatures which can be attributed to the chiral anomaly; the breaking of classical chiral symmetry in a quantum theory. This remarkable quantum phenomenon, first discovered in the context of particle physics has now found new life in condensed-matter physics, connecting topological quantum matter and band theory with effective field theoretic models. In this paper we investigate the interplay between interactions and the chiral anomaly in field theories inspired by semimetals using Fujikawa's path integral method. Starting from models in one spatial dimension we discuss how the presence of interactions can affect the consequences of the chiral anomaly leading to renormalization of excitations and their transport properties. This is then generalized to the three-dimensional case where we show that the anomalous response of the system, namely, the chiral magnetic and quantum Hall effects, are modified by the presence of interactions. These properties are investigated further through the identification of anomalous modes which exist within interacting Weyl semimetals. These massive excitations are nonperturbative in nature and are a direct consequence of the chiral anomaly. The effects of interactions on mixed axial-gravitational anomalies are then investigated and the conditions required for interaction effects to be observed are discussed.

Anomalies↗
DOE OSTI2025

Bottom-up fabrication of 2D Rydberg exciton arrays in cuprous oxide

Solid-state platforms provide exceptional opportunities for advancing on-chip quantum technologies by enhancing interaction strengths through coupling, scalability, and robustness. Cuprous oxide (Cu 2 O) has recently emerged as a promising medium for scalable quantum technology due to its high-lying Rydberg excitonic states, akin to those in hydrogen atoms. To harness these nonlinearities for quantum applications, the confinement dimensions must match the Rydberg blockade size, which can reach several microns in Cu 2 O. Using a CMOS-compatible growth technique, this study demonstrates the bottom-up fabrication of site-selective arrays of Cu 2 O microparticles. We observed Rydberg excitons up to the principal quantum number n = 5 within these Cu 2 O arrays on a quartz substrate and analyzed the spatial variation of their spectrum across the array, showing robustness and reproducibility on a large chip. These results lay the groundwork for the deterministic growth of Cu 2 O around photonic structures, enabling substantial light-matter interaction on integrated photonic platforms and paving the way for scalable, on-chip quantum devices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synergetic Effects of Soil Organic Matter Components During Interactions with Minerals

Mineral-associated soil organic matter (SOM) is critical for stabilizing organic carbon and mitigating climate change. However, mineral-SOM interactions at the molecular scale, particularly synergetic adsorption through organic-organic interaction on the mineral surface known as organic multilayering, remain poorly understood. This study investigates the impact of organic multilayering on mineral-SOM interactions, by integrating macroscale experiments and molecular-scale simulations that assess the individual and sequential adsorption of major SOM compounds – lauric acid (lipid), pentaglycine (amino acid), trehalose (carbohydrate), and lignin onto soil minerals. Ferrihydrite, Al-hydroxide, and calcite are exposed to SOM compounds to determine adsorption affinities and binding energies. Results show that lauric acid has 20-40 times higher K d than pentaglycine, following the order K d (ferrihydrite) > K d (Al-hydroxide) >> K d (calcite). Molecular-scale simulations confirm that lauric acid has a higher binding energy (30.8 kcal/mol) on ferrihydrite than pentaglycine (6.0 kcal/mol), attributed to lipid hydrophobicity. The lower binding energy of pentaglycine results from its hydrophilic amide groups, facilitating partitioning into water. Sequential experiments examine how the first layer of lipid or amino acid affects the adsorption of carbohydrate/lignin, which show little or no individual adsorption affinities. Macroscale results reveal that lipid and amino acid adsorption induce ferrihydrite particle repulsion increasing reactive surface area and enhancing carbohydrate/lignin adsorption independently and synergistically through organic multilayering. Molecular-scale results reveal that amino acid adsorbed on ferrihydrite interacts more readily with lignin macroaggregates (preformed in solution) than with individual lignin units, indicating organic multilayering via H-bonding. Further, these findings reveal the molecular mechanisms of SOM-mineral interactions, crucial for enhancing soil carbon stabilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Functional Relevance of CASP16 Nucleic Acid Predictions as Evaluated by Structure Providers

ABSTRACT Accurate biomolecular structure prediction enables the prediction of mutational effects, the speculation of function based on predicted structural homology, the analysis of ligand binding modes, experimental model building, and many other applications. Such algorithms to predict essential functional and structural features remain out of reach for biomolecular complexes containing nucleic acids. Here, we report a quantitative and qualitative evaluation of nucleic acid structures for the CASP16 blind prediction challenge by 12 of the experimental groups who provided nucleic acid targets. Blind predictions accurately model secondary structure and some aspects of tertiary structure, including reasonable global folds for some complex RNAs; however, predictions often lack accuracy in the regions of highest functional importance. All models have inaccuracies in non‐canonical regions where, for example, the nucleic‐acid backbone bends, deviating from an A‐form helix geometry, or a base forms a non‐standard hydrogen bond (not a Watson‐Crick base pair). These bends and non‐canonical interactions are integral to forming functionally important regions such as RNA enzymatic active sites. Additionally, the modeling of conserved and functional interfaces between nucleic acids and ligands, proteins, or other nucleic acids remains poor. For some targets, the experimental structures may not represent the only structure the biomolecular complex occupies in solution or in its functional life cycle, posing a future challenge for the community.

Biochemistry & Molecular Biology↗
DOE OSTI2023

The hidden structure of hydrodynamic transport in random fracture networks

We study the large-scale dynamics and prediction of hydrodynamic transport in random fracture networks. The flow and transport behaviour is characterized by first passage times and displacement statistics, which show heavy tails and anomalous dispersion with a strong dependence on the injection condition. The origin of these behaviours is investigated in terms of Lagrangian velocities sampled equidistantly along particle trajectories, unlike classical sampling strategies at a constant rate. The velocity series are analysed by their copula density, the joint distribution of the velocity unit scores, which reveals a simple, albeit hidden, correlation structure that can be described by a Gaussian copula. Based on this insight, we derive a Langevin equation for the evolution of equidistant particle speeds. In this framework, particle motion is quantified by a stochastic time-domain random walk, the joint density of particle position, and speed satisfies a Klein–Kramers equation. The upscaled theory quantifies particle motion in terms of the characteristic fracture length scale and the distribution of Eulerian flow velocities. That is, it is predictive in the sense that it does not require the a priori knowledge of transport attributes. The upscaled model captures non-Fickian transport features, and their dependence on the injection conditions in terms of the velocity point statistics and average fracture length. It shows that the first passage times and displacement moments are dominated by extremes occurring at the first step. The presented approach integrates the interaction of flow and structure into a predictive model for large-scale transport in random fracture networks.

42 ENGINEERING↗
DOE OSTI2023

Avoided Level Crossing and Entangled States of Interacting Hydrogen Molecules Detected by the Quantum Superposition Microscope

Pump–probe measurements by ultrashort THz pulses can be used to excite and follow the coherence dynamics in the time domain of single hydrogen molecules (H 2 ) in the junction of a scanning tunneling microscope (STM). By tailoring the resonance frequency through the sample bias, we identified two spectral signatures of the interactions among multiple H 2 molecules. First, the avoided level crossing featured by energy gaps ranging from 20 to 80 GHz was observed because of the level repulsion between two H 2 molecules. Second, the tip can sense the signal of H 2 outside the junction through the projective measurement on the H 2 inside the junction, owing to the entangled states created through the interactions. A dipolar-type interaction was integrated into the tunneling two-level system model of H 2 , enabling accurate reproduction of the observed behaviors. Furthermore, our results obtained by the quantum superposition microscope reveal the intricate quantum mechanical interplay among H 2 molecules and additionally provide a 2D platform to investigate unresolved questions of amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enabling Ethanol Dehydrogenation Catalysis by Postsynthetic Anion Exchange of Triazolate-Based Metal–Organic Frameworks

Materials containing soft, polarizable elements are expanding the boundaries of catalytic properties, offering unique electronic communication and stability characteristics compared with their harder counterparts due to the enhanced covalent nature of metal–ligand interactions. However, integrating soft components like sulfur into metal–organic frameworks (MOFs) for catalytic applications remains a largely underexplored challenge. Here, we report the synthesis of a family of triazole-based MOFs and expand upon established postsynthetic anion exchange methods to incorporate sterically encumbered polarizable elements, such as alkyl thiolates. Single-crystal X-ray diffraction, coupled with elemental analysis, confirms the successful anion exchange within M 2 X 2 BBTA (M = Co, Ni; X = μ-Cl, μ-OH, μ-SH, μ-SMe, μ-SEt; H 2 BBTA = 1H,5H-benzo(1,2-d:4,5-d′)bistriazole). We found that the anion identity significantly impacts the catalytic activity and selectivity of the MOFs, especially in nonoxidative ethanol dehydrogenation. Temperature-programmed experiments indicated that the metal single sites act as catalytically active sites below 250 °C. This work not only expands the synthetic toolbox for incorporating polarizable components into MOFs but also provides critical insights into their catalytic potential.

Anions↗
DOE OSTI2025

Mechanistic studies of small molecule ligands selective to RNA single G bulges

Abstract Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Core-flood Effluent and Shale Surface Chemistries in Predicting Interaction between Shale, Brine, and Reactive Fluid

We report field and laboratory observations to date indicate that the efficiency of hydraulic fracturing, as it relates to hydrocarbon recovery, depends significantly on geochemical alterations to rock surfaces that diminish accessibility by partial or total plugging of the pore and fracture networks. This is caused by mineral scale deposition such as coating of fracture surfaces with precipitates, particle migration, and/or crack closure due to dissolution under stress. In reactive flow-through experiments, mineral reactions in response to acidic fluid injection significantly reduced system porosity and core permeability. The present study focuses on changes to fluid chemistry and shale surfaces (inlet and fracture walls) resulting from shale-fluid interactions and integrating these findings for an improved estimate of transport-related consequences. The reacted shale surfaces were examined by spatially-resolved scanning electron microscopy - energy dispersive spectroscopy (SEM-EDS) analysis. Importantly, inductively coupled plasma - mass spectrometry/optical emission spectroscopy (ICP-MS/OES) was utilized to probe the chemical evolution of the core-flood effluents. The three study cores selected from the Marcellus formation represent different mineralogies and structural features. In flow-through experiments, lab-generated brine and HCl-based fracture fluid (pH=2) were injected sequentially under effective stress (up to 500 psi) at reservoir temperature (80°C). SEM-EDS results confirmed by the ICP concentration trends showed significant Fe hydroxide precipitates in clay- and pyrite-rich outcrop samples due to partial oxidation of Fe-bearing phases in the case of intrusion of low salinity water-based fluids. Porosity reduction in the MSEEL (Marcellus Shale Energy and Environmental Laboratory) carbonate-rich sample is related to compaction of cores under stress due to matrix softening with substantial dissolution, and pore-filling by hydroxides, as well as barite and salts. Despite the same fluid compositions and experimental conditions used for both MSEEL samples, barite precipitation was much more intense in the MSEEL clay-rich sample due to its greater sorption capacity and additional sulfate source as well as fissile nature with multiple lengthwise cracks. ICP tests revealed time-resolved concentration trends in produced brine and reactive fluids that in turn complemented the pre-/post-reaction SEM-EDS observations.

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

Towards Exascale Astrophysics of Mergers and Supernovae (TEAMS)

The major goals of the TEAMS project are (i) to improve the modeling of many of the suggested astrophysical sites of the r‐process, as well as some potential p‐process sites, (ii) to use our models to support and guide the experimental efforts at FRIB and similar facilities, and (iii) to use our tools to cement our understanding of the roles that massive stars play in galactic chemical evolution. As part of the TEAMS project, Mezzacappa (UTK, Reddy (UW), Surman (ND), and Steiner (UTK) are (i) generating equations of state and neutrino opacities for simulations of core‐collapse supernovae and neutron star mergers which are more faithful to current understanding of the nucleon‐nucleon interaction, (ii) integrating those new equations of state and neutrino opacities into new simulation codes being developed, (iii) performing detailed nuclear reaction network post‐processing to determine abundances from simulations and (iv) quantifying the impact of nuclear physics uncertainties on r‐process abundances.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Can Simple Machine Learning Tools Extend and Improve Temperature-Based Methods to Infer Streambed Flux?

Temperature-based methods have been developed to infer 1D vertical exchange flux between a stream and the subsurface. Current analyses rely on fitting physically based analytical and numerical models to temperature time series measured at multiple depths to infer daily average flux. These methods have seen wide use in hydrologic science despite strong simplifying assumptions including a lack of consideration of model structural error or the impacts of multidimensional flow or the impacts of transient streambed hydraulic properties. We performed a “perfect-model experiment” investigation to examine whether regression trees, with and without gradient boosting, can extract sufficient information from model-generated subsurface temperature time series, with and without added measurement error, to infer the corresponding exchange flux time series at the streambed surface. Using model-generated, synthetic data allowed us to assess the basic limitations to the use of machine learning; further examination of real data is only warranted if the method can be shown to perform well under these ideal conditions. We also examined whether the inherent feature importance analyses of tree-based machine learning methods can be used to optimize monitoring networks for exchange flux inference.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Occupancy-Driven Stochastic Decision Framework for Ranking Commercial Building Loads

For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services. In this paper, we present a data-driven stochastic decision-support framework to dynamically rank load control alternatives in a commercial building, addressing the needs of multiple decision criteria (e.g. occupant comfort, grid service quality) under uncertainties in occupancy patterns. We adopt a stochastic multi-criteria decision algorithm recently applied to prioritize residential on/off loads, and extend it to i) consider complex load control decisions (e.g. dimming of lights, changing zone temperature set-points) in a commercial building; and ii) systematically integrate zonal occupancy patterns to better identify short-term (and time-varying) opportunities for grid service participation. We evaluate the performance of the proposed framework for curtailment of air-conditioning, lighting, and plug-loads in a multi-zone commercial office building for a range of design choices. With the help of a prototype system that integrates an interactive \textit{Data Analytics and Visualization} frontend we demonstrate a way for the building operators to monitor and change in real-time the available flexibility in energy consumption and to develop trust in the decision recommendations by interpreting the rationale behind the ranking.

Jain, Milan↗
DOE OSTI2021

IEEE P2988: Recommended Practice of Use and Functions of Virtual Synchronous Machines

Power systems are going through a paradigm shift from centralized generation to distributed generation. This brings unprecedented challenges to power systems stability, reliability, and security. Operating power electronic converters as Virtual Synchronous Machines (VSMs) can bring backward compatibility to power systems, unify and harmonize the integration and interaction of future power systems players, and improve power system stability, reliability, and security. This is vital for the large-scale adoption of distributed energy resources, the advancement of sustainability, and the development of a low-carbon economy. This IEEE 2988 Recommended Practice will define the fundamental principles, mandatory functions, and optional functions of a VSM, i.e., a power electronic converter that is operated to behave like conventional synchronous machines. It will not describe or specify power semiconductor devices, hardware topologies, or micro-controllers that are used to build a VSM. This talk will discuss the activities and development plan for IEEE 2988 with the aim to engaging broad stakeholders and widening participation.

Zhong, Qing-Chang↗