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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Characterization of Microbial Consortia and the Products Associated with Selenium Reduction in Real Flue Gas Desulfurization (FGD) Wastewater

Biological treatment is a recognized approach for removing toxic selenate and selenite oxyanions present in flue gas desulfurization (FGD) wastewater. However, the knowledge on the specific microbial species or communities responsible for reducing water-soluble selenium oxyanions to insoluble elemental selenium remains limited. In addition, the selenium oxyanion reduction genes and pathways have yet to be understood in these wastewaters. This study characterizes selenium oxyanion reducing bacteria (SeRB) native to FGD wastewater, and the resulting elemental selenium particles formed. By selecting for native SeRB microbes in a defined media, a novel resolution of these organisms has been achieved. This research identifies previously unrecognized selenium oxyanion reducing capabilities in Anaerosolibacter, alongside predominant SeRB from Mesobacillus and Tepidibacillus genera. This work encompasses both 16S and metagenomic techniques to recover novel metagenome assembled genomes (MAGs), distinct to this environment. The biogenic selenium produced by these organisms were predominantly of elemental selenium, in either amorphous or with a hexagonal structure. In addition, the elemental selenium particles formed where shown to increase in purity as the microbes were enriched. This study identifies the SeRB present in FGD wastewater and characterizes their selenium products, offering crucial insights to enhance the efficiency of biological treatment strategies and the potential of selenium recovery from this industrial waste.

microbiology↗
DOE OSTI2024

YOU-ONLY-LOOK-ONCE (YOLO) FOR RADIO FREQUENCY SIGNAL CLASSIFICATION

We propose a method that uses deep learning (DL) to identify and frame various signals that are present in an environment. This DL framework is based on the You Only Look Once (YOLO) object detection pipeline Our work demonstrates a specific application of high performance computing and computer vision to the field of telecommunications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Validating Simulated Models of Energy Consumption by a Battery Electric Motorcoach: A real-world deployment in a harsh climate.

Many efforts have been made to simulate energy consumption of battery electric buses (BEBs) to optimize their deployment into existing fleets. The models produced, however, are rarely validated against real-world consumption data, limiting their generalizability and widespread application to fleets around the US. Furthermore, a major concern specific to BEBs is the effects of harsh climates on their performance. We build upon the state-of-the-art energy consumption modeling techniques developed for BEBs and apply them to a unique geographic context and a unique electrified vehicle. This geography, climate, and vehicle further the existing understanding of the factors affecting medium- and heavy-duty electric vehicles (MHDEVs) by allowing for new relationships to be tested and by assessing the generalizability of known relationships to new contexts. We find that temperature is less predictive of energy consumption for the battery electric motorcoach (BEM) in the case study environment than it is for BEBs in other studies. A mitigating factor that we presume to be working on the relationship between temperature and energy consumption is the fact that the BEM route does not stop between origin and destination to exchange passengers, and in turn, conditioned cabin air. Our model also incorporates wind speed and direction relative to travel, which is a novel contribution of our methodology. Results from our study are helpful for transit service planners, fleet operators, and logistics firms for improving their ability to predict performance of potential deployments of MHDEVs into existing operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2025

The Verification and Validation of a Magnetic Plasma Fluid Model Utilizing the MOOSE (Multiphysics Object Oriented Simulation Environment) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification, benchmarking, and validation studies have been conducted. Verification studies involved utilizing the method of manufactured solutions and comparing the convergence slope of a known solution to the theoretical slope. Benchmarking consists of comparisons to existing edge codes, namely BOUT++ and SOLEDGE3X. Validation efforts focused on comparisons against open-source data from the TCV tokamak.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

De-Risking Exploration for Geothermal Plays in Magmatic Environments Through Open-Source Tools: An Open-Source Python Framework for 2D and 3D Play Fairway Analysis

The De-Risking Exploration for Geothermal Plays in Magmatic Environments (DEEPEN) project seeks to accelerate superhot geothermal development by reducing exploration risk through advanced open-source modeling tools. This work presents a novel Python-based framework, geoPFA, for conducting 2D and 3D play fairway analysis (PFA) tailored to superhot geothermal systems. Building on previous methodologies, the framework integrates thermo-hydro-mechanical-chemical simulation outputs from TReactMech, resulting in improved representation of subsurface properties that are critical to superhot resource producibility. The workflow has been applied to the Nesjavellir field in Iceland, a candidate site for the third Iceland Deep Drilling Project's superhot production scenarios. This application demonstrates the value of modular, transparent, and extensible workflows for integrating geological, geophysical, and simulation-derived datasets in high-enthalpy environments. Preliminary results indicate favorable zones consistent with known hydrothermal activity and suggest possible upflow from the Hengill volcanic system. The geoPFA library is publicly available, offering a scalable and reproducible approach to geothermal exploration across varied geological contexts.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Simulating Thermoelectric Devices Using the MOOSE Framework

Thermoelectric generators (TEG) are devices that generate energy by converting heat into electricity or provide cooling via the Peltier effect. This feature of thermoelectric devices originates from the Seebeck, Peltier, Thomson, and Joule heating effects. TEGs can be applied in energy and thermal management systems such as waste heat recovery and refrigeration, respectively. Thermoelectric device design is influenced by the material selection and the device's geometry operating conditions. Therefore, predicting, verifying, and validating thermoelectric device performance using simulations tools is essential to deploying thermoelectric devices in industry. The Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework is an open-source simulation tool capable of modeling simple to complex systems. In this work, we demonstrate MOOSE's thermoelectric device modeling capabilities by simulating a unicouple, module, and exhaust gas recovery system. The Seebeck, Peltier, Thomson, and Joule heating physics are implemented into MOOSE. The MOOSE thermoelectric physics were thoroughly verified and validated using published COMSOL® results and experimental data. In addition, thermoelectric modules were integrated into an exhaust gas recovery system using the MOOSE MultiApp function as a demonstration of the model's ability. The verification and validation results and exhaust gas heat recovery system showcases MOOSE's capability to model thermoelectric devices and integrate these devices into practical energy systems.

42 - ENGINEERING↗
DOE OSTI2026

Post-Mortem Characterization of Cerium Speciation in Molten Calcium Chloride

Abstract Advancing radiochemistry and nuclear materials science requires understanding actinide interactions with molten salts, which are used in next-generation nuclear reactors and for processing of actinides to recover useful fissile material. Understanding chemical interactions of actinides with molten salts has been limited by challenges in developing spectroscopic and X-ray techniques that are compatible with the high temperatures necessary to study molten salts. In this work, interactions of CeO2 (serving as a nonradioactive surrogate for uranium and plutonium) with CaCl2 are characterized following heating. Scanning electron microscopy indicates CeO2 morphological changes from small (<1 μm) particles to 3–5 μm sheets. Powder X-ray diffraction and infrared and Raman spectroscopies show the formation of CeOCl at higher (850–1050 °C) temperatures. In the absence of a chemical reducing agent, it was found that a high-temperature, low-oxygen environment is the key to the formation of oxychloride and that oxychloride formation is inhibited by annealing the CeO2 starting material. Lastly, thermal analysis revealed lowering of the melting point of CaCl2 after heating with CeO2. In all, this work identifies applicable spectroscopic techniques to target studies of heavy elements in molten salt environments and highlights the relationship between chemical speciation and melting behavior, a key thermophysical property.

Kelly, Sheridon N. [Lawrence Livermore National La↗
DOE OSTI2026

Performance of reanalysis and mesoscale models off the coast of Hawai'i

The eastern Hawai'i coast in the United States is characterized by considerable wind resource fuelled by persistent trade winds, making it an important area for energy research. The need is strong for reanalyses and higher-resolution regional simulations where observations have been historically limited, such as Hawai'i's offshore environments. However, studies using offshore observations in other parts of the world have shown that significant errors can occur in reanalyses and wind datasets, which can lead to inaccurate estimates of wind energy generation, payback periods, and extreme weather risks at project locations. The degree of such errors is influenced by a number of factors, including spatial resolution and the handling of processes within the planetary boundary layer (PBL). In this work, we provide a wind resource characterization from year-long lidar buoy measurements off the eastern coast of O'ahu, Hawai'i, an environment previously unobserved at the rotor level, and use the characterization to evaluate the performance of two simulation datasets. The O'ahu deployment location is meteorologically unique and less complex than land-based wind resource characterizations, being strongly characterized by trade winds with minimal land–atmosphere interaction influences. Despite the unique and fairly consistent meteorological conditions, we hypothesize that distinct simulation datasets will exhibit diverse ranges of errors similar to those that have been seen for other offshore locations. We find the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) to strongly underestimate observed wind speeds at the O'ahu location (bias = −1.54 m s −1 at a height of 140 m above sea level), while a regional Weather Research and Forecasting Model (WRF) simulation produced by the University of Hawai'i (UH-WRF) provides a significantly smaller wind speed bias (−0.25 m s −1 ), highlighting the value of running regional, higher-resolution simulations. The large bias noted for ERA5 is driven by significant underestimation of fast wind speeds (>9 m s −1 ), which the study site is largely characterized by, along with discontinuities in the ERA5 diurnal cycle. We also speculate that the relative sparsity of observations for data assimilation in this remote part of the world could influence the performance of ERA5 and that challenges with characterizing island effects could impact the performance of both datasets.

17 WIND ENERGY↗
DOE OSTI2025

Interfacial Strong Coupling and Negative Dispersion of Propagating Polaritons in Freestanding Oxide Membranes

Membranes of complex oxides like perovskite SrTiO3 extend the multi-functional promise of oxide electronics into the nanoscale regime of 2D materials. Here, it is demonstrated that freestanding oxide membranes supply a reconfigurable platform for nano-photonics based on propagating surface phonon polaritons. Infrared near-field imaging and spectroscopy enabled by a tunable ultrafast laser are applied to study pristine nano-thick SrTiO3 membranes prepared by hybrid molecular beam epitaxy. As predicted by coupled mode theory, it is found that strong coupling of interfacial polaritons realizes symmetric and antisymmetric hybridized modes with simultaneously tunable negative and positive group velocities. By resolving reflection of these propagating modes from membrane edges, defects, and substrate structures, their dispersion is quantified with position-resolved nano-spectroscopy. Remarkably, polariton negative dispersion is found to be both robust and tunable through choice of membrane dielectric environment and thickness, and proposes a novel design for in-plane Veselago lensing harnessing this control. This work lays the foundation for tunable transformation optics at the nanoscale using polaritons in a wide range of freestanding complex oxide membranes.

freestanding oxide membranes↗
DOE OSTI2026

Quantum Theory of Surface Lattice Resonances

The collective interactions of nanoparticles arranged in periodic structures give rise to high‐ in‐plane diffractive modes known as surface lattice resonances. Although these resonances and their broader implications have been extensively studied within the framework of classical electrodynamics and linear response theory, a quantum optical theory capable of describing the dynamics of these structures, especially in the presence of material nonlinearities beyond ad hoc few‐mode approximations, is largely missing. To this end, we consider a lattice of metallic nanoparticles coupled to the electromagnetic field and derive the quantum input–output relations within the electric dipole approximation. As applications, we analyze coupling between the nanoparticle array and external quantum emitters, and show how the formalism extends to molecular optomechanics, where the high ‐factors of SLRs enable coupling to collective vibrational modes. We further consider arrays composed of saturable excitonic emitters, demonstrating how emitter nonlinearities can be used to switch the SLR condition between electronic transitions. Using a perturbative approach that accounts for population dynamics, we show how these effects can be probed in pump–probe experiments and give rise to nonlinear phase‐matching phenomena. Our work provides a microscopic framework for modeling SLRs interacting with quantum emitters without phenomenological descriptions of the electromagnetic environment.

molecular optomechanics↗
DOE OSTI2025

Interplay between hydrogen, temperature, and character angle on dissociated dislocation energies in Fe–Ni–Cr austenitic stainless steels

Dislocation energy has an important role in the mechanical performance of structural metals. While dislocation energies cannot be fully obtained from continuum theories due to the contribution of the dislocation core, they have been calculated via atomistic simulations in elemental metals. However, constraints on the local atomic environments have prevented the use of such approaches in systems that incorporate alloying or interstitial solutes. In this work, we develop robust molecular dynamics methods to resolve these issues through a geometric construction of dislocation dipoles and the calculation of time-averaged energies. Furthermore, we apply these methods to calculate dislocation energies (including core energies) in an Fe 70 Ni 11 Cr 19 austenitic steel at a variety of character angles, hydrogen concentrations, temperatures, and dipole spacings. The resulting highly converged energies show an excellent agreement with continuum expressions. Overall, hydrogen concentrations up to 1.0 % do not have a significant effect on the elastic parameters and dislocation energy. The methods and insights derived in this work have the potential to facilitate the calculation of dislocation energies in a wide range of systems, and to guide our understanding of hydrogen embrittlement.

Alloyed systems↗
DOE OSTI2024

Charge Transfer Plasmonics in Bespoke Graphene/α-RuCl 3 Cavities

Surface plasmon polaritons (SPPs) provide a window into the nano-optical, electrodynamic response of their host material and its dielectric environment. Graphene/α-RuCl 3 serves as an ideal model system for imaging SPPs since the large work function difference between these two layers facilitates charge transfer that hole dopes graphene with n ~ 10 13 cm –2 free carriers. In this work, we study the emergent THz response of graphene/α-RuCl 3 heterostructures using our home-built cryogenic scanning near-field optical microscope. Using phase-resolved imaging, we clearly observe long wavelength, heavily damped THz SPPs in a series of variable-size graphene cavities. From this, we extract the plasmonic wavelength and scattering rate in the graphene/α-RuCl 3 heterostructures. We determine that the measured plasmon wavelength and electronic scattering rate match our heterostructures’ theoretically predicted values. Here, our results demonstrate that shaping graphene into bespoke cavity structures enables observation and quantification of SPPs in heavily doped graphene that are largely not addressable with other experimental techniques. Moreover, the manifest lack of metallicity observed in the adjacent doped α-RuCl 3 layer provides significant constraints on the nature of the interfacial charge transfer in this 2D heterostructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗
DOE OSTI2026

Quantifying the relationship between electric field enhancement and plasmon-driven electron transfer

Plasmonic materials interact strongly with light to create localized, out-of-equilibrium environments with intense electromagnetic fields known as hotspots. After forming, hotspots dissipate energy into their surroundings and can transfer energy and charge carriers to nearby molecules, giving plasmonic materials the potential to drive reactions with sunlight. However, the field needs a better mechanistic understanding of plasmon–molecule interactions and how the local plasmon environment, specifically the electromagnetic field enhancement and spatial distribution of hotspots, impacts the reaction yield. Here, in this work, we mapped plasmon-driven charge transfer across ordered plasmonic substrates using diffraction-limited surface-enhanced Raman spectroscopy (SERS) microscopy to understand the relationship between the average local electric field enhancement and charge transfer reaction yield. We tracked the plasmon-induced electron transfer to buckminsterfullerene (C 60 ) and found that areas with the greatest SERS intensity were not the areas with the greatest ensemble-averaged reduction of C 60 , suggesting that areas with higher electric field enhancement—or “hotter,” more enhancing hotspots—do not improve the charge transfer reaction yield. This work shows that efforts to improve plasmon-driven charge transfer should not merely focus on creating substrates with extremely enhancing regions but also consider how other factors could optimize photoreduction yields.

Koble, MaKenna M. [Univ. of Minnesota, Minneapolis↗
DOE OSTI2024

Bacterial synergies amplify nitrogenase activity in diverse systems

Endophytes are microbes living within plant tissue, with some having the capacity to fix atmospheric nitrogen in both a free-living state and within their plant host. They are part of a diverse microbial community whose interactions sometimes result in a more productive symbiosis with the host plant. Here, we report the co-isolation of diazotrophic endophytes with synergistic partners sourced from two separate nutrient-limited sites. In the presence of these synergistic strains, the nitrogen-fixing activity of the diazotroph is amplified. One such partnership was co-isolated from extracts of plants from a nutrient-limited Hawaiian lava field and another from the roots of Populus trees on a nutrient-limited gravel bar in the Pacific Northwest. The synergistic strains were capable of increasing the nitrogenase activity of different diazotrophic species from other environments, perhaps indicating that these endophytic microbial interactions are common to environments where nutrients are particularly limited. Multiple overlapping mechanisms seem to be involved in this interaction. Though synergistic strains are likely capable of protecting nitrogenase from oxygen, another mechanism seems evident in both environments. The synergies do not depend exclusively on physical contact, indicating a secreted compound may be involved. This work offers insights into beneficial microbial interactions, providing potential avenues for optimizing inocula for use in agriculture.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Screening of Polar Electron-Phonon Interactions near the Surface of the Rashba Semiconductor BiTeCl

Understanding electron-phonon coupling in noncentrosymmetric materials is critical for controlling the internal fields which give rise to Rashba interactions. We apply time- and angle-resolved photoemission spectroscopy (trARPES) to study coherent phonons in the surface and bulk regions of the polar semiconductor BiTeCl. Aided by \textit{ab initio} calculations, our measurements reveal the coupling of out-of-plane $A_1$ modes and an in-plane $E_2$ mode. By considering how these modes modulate the electric dipole moment in each unit cell, we show that the polar $A_1$ modes are more effectively screened in the metallic surface region, while the non-polar $E_2$ mode couples in both regions. Finally, in addition to informing strategies to optically manipulate Rashba interactions, this work has broader implications for the behavior of electron-phonon coupling in systems characterized by inhomogeneous dielectric environments.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
DOE OSTI2026

Lithium–Divertor Interactions and Helium/Hydrogen Trapping in Lithiated Metals (Final Technical Report)

The goal of this project was to develop a fundamental understanding of helium and hydrogen behavior in lithium, both in bulk and at interfaces with tungsten, in order to inform the design of lithium based plasma facing components for fusion devices. Over the course of the award, the project produced the first comprehensive, peer reviewed dataset describing helium energetics, migration behaviors, and defect interactions in lithium. The research demonstrated that helium behaves in ways not previously observed in any other body centered cubic (BCC) metal: its interstitial configurations are more stable than substitutional ones, and its migration barriers are extraordinarily low, in some cases more than an order of magnitude below those in tungsten or iron. These discoveries reveal that helium in lithium diffuses so rapidly that its transport may be dominated by translational motion rather than the vibrationally activated mechanisms that underpin conventional solid state diffusion. This work lays a scientific foundation for understanding gas retention, bubble formation, and wall evolution in lithium based fusion environments and provides new computational tools, most notably a newly developed Li–He interatomic potential, for advancing future modeling efforts.

36 MATERIALS SCIENCE↗