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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks (Final Technical Report)

This is the final technical report from the first phase of a project that changed institutions. The grant was titled “Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks.” The overall objectives of this project were to (1) provide model‐compatible datasets of key plant hydraulic traits and status for model evaluation, parameterization and validation and (2) use these data to pinpoint ecosystem responses to a changing hydroclimate by addressing both long‐term climatic drying and episodic extreme droughts. We planned to address the objectives with three research activities to quantify plant responses to chronic water stress and episodic drought: (1) generate high frequency observations of soil and plant hydraulic data across different landscape positions at multiple sites, (2) quantify plant hydraulic trait plasticity in response to experimental soil moisture reduction in situ in two central hardwood forests, and (3) simulate the carbon consequences of incorporating plant hydrodynamics and plant acclimation to water stress in the DOE‐sponsored plant hydrodynamics model FATES‐HYDRO. As of the transfer of this project to another institution, we had made substantial progress on activities 1 and 2, and started activity 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Identifying geological structures through microseismic cluster and burst analyses complementing active seismic interpretation

At the Decatur carbon capture and storage site (IL, USA) CO 2 has been injected from 2011–2014 and from 2017 to present near the base of the Lower Mt. Simon Sandstone saline reservoir, resulting in microseismicity. Microseismicity is mainly located in the basement and distributed in distinct spatial clusters. The lack of significant impedance contrasts within the basement makes the interpretation of active-source seismic reflection data challenging, however, recent reprocessing allowed to resolve faults above and at the top of the basement. These faults generally do not coincide with the location of microseismic events and their continuation to the general depth of the seismic events cannot be assumed. This paper shows how the interpretation of the microseismicity can complement structural interpretations of active-source seismic reflection data. In particular, we analyze clusters and bursts (abrupt increases) of microseismicity, identify unresolved, smaller-scale weaknesses and extract statistical parameters. These parameters allow comparisons with the interpreted faults, and with fracture sets intercepted by boreholes. During injection at the Decatur site, the injection pressure was kept far below fracture pressure, nevertheless, seismic events were induced and spread far beyond the expected extent of the CO 2 plume. We argue that local stress transfers related to the CO 2 injection reactivated pre-existing fractures within the critically stressed basement. Finally, we conducted a slip tendency analysis for faults interpreted from active seismic, selected cluster, bursts and nodal planes from focal mechanisms to determine if the interpreted structures are optimally oriented with respect to the stress regime. Our results suggest that the orientation of fractures close to the injection well, generally shows slight deviations from the optimal orientation for slip. This might indicate either slight local deviations of the maximum horizontal stress azimuth from the average direction used in the analysis, or the lack of optimally oriented fractures at this location.

58 GEOSCIENCES↗
DOE OSTI2022

Analysis of Postulated Accident Scenarios for the Transformational Challenge Reactor

The Transformational Challenge Reactor (TCR) is a helium-cooled, yttrium-hydride-moderated reactor that was designed for the U.S. Department of Energy Office of Nuclear Energy. A key objective of the TCR was to employ advanced manufacturing techniques in a nuclear system and demonstrate their potential for revolutionizing the nuclear reactor design process. One purpose of the present work is to demonstrate the safety of the TCR under postulated accidents. Based on RELAP5-3D and COMSOL analyses, the TCR remained below all current safety limits and far below the expected failure limits for the core materials. Another purpose of this work is to provide useful insights and recommendations regarding the application of RELAP5-3D to gas-cooled or other advanced reactors. A novel approach was implemented for simultaneously modeling conduction and radiation in RELAP5-3D, which was found to provide reasonable predictions of radial core, vessel, and ex-vessel heat transfer during postulated events. A multicode approach was also applied, in which high-fidelity COMSOL calculations were used to tune the radial heat transfer parameters in RELAP5-3D. The tuned RELAP5-3D model demonstrated comparable peak temperature predictions as COMSOL, despite a coarse treatment of the core in RELAP5-3D consisting of only two lumped heat structures. This high-fidelity tuning approach enabled enhanced accuracy as well as minimal complexity within the RELAP5-3D model, even for complex fuel geometric designs as in the TCR. Finally, investigations were made into the potential for flow reversal during a pressurized loss-of-forced-flow event in the TCR. The TCR is designed with downward helium flow through the core during normal operation. The RELAP5-3D model predicted that this downward flow would persist, without flow reversal, up to several days after the circulator trip. This was attributed to natural circulation hysteresis effects as have been noted in similar thermofluidic systems. Although flow stagnation and eventual reversal did not lead to unsafe TCR conditions, interesting spatial effects were observed which may have safety relevance for other reactor system designs and coolant types that are designed for downward core flow during normal operation, warranting closer investigation of the flow reversal phenomenon.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Revisiting the first Sandia Fracture Challenge with transient deformation heating and strain localization considerations

In this study, we present a systematic experimental study and accompanying theoretical analysis of the dependence of ductile fracture on strain localization, strain hardening rates, deformation-induced thermal softening, and transient heat conduction under spatially uniform as well as spatially heterogeneous deformation. Spatially uniform cases are studied via standard dogbone shaped specimens subject to uniaxial tension. Spatially heterogeneous deformation is studied via the so-called Sandia Fracture Challenge (SFC) specimen, which is a standard compact tension specimen modified with three machined holes in front of a blunt notch. We utilize the same precipitation hardened martensitic stainless steel used in the first SFC experiments, i.e. 15-5 PH with an H1075 heat treatment. We also study 15-5 PH in Condition A and with the H900 heat treatment, each of which has a different hardening behavior and ductility. We find that the ductility does not correlate with the deformation to first crack initiation in the SFC specimen. Instead, hardening rates are better correlated. Moreover, a re-examination finds that an accurate calibration of the hardening rates is strongly correlated with accurate blind predictions of ductile fracture in the SFC specimens. Given that thermal softening can greatly affect hardening rates, we provided a thermographic analysis of deformation-induced heating and transient heat transfer in both the dogbone shaped samples and the SFC specimens. Transient heating in stainless steels is found to have first-order effects on the strain at the onset of necking, strain to fracture, as well as strain localization and ductile fracture in complex geometries even under so-called quasi-static loading rates.

42 ENGINEERING↗
DOE OSTI2022

Momentum conservation in current drive and alpha-channeling-mediated rotation drive

Alpha channeling uses waves to extract hot ash from a fusion plasma, transferring energy from the ash to the wave. It has been proposed that this process could create a radial electric field, efficiently driving E × B rotation. However, existing theories ignore the nonresonant particles, which play a critical role in enforcing momentum conservation in quasilinear theory. Because cross field charge transport and momentum conservation are fundamentally linked, this non-consistency throws the rotation drive into question. This paper has two main goals. First, we provide a pedantic and cohesive introduction to the recently developed simple, general, self-consistent quasilinear theory for electrostatic waves that explains the torques which allow for current drive parallel to the magnetic field, and charge extraction across it; a theory that has largely resolved the question of rotation drive by alpha channeling. We show how the theory reveals a fundamental difference between the reaction of nonresonant particles to plane waves that grow in time vs steady-state waves that have a nonuniform spatial structure, allowing rotation drive in the latter case while precluding it in the former, and we review the local and global conservation laws that lead to this result. Second, we provide two new results in support of the theory. First, we provide a novel two-particle Hamiltonian model that rigorously establishes the relationship between charge transport and momentum conservation. Second, we compare the new quasilinear theory to the oscillation-center theories of ponderomotive forces, showing how the latter often obscure the time-dependent nonresonant recoil, but ultimately lead to similar results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Neural Network‐Based Methods for Ocean Surface Wave Measurement Using Submarine Distributed Acoustic Sensing (DAS)

Two new data-driven models for estimating ocean surface waves from distributed acoustic sensing (DAS) submarine cable strain rate are developed using supervised machine learning on a 10-day data set collected offshore of Oliktok Point, Alaska. The new models were trained on target data from seafloor pressure moorings at three sites spaced evenly along 27.1 km of cable and were benchmarked against an empirical transfer function method previously used to estimate waves from DAS. A model which uses convolutional neural networks to transform 2-km frequency-wavenumber strain spectra to seafloor pressure spectra outperforms the benchmark in wave height prediction (RMSE of 0.15 vs. 0.41 m) and period prediction (0.29 vs. 0.37 s) when evaluated on a held-out test data set. When applied to a DAS data set collected on the same cable 2 years prior, the CNN-based model maintained similar significant wave height performance (RMSE = 0.23 m) relative to available satellite altimetry data. A two-hidden-layer, fully connected neural network which transforms 1-D strain spectra to seafloor pressure spectra also outperforms the benchmark in wave height prediction (RMSE of 0.19 vs. 0.41 m), but does not generalize as well to the prior data. Regression-based machine learning is useful for estimating waves from DAS data when the pressure-strain relationship varies temporally and spatially across different wave conditions. Models can be applied to DAS data to measure waves with higher spatial resolution and longer temporal coverage than traditional methods, which often measure waves only at a single point.

Davis, Jacob R. [Univ. of Washington, Seattle, WA ↗
DOE OSTI2025

Nanotomography for Quantitative 3D Particle Reconstruction

Particulates are ubiquitous across fuel cycle operations and carry critical information about particle formation, processing, and potential proliferation-related activities. Traditional analytical techniques, including micro-Raman spectroscopy and standard electron microscopy, are often limited in spatial resolution or dimensionality, particularly when used to examine metallic or submicron-scale features. Understanding particle morphology, phase distribution, and internal porosity is essential for constraining formation conditions, thermodynamic environments, and material transport behavior. In this report, we demonstrate the application of plasma focused ion beam nanotomography to reconstruct micron-scale particulates at nanoscale resolution. Using high-resolution backscattered electron imaging and Avizo software, we obtained 3D reconstructions that enabled quantitative analysis of particle morphology, phase composition, and internal voids. Representative examples include a Ta particle with a large central void and a composite particle with embedded tetrahedral crystalline structures. These reconstructions reveal structural and compositional details that are inaccessible through conventional 2D imaging. The results demonstrate that nanotomography provides both qualitative and quantitative insights into particle formation and behavior. Using nanotomography, porosity and phase distributions can be quantified to inform models of particle density, transport, and solidification conditions. Beyond technical insights, the workflow developed here establishes a transferable capability for analyzing heterogeneous particles and has potential applications in bulk materials studies via x-ray computed tomography or other volumetric imaging modalities. Ongoing efforts are focused on optimizing the workflow to process multiple particles simultaneously, increasing throughput and statistical robustness. Overall, this work illustrates the power of nanotomography as a tool for connecting particulate morphology to formation mechanisms, composition, and transport, thereby strengthening analytical capabilities for nuclear forensics, fuel cycle analysis, and related scientific investigations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING↗
DOE OSTI2021

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Unification of nonequilibrium molecular dynamics and the mode-resolved phonon Boltzmann equation for thermal transport simulations

Nano-size confinement induces many intriguing non-Fourier heat conduction phenomena, such as nonlinear temperature gradients, temperature jumps near the contacts, and size-dependent thermal conductivity. Over the past decades, these effects have been studied and interpreted by nonequilibrium molecular dynamics (NEMD) and phonon Boltzmann transport equation (BTE) simulations separately, but no theory that unifies these two methods has ever been established. In this work, we unify these methods using a quantitative mode-level comparison and demonstrate that they are equivalent for various thermostats. We show that different thermostats result in different non-Fourier thermal transport characteristics due to the different mode-level phonon excitations inside the thermostats, which explains the different size-dependent thermal conductivities calculated using different reservoirs, even though they give the same bulk thermal conductivity. Specifically, the Langevin thermostat behaves like a thermalizing boundary in phonon BTE and provides mode-level thermal-equilibrium phonon outlets, while the Nose-Hoover chain thermostat and velocity rescaling method behave like biased reservoirs, which provide a spatially uniform heat generation and mode-level nonequilibrium phonon outlets. These findings explain why different experimental measurement methods can yield different size-dependent thermal conductivity. They also indicate that the thermal conductivity of materials can be tuned for various applications by specifically designing thermostats. Finally, the unification of NEMD and phonon BTE will largely facilitate the study of thermal transport in complex systems in the future by, e.g., replacing computationally unaffordable first-principles NEMD simulations with computationally less expensive spectral BTE simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Electronic structure and photophysics of a supermolecular iron complex having a long MLCT-state lifetime and panchromatic absorption

Exploiting earth-abundant iron-based metal complexes as high-performance photosensitizers demands long-lived electronically excited metal-to-ligand charge-transfer (MLCT) states, but these species suffer typically from femtosecond timescale charge-transfer (CT)-state quenching by low-lying nonreactive metal-centered (MC) states. Here, we engineer supermolecular Fe(II) chromophores based on the bis(tridentate-ligand)metal(II)-ethyne-(porphinato)zinc(II) conjugated framework, previously shown to give rise to highly delocalized low-lying 3 MLCT states for other Group VIII metal (Ru, Os) complexes. Electronic spectral, potentiometric, and ultrafast pump–probe transient dynamical data demonstrate that a combination of a strong σ-donating tridentate ligand and a (porphinato)zinc(II) moiety with low-lying π*-energy levels, sufficiently destabilize MC states and stabilize supermolecular MLCT states to realize Fe(II) complexes that express 3 MLCT state photophysics reminiscent of their heavy-metal analogs. The resulting Fe(II) chromophore archetype, FeNHCPZn, features a highly polarized CT state having a profoundly extended 3MLCT lifetime (160 ps), 3 MLCT phosphorescence, and ambient environment stability. Density functional and domain-based local pair natural orbital coupled cluster [DLPNO-CCSD(T)] theory reveal triplet-state wavefunction spatial distributions consistent with electronic spectroscopic and excited-state dynamical data, further underscoring the dramatic Fe metal-to-extended ligand CT character of electronically excited FeNHCPZn. This design further prompts intense panchromatic absorptivity via redistributing high-energy absorptive oscillator strength throughout the visible spectral domain, while maintaining a substantial excited-state oxidation potential for wide-ranging photochemistry––highlighted by the ability of FeNHCPZn to photoinject charges into a SnO 2 /FTO electrode in a dye-sensitized solar cell (DSSC) architecture. Concepts enumerated herein afford opportunities for replacing traditional rare-metal–based emitters for solar-energy conversion and photoluminescence applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Multimessenger signals of heavy axionlike particles in core-collapse supernovae: Two-dimensional simulations

Core-collapse supernovae are a useful laboratory to probe the nature of exotic particles. If axionlike particles (ALPs) are produced in supernovae, they can affect the transfer of energy and leave traces in observational signatures. In this work, we present results from two-dimensional supernova models including the effects of the production and the absorption of ALPs that couple with photons. It is found that the additional heating induced by ALPs can enhance the diagnostic energy of explosion, E diag . For example, for moderate ALP-photon coupling, we find explosion energies ~0.6×10 51 erg compared to our reference model without ALPs of ~0.4×10 51 erg in the first ~0.5 s postbounce explored in this work. Further, our findings indicate that when the coupling constant is sufficiently high, the neutrino luminosities and mean energies are decreased because of the additional cooling of the proto-neutron star via ALPs. The gravitational wave amplitude is also reduced because the mass accretion on the proto-neutron star is suppressed. Although the ALP-photon coupling can foster explodability, including enhancing the explosion energy closer to recent observations, more long-term simulations in three spatial dimensions are needed to draw robust conclusions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A prototype scintillator real‐time beam monitor for ultra‐high dose rate radiotherapy

Background: FLASH Radiotherapy (RT) is an emergent cancer RT modality where an entire therapeutic dose is delivered at more than 1000 times higher dose rate than conventional RT. For clinical trials to be conducted safely, a precise and fast beam monitor that can generate out-of-tolerance beam interrupts is required. This paper describes the overall concept and provides results from a prototype ultra-fast, scintillator-based beam monitor for both proton and electron beam FLASH applications. Purpose: A FLASH Beam Scintillator Monitor (FBSM) is being developed that employs a novel proprietary scintillator material. The FBSM has capabilities that conventional RT detector technologies are unable to simultaneously provide: (1) large area coverage; (2) a low mass profile; (3) a linear response over a broad dynamic range; (4) radiation hardness; (5) real-time analysis to provide an IEC-compliant fast beam-interrupt signal based on true two-dimensional beam imaging, radiation dosimetry and excellent spatial resolution. Methods: The FBSM uses a proprietary low mass, less than 0.5 mm water equivalent, non-hygroscopic, radiation tolerant scintillator material (designated HM: hybrid material) that is viewed by high frame rate CMOS cameras. Folded optics using mirrors enable a thin monitor profile of ∼10 cm. A field programmable gate array (FPGA) data acquisition system generates real-time analysis on a time scale appropriate to the FLASH RT beam modality: 100–1000 Hz for pulsed electrons and 10–20 kHz for quasi-continuous scanning proton pencil beams. An ion beam monitor served as the initial development platform for this work and was tested in low energy heavy-ion beams ( 86 Kr +26 and protons). A prototype FBSM was fabricated and then tested in various radiation beams that included FLASH level dose per pulse electron beams, and a hospital RT clinic with electron beams. Results: Results presented in this report include image quality, response linearity, radiation hardness, spatial resolution, and real-time data processing. Furthermore, the HM scintillator was found to be highly radiation damage resistant. It exhibited a small 0.025%/kGy signal decrease from a 216 kGy cumulative dose resulting from continuous exposure for 15 min at a FLASH compatible dose rate of 237 Gy/s. Measurements of the signal amplitude versus beam fluence demonstrate linear response of the FBSM at FLASH compatible dose rates of >40 Gy/s. Comparison with commercial Gafchromic film indicates that the FBSM produces a high resolution 2D beam image and can reproduce a nearly identical beam profile, including primary beam tails. The spatial resolution was measured at 35–40 µm. Tests of the firmware beta version show successful operation at 20 000 Hz frame rate or 50 µs/frame, where the real-time analysis of the beam parameters is achieved in less than 1 µs. Conclusions: The FBSM is designed to provide real-time beam profile monitoring over a large active area without significantly degrading the beam quality. A prototype device has been staged in particle beams at currents of single particles up to FLASH level dose rates, using both continuous ion beams and pulsed electron beams. Using a novel scintillator, beam profiling has been demonstrated for currents extending from single particles to 10 nA currents. Radiation damage is minimal and even under FLASH conditions would require ≥50 kGy of accumulated exposure in a single spot to result in a 1% decrease in signal output. Beam imaging is comparable to radiochromic films, and provides immediate images without hours of processing. Real-time data processing, taking less than 50 µs (combined data transfer and analysis times), has been implemented in firmware for 20 kHz frame rates for continuous proton beams.

2D beam imaging↗
DOE OSTI2020

Isoenergetic two-photon excitation enhances solvent-to-solute excited-state proton transfer

Two-photon excitation (TPE) is an attractive means for controlling chemistry in both space and time. Since isoenergetic one- and twophoton excitations (OPE and TPE) in non-centrosymmetric molecules are allowed to reach the same excited state, it is usually assumed that they produce similar excited-state reactivity. We compare the solvent-to-solute excited-state proton transfer of the super photobase FR0-SB following isoenergetic OPE and TPE. We find up to 62% increased reactivity following TPE compared to OPE. From steady-state spectroscopy, we rule out the involvement of different excited states and find that OPE and TPE spectra are identical in non-polar solvents but not in polar ones. We propose that differences in the matrix elements that contribute to the two-photon absorption cross sections lead to the observed enhanced isoenergetic reactivity, consistent with the predictions of our high-level coupledcluster-based computational protocol. We find that polar solvent configurations favor greater dipole moment change between ground and excited states, which enters the probability for TPE as the absolute value squared. This, in turn, causes a difference in the Franck– Condon region reached via TPE compared to OPE. We conclude that a new method has been found for controlling chemical reactivity via the matrix elements that affect two-photon cross sections, which may be of great utility for spatial and temporal precision chemistry.

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

Thermal Conductivity Degradation in High Burnup U-Pu-Zr Fuel

Recent advancements in the characterization of irradiated U-Pu-Zr fuels have revealed complexities that challenge existing understanding of constituent redistribution. Traditionally, models have proposed three concentric regions within the fuel, each characterized by distinctive phases and porosity. However, through detailed analysis of high burnup U-Pu-Zr, we discovered the presence of four distinct constituent redistribution regions. Particularly novel is the observation of significant Pu redistribution, a previously unreported phenomenon that necessitates a reevaluation of current models. This work aims to delve deeper into these findings, seeking to correlate mesoscale measurements of thermal diffusivity and respective thermal conductivity with the phases present in each redistribution region. To achieve this objective, we employed mesoscale thermoreflectance methods using the unique, Idaho National Laboratory (INL) developed, Thermal Conductivity Microscope (TCM) at INL’s Irradiated Materials Characterization Laboratory. The TCM employs two tightly focused lasers: one for heating to generate periodic thermal waves in the substrate, and another spatially separated probe laser to detect changes in the optical reflectivity of the gold-coated substrate resulting from thermal wave diffusion. We conducted several thermal diffusivity measurements within each region of constituent redistribution of a U-19Pu-10Zr fuel pin cross section irradiated to 11 at. % burnup. The TCM measurement positions strategically aligned with transmission electron microscopy (TEM) lift-out locations previously collected from the fuel sample. Complementary microstructural analysis techniques such as optical and scanning electron microscopy (OM/SEM), electron probe microanalysis for chemical compositions, and TEM-based selective area electron diffraction (SAED) analysis for crystallographic insights into each phase were also utilized. This comprehensive approach allowed us to correlate local thermal diffusivity data with microstructural characteristics, enabling the computation of local thermal conductivity at each position. The significance of this contribution lies in its pioneering use of the TCM for ternary fuel mesoscale examination, shedding light on the previously overlooked effects of Pu redistribution on local thermal conductivity. By informing current models capturing constituent redistribution and heat transfer, our findings pave the way for more accurate predictions of metallic fuel performance. Moreover, this work sets the stage for future comparisons with similar TCM examinations on U-19Pu-10Zr fuels at ultra-low burnup, facilitating a comprehensive understanding of thermal property changes across different burnup levels. Ultimately, our study not only enriches our understanding of the thermophysical properties of individual redistribution regions within U-Pu-Zr fuel but also offers valuable insights for the design and operational parameters of proposed next-generation fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Embedding PbS Quantum Dots (QDs) in Pb-Halide Perovskite Matrices: QD Surface Chemistry and Antisolvent Effects on QD Dispersion and Confinement Properties

Hybrid materials of metal chalcogenide colloidal quantum dots (QDs) embedded in metal halide perovskites (MHPs) have led to composites with synergistic properties. Here, we investigate how QD size, surface chemistry, and MHP film formation methods affect the resulting optoelectronic properties of QD/MHP “dot-in-matrix” systems. We monitor the QD absorption and photoluminescence throughout synthesis, ligand exchange, and transfer into the MHP ink, and we characterize the final QD/MHP films via electron microscopy and transient absorption. In addition, we are the first to globally map how PbS QDs are distributed on the micrometer scale within these dot-in-matrix systems, using three-dimensional (3D) tomography time-of-flight secondary ion mass spectrometry. The surface chemistry imparted during synthesis directly affects the optical properties of the dot-in-matrix composites. Pb-halide passivation leads to QD/MHP dot-in-matrix samples with optical properties that are well-described by a theoretical model, based on a Type I finite-barrier heterostructure between the PbS QD and the MHP matrix. Samples without Pb-halide passivation show complicated size-dependent behavior, indicating a transition from a Type I heterostructure between the PbS QD wells and MHP barriers for small-sized QDs to PbS QDs that are electronically decoupled from the MHP matrix for larger QDs. Furthermore, the choice in perovskite antisolvent crystallization method leads to a difference in the spatial QD distribution within the perovskite matrix, differences in carrier lifetime, and photoluminescence shifts of up to 180 meV for PbS in methylammonium lead iodide. This work establishes an understanding of such emerging synergistic systems relevant for technologies such as photovoltaics, infrared emitters and detectors, and other unexplored technological applications.

92 SC - Basic Energy Sciences (BES) (SC-22)↗
DOE OSTI2026

Strain-Modified Raman Responses in Monolayer MoS 2 Nanobubbles Resolved at 5 nm

The formation of nanoscale bubbles is an unavoidable consequence during the transfer of two-dimensional materials onto target substrates, driven by van der Waals interactions at the interface. While often viewed as imperfections, these nanoscale bubbles have garnered considerable scientific interest due to the substantial in-plane strain gradients they induce, which in turn give rise to a variety of intriguing optoelectronic effects, particularly in semiconducting transition metal dichalcogenides. Determining and analyzing the strain distribution within nanobubbles at the nanoscale is crucial for advancing our understanding of these underlying strain-induced effects. Here, we present a high-resolution scanning tunneling microscopy-based tip-enhanced Raman spectroscopic investigation of localized nanoscale strain distribution within the nanobubbles formed between monolayer MoS 2 and Au interface. By employing cryogenic temperature (78 K), we successfully differentiate the nanoscale Raman signatures between nanobubble edge and pristine MoS 2 . We verify a maximum tensile strain of ∽1.15–1.34% at the nanobubble edge, which gradually diminishes toward the center, yielding a cross-sectional strain profile consistent with a doughnut-shaped distribution. Furthermore, we report to achieve ∽5 nm spatial resolution in probing such edge-localized strain within the nanobubble. In addition, comparative average strain analysis of such MoS 2 nanobubbles is conducted via geometric mechanistic analysis such as membrane and nonlinear plate theories, providing key insight into the geometric nature near the bubble edge. Our work provide fundamental information about strain-induced nanoscale chemical understanding of 2D materials on the nanometer scale, paving the way for practical applications of nanobubbles in strain-engineered optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

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