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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Review of ECCS Acceptance Criteria and Experimental Basis Evolution Toward Fuel Fragmentation, Relocation, and Dispersal Studies

The U.S. nuclear industry is pursuing extensions of light water reactor (LWR) fuel burnup and enrichment limits to approximately 75 GWd/t and 10 wt.% 235 U to achieve economic and operational benefits. A central safety consideration in this effort is the behavior of high burnup (HBu) fuel during loss-of-coolant accidents (LOCAs), particularly fuel fragmentation, relocation, and dispersal (FFRD). Here, this work provides a historical and technical review of U.S. LOCA regulation and experimentation, clarifying how the evolution of Emergency Core Cooling System (ECCS) acceptance criteria in 10 CFR 50.46 has shaped both testing approaches and interpretations of fuel safety. The study revisits the original intent of the ECCS criteria, showing that the peak cladding temperature and equivalent cladding reacted limits were developed as surrogates to preserve a coolable geometry. The explicit inclusion of the coolable geometry criterion in the regulation was intended to emphasize the underlying safety philosophy and as a safeguard against unforeseen failure modes, an intent that remains directly relevant to modern concerns regarding FFRD. The review traces the lineage of HBu LOCA experiments to the Argonne National Laboratory furnace tests, from which subsequent programs at Studsvik, Halden, and Oak Ridge National Laboratory were derived. These tests employed a 5 °C/s heating rate inherited from early embrittlement studies, a stylized temperature history that does not represent actual LWR LOCA thermal-hydraulics. Comparison of these test conditions to pressurized water reactor large break LOCAs and separate effects data indicates that the existing HBu LOCA database may not be fully applicable to all LWR LOCA scenarios, from which a qualitative framework for applicability is proposed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Laboratory evolution in Novosphingobium aromaticivorans enables rapid catabolism of a model lignin-derived aromatic dimer

Lignin contains a variety of interunit linkages, leading to a range of potential decomposition products that can be used as carbon and energy sources by microbes. β-O-4 linkages are the most common in native lignin, and associated catabolic pathways have been well characterized. However, the fate of the mono-aromatic intermediates that result from β-O-4 dimer cleavage has not been fully elucidated. Here, we used experimental evolution to identify mutant strains of Novosphingobium aromaticivorans with improved catabolism of a model aromatic dimer containing a β-O-4 linkage, guaiacylglycerol-β-guaiacyl ether (GGE). We identified several parallel causal mutations, including a single nucleotide polymorphism in the promoter of an uncharacterized gene that roughly doubled the growth yield with GGE. We characterized the associated enzyme and demonstrated that it oxidizes an intermediate in GGE catabolism, β-hydroxypropiovanillone, to vanilloyl acetaldehyde. Identification of this enzyme and its key role in GGE catabolism furthers our understanding of catabolic pathways for lignin-derived aromatic compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Uncertainty guided online ensemble for non-stationary data streams in fusion science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior with distribution drifts, resulted by both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with such non-stationary data streams. Online learning techniques have been leveraged in other domains, however it has been largely unexplored for fusion applications. In this paper, we investigate online learning for continuous adaptation to drifting data streams in the prediction of Toroidal Field (TF) coils deflection at the DIII-D fusion facility. We further address the short-term performance degradation inherent to standard online learning, which arises because ground truth is unavailable at prediction time. To mitigate this issue, we propose an uncertainty-guided online ensemble framework. The method leverages the Deep Gaussian Process Approximation (DGPA) for calibrated uncertainty estimation and uses these uncertainty measures to guide a meta-algorithm that aggregates predictions from learners trained over different historical horizons. Our results show that online learning reduces prediction error by 80% compared to a static model. The online ensemble and the proposed uncertainty-guided ensemble further reduce error by approximately 6%, and 10% respectively, relative to standard single-model online learning, while also providing calibrated uncertainty estimates to support operational decision-making.

AI↗
DOE OSTI2025

Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2025

Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2026

Preheat effects in laser-driven Rayleigh–Taylor instability experiments at intensities greater than $10^{15}$ $\textrm{W}$ $\textrm{cm}^{-2}$ at OMEGA EP and the NIF

The propagation of high-energy X-rays or hot electrons have the potential to alter the initial conditions in experimental target designs, especially at material interfaces, for laser-driven inertial confinement fusion (ICF) and high-energy density (HED) experimental platforms. Hot-electron preheat can drastically modify the initial conditions of experimental targets used to study the deceleration-stage Rayleigh–Taylor instability (RTI) both with and without applied magnetic fields. Therefore, it is necessary to understand and quantify the impact of hot-electron preheat. The hydrodynamic (HD) capabilities in the Ares code are used to study the effects varying levels of preheat can have on RTI evolution. The experimental and computational studies presented in this work demonstrate that at high laser intensities of around or greater than 10 15 W cm −2 , there is hot-electron generation from laser plasma instabilities which induces substantial preheat and impacts the morphology of RTI evolution and even inhibits the intended RTI growth such that it is not observable experimentally. The necessity of better quantifying hot-electron induced preheat and mitigating its impact on such high-intensity direct-drive laser experiments in the future is discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Extending evolutionary forecasts across bacterial species

Improving evolutionary forecasting requires progressing from studying repeated evolution of a single genotype under identical conditions to formulating broad principles. These principles should enable predictions of how similar species will adapt to similar selective pressures. Evolve-and-resequence experiments with multiple species allow testing forecasts on different biological levels and elucidating the causes for failed predictions. Here, we show that forecasts for adaptation to static culture conditions can be extended to multiple species by testing previous predictions for Pseudomonas syringae and Pseudomonas savastanoi. In addition to sequence divergence, these species differ in their repertoire of biofilm regulatory genes and structural components. Consistent with predictions, both species repeatedly produced biofilm mutants with a wrinkly spreader phenotype. Predominantly, mutations occurred in the wsp operon, with less frequent promoter mutations near uncharacterized diguanylate cyclases. However, mutational patterns differed on the gene level, which was explained by a lack of conservation in relative fitness of mutants between more divergent species. The same mutation was the most frequent for both species suggesting that conserved mutation hotspots can increase parallel evolution. This study shows that evolutionary forecasts can be extended across species, but that differences in the genotype–phenotype–fitness map and mutational biases limit predictability on a detailed molecular level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Microstructure Clones

Background: A material’s microstructure drives its material performance. Contemporary crystal plasticity experiments compare full-field strain measurements of polycrystal specimens to models. Because each specimen is unique, it is impossible to know which features of the observed deformation are deterministic vs statistical; thus, differences between model and experiment may or may not be significant. Objective: This paper introduces the invention of microstructure clones. Microstructure clones are 2D oligocrystal specimens that have nearly identical microstructures to remedy the aforementioned experimental limitations. Having specimens with nearly identical microstructures will allow for multiple destructive tests of a microstructure (either as repeats or intentionally different experiments), an ability to “see the future” by providing insight into how a specimen will deform, variability quantification, and experimental investigations of response to small microstructural changes. Methods: This work introduces microstructure clones. Repeatability of these clones is demonstrated in tensile bars of pure nickel. Local strain measurements from digital image correlation are compared between clone specimens and compared to results from a crystal plasticity finite element model. Results: Two sets of microstructure clones were tested in this study and displayed very consistent deformation responses within each clone set. Small observed differences in deformation invite investigation into microstructure stochasticity and the effect of small microstructural and loading differences. Conclusions: Microstructure clones represent a significant shift in understanding structure–property relationships. This work reshapes experimental crystal plasticity to allow for experiments that control for specific variables, quantification of microstructural stochasticity (and other sources of stochasticity), and opportunities for replicating experiments.

Crystal Plasticity↗
DOE OSTI2025

Processing behavior evolution of recycled polypropylene: An integrated experimental and Computer-Aided engineering simulation study

Polypropylene (PP) comprises 21% of global plastics production and 18% of plastics waste, yet less than 1% of solid-waste PP is recycled in the United States (U.S.), representing significant environmental and economic challenges. Mechanical recycling, the most prevalent recycling method, subject's materials to thermomechanical stresses, which typically degrade polymer properties, affecting the quality of polymer products. This study replicates the impact of mechanical recycling through multiple extrusion cycles to examine the effects on PP's processing behavior. Dynamic scanning calorimetry (DSC) measurements showed stable melting behavior across all processing conditions, while crystallization analysis exhibited consistent shifts in kinetic parameters. Rheological characterization demonstrated progressive viscosity reductions through successive cycles, particularly pronounced at elevated reprocessing temperatures. Here, the integration of this experimental data into injection molding simulations showed that recycled PP maintains viable processing characteristics. Our findings establish quantitative correlations between processing history and material behavior, enabling optimization of processing parameters directly rather than relying on trial-and-error approaches. While these results reflect idealized recycling conditions with minimal contamination, they provide a framework for understanding fundamental property evolution during mechanical recycling.

42 ENGINEERING↗
DOE OSTI2025

Triel-Defined Helicity in One-Dimensional III–VI–VII van der Waals Crystals

Inorganic extended lattice solids that bear complex helical motifs manifest unusual physical and quantum states that arise due to their noncentrosymmetric or chiral nature. However, the systematic understanding of how elemental composition influences the structure and physical properties in helical inorganic crystals has been precluded by the rarity of these materials and the lack of modular phases that display such motifs. Here, we report the synthesis of AlSeI single crystals, the first aluminum-containing helical crystal in the III-VI-VII 1D van der Waals class. AlSeI completes the experimentally accessible triel series in the helical selene iodides alongside InSeI and GaSeI. Using the Al, Ga, and In triel series in this selene iodide class, we experimentally demonstrate the evolution of the local quasi-tetrahedral building unit geometry, chain packing, helical parameters, and band gaps based primarily on the identity of the triel atom. Our results underscore the chemical modularity of these phases, the broad range of helical parameters, and the spectrum of electronic states from the visible to the ultraviolet range in this emergent class of 1D, exfoliable, and helical extended lattice solids.

Chemical structure↗
DOE OSTI2025

An experimental and computational study of thin-layer Rayleigh–Taylor instability development during deceleration with and without an externally applied magnetic field

The importance of mitigating the Rayleigh–Taylor instability (RTI) in inertial confinement fusion (ICF) is critical to successfully achieve high gain fusion yield. Consequently, understanding the seed mechanisms of RTI and the potential evolution of RTI in ICF relevant conditions is crucial. Single feature perturbations consistently demonstrate non-linear RTI evolution, for which an experimental platform on OMEGA-EP is developed. Manufacturing defects introduced into the target design require exploration of unanticipated changes to RTI development and an identification of targets that will still render quantifiable physics results. Consequently, it is presented that the inherent 3D nature of experimental targets necessitates 3D modeling for accurate design work and predictive modeling of experimental targets, especially when high resolution imaging diagnostics, like Fresnel Zone Plates, are utilized. A study of the morphology of the RTI evolution due to changing initial conditions and the presence of an externally applied magnetic field are also explored. Experimental data show thin-layer RTI morphology comparable to resistive magneto hydrodynamic 3D results. A discussion on the impacts of an externally applied magnetic field makes the case for continued efforts to observe a magnetic field's impact on RTI morphology.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Linking Pressure to Electrochemical Evolution in Solid-State Conversion Cathode Composites

Conversion-type cathodes, such as sulfur, FeS 2 , and FeF 3 , offer high theoretical capacities in solid-state lithium batteries but are hindered by substantial volume changes during cycling, leading to interfacial contact loss, crack formation, and microstructural degradation. Here, we investigate the relationships between electrochemical, mechanical, and structural evolution in solid-state electrode composites with these three active materials. Using real-time stack-pressure monitoring, synchrotron X-ray absorption spectroscopy, and electrokinetic modeling, we elucidate how stress evolution is linked to reversible and irreversible redox reactions. Nonlinear stack pressure evolution in cells with sulfur, FeS 2 , and FeF 3 electrode composites is found to arise from material-specific volume changes, the balance of volume change between the working and counter electrode, and the formation of distinct reaction intermediates. The three materials exhibit distinct stack pressure evolution, which is closely related to the different reaction processes in the materials, as demonstrated with X-ray absorption spectroscopy measurements. Through mesoscale modeling, we relate the experimental measurements to species evolution at the particle scale and track the dynamic coexistence of intermediate phases. Our findings highlight the importance of designing for volume changes of a given active material in solid-state battery systems.

batteries↗
DOE OSTI2025

A Review of Intense Electromagnetic Fields in Heavy-Ion Collisions: Theoretical Predictions and Experimental Results

In heavy-ion collisions at relativistic energies, the incident nuclei travel at nearly the speed of light. These collisions deposit kinetic energy into the overlap region and create a high-temperature environment where hadrons “melt” into deconfined quarks and gluons. The spectator nucleons, which do not undergo scatterings, generate an ultraintense electromagnetic field—on the order of 10 18 G at the Relativistic Heavy Ion Collider and 10 19 G at the Large Hadron Collider. These powerful electromagnetic fields have a substantial impact on the produced particles, not only complicating the study of particle interactions but also inducing novel physical phenomena. To explore the nature of these fields and their interactions with deconfined quarks, we provide a detailed overview, encompassing theoretical estimations of their generation and evolution, as well as experimental efforts to detect them. We also provide physical interpretations of the discovered results and discuss potential directions for future investigations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Triaxiality of neutron-rich ruthenium nuclei studied by lifetime measurements

The breaking of axial symmetry in nuclei enables otherwise precluded behaviours, making it an interesting phenomenon to study. Experimental fingerprints such as very low-lying $2^+_2$ states suggest pronounced triaxial deformation for the neutron-rich ruthenium isotopes. Nevertheless, theoretical calculations differ in the description of the triaxial deformation and its evolution with neutron number, making experimental data crucial to understanding it. We investigated the evolution of the degree of triaxiality and $γ$ rigidity in neutron-rich ruthenium isotopes by measuring lifetimes of excited states in 108-112 Ru with the recoil distance Doppler-shift method. The experiment was carried out at the Grand Accélérateur National d’Ions Lourds using the Advanced Gamma Tracking Array coupled to the Variable Mode Spectrometer. We obtained B(E2) values for 29 transitions in the studied nuclei and compared them with fully microscopic symmetry conserving configuration mixing calculations, and phenomenological generalized triaxial rotor and triaxial particle-rotor models. The models generally reproduce the measured transition strengths, and show an increase in triaxiality with neutron number, reaching near maximum triaxiality in 112 Ru. The results are consistent with a transition from soft to rigid motion as the neutron number increases.

Heines, Johannes Sorby [Univ. of Oslo (Norway); No↗
DOE OSTI2025

Comparison of laser-produced plasma spatio-temporal electron density evolution measured using interferometry with simulation results

Due to the difficulties associated with experimental measurements of laser-produced plasma (LPP) properties during the earliest stages of plasma evolution, radiation hydrodynamic codes are often used. However, although these codes have been extensively validated in the higher intensity regimes, validation at low to moderate intensities has been limited. In this study, the spatio-temporal electron density evolution in an LPP generated at moderate laser intensities and at various laser wavelengths was validated against the FLASH code for times up to 20 ns. The LPP was generated by focusing the fundamental and various harmonics radiation (1064, 532, and 266 nm) from a 6 ns full width half maximum Nd:YAG laser, at a laser intensity of 10 GW cm -2 , onto a copper target. The spatio-temporal density evolution of the expanding plasma was analyzed using Nomarski interferometry. Experimental measurements were found to be consistent with FLASH simulations, and the dependence of electron densities on wavelength was found to be in agreement with analytical models, varying as n e ∝ λ -0.7 . However, slight differences were noted in the widths and shape functions of the experimental and simulated electron density profiles.

2D fast imaging↗
DOE OSTI2025

A microstructural signature of the coesite-quartz transformation: New insights from high-pressure experiments and EBSD

Ultra-high pressure (UHP) metamorphism is difficult to identify in continental crust as few petrological barometers are suitable for dominantly felsic lithologies. In such cases, burial to extreme depths is commonly identified through the preservation of coesite, a high-pressure polymorph of SiO 2 that typically forms at depths exceeding ∼ 100 km (i.e., > 2 GPa pressure). Unfortunately, coesite readily transforms to quartz upon exhumation, meaning that UHP terranes may often be overlooked. While some studies have suggested that quartz may inherit an orientation signature indicative of former coesite, both the specific nature of this signature and the conditions favouring its development remain uncertain. Here, to address this problem, we combine electron backscatter diffraction analysis of natural and experimental samples to explore microstructural evolution across the coesite-quartz phase transformation. We demonstrate that neighbouring domains of quartz commonly feature an 84 ± 4° rotation of [c] axes around the pole of a common {m} plane. This orientation relationship is a product of epitaxy, whereby the {$11\bar{2}2$} Japan twin plane in quartz nucleates on the (010) plane in coesite. In supercell simulations, the nucleation of Japan twins can be explained by the energetically favourable alignment of quartz tetrahedra on parental coesite tetrahedra. Through experiments, we demonstrate that this signature emerges over a broad range of conditions, regardless of the availability of nucleation sites (e.g., grain boundaries) or the density of crystal lattice defects (e.g., dislocations). Overall, our work provides a quantitative and unambiguous tool for identifying UHP terranes from quartz in isolation.

Coesite↗
DOE OSTI2025

Surface Charge in Electrical Double Layer as a Kinetic Descriptor of Electrocatalytic Reactions

The successful commercialization of electrochemical energy-conversion systems hinges on a deeper understanding of electrocatalytic reaction kinetics. Despite extensive research, a key descriptor that characterizes electrolyte effects on reaction kinetics remains elusive. Here, surface charge in electrical double layers (EDLs) is introduced as a descriptor for electrolyte-dependent kinetics. The surface charge is calculated with a continuum EDL model parameterized by density-functional theory. The model is validated by reproducing the anomalously low slope of Pt(111) in Parsons-Zobel plots. Strong correlations are observed between calculated surface charge and experimental kinetic currents for hydrogen evolution, oxygen reduction, and CO 2 -reduction reactions across various pH levels and cationic species. These correlations can be either promotional or inhibitory, depending on solute-intermediate interactions. In acidic media, incorporating adsorbate charge captures specific adsorption effects in oxygen reduction reaction. In conclusion, these findings establish surface charge density as a key descriptor for electrolyte-dependent kinetics, which will guide the design of the electrode/electrolyte interface.

Adsorption↗