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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 OSTI2025

Extending the capillary wave model to include the effect of bending rigidity: X-ray reflectivity and diffuse scattering

The surface roughness of a thin film at a liquid interface exhibits contributions of thermally excited fluctuations. This thermal roughness depends on temperature (𝑇), surface tension (𝛾), and elastic material properties, specifically the bending modulus (𝜅) of the film. A nonzero 𝜅 suppresses the thermal roughness at small length scales compared to an interface with zero 𝜅, as expressed by the power spectral density of the thermal roughness. The description of the x-ray scattering of the standard capillary wave model (CWM), which is valid for zero 𝜅, is extended to include the effect of 𝜅. The extended CWM (eCWM) provides a single analytical form for both the specular x-ray reflectivity (XRR) and the diffuse scattering around the specular reflection, and recovers the expression of the CWM at its zero 𝜅 limit. This theoretical approach enables the use of single-shot grazing incidence x-ray off-specular scattering (GIXOS) measurements for characterizing the structure of thin films on a liquid surface. The eCWM analysis approach decouples the thermal roughness factor from the surface scattering signal, providing direct access to the intrinsic surface-normal structure of the film and its bending modulus. Moreover, the eCWM facilitates the calculation of reflectivity at any desired resolution (pseudo-XRR approach). The transformation into pseudo-XRR provides the benefit of using widely available XRR software to perform GIXOS analysis. The extended range of the vertical scattering vector (𝑄 𝑧 ) available with the GIXOS pseudo-XRR approach allows for a higher spatial resolution than with conventional XRR. Experimental results are presented for various lipid systems, showing strong agreement between conventional specular XRR and pseudo-XRR methods. This agreement validates the proposed approach and highlights its utility for analyzing soft, thin films.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Bayesian mixture model approach to quantifying the empirical nuclear saturation point

The equation of state (EOS) in the limit of infinite symmetric nuclear matter exhibits an equilibrium density, $n_0 \approx 0.16 \, \mathrm{fm}^{-3}$, at which the pressure vanishes and the energy per particle attains its minimum, $E_0 \approx -16 \, \mathrm{MeV}$. Although not directly measurable, the nuclear saturation point $(n_0,E_0)$ can be extrapolated by density functional theory (DFT), providing tight constraints for microscopic interactions derived from chiral effective field theory (EFT). However, when considering several DFT predictions for $(n_0,E_0)$ from Skyrme and Relativistic Mean Field (RMF) models together, a discrepancy between these model classes emerges at high confidence levels that each model prediction's uncertainty cannot explain. How can we leverage these DFT constraints to rigorously benchmark nuclear saturation properties of chiral interactions? To address this question, we present a Bayesian mixture model that combines multiple DFT predictions for $(n_0,E_0)$ using an efficient conjugate prior approach. The inferred posterior distribution for the saturation point's mean and covariance matrix follows a Normal-inverse-Wishart class, resulting in posterior predictives in the form of correlated, bivariate $t$-distributions. The DFT uncertainty reports are then used to mix these posteriors using an ordinary Monte Carlo approach. At the 95\% credibility level, we estimate $n_0 \approx 0.157 \pm 0.010 \, \mathrm{fm}^{-3}$ and $E_0 \approx -15.97 \pm 0.40 \, \mathrm{MeV}$ for the marginal (univariate) $t$-distributions. Combined with chiral EFT calculations of the pure neutron matter EOS, we obtain bivariate normal distributions for the nuclear symmetry energy and its slope parameter evaluated at $n_0$: $S_v \approx 32.0 \pm 1.1 \, \mathrm{MeV}$ and $L\approx 52.6\pm 8.1 \, \mathrm{MeV}$ (95\%), respectively. Furthermore, our Bayesian framework is publicly available, so practitioners can readily use and extend our results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This GDR submission includes those weights. The weighting was done using two different approaches: one based on expert opinions, and one based on statistical learning. The weights are intended to describe how useful a particular exploration method is for imaging each component of each play type. They may be adjusted based on the characteristics of the resource under investigation, knowledge of the quality of the dataset, or simply to reduce the impact a single dataset has on the resulting outputs. Within the DEEPEN PFA, separate sets of weights are produced for each component of each play type, since exploration methods hold different levels of importance for detecting each play component, within each play type. The weights for conventional hydrothermal systems were based on the average of the normalized weights used in the DOE-funded PFA projects that were focused on magmatic plays. This decision was made because conventional hydrothermal plays are already well-studied and understood, and therefore it is logical to use existing weights where possible. In contrast, a true PFA has never been applied to superhot EGS or supercritical plays, meaning that exploration methods have never been weighted in terms of their utility in imaging the components of these plays. To produce weights for superhot EGS and supercritical plays, two different approaches were used: one based on expert opinion and the analytical hierarchy process (AHP), and another using a statistical approach based on principal component analysis (PCA). The weights are intended to provide standardized sets of weights for each play type in all magmatic geothermal systems. Two different approaches were used to investigate whether a more data-centric approach might allow new insights into the datasets, and also to analyze how different weighting approaches impact the outcomes. The expert/AHP approach involved using an online tool (https://bpmsg.com/ahp/) with built-in forms to make pairwise comparisons which are used to rank exploration methods against one-another. The inputs are then combined in a quantitative way, ultimately producing a set of consensus-based weights. To minimize the burden on each individual participant, the forms were completed in group discussions. While the group setting means that there is potential for some opinions to outweigh others, it also provides a venue for conversation to take place, in theory leading the group to a more robust consensus then what can be achieved on an individual basis. This exercise was done with two separate groups: one consisting of U.S.-based experts, and one consisting of Iceland-based experts in magmatic geothermal systems. The two sets of weights were then averaged to produce what we will from here on refer to as the "expert opinion-based weights," or "expert weights" for short. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. More information on this approach along with the dataset used to produce the statistical weights may be found in the linked dataset below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Fast Magnetic Reconnection with Turbulence in High Lundquist Number Limit

Here, we use extensive 3D resistive MHD simulations to study how large-scale current sheets will undergo fast reconnection in the high Lundquist number S limit (above ~104), when the system is subject to different externally driven turbulence levels and the self-generated turbulence produced by 3D reconnection dynamics. We find that the normalized global reconnection rate ~0.01–0.13 is weakly dependent on S. Global reconnection with the classic inflow/outflow configurations is observed, and 3D flux ropes are hierarchically formed and ejected from reconnection regions. A statistical separation of the reconnected magnetic field lines follows a superdiffusive behavior, from which the rate is measured to be very similar to that obtained from the mixing of tracer populations. We find that the reconnection rate scales roughly linearly with the turbulence level during the peak of reconnection. This scaling is consistent with the turbulence properties produced by both the externally driven and self-generation processes. These results imply that large-scale thin current sheets tend to undergo rigorous reconnection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Sneaking in SpyCatcher using cell penetrating peptides for in vivo imaging

Abstract In vivo imaging of protein complexes is a powerful method for understanding the underlying biological function of these key biomolecules. Though the engineering of small, high affinity nanobodies have become more prevalent, the off-rates of these tags may result in incomplete or partial labeling of proteins in live cells. The SpyCatcher003 and SpyTag split protein system allow for irreversible, covalent binding to a short target peptide unlike nanobody-affinity based probes. However, delivering these tags into a cell without disrupting its normal function is a key challenge. Cell penetrating peptides (CPPs) are short peptide sequences that facilitate the transduction of otherwise membrane-impermeable ‘cargo’ , such as proteins, into cells. Here we report on our efforts to engineer and characterize CPP-SpyCatcher003 fusions as modular imaging probes. We selected three CPPs, CUPID, Pentratin, and pVEC, to engineer fusion protein probes for superresolution microscopy, with the aim to eliminate prior permeabilization treatments that could introduce imaging artifacts. We find that fusing the CPP sequences to SpyCatcher003 resulted in dimer and multimer formation as determined by size exclusion chromatography, dynamic light scattering, and SDS resistant dimers on SDS-PAGE gels. By isolating and labeling the monomeric forms of the engineered protein, we show these constructs retained their ability to bind SpyTag and all three CPP sequences remain membrane active, as assessed by CD spectroscopy in the presence of SDS detergent. Using fluorescence and super resolution Lattice structured illumination microscopy (Lattice SIM) imaging we show that the CPPs did not enhance uptake of SpyCatcher by E. coli, however with Caulobacter crescentus cells, we show that Penetratin, and to a lesser degree CUPID, does enhance uptake. Our results demonstrate the ability of the CPP-SpyCatcher003 to label targets within living cells, providing the groundwork for using split protein systems for targeted in vivo imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Benchmarking Concentration and Extraction Methods for Wastewater-Based Surveillance of Eight Human Respiratory Viruses: Implications for Rapid Application to Novel Pathogens

To provide early warning and support a rapid response to a novel virus through wastewater surveillance, it would be ideal to understand in advance which concentration and extraction methods are likely to be effective for dPCR-based methods, depending on virus characteristics. In this study, we spiked raw wastewater samples with eight human respiratory viruses and processed them with four methods that concentrate and/or extract nucleic acids from both liquid and solid fractions (Promega, Nanotrap, and InnovaPrep) or only the solid fraction of wastewater (Solids). Our findings provide encouraging evidence that all four methods combined with dPCR could detect an emerging virus in wastewater, although they differed in sensitivity. The pattern of recovery efficiency for adenoviruses, coronaviruses, and influenza A viruses was consistent across methods, with Promega producing higher median recovery efficiencies, while distinct patterns were observed for coxsackieviruses. We also normalized the concentration data with two endogenous fecal indicators, PMMoV and Carjivirus (formerly crAssphage). We found that normalization could reduce method-associated differences if the indicator exhibited a recovery pattern similar to that of the target virus. These findings can guide the selection of concentration and extraction methods for wastewater monitoring based on the properties of target viruses, thus enhancing pandemic preparedness.

Biological and medical sciences↗
DOE OSTI2024

A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach

Deep learning (DL) models are extensively used as surrogate models for high-fidelity simulations of multiphase fluid flow in porous media at large scales, enabling fast forecasts of the spatial–temporal evolution of three-dimensional (3D) state variables in geological carbon storage (GCS). However, training these models in high-dimensional space remains computationally demanding and prone to overfitting because of limited training data. This paper presents a novel workflow to address these challenges by integrating dimension reduction (DR) methods. Here, the proposed workflow employed pre-trained DR models to extract the latent variables of geological models and state variables and utilized the multi-layer perceptron (MLP) for constructing mapping functions between the input and output variables in latent spaces. Subsequently, the pre-trained reconstruction models converted the MLP-predicted latent state variables to their original high-dimensional form. Furthermore, we proposed a novel strategy for the DR and reconstruction of 3D saturation fields to account for the unique data characteristics of sparsity, nonuniformity, and discontinuity. The proposed strategy applied PCA and inverse PCA for 2D average saturation fields and developed a DL-based 3D reconstruction model, leveraging three 2D average saturation fields as input to produce a 3D saturation field as output. The pre-training of DR and reconstruction models and training of MLP models were conducted on 84 Gulf of Mexico (GoM) simulations and evaluated on 12 testing simulations. Each simulation contained 720 monthly time steps, with the first 360 months as the injection period and the rest as the post-injection period. The proposed workflow, incorporating DR and DL models, accurately predicts the normalized 3D pressure fields, achieving mean square error (MSE) of 2.92 × 10 -7 compared to the ground truth obtained from a full-physics simulator. Furthermore, the proposed strategy outperformed PCA and convolutional autoencoder (CAE) models on 3D saturation fields, resulting in minor workflow prediction errors with an MSE of 2.93 × 10 -5 . The results suggest the proposed workflow provides sufficient predictive fidelity across temporal and spatial scales, and enables a speedup of 160 times compared to the full-physics simulator, facilitating improved decision-making and risk assessment for large-scale GCS management in real-time scenarios.

3D reconstruction model↗
DOE OSTI2023

Observations of Boundary Layer Convergence Lines and Associated Updrafts in the U.S. Southern Great Plains

Abstract Boundary layer convergence lines (CLs) are highly effective at deep-convection initiation (DCI), suggesting that their associated updraft properties differ from those of more widespread turbulent updrafts in the planetary boundary layer (PBL). This study exploits observations at the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) observatory in Oklahoma from 2011 to 2016 to quantify CL properties and their relation to turbulent PBL eddies preceding CL arrival. Two independent methods for estimating CL properties are developed at two locations in the SGP region, both relying on the assumption of a 2D circulation in the CL-normal plane but using different combinations of instruments. The first (the radar method) relies mainly on scanning radar data and is applied to 61 CLs passing near a high-resolution scanning radar based in Nardin, Oklahoma, while the second (the surface method) relies mainly on surface wind data and is applied to 68 CLs crossing the SGP facility in nearby Lamont, Oklahoma. Mean daytime (1000–1900 LST) CL width (∼2 km) and convergence magnitude (∼0.003 s −1 ) are similar for both methods, and mean daytime CL depth is ∼0.75 km. The two methods disagree at night (0000–1000 and 1900–2400 LST), where the surface method estimates wider and weaker CLs than the radar method. This difference may stem from the radar beam overshooting the shallow, highly stable nocturnal PBL. The largest CL updrafts are slightly wider (∼20%) and stronger (∼40%) than the largest PBL updrafts in the pre-CL period, generating 50%–100% larger updraft mass fluxes over most of the PBL depth. Significance Statement Deep convection is commonly initiated by boundary layer convergence lines (CLs), which are associated with intense surface-based wind convergence and strong updrafts that may lift air to saturation. Although CLs form regularly, they are far less common than ordinary, short-lived turbulent thermals in the daytime boundary layer. To better understand why CLs are so effective at deep-convection initiation, we observationally quantify their morphologies and strengths and compare these properties to those of surrounding turbulent updrafts. Perhaps surprisingly, the CLs are found to exhibit only slightly larger scales and strengths as the turbulent updrafts. Although these marginal increases help to explain the preference for storms to initiate along CLs, they likely are not the whole story.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Nuclear Material Control & Accounting for Pebble Bed Reactors (FY 2023 Summary Report)

This report discusses the work done under the US Department of Energy NE-5 Advanced Reactor Safeguards and Security Program during FY 2023. It provides a summary of material control and accounting (MC&A) for pebble bed reactors (PBRs) and addresses some of the main challenges with current PBR MC&A approaches that will inform safeguards and security by design efforts. The efforts to date have focused on tristructural isotropic (TRISO) pebble fuel material accounting and control including working with partners in industry, loss and production of nuclear material as part of reactor operations, burnup modeling and measurements, uncertainty quantifications for such modeling and measurements, statistical approaches needed, and measurement methods. The unique fuel management and utilization in a PBR, where the fuel in spherical form is introduced and circulates through the reactor, poses special challenges for MC&A. This contrasts with traditional water-cooled reactors in which the fuel is contained in large assemblies and can be easily identified and counted. Even online fueled reactors, such as the CANDU reactors (none of which operate in the United States), are significantly different because the fuel is still contained in relatively large assemblies, is uniquely identified, and the number of assemblies that pass through the core on an annual basis is much fewer than the hundreds of thousands that circulate in a PBR, none of which are uniquely identified. Additionally, the nature of the TRISO fuel results in very low heavy metal loading with each pebble containing less than 10 g of uranium and on the order of less than 1 g of fissile material. This low fuel density and the robustness of the TRISO particles are major features of the TRISO fuel from a safety basis as each TRISO particle and pebble acts as a containment for the nuclear material and fission products during normal and accident conditions. This also results in very low plutonium loading per pebble during normal operations, which is on the order of 0.1 g at full burnup. A major feature of PBRs is that they will allow for significantly higher burnup, on the order of 160 GWd/THM compared to the burnup of traditional LWRs, which is on the order of 45 GWd/THM. This is achieved by monitoring the pebbles as they circulate through the reactor and allowing them to be reintroduced into the core until the desired burnup is achieved and they are removed from the reactor and enter the spent fuel storage areas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Characterization Techniques Investigated for Characterization of Anomalous Materials in Plutonium Oxide – 25666

The DOE has adopted a Dilute and Dispose approach for processing surplus plutonium which consists of blending plutonium oxide with adulterants and packaging it in a form which is acceptable for disposal at the Waste Isolation Pilot Plant. The feed material for the downblend process is intended to be pure plutonium oxide powder, however other objects are occasionally encountered within the oxide, particularly with legacy material. Potential technologies which could assist in the resolution of incidents where such anomalies are encountered have been investigated. Resolution of these incidents requires characterization of the anomalous object so that plutonium oxide processing can resume and so that a disposition pathway can be determined for the anomalous material. Technologies including gamma ray spectroscopy, alpha-gamma coincidence, LiDAR volumetric measurements, and surface conductivity measurements were investigated for this purpose, with a focus on systems which can be easily introduced into the processing environment when an anomaly is encountered, then removed from the environment after resolution to avoid impeding normal processing activities. This places an emphasis on small and portable measurement systems and systems that can operate in a high-background, oxide-processing environment. Gamma ray systems investigated include the GR1™a CZT detector and the MicroGe™a germanium detector, with a focus on detecting characteristic gamma rays from Pu-239 and other actinides. A gamma ray and alpha particle coincidence method was investigated with the goal of identifying actinides in the presence of a gamma ray background produced by adjacent plutonium oxide material. Leica™b BLK360 G1 and Keyence™c LJ-X8300 LiDAR systems were investigated for use in conjunction with mass measurements to gain accurate material density values, and a Foerster Sigmatest™d 2.070 was tested to determine surface conductivity. The combination of these properties would allow improved identification and characterization of a wide variety of potential anomalous material.

Munson, Justin M.↗
DOE OSTI2020

Measurement of free chlorine levels in water using potentiometric responses of biofilms and applications for monitoring and managing the quality of potable water

We report residual free chlorine is not monitored continuously at scale in drinking water distribution systems because existing real-time sensor technologies require frequent maintenance, cleaning, and calibration, which makes these products too costly to be used throughout a distribution system. As a result, current measurement approaches require manual sampling, which is not feasible for the consistent monitoring of free chlorine because chlorine concentrations vary significantly throughout pipeline distribution and over time and space. This research presents an alternative and cost-effective method of predicting free chlorine levels in drinking water using graphite electrodes coated with naturally grown microbial biofilms. This Microbial Potentiometric Sensor (MPS) array was installed in a Continuously Mixed Batch Reactor (CMBR), and drinking water containing variable free chlorine concentrations. The chlorine concentrations were introduced in a controlled manner, and the MPS signals were monitored over time. MPS signals were measured from the change in Open Circuit Potential (OCP) across the MPS array in real-time. An empirically derived relationship between the normalized change in OCP and free chlorine was established by fitting individual and average MPS data to a decaying exponential growth function in order to predict free chlorine levels. The results show that free chlorine can be predicted with reasonable accuracy, with model validation showing an average absolute error of ±0.09 ppm below 1.1 ppm and ±0.30 ppm between 1.1 and 2.7 ppm. However, the accuracy of predictions was reduced at higher free chlorine levels. The researchers conclude that MPS systems may benefit drinking water distribution systems by measuring free chlorine. These advantages of the MPS are especially pronounced in the developing world because this system is inexpensive and does not require routine maintenance or cleaning. The system relies on a naturally forming and regenerating biofilm and an inexpensive potentiometric meter to produce stable measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Medium-scale to large-scale implementation of cyber-physical human experiments in live traffic

Autonomous Vehicles (AVs) such as cars and trucks are being developed and tested as Cyber-Physical Human systems while the technology improves. Before these systems can achieve full autonomy, some serve as tools in the form of adaptive cruise control. The CIRCLES Consortium investigates the potential for AVs to increase fuel efficiency of highway traffic by smoothing “stop-and-go” traffic waves that result from normal human driving behavior in congestion. We have performed an experiment to evaluate the real world effects of implementing this strategy. A medium-scale experiment was performed on I-24 near Nashville, TN in August 2021. This was a precursor to a larger experiment that will take place November 2022. We examine how the human part of the experiment will change as we scale up from an 11 vehicle test (four AVs) to 100 AVs. There are many solutions to problems of the medium-scale experiment that would be inconvenient, complicate the experience, or not be practicable. The medium-scale experiment involved 11 cars of which four had a custom control algorithm installed to be engaged by the driver. The large-scale experiment will have 100 cars, all with custom control algorithm installed to act on traffic when the controller is engaged. We examine key choices made for the medium experiment, and how some will be different for the large experiment. Our experience performing the medium-scale experiment has made it clear that repeating our methods from this smaller one are inefficient or impossible if used for the large-scale experiment and will be improved.

McQuade, Sean T.↗
DOE OSTI2020

How analytic choices can affect the extraction of electromagnetic form factors from elastic electron scattering cross section data

Scientists often try to incorporate prior knowledge into their regression algorithms, such as a particular analytic behavior or a known value at a kinematic endpoint. Unfortunately, there is often no unique way to make use of this prior knowledge, and thus, different analytic choices can lead to very different regression results from the same set of data. In this paper, to illustrate this point in the context of the proton electromagnetic form factors, we use the Mainz elastic data with its 1422 cross section points and 31 normalization parameters. Starting with a complex unbound non-linear regression, we will show how the addition of a single theory-motivated constraint removes an oscillation from the magnetic form factor and shifts the extracted proton charge radius. We then repeat both regressions using the same algorithm, but with a rebinned version of the Mainz dataset. These examples illustrate how analytic choices, such as the function that is being used or even the binning of the data, can dramatically affect the results of a complex regression. These results also demonstrate why it is critical when using regression algorithms to have either a physical model in mind or a firm mathematical basis

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Characterization of Surrogate Molten Salt Reactor Aerosol Streams

Measuring the aerosol evolution from MSRs is important for monitoring the off-gas system of the reactor and is particularly important for detecting off-normal conditions. In a molten salt reactor (MSR) accident scenario, an aerosol release would be a major factor in the source term. This aerosol stream would likely be generated from a breach in the cover gas system, which causes particles produced from fission itself to escape, or from a salt spill that produces aerosols through splashing and secondary reactions. The particle size of the produced aerosols is anticipated to vary greatly and range from 0.01 to 10 µm. The transport of these aerosols would be dependent on the particle size. A better understanding of aerosol generation, size, and monitoring methods are needed to inform estimation and mitigation of potential aerosolized source terms from MSRs. While salt spill experiments are being performed at Argonne National Laboratory, the development of aerosol characterization and monitoring methods are being developed at Oak Ridge National Laboratory. To generate prototypic aerosols for use in testing monitoring instruments and mitigation methods, a surrogate aerosol stream was produced with a Collison nebulizer, and the particle size distributions were measured with a cascade impactor. The results demonstrated that by changing the nebulizer pressure, the aerosol particle size distribution can be adjusted to best match the region of interest for experiments with higher pressures, driving the particle size down. However, nearly all aerosols formed exceeded 1 µm in diameter, providing a lower bound for the surrogate aerosol stream. In addition to verifying the applicability of this surrogate aerosol stream, this work has shown that a laser induced breakdown spectroscopy monitoring system that is under development is resilient to changes in particle sizes, increasing its robustness for off-gas monitoring.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

From Structure to Function: Zn/Mn-Modified Maghemite as an Advanced Nanoplatform for Magnetic Hyperthermia and Radionuclide Therapy

The development of nanoplatforms capable of efficient heat generation and stable radionuclide delivery is essential for effective bimodal cancer therapy. Here, in this study, binary (Fe–M) and ternary (Fe–M–M′) metal oxide nanoparticles were synthesized via a polyol method optimized to produce flower-like γ-Fe 2 O 3 (maghemite) structures, with M and M′ representing Zn and/or Mn. Comprehensive structural and magnetic characterization was conducted to explain the relationship between composition, defect structure, and hyperthermic performance. The analyses revealed that cation substitution induced an Fe-site vacancy, primarily at octahedral positions, leading to local structural distortions, as confirmed by powder X-ray diffraction and pair distribution function analysis. The optimized composition, with Zn/Mn/Fe = 0.040:0.182:1, exhibited the highest concentration of vacancies and structural disorder. These vacancies altered the bonding environment, enhancing magnetic interactions at tetrahedral sites while weakening those at the octahedral positions. The resulting multicore nanoflowers (20–63 nm; core size 13–18 nm) displayed strong heating performance, with intrinsic loss power ranging from 0.34 to 5.77 nHm 2 kg –1 . The optimized sample achieved a temperature increase of 30 °C within 2 min and a specific absorption rate of 369 W g –1 . This composition was further coated with citrate (CA) and successfully radiolabeled with 177 Lu, achieving a radiolabeling yield of 92.7% and excellent stability, thus forming a robust nanoplatform for combined magnetic hyperthermia and radionuclide therapy. Biological evaluation of the optimized S5 composition revealed selective cytotoxicity toward HeLa and LS174 cells, while toxicity was significantly lower to A549, A375, and normal MRC-5 cells. Citrate coating of S5 nanoparticles (S5@CA) drastically reduced their cytotoxicity across all tested cell lines (IC 50 > 200 μg mL –1 ), confirming their enhanced biocompatibility for therapeutic applications. In HeLa cells subjected to magnetic hyperthermia, the viability decreased to approximately 84% after 30 min and 61% after 60 min of treatment, demonstrating the sustained hyperthermic effect at a controlled working temperature of 48 °C. These results underscore the effectiveness of cation substitution and vacancy engineering in tailoring the functional properties of maghemite-based nanomaterials for advanced multimodal cancer therapies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Cascades between Light and Heavy Fermions in the Normal State of Magic-Angle Twisted Bilayer Graphene

We present a framework for understanding the cascade transitions and the Landau level degeneracies of twisted bilayer graphene. The Coulomb interaction projected onto narrow bands causes the charged excitations at an integer filling to disperse, forming new bands. If the excitation moves the filling away from the charge neutrality point, then it has a band minimum at the moiré Brillouin zone center with a small mass that compares well with the experiment; if towards the charge neutrality point, then it has a much larger mass and a higher degeneracy. At a nonzero density away from an integer filling the excitations interact. The system on the small mass side has a large bandwidth and forms a Fermi liquid. On the large mass side the bandwidth is narrow, the compressibility is negative and the Fermi liquid is likely unstable. This explains the observed sawtooth features in compressibility, the Landau fans pointing away from charge neutrality and their degeneracies. The framework sets the stage for superconductivity at lower temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Mass measurement of 27 P to constrain type-I x-ray burst models and validate the isobaric multiplet mass equation for the $A = 27, T = \frac{3}{2}$ isospin quartet

Background: Light curves are the primary observable of type-I x-ray bursts. Computational x-ray burst models must match simulations to observed light curves. Most of the error in simulated curves comes from uncertainties in rp process reaction rates, which can be reduced via precision mass measurements of neutron-deficient isotopes in the rp process path. Purpose: Perform a precise atomic mass measurement of 27 P. Use this new measurement to calculate rp process reaction rates and input these rates into an x-ray burst model to reduce simulated light curve uncertainty. Use the mass measurement of 27 P to validate the isobaric multiplet mass equation (IMME) for the A = 27 T = 3/2 isospin quartet which 27 P belongs to. Method: High-precision Penning trap mass spectrometry utilizing the time-of-flight ion cyclotron resonance technique was used to determine the atomic mass of 27 P. The MESA code (Modules for Experiments in Stellar Astrophysics) was then used to simulate x-ray bursts using a one-dimensional multizone model to produce updated light curves. Results: The mass excess of 27 P was measured to be –670.7(6) keV, a 14-fold precision increase over the mass reported in the 2020 Atomic Mass Evaluation (AME2020). The 26 Si(p, $γ$) 27 P– 27 P($γ$, p) 26 Si rate equilibrium has been determined to a higher precision based on the precision mass measurement of 27 P. x-ray burst light curves were produced with the MESA code using the new reaction rates. Changes in the mass of 27 P seem to have minimal effect on light curves, even in burster systems tailored to maximize impact. Conclusion: The mass of 27 P does not play a significant role in x-ray burst light curves. It is important to understand that more advanced models do not just provide more precise results, but often qualitatively different ones. This result brings us a step closer to being able to extract stellar parameters from individual x-ray burst observations. In addition, the IMME has been validated for the A = 27, T = 3/2 quartet. The normal quadratic form of the IMME using the latest data yields a reduced $χ$ 2 of 2.9. Finally, the cubic term required to generate an exact fit to the latest data matches theoretical attempts to predict this term.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗