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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 37 records · Page 2

Production, Purification and Characterization of Radioisotopes (Final Report)

This collaborative proposal between the University of Alabama at Birmingham (UAB, PI Suzanne Lapi), and Los Alamos National Laboratory (LANL, collaborator Michael Fassbender) aims to develop novel techniques for isotope production. This proposal takes advantage of complementary techniques available at the UAB cyclotron facility and LANL isotope production facility (IPF) and involved UAB faculty, postdocs, graduate students and undergraduates as well as LANL scientists and staff. This project involved the development of separation techniques for radioisotope production at UAB, using radiotracer analogues produced using the TR24 cyclotron, which would directly translate to separations of the desired isotopes produced at LANL via neutron spallation. Extended visits to LANL by UAB students involved in this initiative were originally envision but were hampered due to COVID restrictions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

High pressure Raman spectroscopy of boron-rich boron carbides up to 50 GPa

We investigated the effects of increased boron content on the resistance to non-hydrostatic stress-induced (NHSI) local amorphous zones in boron-rich boron carbide (BxC) compounds. Using high-pressure Raman spectroscopy, we subjected B 4.3 C, B 6.4 C, and B 10.4 C to pressures up to 50 GPa and monitored their responses. Our results show that higher boron content delays the onset of NHSI local amorphous zone formation, shifting it from 35 GPa in B 4.3 C to approximately 50 GPa in B 10.4 C. This enhanced resistance is attributed to a reduction in the formation of the B 12 (CCC) polytype, which is susceptible to amorphization, and the greater flexibility of B–B–B chains. Furthermore, alternative mechanisms, such as boron vacancy-driven C–C bond formation, provide additional insights into defect-mediated structural changes that may influence the amorphization process. In conclusion, these findings highlight the dual role of boron content and defect mechanisms in improving the structural stability of B x C materials under extreme environments.

36 MATERIALS SCIENCE↗

Microwave-photonic control of optically accessible spin defects in diamond

A growing variety of optically accessible spin qubits have emerged in recent years as key components for quantum sensors, computers, and memories. However, the scalability of conventional spin-based quantum architectures remains limited by direct microwave delivery, which introduces thermal noise, electromagnetic crosstalk, and design constraints for cryogenic, high-field, and distributed systems. In this work, we present a unified framework for RF-over-fiber (RFoF) control of spins accessible through optically detected magnetic resonance (ODMR) spectroscopy of nitrogen-vacancy (NV) centers in diamond. The RFoF platform relies on an intensity-modulated 1310 nm laser carrying microwave signals over fiber and a high-speed photodiode for optical-to-electrical conversion to drive NV spin transitions. We report an RFoF power-conversion efficiency of 3.42% for an RF output PRF,out=-5.5 dBm at 2.87 GHz, enabling clear resolution of Zeeman splitting in

Rahman, M Reefaz [ORNL] (ORCID:0000000323541611)↗

Radon emanation rate measurements using liquid scintillation counting

This article describes a radon emanation measurement technique using liquid scintillator counting. A model for radon loading and transport is described, along with its calibration. Detector background and blank have been studied and quantified. The Minimal detectable activity has been determined for the counting setup using a toy Monte Carlo simulation. Here, the measurement technique is validated using a butyl rubber sample previously used for cross-calibration between different radon counting facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Efficient Perovskite Solar Cells Achieved via Rapid Photonic Annealing of all Stacking Layers: Unveiling the Crystallization Energy Window

In this study, we report high-performance perovksite solar cells (PSCs) with rapid photonic annealing (RPA) of all stacking layers, enabled by ultraviolet (UV) light-emitting diode (LED) sources, to replace lengthy and energy-intensive thermal annealing (TA). The UV-LED annealing technique allows for layer-specific annealing, where the selected light source provides a precise UV wavelength for maximizing the amount of light absorption by the target layer. The disparity in optical absorption between the target layer and the underlying films allows the stack of the underlying films to remain relatively unaffected, making this process ideal for heating sensitive substrates. Along with a systematic investigation into the layer-specific annealing mechanism of RPA, the results demonstrated that this UV-LED-based photonic annealing of all stacking layers (7 s for perovskite absorber) can produce PSCs with the power conversion efficiency (PCE) of over 23%, the highest reported among optically annealed PSCs. Moreover, the RPA device retains over 80% of the initial PCE over 1000 h under continuous 1 sun illumination at 55 °C and 30%–60% relative humidity (RH), while TA control device drops to 50% of its initial efficiency. Furthermore, these findings represent significant strides toward achieving rapid, cost-effective, and scalable manufacturing of commercial perovskite photovoltaics (PV).

14 SOLAR ENERGY↗

Sensitivity of nEXO to 136 Xe charged-current interactions: Background-free searches for solar neutrinos and fermionic dark matter

We study the sensitivity of nEXO to solar neutrino charged-current interactions, 𝜈 𝑒 + 136 Xe → 136 Cs*+𝑒 − , as well as analogous interactions predicted by models of fermionic dark matter. Due to the recently observed low-lying isomeric states of 136 Cs, these interactions will create a time-delayed coincident signal observable in the scintillation channel. Here we develop a detailed Monte Carlo simulation of scintillation emission, propagation, and detection in the nEXO detector to model these signals under different assumptions about the timing resolution of the photosensor readout. We show this correlated signal can be used to achieve background discrimination on the order of 10 −9 , enabling nEXO to make background-free measurements of solar neutrinos above the reaction threshold of 0.668 MeV. We project that nEXO could measure the flux of neutrinos from the carbon-nitrogen-oxygen cycle with a statistical uncertainty of 25%, thus contributing a novel and competitive measurement toward addressing the solar metallicity problem. Additionally, nEXO could measure the mean energy of the 7 Be neutrinos with a precision of 𝜎 ≤ 1.5 keV and could determine the survival probability of 7 Be and pep solar 𝜈𝑒 with precision comparable to the state of the art. These quantities are sensitive to the Sun’s core temperature and to nonstandard neutrino interactions, respectively. Here, the strong background suppression would allow nEXO to search for charged-current interactions of fermionic dark matter in the mass range 𝑚 𝜒 = 0.668–7 MeV with a sensitivity up to three orders of magnitude better than current limits.

47 OTHER INSTRUMENTATION↗

Migration of Al within dealuminated beta extruded catalysts influences olefin distribution during ethanol upgrading

Zeolites serve as essential catalytic platforms for many industrial processes, including emerging ethanol-to-olefins (ETO) upgrading technologies. Although metal-loaded (Cu, Zn, Y) dealuminated beta (deAlBeta) zeolite powders are promising catalysts for direct ETO conversion with high selectivity to butene-rich C3+ olefins necessary for production of sustainable aviation fuels (SAF), development of these materials as shaped technical bodies through the incorporation of binders is required for scale-up and commercial viability. Here, we report the ethanol upgrading performance of Cu-Zn-Y/deAlBeta extruded catalysts formulated with either alumina or kaolin clay binders. Both extrudates exhibit high ethanol dehydration reactivity which competes with the initial ethanol dehydrogenation step in the direct ETO reaction network. Consequently, elevated selectivity to dehydration side products (ethylene, diethyl ether) at ∼100% ethanol conversion is observed on Cu-Zn-Y/deAlBeta extrudates compared to the powder catalyst, which inhibits production of desired C3+ olefins. Utilizing microscopy and spectroscopic characterizations, we attribute this to Al migration from binder to zeolite particles within the extrudates, thus re-aluminating the zeolite and generating Brønsted acid sites active for dehydration reactions. This work elucidates the effects of binder incorporation on ETO product distributions and emphasizes that binder selection must be carefully considered during design of extruded zeolite catalysts.

Jacobs, Hunter [ORNL] (ORCID:000000016190874X)↗

Production and radiochemistry of the in vivo PET generator 140 Nd/ 140 Pr as an imaging surrogate for F-block therapeutic radionuclides

Theranostics, a combined approach of diagnostics and therapeutics, often employs F-block therapeutic radionuclides including 225 Ac, 177 Lu, and 161 Tb. While there is a lack of F-block PET imaging radionuclides, the in vivo PET generator pair 140 Nd/ 140 Pr can act as a theranostic imaging counterpart to the F-block therapeutic radionuclides. In this study, we explored the production and separation of high purity 140 Nd via the 141 Pr(p,2n) 140 Nd reaction route. Monoisotopic 141 Pr targets irradiated with 20 MeV protons for 10 min with 10 µA beam current yielded 21.45 ± 0.82 MBq (580 ± 22 µCi) of 140 Nd. A two-step separation method was developed for the purification of 140 Nd from the 141 Pr target material. Recoveries of 27.4 ± 2.1% 140Nd were obtained upon separation with < 20 ppb of 141 Pr target material in the final product. Radiolabeling of Macropa and DOTA chelators with 140 Nd resulted in [ 140 Nd]Nd-Macropa with a molar activity of 74.0 MBq/µmol (2.0 mCi/µmol) and [ 140 Nd]Nd-DOTA with a molar activity of 70.3 MBq/µmol (1.9 mCi/µmol). An imaging study with a phantom indicated the PET spatial resolution of 140 Nd/ 140 Pr was distinguishable down to 2.4 mm. This study sets the stage for the 140 Nd/ 140 Pr in vivo PET generator to be explored in radiopharmaceutical applications.

F-block↗

High-pressure high-temperature melting and recrystallization of nanolamellar high-entropy alloys

Additively manufactured (AM) High Entropy Alloys (HEAs) are notable for their exceptional high-yield strength and large tensile ductility. The nanolamellar Eutectic HEA (EHEA) AlCoCrFeNi 2.1 was fabricated by laser powder bed fusion (L-PBF) in the as-printed form (EHEA1) and subsequently annealed at 1000oC (EHEA2) and 600oC (EHEA3) to achieve a broad range of mechanical properties. EHEA2 and EHEA3 samples were studied using Scanning transmission electron microscopy (STEM), energy dispersive X-ray diffraction (EDXRD) at high-pressures and high temperatures, nanoindentation hardness and modulus measurements. According to EDXRD EHEA2 and EHEA3 are composed of B2 and L1 2 phases. High-pressure high-temperature EDXRD studies show melting for EHEA2 at 1698 ± 25 K at a pressure of 6.5 GPa and melting for EHEA3 at 1598 ± 25 K at a pressure of 5.8 GPa. Post-melt and recrystallized samples were recovered at ambient conditions, and XRD analysis showed retention of B2 and L1 2 phases, although a new σ phase appeared for both EHEA2 and EHEA3 samples due to high-pressure and high-temperature melting and recrystallization experiment. SEM analysis also demonstrated the preservation of the nanolamellar morphology. Nanoindentation studies revealed that recrystallized EHEAs retain their original mechanical property hierarchy, with EHEA3 being 47% harder than EHEA2, largely related to higher content of B2-phase and retention of nanolamellar morphology. We also present Pressure-Volume-Temperature (P-V-T) data for 3-D printed and annealed eutectic high entropy alloys and extract mechanical and thermal properties data.

36 MATERIALS SCIENCE↗

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗

Investigating the Theranostic Potential of Elementally Matched [ 43 Sc]Sc-PSMA-617 and [ 47 Sc]Sc-PSMA-617

The theranostic approach, which employs diagnostic radiopharmaceuticals to select patients who would benefit from targeted radiotherapy agents, has become an invaluable strategy for effective medical care. Scandium radionuclides offer the advantage of forming elementally matched and chemically identical diagnostic and therapeutic compounds, making them ideal candidates for this strategy. PSMA-617 is an established prostate-specific membrane antigen targeting agent and can be used as a proof of concept to investigate 43 Sc, the diagnostic nuclide, and 47 Sc, the therapeutic nuclide, as a theranostic pair. Methods: Cellular uptake, competitive binding assays, and internalization studies were carried out using LNCaP or PC-3 cell lines. [ 43 Sc]Sc-PSMA-617 was used in PET imaging studies in LNCaP or PC-3 tumor models, with time points ranging from 1–9 h. LNCaP tumor-bearing mice injected with [ 47 Sc]Sc-PSMA-617 were imaged using SPECT up to 48 h. A longitudinal study was carried out using LNCaP tumor-bearing mice imaged with [ 43 Sc]Sc-PSMA-617 prior to receiving a therapeutic dose of [ 47 Sc]Sc-PSMA-617. Results: 43 Sc and 47 Sc were incorporated into PSMA-617 at radiochemical yields of >99%. Cellular uptake studies demonstrated high uptake and specificity to PSMA receptors for [ 47 Sc]Sc-PSMA-617. In vivo PET studies showed specificity of [ 43 Sc]Sc-PSMA-617 while SPECT studies demonstrated tumor retention of [ 47 Sc]Sc-PSMA-617 up to 48 h. [ 47 Sc]Sc-PSMA-617 demonstrated therapeutic efficacy by delaying tumor growth and increasing survival rates from a single administered dose in xenograft models. More importantly, the PET results from [ 43 Sc]Sc-PSMA-617 PET were highly correlated with the therapeutic response from [ 47 Sc]Sc-PSMA-617, showing that 43 Sc PET data can predict therapeutic outcomes in individual animals from 47 Sc agents, even in animals sharing a genetic background and implanted with tumors from the same cell line. Conclusions: Two chemically identical, PSMA-targeting radioscandium pharmaceuticals demonstrated in vivo stability, specificity and retention in PSMA+ tumor models. A theranostic study showed that a higher 43 Sc PET SUVmean was strongly correlated to therapeutic response from the 47 Sc agent, demonstrating that 43 Sc and 47 Sc can be used as an elementally matched theranostic pair.

Biodistribution↗

High‐Resolution National‐Scale Water Modeling Is Enhanced by Multiscale Differentiable Physics‐Informed Machine Learning

Abstract The National Water Model (NWM) is a key tool for flood forecasting, planning, and water management. Key challenges facing the NWM include calibration and parameter regionalization when confronted with big data. We present two novel versions of high‐resolution (∼37 km 2 ) differentiable models (a type of hybrid model): one with implicit, unit‐hydrograph‐style routing and another with explicit Muskingum‐Cunge routing in the river network. The former predicts streamflow at basin outlets whereas the latter presents a discretized product that seamlessly covers rivers in the conterminous United States (CONUS). Both versions use neural networks to provide a multiscale parameterization and process‐based equations to provide a structural backbone, which were trained simultaneously (“end‐to‐end”) on 2,807 basins across the CONUS and evaluated on 4,997 basins. Both versions show great potential to elevate future NWM performance for extensively calibrated as well as ungauged sites: the median daily Nash‐Sutcliffe efficiency of all 4,997 basins is improved to around 0.68 from 0.48 of NWM3.0. As they resolve spatial heterogeneity, both versions greatly improved simulations in the western CONUS and also in the Prairie Pothole Region, a long‐standing modeling challenge. The Muskingum‐Cunge version further improved performance for basins >10,000 km 2 . Overall, our results show how neural‐network‐based parameterizations can improve NWM performance for providing operational flood predictions while maintaining interpretability and multivariate outputs. The modeling system supports the Basic Model Interface (BMI), which allows seamless integration with the next‐generation NWM. We also provide a CONUS‐scale hydrologic data set for further evaluation and use.

Song, Yalan [Civil and Environmental Engineering T↗

Hydrolysis Reaction Pathways of Thorium Oxide Nanoclusters

Density functional theory benchmarked by correlated molecular orbital theory is used to develop a fundamental and predictive understanding of the interaction of thorium oxide nanoclusters with gas phase water to provide insight into nuclear-waste storage, production of thorium nuclear reactor fuels, and reprocessing of spent fuel. The structures of Th n O 2n (n = 3 – 6) clusters and their interactions with water have been studied at the B3LYP, MP2, and CCSD(T) levels. Hydrolysis is initiated by the formation of Lewis acid-base adducts, with relative H 2 O binding energies (physisorption) ranging from −15 kcal/mol to −22 kcal/mol. The initial H 2 O physisorption energy is ca. −21 kcal/mol regardless of the cluster size and is consistent with the experimentally obtained initial adsorption energy on a thorium dioxide surface. The physisorption enthalpies for additional water molecules can be affected by the presence of terminal groups OH groups generated by proton transfer to a Th-O near the site of adsorption. The hydrolysis products (chemisorption) form either bridging or terminal hydroxides. More exothermic hydrolysis steps were predicted for the formation of terminal hydroxides as compared to the formation of bridging hydroxides. Here, the calculated transition state barriers for transfer of protons from bound water complexes to form the chemisorption products are very low. Overall, water readily reacts with thorium oxide clusters preferring hydroxide products over hydrated complexes. First and second order fits were predicted for the combined physisorption and chemisorption energies for the hydrolysis of thorium oxide clusters. Finally, ionization energies and electron affinities were calculated as were HOMO-LUMO gaps to provide additional insights into the properties of the thorium oxide and hydroxide clusters.

Adsorption↗

Cryo-EM Visualization of Intermolecular π-Electron Interactions within π-Conjugated Peptidic Supramolecular Polymers

The self-assembly of “π-peptides” – molecules with π-electron cores substituted with two or more oligopeptide chains – brings organic electronic function into biologically relevant nanomaterials. π-Peptides assemble into fibrillar nanomaterials as driven by enthalpic peptide-based hydrogen bonding networks and pi-core-based quadrupolar interactions. A large body of spectroscopic, morphological and computational studies informs on the nature of the self-assembly process and the resulting nanostructures, but detailed structural information has remained elusive. Here, inspired by the recent use of cryogenic electron microscopy (cryo-EM) to provide high-resolution structures for synthetic peptide nanomaterials, we present here the use of cryo-EM to offer ca. 3 Å resolution of π-peptide nanomaterial assemblies, visualizing for the first time the nature of the intermolecular π-core electronic interactions responsible for energy transport through these supramolecular materials.

Group theory↗

A Machine Learning based Approach of Estimating Equivalent Circuit Model Parameters at Different SoCs of Li-ion Batteries from Voltage Relaxation

Abstract: In this study, an approach of estimating the equivalent circuit model (ECM) parameters for Li-ion batteries (LIBs) is proposed based on the voltage value at different intervals while relaxing the LIB after discharge. The typical approach for estimating ECM parameters of a LIB is to conduct electrochemical impedance spectroscopy (EIS) measurements at different frequencies and fit them to a predefined circuit model, which requires additional measuring arrangements and specialized devices. The proposed methodology utilizes four different voltages at 0s, 60s, 360s, and 1800s alongside the specific state of charge (SoC) value for a specific constant discharge current value of ~1C until the relaxation stage to train and evaluate three regression-based machine learning models— Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gaussian Process Regression (GPR)—for estimating the ECM parameters of the selected model. Bayesian optimization is employed for hyperparameter tuning to achieve optimal performance for all the regressor models, among which, the GPR provided the best performance with the root-mean-squared error (RMSE) of less than 4x10-4 on average for the resistive components and less than 0.27 for capacitive components with excellent R2 scores. The simplicity of the approach enables it to eliminate the need for sophisticated measuring equipment and computation power.

Sagar, Md. Samiul [The University of Alabama (UA)]↗

Comparative Evaluation of the Single-Phase Shift and Extended-Phase Shift Control for Isolated DC-DC Converter

Abstract: This paper presents a comparative evaluation of the Single-Phase Shift (SPS) and Extended-Phase Shift (EPS) controls for the isolated DC-DC Converter. The analysis is based on the power regulation range, flexibility of operation, current stress on power devices, system efficiency while focusing on the issue of backflow power, control complexity, design and implementation overhead, and stability of the entire system. It is also examined how the backflow influences power circulation and increases current stress. Here, the Dual Active Bridge (DAB) Converter is employed to assess the performance of the control methods. Compared to SPS control, EPS offers a wider power regulation range, greater flexibility, lower current stress, and better system efficiency. However, EPS has increased control complexity, design and implementation overhead, and often requires sophisticated feedback control loops. The comparison is made through mathematical modeling of power transfer, backflow, and current stress. Simulation results validate the comparative analysis presented.

Amir, Aamir [The University of Alabama (UA)]↗

Shear strength of a refractory high entropy alloy MoNbTaVW under high pressure

Radial X-ray diffraction (R-XRD) was performed in situ using a Panoramic Diamond Anvil Cell on the refractory high entropy alloy MoNbTaVW. The lattice parameters were determined through a Le Bail fit using a body centered cubic (BCC) lattice of symmetry $Im$$\overline{3}$$m$ (international space group number 229). Upper and lower bounds to the shear strength were determined up to 80 GPa nonhydrostatically using copper as a pressure standard. The equation of state was derived at the magic angle ψ = 54.7° and yielded a bulk modulus of K 0 = 220.8 ± 1.65 GPa. The experimental lattice parameters and bulk modulus match closely with corresponding density functional theory (DFT) calculations. The BCC phase remains stable up to the highest pressure of 80 GPa studied and is shown to be elastically anisotropic. The shear strength was found to saturate around 70 GPa with a value of τ = 1.75 GPa, and the shear moduli are presented in different limits of iso-strain and iso-stress.

36 MATERIALS SCIENCE↗