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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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859 records · Page 10

Adsorption of hydroxamic acid ligands for improved extraction of rare earth elements from monazite ores

Efficient separation of rare earth element (REE) ores via froth flotation requires the development of novel ligands with enhanced adsorption capacity and selectivity. To realize these advances, understanding the mechanisms underlying interactions between the ligand and mineral surfaces is essential. This study systematically evaluates the adsorption behavior of alkyl- and aromatic alkyl-substituted hydroxamic acid ligands on monazite surfaces using complementary spectroscopic techniques, including UV–visible (UV–vis) spectroscopy, Raman spectroscopy, infrared spectroscopy, and vibrational sum frequency generation (SFG) spectroscopy, together with the ab initio molecular dynamics (AIMD) simulations. Among the studied ligands, octanohydroxamic acid (OHA) and 4-ethoxy-N,2-dihydroxybenzamide (EDHBA) exhibit high adsorption capacity under basic pH (8–10) by forming multilayers on the surface. OHA has a higher equilibrium adsorption capacity compared to EDHBA, but it forms a less stable multilayer susceptible to disruption in the presence of interfering ions. AIMD results show that OHA adopts a single stable chelating geometry, while EDHBA exhibits multiple binding modes involving distinct interactions with La surface atoms and phosphate-bound oxygens, resulting in more complex adsorption kinetics. The variations in surface binding and intermolecular interactions observed between alkyl and aromatic molecules influence the differences in adsorption kinetics, equilibrium adsorption capacities on the mineral surface, and their flotation performance. This work provides valuable insight into the adsorption mechanism of ligands at mineral interfaces, which is crucial for guiding the design of new ligands with enhanced separation performance.

Zhou, Muchu [ORNL] (ORCID:0000000182650215)

Interface Evolutionand Long-Term Performance of NegativeCarbon Fiber Structural Electrodes

Abstract Laminated structural batteries present a transformative solution to reducing weight constraints in electric vehicles. These structural batteries are based on a multifunctional material that incorporates an energy storage function within a carbon fiber-reinforced polymer. Despite the potential of this technology, the intricate morphology of fiber–matrix or electrode–electrolyte interfaces and the impact of long-term cycling at low current rates (C-rates) on these interfaces remain insufficiently understood. This study addresses these critical knowledge gaps by examining the influence of matrix composition on the long-term electrochemical performance of structural battery electrodes and exploring advanced techniques to investigate carbon fiber–matrix interfaces. Localized imaging and X-ray scattering techniques were used to characterize morphological changes at the electrode–electrolyte interfaces by analyzing negative structural electrodes. The findings revealed that the matrix composition influences long-term electrochemical behavior and fiber–matrix interface formation. While the intrinsic properties of carbon fibers largely remain unaffected by long-term cycling, cycling promotes debonding at fiber–matrix interfaces. Nonetheless, residual regions of adhesion persist, underscoring the potential for preserving multifunctionality even under prolonged cycling conditions. These insights advance the understanding of interface dynamics, which is critical for optimizing structural battery technologies.

Chemistry

Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation

Abstract Motivation Knowledge-guided learning offers effective and robust model training strategies in data-scarce settings by incorporating established domain knowledge, thereby enhancing generalization, robustness, and interpretability. By contrast, conventional deep learning approaches rely purely on data-driven learning, which can limit robust model interpretability, particularly in high-dimensional settings with limited size samples. In computational biology, knowledge-guided learning has primarily leveraged network- and structural-based knowledge, leading to biologically interpretable representations and enhanced predictive performance compared to conventional approaches. However, curated biomarkers, one of the most accessible forms of biological knowledge, remain largely unexplored within knowledge-guided paradigms. Results In this study, we propose a model-agnostic training paradigm, Biomarker-driven Explainable Prior-guided Learning (BioExPL), that can be applied to any neural networks that incorporates curated prior knowledge. BioExPL enforces neural networks to reflect curated biomarker priors in their latent representations through a novel knowledge-alignment loss. BioExPL consistently demonstrated significantly improved predictive performance and enhanced model interpretability with minimized computational overhead in simulation studies and intensive experiments on multiple cancer datasets. BioExPL not only integrates prior curated knowledge into the model but also accurately identifies unknown associated signals additionally. BioExPL is model-agnostic and domain-independent, enabling its integration into diverse neural network architectures. Availability and implementation The open-source is publicly available at: https://github.com/datax-lab/BioExPL.

Baek, Beomsu [Department of Computer Science, Univ

A General Solution Route to Nanoporous Metal Oxide Films

Metal oxide semiconductors are of interest as efficient, stable, and low-cost photoanode materials for photoelectrochemical water splitting, but their characteristically poor charge transport properties remain a fundamental challenge to practical use. Nanoporous metal oxide films that feature open bicontinuous networks of nanocrystals and nanopores can overcome such inefficient charge transport to enable high-performance photoanodes. Here, this paper describes a general method to make high-quality nanoporous films of metal oxides by spin coating and calcining molecular inks that contain a porosity-generating block copolymer. Phase-pure nanoporous films of BiFeO 3 , FeWO 4 , WO 3 , Fe 2 O 3 , and TiO 2 serve to demonstrate the versatility of the approach. It is demonstrated that the crystallite size, film porosity, and film thickness can be independently tuned by adjusting the ink composition and film processing conditions. The method is extended to fabricate core–shell nanoporous films consisting of a nanoporous film coated in a thin shell of a second metal oxide, using WO 3 –BiVO 4 and BiFeO 3 –BiVO 4 as examples. Given its simplicity and flexibility, this solution-phase route should prove useful for making nanoporous films of many different materials for a variety of applications, including energy conversion and storage, catalysis, and chemical sensing.

coating materials

Surface science insight note: Optimizing XPS instrument performance for quantification of spectra

X-ray photoelectron spectroscopy (XPS) provides quantitative information from photoemission peaks and shapes observed within the background due to the inelastic scattering of photoelectrons. To quantify the signal, both photoemission peaks and background in spectra must be adjusted for instrumental transmission variations that are a consequence of changes in efficiency when recording electrons with different kinetic energy. While it is generally assumed that correcting spectroscopic data for transmission is a necessary part of quantification by XPS, there are consequences for the quantification of spectra measured using an instrument for which transmission has significant curvature. In this Insight, the implications of curvature in transmission characteristics are discussed and a method based on XPS microscopy is proposed that ensures the transmission response of an instrument is free from significant curvature. An example of an instrument for which a flat transmission response is presented is achieved through collecting spectra using lens modes designed to measure stigmatic images.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Evaluation of 3D pixel silicon sensors for the CMS Phase-2 Inner Tracker

The high-luminosity upgrade of the CERN LHC requires the replacement of the CMS tracking detector to cope with the increased radiation fluence while maintaining its excellent performance. An extensive R&D program, aiming at using 3D pixel silicon sensors in the innermost barrel layer of the detector, has been carried out by CMS in collaboration with the FBK (Trento, Italy) and CNM (Barcelona, Spain) foundries. The sensors will feature a pixel cell size of 25 × 100 µm 2 , with a centrally located electrode connected to the readout chip. The sensors are read out by the RD53A and CROCv1 chips, developed in 65 nm CMOS technology by the RD53 Collaboration, a joint effort between the ATLAS and CMS groups. This paper reports the results achieved in beam test experiments before and after irradiation, up to a fluence of approximately 2 . 6 × 1 0 16 n eq /cm 2 . Measurements of assemblies irradiated to a fluence of 1 × 10 16 n˙eq/cm 2 show a hit detection efficiency higher than 96% at normal incidence, with fewer than 2% of channels masked, across a bias voltage range greater than 50 V . Even after irradiation to a higher fluence of 1.6 × 10 16 n˙eq/cm 2 , similar performance is maintained over a bias voltage range of 30 V , remaining well within CMS requirements.

3D pixel

Theoretical design and performance of three-dimensional, pillared FeS 2 cathodes

Three-dimensional (3D) electrode design can provide improved capacities and rate capabilities over conventional two-dimensional electrodes by enhancing electrical and ionic transport. Here, expanding upon our previous modeling efforts for conversion chemistry lithium-ion batteries, we develop a pseudo-four-dimensional (P4D) approach that is subsequently used to investigate the design of a pillared FeS 2 electrode. The model considers transport in three dimensions with an additional “fourth” dimension corresponding to the solid-state lithium transport within the active material particles. Additionally, we allow for expansion of the active material during the conversion reaction to understand how internal stresses impact the electrochemical performance of the cell. By optimizing the model with respect to areal capacity, we are able to predict areal capacities up to 16.8 mAh/cm 2 for an areal current density of 1.78 mA/cm 2 and a 103% improvement for the three-dimensional electrodes over planar electrodes of equal volume. Despite the promising results, our simulations suggest that 3D design may be difficult for conversion cathode materials due to the large internal stresses that arise during conversion. Nevertheless, the model is robust and adaptable to other materials that may be more suitable for 3D electrodes due to a lesser change in volume during discharge.

Conversion cathode materials

Recyclable Materials for Resource Constrained Environments

In-space manufacturing exhibits severe limitations in resources as astronauts are only afforded with the materials that are brought on-board the space craft. Consequently, the use of recyclable and re-usable materials is paramount. Researchers at NLR leverage their expertise in polymer and recycling chemistry to develop material systems capable of high performance applications with intentional consideration on multi-life use through chemical recycling, mechanical recycling, bio-degradation, and thermoforming. Disclosed within this poster presentation are highlighted projects that illustrate several recyclable by design material systems that have been developed.

09 BIOMASS FUELS

Unique Conductivity Behavior in Water-In-Salt Electrolytes Driven by Ion Clusters

Understanding and predicting ion transport in aqueous electrolytes are crucial for advanced energy storage and biophysics, and many emergent technologies yet remain elusive. Herein, we introduce a unified framework to quantitatively describe and predict electrolyte conductivity that shifts from conventional molar concentration-based metrics to a volume fraction-based approach. Through analyzing a variety of electrolyte solutions via this perspective, we observe a universal conductivity peak at a 37% volume fraction. Small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations reveal that nanometer-scale ion clusters drive this general behavior. Moreover, key geometric features of the ion transport pathwayssuch as pore size, tortuosity, and connectivityfollow a consistent dependence with respect to the volume fraction, reinforcing the argument for the universal conductivity trend. This paradigm shift opens new avenues for designing high-performance electrolytes and provides transformative insights for advancing studies in many fields, wherein molecular aggregates dictate transport properties.

Nguyen, Huong T. D.

Intrinsically Conductive {pi}‑d Conjugated Layers with Co–N4 Active Sites for Efficient Nitrate Electrocatalysis and Zinc-Nitrate Batteries

Electrochemical synthesis of ammonia from nitrate has been extensively investigated as a potential alternative to the energy-intensive Haber-Bosch process. This approach not only operates under ambient conditions but also simultaneously removes nitrate contaminants while producing ammonia as a value-added product. However, the ongoing quest lies in designing an efficient electrocatalyst that achieves a high ammonia yield rate, high selectivity, and long-term stability. Herein, we report the outstanding performance of a Co–N4 coordinated π-d layered Co3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) in nitrate electrocatalysis. The unique combination of abundant Co–N4 active sites and superior electrical conductivity enables significant electrocatalytic activity, delivering a maximum ammonia yield rate of 56.8 mg cm–2 h–1 at −0.8 V vs RHE and a Faradaic efficiency of ∼91% at −0.4 V vs RHE. Mechanistic analysis reveals that alkaline conditions accelerate water dissociation to generate adsorbed hydrogen intermediates (H*), which are utilized by Co–N4 sites to drive the stepwise hydrogenation of nitrate to ammonia while suppressing competing hydrogen evolution reaction (HER) pathways. Furthermore, integration of this catalyst into a zinc-nitrate battery resulted in a maximum power density of 5.3 mW cm–2 and an open-circuit potential of ∼1.45 V. These results highlight the potential of π-d conjugated Co–N4 materials as an efficient catalyst for both environmental remediation and energy conversion.

Namvar, shahrirar

Density Functional Theory Analysis of Candidate Tritium Permeation Barriers for Vanadium Alloys as a Fusion Structural Material

Vanadium alloys are being considered as a candidate structural material for the breeder blanket component of future fusion reactors due to their good thermal conductivity, low activation, and chemical compatibility with FLiBe. However, vanadium has a high hydrogen solubility, resulting in hydrogen diffusion and trapping in the vanadium structural alloy and lower than expected tritium breeding ratios. To mitigate the permeation of hydrogen into the structural alloy, a tritium permeation barrier will be coated onto the vanadium alloy. Multiple materials have been proposed as candidate tritium permeation barriers, but the extent to which each of these materials impacts hydrogen diffusion and trapping is still unknown. In this project, we perform atomic-scale calculations to narrow down the list of potential tritium permeation barrier candidates and to understand the mechanisms through which hydrogen diffusion is affected in these materials.

36 MATERIALS SCIENCE

Techno-Economic Evaluation of a 600MW Pumped Storage Hydropower Plant using the Pumped Storage Hydropower Valuation Tool

This paper presents a techno-economic evaluation of the proposed 600 MW, 8-hour Craig – Hayden pumped storage hydropower project using the U.S. Department of Energy’s Pumped Storage Hydropower Valuation Tool. The analysis integrates plant technical characteristics, regional grid conditions, and market-based operating assumptions to quantify stacked value streams from energy arbitrage, capacity, ancillary services, transmission congestion relief, and reliability. Both price taker and price influencer frameworks are applied to examine the impact of market participation and system interactions on lifecycle economic performance using Benefit - Cost Analysis and Multi - Criteria Decision Analysis. The results show that the price taker approach provides higher revenue estimates based on exogenous price signals, while the price influencer approach captures production cost savings, renewable curtailment reduction, and market price formation, yielding more conservative but system-representative outcomes. The study demonstrates the strategic value of long-duration PSH for enhancing operational flexibility, resource adequacy, and grid reliability in a high-renewable Western Interconnection.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046

Activation dynamics of a water-soluble human mu-opioid receptor

The mu-opioid receptor (MOR), a class A G protein-coupled receptor mediates opioid analgesia and remains a central target for pain therapeutics. While crystal structures of MOR exist, they provide limited insight into the receptor’s dynamic conformational landscape underlying function. Here, we engineered a thermostable water-soluble MOR variant (wsMOR) that retains native-like ligand-binding and activation dynamics. This variant enables high-yield production and detailed solution-phase structural studies that are challenging with membrane-embedded MOR, providing a valuable tool for studying receptor activation and aqueous-phase drug screening. Using a combined computational and experimental approach, we performed long-timescale all-atom molecular dynamics simulations together with neutron scattering and single-molecule FRET, revealing a structurally stable receptor with a diverse ensemble of conformations at different temporal resolutions. In the ligand-free state, wsMOR displayed high conformational flexibility, which decreased upon agonist binding, particularly in transmembrane helix 6, a hallmark of G protein-coupled receptor activation. Positive allosteric modulation and G protein binding further stabilized active-like states. These findings highlight wsMOR’s conformational plasticity across picosecond to millisecond timescales and provide a foundation for structure-guided development of next-generation opioid ligands with improved efficacy and safety.

E, Agyemang [University of Tennessee Knoxville]

Wide-ranging predictions of new stable compounds powered by recommendation engines

The computational search for new stable inorganic compounds is faster than ever, thanks to high-throughput density functional theory (DFT). However, stable compound searches remain highly expensive because of the enormous search space and the cost of DFT calculations. To aid these searches, recommendation engines have been developed. We conduct a systematic comparison of the performance of previously developed recommendation engines, specifically ones based on elemental substitution, data mining, and neural network prediction of formation enthalpy. After identifying ways to improve the recommendation engines, we find the neural network to be superior at recommending stable Heusler compounds. Armed with improved recommendation engines, we identify tens of thousands of compounds that are stable at zero temperature and pressure, now available in the Open Quantum Materials Database. We summarize this diverse pool of compounds, including the elusive mixed anion compounds, and two of their many applications: thermoelectricity and solar thermochemical fuel production.

Science & Technology - Other Topics

Revealing the Roles of CuF 2 /NiF 2 Incorporation in the Electrochemical Performance of FeF 3 Cathodes in Solid‐State Batteries

Mixed metal fluorides have been considered as a promising candidate to lower the voltage hysteresis of conversion-type iron fluoride cathodes, but their cycling stability is limited due to transition metal dissolution and interphase growth in liquid electrolyte batteries. Here, we study the role of incorporating CuF 2 and NiF 2 in the electrochemical performance of FeF 3 cathode in halide-based solid-state batteries to test whether we can transfer the kinetic benefit of low voltage hysteresis to solid-state batteries while using solid electrolyte to eliminate transition metal dissolution and stabilize the interphase. Synchrotron X-ray absorption spectroscopy results indicated the redox reactions are attributed to Cu 0 /Cu + and Fe 0 /Fe 2+ in 25CuF 2 -75FeF 3 and Ni 0 /Ni 2+ and Fe 0 /Fe 3+ in 10NiF 2 -90FeF 3 . While no apparent improvement in electrode kinetics can be observed, the incorporation of CuF 2 and NiF 2 can largely improve the cycling stability of FeF 3 cathodes. In conclusion, the results demonstrate the advantages of using solid-state concept to improve the cycling stability of conversion-type cathodes.

25 ENERGY STORAGE

Design of a Cryogenic Assembly for Comparing Qubit Infrared Packaging Inefficiencies

It is well known that everything emits infrared (IR) light in the form of thermal radiation. IR radiation on superconducting qubits carries enough energy to cause decoherence and so-called “quasiparticle poisoning.” Therefore, proper IR shielding is needed to keep the qubit in a high coherence state. However, trying to extract IR-specific information from a qubit is difficult, so a microwave kinetic inductance detector (MKID) can be used instead. We show that the IR shielding inefficiencies of MKID packages can only be compared with other packaging inefficiencies. We create a cryogenic assembly CAD design, consisting of magnetic shield cans, a copper mounting plate and mounts, and an MKID enclosure, which thermalizes the assembly to dilution refrigerator temperatures. Phase 1 of this design involves using a narrowband IR laser source to test the IR shielding of packaging at the laser’s wavelength. When the best IR shielding packaging is determined, the superconducting qubit can replace the MKID, allowing the qubit to avoid decoherence due to IR radiation and boost its performance and coherence lifetime.

Mailliard, Robert J. [Fermilab] (ORCID:00090000277

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)

Polymer-assisted transfer of MBE-grown van der Waals materials

Molecular beam epitaxy (MBE) has been used to create high-quality, large-scale two-dimensional van der Waals (2D vdW) materials. However, due to the strong adhesion between the substrate and deposited materials, the peel-off and dry transfer of MBE-grown vdW films onto other substrates has been challenging. This limits the study and use of MBE films for heterogeneous integration including stacked and twisted heterostructures. In this work, we develop a polymer-assisted dry transfer method and successfully perform full-film transfer of various MBE-grown 2D vdW materials including transition metal dichalcogenides (TMD), topological insulators (TI) and 2D magnets. In particular, we transfer air-sensitive 2D magnets, characterize their magnetic properties, and compare them with as-grown materials. The results show that the transfer technique does not degrade the magnetic properties, with the Curie temperature and hysteresis loops exhibiting similar behaviors after the transfer. Our results enable further development of heterogeneous integration of 2D vdW materials based on MBE growth.

Li, Ziling [The Ohio State University]