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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 379 records · Page 21

Intercalation-Activated Layered MoO 3 Nanobelts as Biodegradable Nanozymes for Tumor-Specific Photo-Enhanced Catalytic Therapy

The existence of natural van der Waals gaps in layered materials allows them to be easily intercalated with varying guest species, offering an appealing strategy to optimize their physicochemical properties and application performance. Herein, we report the activation of layered MoO 3 nanobelts via aqueous intercalation as an efficient biodegradable nanozyme for tumor-specific photo-enhanced catalytic therapy. In this work, the long MoO 3 nanobelts are grinded and then intercalated with Na + and H 2 O to obtain the short Na + /H 2 O co-intercalated MoO 3–x (NH–MoO 3–x ) nanobelts. In contrast to the inert MoO 3 nanobelts, the NH–MoO 3–x nanobelts exhibit excellent enzyme-mimicking catalytic activity for generation of reactive oxygen species, which can be further enhanced by the photothermal effect under a 1064 nm laser irradiation. Thus, after bovine serum albumin modification, the NH–MoO 3–x nanobelts can efficiently kill cancer cells in vitro and eliminate tumors in vivo facilitating with 1064 nm laser irradiation.

36 MATERIALS SCIENCE↗

Enzymatic depolymerization of polyester: Foaming as a pretreatment to increase specific surface area

Abstract Poly(ethylene terephthalate) (PET) is widely used for its high strength‐to‐weight ratio, gas barrier properties, and chemical resistance. The growing PET use highlights the demand for a better recycling system. Enzymatic recycling, alongside mechanical and chemical methods, is eco‐friendly and yields properties similar to virgin PET. Substrate properties ( T g , crystallinity, and specific surface area [SSA]) and enzyme stability significantly impact conversion efficiency. Higher SSA and lower crystallinity tend to yield improved depolymerization when employing leaf compost‐cutinase (LCC‐ICCG) enzymes. This study explored melt extrusion and foaming as pretreatment techniques to modify PET structural properties, using a low‐cost chemical foaming agent (CFA). The monomer conversion rate and efficiency during depolymerization were measured and related to the processing, extrudate micro‐ and meso‐structure, and polyester type. Pretreated PET substrates showed reduced T g , crystallinity, density, and enhanced SSA, resulting in a 90% mass loss for foamed RPET and VPET substrates within 2 days. In contrast, PET with ~30% of cyclohexanedimethanol comonomer exhibited a nearly 50% lower depolymerization rate, with zero BHET production. It indicates that the combination of low crystallinity, low T g , and high SSA leads to improved monomer conversion. These findings emphasize the significance of amorphization and foaming in enhancing PET enzymatic depolymerization.

42 ENGINEERING↗

A separations and purification process for improving yields and meeting fuel contaminant specifications for high-octane gasoline produced from dimethyl-ether over a Cu/BEA catalyst

In this work, we have been developing a three-step conversion of biomass-derived syngas to methanol to dimethyl-ether (DME) to non-aromatic hydrocarbons for use as high-octane gasoline and sustainable aviation fuel. This process produces branched alkanes from DME using a Cu/BEA catalyst and is a promising alternative to other syngas conversion processes such as Fischer-Tropsch to linear alkanes and traditional ZSM-5 catalyzed methanol to aromatic gasoline. In this short article we describe some advances in our understanding related to separations and purification via the use of more detailed experimental speciation in an updated process model involving multiple phase equilibrium-based separation steps. Primary modeled reactor outlet constituents (and weight %) are: C3 and lighter hydrocarbon gases (11.1%), C4s (54.5%), H 2 (1.2%), CO 2 (2.9%), water (5.0%), unreacted DME (16.5%), methanol (2.3%), and C5+ hydrocarbons (6.4%). DME (the primary reactant) and H 2 recycle and reuse are important for the overall process efficiency, and the recycle of C4s is important to increase the C5+ yield via reactivation and homologation. Thus H 2 , C4s, and DME are targeted for recycle, while methanol and water need to be removed from the product to conform with fuel specifications. Model predictions from Aspen Plus using the NRTL-RK property method indicate a fuel composition with C5+ content of 97.1 wt%, with minor constituents: 2.4 wt% C4s, 0.3 wt% methanol, 0.1 wt% DME, 0.03 wt% water, and 0.01 wt% C3s. These ranges of minor components conform with fuel quality requirements, and the modeled product is amenable for unconstrained blending to boost gasoline octane ratings.

09 BIOMASS FUELS↗

Establishing the accuracy of position–specific carbon isotope analysis of propane by GC–pyrolysis–GC–IRMS

Rationale: Position-specific (PS) δ 13 C values of propane have proven their ability to provide valuable information on the evolution history of natural gases. Two major approaches to measure PS δ 13 C values of propane are isotopic 13 C nuclear magnetic resonance (NMR) and gas chromatography-pyrolysis-gas chromatography-isotope ratio mass spectrometry (GC-Py-GC-IRMS). Measurement accuracy of the isotopic 13 C NMR has been verified, but the requirements of large sample size and long experimental time limit its applications. GC-Py-GC-IRMS is a more versatile method with a small sample size, but its accuracy has not been demonstrated. Methods: We measured the PS δ 13 C values of propane from nine natural gases using both 13 C NMR and GC-Py-GC-IRMS, then evaluated the accuracy of the GC-Py-GC-IRMS method. Results: The results show that large carbon isotope fractionations occurred for both terminal and central carbons within propane during pyrolysis. The isotope fractionations during the pyrolysis are reproducible at optimum conditions, but vary between the two GC-Py-GC-IRMS systems tested, affected by experimental conditions (e.g., pyrolysis temperature, flow rate, and reactor conditions). Conclusions: It is necessary to evaluate and calibrate each GC-Py-GC-IRMS system using propane gases with accurately determined PS δ 13 C values. Finally, this study also highlights a need for PS isotope standards for propane and other molecules (e.g., butane and acetic acid).

03 NATURAL GAS↗

Influence of ion site occupancies on the unit cell parameters, specific volumes, and densities of M 8 (AlSiO 4 ) 6 X 2 sodalites where M = Li, Na, K, Rb, and Ag and X = Cl, Br, and I

Here, this paper discusses the effects of composition on the unit cell parameter (a), unit cell volume (V), specific volume (v), and density (ρ) of various sodalite compositions including $M^+_8$(AlSiO 4 ) 6 Cl 2 (M = Li, Na, K, Rb, and/or Ag) and Na8(AlSiO 4 ) 6 $X^-_2$(X = Cl, Br, and/or I). Compositional models were developed, and the results show that the models are successful at predicting a, V, and v (and thus ρ) within the compositional range available in the literature. Discussion is included on the correlation between the ionic radii of the alkali metals and halides in the sodalite β-cages and the measured values of a, V, v, and ρ. The data show linear increases in a and ρ with increases in the average ionic radii of the M + and X - constituents (data for v show a linear decrease).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Application of machine learning for modeling brønsted-guggenheim-scatchard specific ion interaction theory (SIT) coefficients

Machine learning methodologies can provide insight into Brønsted-Guggenheim-Scatchard specific ion interaction theory (SIT) parameter values where experimental data availability may be limited. This study develops and executes machine learning frameworks to model the SIT interaction coefficient, ε. Key findings include successful estimations of ε via artificial neural networks using clustering and value prediction approaches. Additionally, applicability to other chemical parameters is also assessed briefly. Models developed here provide support for a use-case of machine learning in geologic nuclear waste disposal research applications, namely in predictions of chemical behaviors of high ionic strength solutions (i.e., subsurface brines).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Product-specific kinetics reveal effect of epoxy crystallization on thermoset thermal degradation

Crystallization is a common problem for epoxy resins, which are ubiquitous in industrial and commercial use. Integration of crystallized epoxy monomers into cured thermosets has been shown to alter the thermosets’ final mechanical properties. However, no studies have investigated the impact of these crystals on the thermal stability of the thermoset. Here we investigate the degradation kinetics of a bisphenol F–based epoxy thermoset with and without crystallized monomers using Product-Specific Kinetic (PSK) analysis coupled with Evolved Gas Analysis-Mass Spectrometry (EGA-MS). PSK analysis revealed significant differences in evolved product ion kinetics, suggesting changes in the degradation kinetics between thermoset configurations. Further, it was concluded that early stages of degradation are influenced most by crystal presence due to the high concentration of unreacted epoxy monomers and lower cross-linking density of the cured network. After post-cure annealing, significant changes are observed in the degradation kinetics of thermosets without crystal inclusions. Conversely, post-cure annealing procedures of crystal integrated thermosets showed little change in the thermoset degradation kinetics across all conversion extents. These findings suggest that post-cure annealing of thermosets with crystals present at the onset does not alter the cross-linking density of the polymer network enough to significantly change the degradation kinetics. We hypothesize this is because the excess monomers from the melted crystals are unable to find suitable reaction sites for complete binding into the polymer network, which has direct implications for the material properties and final thermal stability of the thermoset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10 –6 ) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10 –6 ) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10 –6 ) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

60 APPLIED LIFE SCIENCES↗

A Proxy Method to Bridge LCA Data Gaps Using Automated Material Classification and Probabilistic Under-Specification

Life cycle assessments (LCAs) are essential for understanding the environmental impacts of material production. However, gaps in life cycle inventory (LCI) data for material and chemical inputs present a key challenge for LCA practitioners, especially in the early design stages. Strategies for filling in these gaps require additional time and expertise, which can hinder the LCA’s completion. This study combined automatic material classification and probabilistic under-specification to create a time-efficient method to fill material LCI data gaps. To illustrate the proposed method, proxy environmental impact distributions were generated using publicly available material LCI data classified into the ChemOnt chemical taxonomy using the open-source chemical classification software ClassyFire. Input materials with data gaps were then classified into the same taxonomy, where proxy environmental impact values could be selected from the available distributions to quickly fill in any data gaps. Although these methods were applied to classify material production processes available in the Federal LCA Commons and Ecoinvent databases, they can be applied to any LCA database. This study shows that classifying materials by their chemical structure produces taxonomies with increased granularity relative to industrial classification, improving the ability of under-specified proxy data to be used for differentiating the environmental impacts of competing designs.

biological databases↗

Spontaneous and Ion-Specific Formation of Inverted Bilayers at Air/Aqueous Interface

Developing better separation technologies for rare earth metals, an important aspect of a sustainable materials economy, is challenging due to their chemical similarities. Identifying molecular scale interactions that amplify the subtle differences between the rare earths can be useful in developing new separation technologies. Here, we describe ion-dependent monolayer to inverted bilayer transformation of extractant molecules at the air/aqueous interface. The inverted bilayers form with Lu 3+ ions but not with Nd 3+ . By introducing Lu 3+ ions to preformed monolayers, we extract kinetic parameters corresponding to the monolayer to inverted bilayer conversion. Further, temperature-dependent studies show Arrhenius behavior with an energy barrier of 40 kcal/mol. The kinetics of monolayer to inverted bilayer conversion is also affected by the character of the background anion, although anions are expected to be repelled from the interface. Our results show the outsized importance of ion-specific effects on interfacial structure and kinetics, pointing to their role in chemical separation methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptation of Wallace's approach to the specific heat of elemental solids with significant intrinsic anharmonicity, particularly the light actinide metals

The quasiharmonic approximation is the most common method for modeling the specific heat of solids; however, it fails to capture the effects of intrinsic anharmonicity. In this study, we introduce the “elastic softening approximation,” an alternative approach to modeling intrinsic anharmonic effects on thermodynamic quantities, which is grounded in Wallace's thermodynamic framework that tracks entropy changes resulting from the continuous change (e.g., softening) of phonons as a function of temperature. A key finding of our study is a correlation between Poisson's ratio and the differential rate of phonon softening at finite frequencies, compared to lower frequencies relevant to elastic moduli measurements. We observe that elemental solids such as α -Be, diamond, Al, Cu, In, W, Au, and Pb, which span a wide range of Poisson's ratios and exhibit varying degrees of intrinsic anharmonicity, consistently follow this trend. When applied to α -U, α -Pu, and δ -Pu, our method reveals unusually large anharmonic phonon contributions at elevated temperatures across all three light actinide metals. These findings are attributed to the unique combination of enhanced covalency and softer elastic moduli inherent in the actinides, potentially influenced by their 5 f -electron bonding. Published by the American Physical Society 2025

36 MATERIALS SCIENCE↗

Recent Progress in Developing Nb 3 Sn Conductors With Increased Specific Heat

A possible approach to reducing Nb 3 Sn magnet training is to increase the energy margin of Nb 3 Sn conductors by enhancing their specific heat (C p ). For this study, we have been developing Nb 3 Sn conductors with increased C p by incorporating substances with high C p at 2-10 K based on a conductor design that is compatible with standard Nb 3 Sn strand production. In the past couple of years our efforts have been mainly focused on improving strand design (e.g., position of high- C p filaments, thickness of the Cu tube for the high-C p filaments, ratio of the Cu powder to the high-C p substance, filament spacing, etc.) in order to obtain good strand drawability and to reduce degradation after rolling, which is needed for production of Rutherford cables. We also tried a new high-C p substance, Gd 2 O 2 S, and verified that it has much higher C p over the whole magnetic field range than the Gd 2 O 3 we used before. With that development work we can now produce high-C p strands with good drawability and low levels of degradation after rolling. This paper reports our findings and the current status of the development of high-C p Nb 3 Sn conductors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Identification and analysis of stem‐specific promoters from sugarcane and energy cane for oil accumulation in their stems

Abstract Considerable recent progress has been achieved in bioengineering oil accumulation in the vegetative tissues of plants, opening an opportunity for large scale production of biodiesel, jet fuel, lubricants, and high‐value lipid bioproducts. For the highly productive C4 crops, such as sugarcane, energy cane, Miscanthus, and fiber sorghums, the bulk of the biomass is the stem. However, little success has been made in accumulating oil in the stem. Since engineering a trait with a constitutive promoter often results in pleiotropic effects that counter trait improvement, identification of stem parenchyma‐specific promoters is a prerequisite for efficient use of the ample photoassimilates stored in mature stem parenchyma cells. In this study, we first identified two TST genes encoding homologues of tonoplast sugar transporters that were strongly and almost exclusively expressed in the stems of canes via a combination of RNA‐seq atlas analysis, in silico analysis of a sugarcane genome, phylogenetic analysis, and quantitative PCR analysis. They were further confirmed in the pith parenchyma cells of the mature stem by RNA in situ hybridization. When fused with the β‐Glucuronidase (GUS) reporter gene, the promoters of two alleles, TST2b‐1A and TST2b‐1C , from one TST gene demonstrated that they could drive the GUS expression exclusively in the stem in Arabidopsis.

09 BIOMASS FUELS↗

QCOR; A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Quantum computing (QC) is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for QC were designed with fault-tolerant hardware in mind, envisioning stand-alone applications. However, the susceptibility of near-term quantum computers to noise limits their stand-alone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, which enables single-source quantum-classical programming. Programs written using the QCOR library–based language extensions can be compiled to produce functional hybrid binary executables. After defining QCOR’s programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed-forward QC. Additionally, QCOR approaches quantum-classical computation in a hardware-agnostic heterogeneous fashion and strives to build on best practices of high-performance computing. The high level of abstraction in the language extension is intended to accelerate the adoption of QC by researchers familiar with classical high-performance computing.

97 MATHEMATICS AND COMPUTING↗

Comparison and investigation of production of specific nuclides by different fission yield data

Generally, passive gamma spectroscopy (PGS) is known as a useful technique for nondestructive measurement of burnup and nuclide production in normal spent nuclear fuel. However, PGS can be used not only for normal spent fuel, but also for molten fuel generated in severe accidents involving core meltdowns. In such cases, it is estimated by the radioactivity ratios of specific nuclides. At the time of the decommissioning of the Three Mile Island's unit 2 reactor, fission products (FPs) such as Cs{sup 134}, Cs{sup 137}, Ce{sup 144}, Eu{sup 154}, Ru{sup 106}, and Sb{sup 125} were concerned. The radioactivity ratios are estimated by numerical simulations. However, there are various uncertainties in numerical simulations. In this study, we evaluated the effect of the difference in fission yield data. We compared the productions of concerned nuclides of Three Mile Island's unit 2 reactor by using Tokyo-tech and JENDL FP Fission Yields Data File 2011(FPY- 2011). Tokyo-tech is newly created by Tsubakihara et al. at Tokyo Institute of Technology. FPY-2011 is currently the latest fission yield data in Japan. In the concerned nuclides, the relative difference (Tokyo-tech/FPY-2011 -1) in the production of Sb{sup 125} is 4.5% and that of Eu{sup 154} is -5.6%. The relative difference in the production of Sb{sup 125} is found to be caused by the difference in the independent yields of Sn{sup 125}, In{sup 125}, Cd{sup 125}, Ag{sup 125}, and Pd{sup 125}. The relative difference in Eu{sup 154} is found to be caused by the relative difference in the production of Sm{sup 152} and the relative difference in the cumulative yield of Eu{sup 153}.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Temporal Study 2022-2024: Sensor-Based Time Series of Surface Water Temperature, Specific Conductance, Total Dissolved Solids, Turbidity, Chlorophyll A, and Dissolved Oxygen from across Multiple Watersheds in the Yakima River Basin in Washington, USA

This dataset supports a broader study examining the drivers of temporal variability in sediment respiration rates in the Yakima River Basin. The dataset provides periodic (bi-weekly or monthly) in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata collected at six sites across the Yakima River Basin in Washington, USA. Sample and sensor data from previous years (2021-2022) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1898912 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1892054, respectively. Related sample data from 2022-2024 are available at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2562910. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions This dataset contains a folder of environmental context photographs and videos and (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) field protocols; (6) international generic sample number (IGSN) mapping file; (7) handheld sensor data; and (8) two sensor subfolders. Each sensor subfolder (BarotrollAtm and MantaRiverData) contains a subfolder containing sensor time series data and plots. The BarotrollAtm Data subfolder contains In Situ Rugged BaroTROLL sensor pressure and air temperature data. The MantaRiverData subfolder contains Eureka Manta+ 35B multisonde temperature, specific conductance, and chlorophyll A. All files are .csv, .pdf, .jpg, .jpeg, .mp4, .png, or .mov.

54 ENVIRONMENTAL SCIENCES↗