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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 91 records · Page 5

Proteomic Characterization of Damaged Single Hairs Recovered after an Explosion for Protein-Based Human Identification

Evidence recovery is challenging where an explosion has occurred. Though hair evidence may be sufficiently robust to be recovered at the site, forensic analysis underutilizes the matrix by relying on morphological analysis. Where DNA is compromised, particularly in hair, protein-based human identification presents a promising alternative. Detection of amino acid polymorphisms in hair proteins as genetically variant peptides (GVPs) permits the inference of individualizing single nucleotide polymorphisms for identification. However, an explosive blast may damage hair proteins and compromise GVP identification. This work evaluates effects of an explosive blast on the hair proteome and GVP identification, investigates microscopy as a predictor of proteome profiling success in recovered hairs to improve analysis throughput, and quantifies discriminative power in damaged hairs. The proteomics dataset has been deposited into the ProteomeXchange Consortium (PXD017427). With the exception of degradation in keratins K75, K80, K40, and keratin-associated protein KAP10-11 as markers of hair cuticular damage, corroborated by scanning electron microscopic analysis, minimal hair proteome degradation following explosion allowed successful proteome profiling of single hairs regardless of morphological damage. Finally, GVP identification remained independent of explosion conditions, permitting similar discriminative power between exploded and undamaged hairs. These findings lend greater confidence to GVP analysis in one-inch hairs for forensic identification and provide information about hair protein localization.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing Solar PV Deployment in Manufacturing: A Morphological Matrix and Fuzzy TOPSIS Approach

The growing energy demand of the industrial sector and the need for sustainable solutions highlight the importance of efficient decision making in solar photovoltaic (PV) implementation. Selecting optimal PV configuration is complex due to the interdependent technical, economic, environmental, and social factors involved. This study introduces an integrated decision-making method combining a morphological matrix and fuzzy TOPSIS to systematically select and rank optimal PV system configurations for manufacturing firms. While the morphological matrix exhaustively examines possible design solutions based on sensing, smart, sustainable, and social (S4) attributes, the fuzzy TOPSIS method ranks the alternatives by handling uncertainty in decision making. A case study conducted in a Mexican manufacturing company validates the methodology’s effectiveness. The optimal PV configuration identified comprehensively addresses operational and sustainability criteria, covering all lifecycle stages. This approach demonstrates quantitative superiority and greater robustness compared to existing fuzzy TOPSIS-based methods for solar PV applications. The findings highlight the practical value of data-driven, multi-criteria decision making for industrial solar energy adoption, enhancing project feasibility, cost efficiency, and environmental compliance. Future research will incorporate discrete event simulation (DES) to further refine energy consumption strategies in manufacturing.

Briceño, Citlaly Pérez↗

Low-Velocity Impact Performances of Healed Polymer Fiber Reinforced Plastics

Extending the lifecycle of traditional carbon or glass fiber-reinforced plastics is a complicated problem. The lack of sustainability limits the applications of the traditional composite materials in the vehicle industries where recycling and repurposing are critical issues. Alternatives for the low-stressed structural components are polymer fiber-reinforced plastics (PFRPs). In PFRPs, both the fibers and matrix are composed of thermoplastic polymers (e.g. polypropylene or polyethylene). They are lightweight, easy to manufacture, and cost-effective. Additionally, recycling and repurposing thermoplastic polymers are well understood. Therefore, the PFRPs have strong advantages compared to the traditional fiber-reinforced composites in low-stressed structural applications. In this study, we investigated the low-velocity impact (LVI) performances of the PFRPs and compared them with carbon fiber-reinforced plastics (CFRPs). A semi-spherical impactor was dropped to flat, square panels, and the absorbed impact energy was measured. The damage mechanisms were examined using a Xray µCT scan. The PFRPs outperformed the CFRPs in terms of perforation energy normalized by plate thickness and density. After the perforation, we healed the fractured plates by leveraging the recyclability of the thermoplastic polymers. The healing process of the panels was identical to the initial panel manufacturing process. No additional materials were added during the healing process. The healed PFRP panels were impacted again and substantially recovered energy absorption capability. We also conducted the repeated-impact test with several different impact energies. Unlike the CFRPs where the impact peak load decreased as the impacts repeated, the PFRPs showed an increasing trend. Such a unique mechanism was due to the strain-hardening behavior of the polymer fibers and matrix. As a result, the repeated-impact life of the PFRPs was significantly enhanced. These results are particularly interesting in the automotive or aerospace industries where repeated LVI is frequently observed.

Ko, Seunghyun↗

Fully Recyclable Advanced Composites with Reduced Cure Times for Improved Manufacturing Efficiency

At Cyclotron Road, the participant team from Mallinda focused its research efforts on developing its Polyimine chemistry for commercial applications. The value-differentiating characteristics of the technology are predicated on the chemical reversibility of the system which opens the door for a number of industrial applications. In short, the company’s technology is a highly crosslinked thermoset polymer network that can exchange covalent bonds within the polymer matrix when the polymer is heated to the glass transition temperature of the material. This leads to a resin system that can alternate between rigid and semi-rigid states; allowing for compression molding, and surface welding of thermosetting composite materials made with polyimine polymers. This research project worked towards improving the thermal properties of its resin from 80 °C to over 260 °C. The improved properties of Mallinda’s resin unlocks development potential within the automotive and aerospace markets where advance composite materials require stringent performance requirements and elevated operating temperatures.

36 MATERIALS SCIENCE↗

Sludge Batch 10 Frit Development and Variability Study Matrix Design

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26H, and Alternate Feed Stock-2 (AFS-2). H-Canyon also had a need to discard Sodium Reactor Experiment (SRE) material that was stored in Tanks 16.3 and 16.4. Savannah River Remediation (SRR) added a portion of the SRE material to Sludge Batch 9 (SB9) in Tank 40 and the remainder was added to SB10 that is currently being prepared in Tank 51. In support of sludge batch preparation and qualification efforts, SRR requested that the Savannah River National Laboratory (SRNL) complete the following tasks based on the SB10 projections provided by the SRR System Planning group.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Beyond Component Optimization: Systems Level Biodesign for Lanthanide Recovery

Global demand for lanthanides (Ln) is projected to rise sharply over the next decade, while geographically concentrated supply chains and the low concentrations and matrix complexity of secondary feedstocks limit the reach of conventional hydro- and pyrometallurgical separation. Engineered biological systems offer a selective, low-energy alternative, and component-level advances in Ln-binding proteins, AI-designed selective scaffolds, and cell-surface display platforms now rival synthetic chelators in affinity and selectivity. These components, however, remain functionally isolated. Currently, there are no engineered chassis coupling recognition, intracellular trafficking, accumulation, and controlled release into an end-to-end pipeline. Here, we outline how new biodesign strategies and chassis selection must move beyond bioleaching to encompass the full recovery pathway. Achieving this requires integrating AI/ML-guided design, genome-scale build tools, high-throughput phenotyping, and biophysical transport modeling within a Design–Build–Test–Learn cycle tuned to recognition, trafficking, accumulation, and release.

Biodesign↗

Analytical derivatives of the individual state energies in ensemble density functional theory. II. Implementation on graphical processing units (GPUs)

Conical intersections control excited state reactivity, and thus, elucidating and predicting their geometric and energetic characteristics are crucial for understanding photochemistry. Locating these intersections requires accurate and efficient electronic structure methods. Unfortunately, the most accurate methods (e.g., multireference perturbation theories such as XMS-CASPT2) are computationally challenging for large molecules. The state-interaction state-averaged restricted ensemble referenced Kohn–Sham (SI-SA-REKS) method is a computationally efficient alternative. The application of SI-SA-REKS to photochemistry was previously hampered by a lack of analytical nuclear gradients and nonadiabatic coupling matrix elements. We have recently derived analytical energy derivatives for the SI-SA-REKS method and implemented the method effectively on graphical processing units. We demonstrate that our implementation gives the correct conical intersection topography and energetics for several examples. Furthermore, our implementation of SI-SA-REKS is computationally efficient, with observed sub-quadratic scaling as a function of molecular size. This demonstrates the promise of SI-SA-REKS for excited state dynamics of large molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Solid, structured composite neutron detectors with high dynamic range capability

Neutron detectors are essential across disciplines such as fundamental science, nuclear security, safeguards, and civilian applications. While 3 He-filled gas proportional counters have long been revered for their efficacy in detecting thermal neutrons and praised for their efficiency, neutron/gamma discrimination, and stability, the scarcity of 3He has spurred a search for alternatives. Here, we explore a solid structured scintillating particle composite (SPC) consisting of 6 Li-containing scintillating glass particles within an acrylic matrix as a neutron detector for high dynamic range applications. We show for the first time that an SPC neutron detector can boast an intrinsic detection efficiency of 0.261% for pure 252 Cf fission neutrons and an overall neutron detection efficiency of (0.546 ± 0.003)% at the Neutron Free-in-Air facility while being able to function in an intense gamma-ray environment. We also show that the SPC neutron detector supports fast neutron capture times and enables a dual-readout scheme that extends the detector dynamic range to high incident neutron fluxes. A scalable fabrication process allows for tailoring the SPC detector properties to the requirements of specific applications. Good agreement is found between the experimental results taken with a National Institute of Standards and Technology traceable 252 Cf source and the coupled MCNP6 and optical-ray-tracing simulations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Synergistic effects of W–Ta alloys exposed to various ELM-like fusion events

Abstract Recently tungsten alloys have shown capabilities in suppressing morphological changes when exposed to harsh fusion conditions. Morphological changes due to He + and D + ions at high temperatures (1000–2000 K) can lead to easier erosion and sputtering of tungten (W) particles towards quenching the fusion plasma. This study investigated W–3Ta alloy as potential plasma facing materials (PFMs) exposed to different edge-localized mode (ELM)-like energies and ion loadings. Performance of W–3Ta has been tested as a function of ELM-like energies (0.6–1.5 GW m −2 ) and varying He + and D + ion concentrations (100% He + , 50% He + :50% D + ,10% He + :90% D + (similar ELM-like reactor condition), and 100% D + ions). Early-stage fuzz formation and surface pores were observed during 100% He + ion irradiation and mixed ion loadings but not observed during 100% D + ion loadings. Pores decreased in quantity and increased in size with increasing transient heat loading. Grain boundaries acted as trapping sites of helium and deuterium atoms during dual beam ion irradiations, as observed through increased pore size along the grain boundary. Qualitative erosion estimates were measured using witness plates. Increased erosion was observed with increasing D + ion concentration, which is attributed to D supersaturation in the near surface region affecting thermal and mechanical properties. More erosion was observed for W–3Ta samples compared to pure W, evident through large (>10 µ m) cracks on the surface, and an increase in W metal x-ray photoelectron spectroscopy peaks under similar loading conditions. The slight enhancement in erosion is attributed to the slightly decreased thermal properties, ∼10% thermal diffusivity drop, of W–3Ta at high temperatures. The damage threshold was impacted by ion loading, where distinct cracking was observed for 100% He + at a lower heat loading. This matrix study using reactor-like loading supports the need for extensive studies on future W alloy PFMs before selecting one as an alternative.

Physics↗

Constructing a Simulation Surrogate with Partially Observed Output

Gaussian process surrogates are a popular alternative to directly using computationally expensive simulation models. When the simulation output consists of many responses, dimension-reduction techniques are often employed to construct these surrogates. However, surrogate methods with dimension reduction generally rely on complete output training data. This article proposes a new Gaussian process surrogate method that permits the use of partially observed output while remaining computationally efficient. The new method involves the imputation of missing values and the adjustment of the covariance matrix used for Gaussian process inference. The resulting surrogate represents the available responses, disregards the missing responses, and provides meaningful uncertainty quantification. In conclusion, the proposed approach is shown to offer sharper inference than alternatives in a simulation study and a case study where an energy density functional model that frequently returns incomplete output is calibrated.

42 ENGINEERING↗

The Diffusion Mechanism of Ge During Oxidation of Si/SiGe Nanofins

A recently discovered, enhanced Ge diffusion mechanism along the oxidizing interface of Si/SiGe nanostructures has enabled the formation of single-crystal Si nanowires and quantum dots embedded in a defect-free, single-crystal SiGe matrix. Here, we report oxidation studies of Si/SiGe nanofins aimed at gaining a better understanding of this novel diffusion mechanism. Here, a superlattice of alternating Si/Si 0.7 Ge 0.3 layers was grown and patterned into fins. After oxidation of the fins, the rate of Ge diffusion down the Si/SiO 2 interface was measured through the analysis of HAADF-STEM images. The activation energy for the diffusion of Ge down the sidewall was found to be 1.1 eV, which is less than one-quarter of the activation energy previously reported for Ge diffusion in bulk Si. Through a combination of experiments and DFT calculations, we propose that the redistribution of Ge occurs by diffusion along the Si/SiO 2 interface followed by a reintroduction into substitutional positions in the crystalline Si.

36 MATERIALS SCIENCE↗

An Alternative Conceptual Model for the Spent Nuclear Fuel–Water Interaction in Deep Geologic Disposal Conditions

For the long-term safety assessment of direct disposal of spent nuclear fuel in deep geologic repositories, knowledge on the radionuclide release rate from the UO 2 matrix is essential. This work provides a conceptual model to explain the results of leaching experiments involving used nuclear fuel or simulant materials in confirmed reducing conditions. Key elements of this model are: direct effect of radiation from radiolytic species (including defects and excited states) in the solid and in the first water layers in contact with its surface; and excess H 2 may be produced due to processes occurring at the surface of the spent fuel and in confined water volumes, which may also play a role in keeping the spent fuel surface in a reduced state. The implication is that the fractional radionuclide release rate used in most long-term safety assessments (10 -7 year -1 ) is over estimated because it assumes that there is net UO 2 oxidation caused by radiolysis, in contrast with the alternative conceptual model presented here. Furthermore, conventional water radiolysis models and radiation chemical yields published in the literature are not directly applicable to a heterogeneous system such as the spent fuel–water interface. Suggestions are provided for future work to develop more reliable models for the long-term safety assessment of spent nuclear fuel disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Low-Cost, High-Performance Carbon Fiber for Compressed Natural Gas Storage Tanks (Final Technical Report – Down Select Report)

The aim of this project is to reduce the cost of Type IV, carbon fiber (CF) composite overwrap compressed gas storage tanks by reducing the cost of CF and CF composites. The project team worked to reduce the cost of CF by exploring and testing opportunities for a low-cost alternative precursor material for CF production to supplant market-dominant and costly polyacrylonitrile (PAN). Concurrently, the team aimed to reduce the cost of the tanks at the composite level by improving the interfacial adhesion between the fibers and the matrix resin through the incorporation of low-cost nanoparticles recycled from waste materials, which would reduce the volume of costly CF required to achieve the same tank performance. At the end of the first year, the project team selected mesophase pitch as the primary precursor candidate from a field of materials based on the superior mechanical performance and cost-saving potential. During the second year, the team produced CFs derived from mesophase pitch achieving an average tensile strength of 365.6 ksi and average tensile modulus of 40.74 Msi. Facility availability for spinning and converting these fibers at greater scale has hindered scale-up demonstration, but the team has identified opportunities to conduct this work in the near term. Cost modeling shows that these mesophase pitch-derived CFs can be up to 40% less expensive than PAN-derived CFs due to the lower cost of the feedstock material, higher throughput, greater conversion yield, and lower cost spinning method and compared to PAN. Additionally, the team has demonstrated at lab-scale that nanoparticle coating CFs can significantly increase the interfacial shear strength and load transfer efficiency of CFs in a matrix. Single filament pull-out testing showed a 27% average increase in max interfacial shear strength due to this coating. A continuous method of applying these coatings to a tow of CF has been developed for scale-up. 26 m tows of coated CFs were produced using this system and formed into composite ring samples for ASTM ring burst testing. Issues with the testing protocol have limited assessment of these results. A prototype Type IV tank was designed to meet ANSI HGV2 standards, and the design criteria set out by DOE, using the CF properties developed by the team paired with a proprietary resin matrix, a polyamide liner, and aluminum end bosses. The tank weighs 153.1 kg and with a total capacity of 5.8 kg H2 (5.6 kg usable), which yields a gravimetric capacity of 1.17 kWh/kg. Cost modeling predicts that the tank will have a projected cost of $15.73/kWh. Tank performance modeling does not include considerations for fiber-matrix load transfer efficiency improvements offered by nanoparticle coating method.

08 HYDROGEN↗

Structure-property relationship between lignin structures and properties of 3D-printed lignin composites

Lignin is a low-cost and renewable bioresource with a huge annual production promising to prepare sustainable materials. However, the poor interfacial adhesion between many lignin-polymer pairs deteriorates the mechanical performance of the composites, which seriously limits the application of lignin in 3D printing via fused depositional modeling. This work examined lignin-polyamide 12 (PA 12) intermolecular interactions (e.g., hydrogen bonding) to address the interface challenge. To realize this goal, the phenolic hydroxyl content was increased for a kraft softwood lignin using a LiBr/HBr demethylation procedure, increasing phenoxy content by 61.7%. Increased hydrogen bonding interactions between modified lignin (Pine-Lig-OH) and PA 12 demonstrated a significantly improved molten dynamic modulus by rheological analysis. Regarding mechanical properties, by adding 20 wt% of Pine-Lig-OH, the tensile strength and Young's modulus reached 46.6 MPa and 1.62 GPa, 30.2% and 33.9% higher than PA 12, respectively. Further morphological analysis proved the interfacial interactions are enhanced by showing the difference in the phase gaps. The dynamic mechanical analysis (DMA) supported the conclusion that Pine-Lig-OH could interact with polymer chains, alternating segmental movements due to the strong interaction. Here, this study presents a method to enhance lignin composite properties by promoting interactions with the polymer matrix through modified functional groups, guiding future lignin composite research.

36 MATERIALS SCIENCE↗

The Influence of Nonlocal Metal–Dielectric Environments on Physical and Chemical Processes

Plasmonic nanolayers and laminar metallic/dielectric multilayers were originally developed for optical cloaking applications and lensing applications that could potentially image objects whose size was below the diffraction limit. These assemblies were initially formed from gold or silver nanorods grown within an alumina mesh. However, more recently, assemblies with similar properties have also been prepared by sequential thin-layer deposition of alternating layers of gold and magnesium fluoride (MgF 2 ). These metal/dielectric composite materials enable control of the dielectric constant in the directions perpendicular to the layers and balance the real and imaginary dielectric constants of the assembly such that the speed and the amplitude of the waves traveling through the assembly are not attenuated. In this Account, we will also focus on a few of the applications ranging from surface wetting to fluorescence quenching to enhancement of photochemical reactions. First, we will share an introduction to processes used to create these materials, which are combinations of low refractive index metals and transparent higher index materials arranged in a scalable repeating fashion. Two fabrication methods were employed: an electrochemical deposition of Ag nanorods into an anodized alumina matrix which produced materials with an anisotropic negative refractive index material within the plane of the film and lamellar metal/dielectric layers in which the negative index perpendicular to the growth direction. These alternating layers of plasmonic metals and dielectric materials were ultimately chosen to prepare films for further testing, because of their relative ease of fabrication. We will continue with a discussion of a few of the applications of both of these nonlocal dielectric composite materials including more specialized plasmonic, composite, and hyperbolic metamaterials including fluorescence quenching, photochemical reactions, and surface wetting. In each of these applications, the unique response caused by the enhancement of the electric field and the interface between hyperbolic materials and plasmonic materials as they interact photophysically with their near neighbors is presented. In each of the applications, the enhanced electric field extends from the composite substrate layer to interact with its near neighbors and beyond. Furthermore, the presence of this extended interaction can be observed in the form of decreased emission lifetime, enhancement of photochemical reaction rates, and changes in the surface energies measured by contact angle goniometry. In this Account, all of these situations will be addressed. Finally, we will conclude with a summary and vision for the future as well as a discussion of the unique challenges and opportunities available as research active faculty at an HBCU.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Woven ceramic matrix composite surrogate model based on physics-informed recurrent neural network

A recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear constitutive behavior of woven ceramic matrix composites (CMCs) driven by matrix damage at multiple length scales. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the multiscale generalized method of cells (MSGMC) approach coupled with a matrix damage model. This coupling permits simulating the nonlinear behavior of woven CMCs based on constituent response at the micro-, meso-, and macroscales. The multiscale repeating unit cell is loaded under non-monotonic conditions including multiple load / unload cycles and tension / compression. The fiber volume fraction as well as the intra- and intertow void volume fractions are also varied in the generation of training data. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input strain sequence and fiber and void volume fractions, the resulting stress versus strain response while satisfying physical constraints such as positive semi-definiteness of the tangent stiffness matrix and linear elastic unloading. Further, the trained surrogate model effectively matches the stress versus strain response and successfully predicts the tangent modulus throughout the loading regime. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex architectures, nonlinear multiaxial material response, and under non-monotonic loading conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Silicon carbide fiber manufacturing: Cost and technology

Significant advances have been made in the past decade concerning silicon carbide fiber manufacturing methods resulting in near-stoichiometric small-diameter fibers that meet the property requirements for most of the ceramic matrix composites (CMC) and nuclear applications. The manufacturing cost, however, remained prohibitively high, preventing the use of it in different applications requiring much lower cost. Silicon carbide (SiC) fiber reinforced CMC is dominated by the cost of SiC fiber which comprises more than 50 % of the finished part cost. Here, this article provides insight into the SiC fiber manufacturing costs and highlights the need for an alternative SiC fiber precursor and manufacturing method. Analysis of the existing polycarbosilane (PCS)-based SiC fiber manufacturing shows that the crosslinking (curing) and raw material preparation steps are high-cost steps that need lower cost options. Alternative SiC fiber precursor should be sought for lowering the cost of SiC fibers.

36 MATERIALS SCIENCE↗

Electrocatalytic CN Coupling: Advances in Urea Synthesis and Opportunities for Alternative Products

Urea is an essential fertilizer produced through the industrial synthesis of ammonia (NH 3 ) via the Haber–Bosch process, which contributes ≈1.2% of global annual CO 2 emissions. Electrocatalytic urea synthesis under ambient conditions via CN coupling from CO 2 and nitrogen species such as nitrate (NO 3 − ), nitrite (NO 2 − ), nitric oxide (NO), and nitrogen gas (N 2 ) has gained interest as a more sustainable route. However, challenges remain due to the unclear reaction pathways for urea formation, competing reactions, and the complexity of the resulting product matrix. This review highlights recent advances in catalyst design, urea quantification, and intermediate identification in the CN coupling reaction for electrocatalytic urea synthesis. Furthermore, this review explores future prospects for industrial CN coupling, considering potential nitrogen and carbon sources and examining alternative CN coupling products, such as amides and amines.

Chemistry↗