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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Quantifying Twist Angles in Cuprate Heterostructures with Anisotropic Raman Signatures

Artificially engineered twisted van der Waals (vdW) heterostructures have unlocked new pathways for exploring emergent quantum phenomena and strongly correlated electronic states. Many of these phenomena are highly sensitive to the twist angle, which can be deliberately tuned to tailor the interlayer interactions. This makes the twist angle a critical tunable parameter, emphasizing the need for precise control and accurate characterization during device fabrication. In particular, twisted cuprate heterostructures based on Bi 2 Sr 2 CaCu 2 O 8 + x (BSCCO) have demonstrated angle-dependent superconducting properties, positioning the twist angle as a key tunable parameter. However, the twisted interface is highly unstable under ambient conditions and vulnerable to damage from conventional characterization tools such as electron microscopy or scanning probe techniques. In this work, a fully non-invasive, polarization-resolved Raman spectroscopy approach is introduced for determining twist angles in artificially stacked BSCCO heterostructures. By analyzing twist-dependent anisotropic vibrational Raman modes, particularly utilizing the out-of-plane A 1g vibrational mode of Bi/Sr at ≈116 cm −1 , clear optical fingerprints of the rotational misalignment between cuprate layers are identified. The high-resolution confocal Raman setup, equipped with polarization control and RayShield filtering down to 10 cm −1 , allows for reliable and reproducible measurements without compromising the material's structural integrity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Binder-Free Graphite Anodes for Next-Generation High-Performance Lithium-Ion Batteries

High-energy density anodes are crucial for next-generation lithium-ion batteries (LIBs) particularly for electric vehicle (EV) applications. Sluggish lithium-diffusion kinetics coupled with conventional anode fabrication processes containing polymeric binders hinder fast-charging capabilities and high-energy density of graphite. Herein, we introduce a binder-free graphite anode fabrication strategy using the electrospinning technique that contains ~2.41% carbon nanotubes (CNTs). Our strategy relies on the formation of an interconnecting conductive CNT network coupled with an ultrathin N-doped carbon coating on graphite particles from sacrificial binders. This combination enhances both structural integrity and electrical conductivity and, in turn, improves fast-charging capabilities and high energy density of LIBs. The binder-free graphite anode achieves ~335.0 mAh g–1 capacity at C/3 rate over 400 cycles with capacity retention of >95% and average Coulombic efficiencies >99.95%. These promising results suggest that the binder-free anode fabrication with a multifunctional design approach could elevate the energy-density limits of the graphite anodes, solving high-energy density requirements of EVs, and potentially provides a path forward for the development of economically feasible energy storage systems for various applications.

Ozcan, Muca [ORNL] (ORCID:0000000320020474)↗
DOE OSTI2025

Mechanism of Lithium Ion Exchange Into Spinel Manganese Oxide

Lithium manganese oxide (LMO) is an effective absorbent for lithium recovery from brines, characterized by its high adsorption capacity, excellent regeneration performance, and selectivity. Here, this study investigates the mechanisms of material degradation during lithium loading and unloading in LMO, employing a combination of time‐resolved Raman spectroscopy, X‐ray diffraction, and X‐ray photoelectron spectroscopy. Key findings reveal that the A 1g vibrational mode wavenumber shifts from 635 cm −1 at the onset of lithium ion exchange to 656 cm −1 after 12 min, indicating local symmetry loss and manganese (Mn) loss during lithium intercalation. The proposed lithium exchange mechanism involves initial occupation of tetrahedral interstitial voids, followed by migration into interstitial sites between Mn octahedral sites. Computational modeling suggests that the loss of symmetry in MnO cubane‐like groups occurs as lithium migrates, significantly affecting the Raman spectra. Importantly, the study demonstrates that after 100 cycles of lithium/hydrogen loading, a 24% loss in Mn is observed, which correlates with decreased structural stability; however, the structural integrity of LMO is enhanced when subjected to multiple cycles without complete loading. Here, these insights contribute to the understanding of LMO's performance in lithium recovery applications and highlight potential strategies to optimize its use in future technologies.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

The Central Role of Oxo Clusters in Zirconium‐Based Esterification Catalysis

Oxo clusters are a unique link between oxide nanocrystals and Metal‐Organic Frameworks (MOFs), representing the limit of downscaling each of the respective crystals. Herein, the superior catalytic activity of clusters, compared to zirconium MOF UiO‐66 and nanocrystals is shown. Focus is on esterification reactions given their general importance in consumer products and the challenge of converting large substrates. Oxo clusters have a higher surface‐to‐volume ratio than nanocrystals, rendering them more active. For large substrates, for example, oleic acid, MOF UiO‐66 has negligible catalytic activity while clusters provide almost quantitative conversion, a fact we ascribe to limited diffusion of large substrates through the MOF pores. Clusters do not suffer from limited mass transfer and we also obtain high conversion in solvent‐free reactions with sterically hindered alcohols (hexanol, 2‐ethyl hexanol, benzyl alcohol, and neopentyl alcohol). The cluster catalyst can be recovered and shows identical activity when reused. The structural integrity of the cluster is confirmed using X‐ray total scattering and pair distribution function analysis. Moreover, when homogeneous zirconium alkoxides are used as catalysts, the same oxo cluster is retrieved, showing that oxo clusters are the active catalytic species, even in previously assumed homogeneously catalyzed reactions.

Pulparayil Mathew, Jikson↗
DOE OSTI2025

Zwitterionic Photocurable Resin for High‐Resolution 3D Printing of Ultralow‐Fouling Microstructures

High‐resolution 3D printing technologies are enabling a new generation of microstructured materials for applications where biocompatibility is critical. However, most conventional 3D‐printable resins yield materials that exhibit trade‐offs between antifouling properties and mechanical robustness, limiting their applicability in living systems. In nature, zwitterionic surface groups form tightly bound hydration layers that act as effective barriers against protein and cell attachment. Inspired by this strategy, a zwitterionic acrylamide‐based photoresist—carboxybetaine di‐methacrylamide (CBDA)—is developed for projection‐based vat photopolymerization, enabling the fabrication of complex microarchitectures with exceptional antifouling properties. The bifunctional monomer allows the formation of dense, cross‐linked networks that resist swelling while maintaining a high density of zwitterionic groups. Printed structures exhibit strong resistance to protein and cell adhesion, as confirmed by porcine blood assays, alongside robust mechanical performance. As a demonstration, a tubular structure featuring a negative Poisson's ratio lattice is printed to showcase structural fidelity and versatility. This resin formulation offers a broadly applicable strategy for fabricating microscale devices and surfaces where antifouling performance and structural integrity are both essential—spanning biomedical interfaces, soft robotics, and beyond.

3D printing↗
DOE OSTI2025

Tunable Crosslinked Ether Polymer Network Electrolytes for High‐Performance All‐Solid‐State Sodium Batteries

All-solid-state batteries (ASSBs) are critical for achieving high energy density and enhanced safety. Solid polymer electrolytes (SPEs) offer key advantages over other electrolytes, including improved safety, flexibility, and interfacial contact. Among the SPEs, ether-based polymers are widely studied due to their ease of processing and high ionic conductivity (σi) in the amorphous state. In this work, the introduction of poly(ethylene glycol) methyl ether methacrylate (PEGMEMA) into an SPE matrix composed of poly(ethylene glycol) diacrylate (PEGDA), poly(ethylene glycol) (PEG2k), and sodium bis(fluorosulfonyl)imide (NaFSI) salt is investigated to facilitate the formation of amorphous, high σ i SPEs through end-group engineering and polymer ratio optimization. PEGMEMA enhances structural integrity via crosslinking with PEGDA through its methacrylate group, while its methyl end group aids ion conduction. A 2:1:7 ratio of PEGDA:PEGMEMA:PEG2k exhibits a σi of 1.16 x 10 -4 S cm -1 and oxidative stability up to 4.4 V at 60 °C. A solid-state cell incorporating this SPE, a Na 2/3 Ni 1/3 Mn 2/3 O 2 (NM12) cathode, and a sodium-metal anode demonstrates excellent cycling stability, retaining over 80 % of its initial capacity for 150 cycles at 60 °C. The findings highlight the potential of end-group engineering in improving the electrochemical performance of SPEs.

25 ENERGY STORAGE↗
DOE OSTI2026

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Prediction of residual stresses in additively manufactured parts using lumped capacitance and classical lamination theory

Several industries are interested in Laser Powder Bed Fusion (L-PBF) Additively Manufactured (AM) metal parts because their designs can be made arbitrarily complex while retaining bulk-type material properties. However, the residual stresses (RS) and distortions caused by the heat gradients inherent to L-PBF processes are detrimental to the structural integrity of the parts and must be taken into consideration during the part design cycle. Predicting the state of stresses in as-built 3D printed parts is a difficult problem that is typically approached with the use of transient thermomechanical Finite Element Models (FEMs). However, the nonlinearities associated with AM processes are difficult to capture in these FEMs without increasing the computational cost of the simulation, limiting their ability to be incorporated into practical design cycles. This work presents a novel analytical framework that combines lumped capacitance nonlinear heat transfer with time dependent classical lamination theory to efficiently and accurately predict RS in as-built L-PBF parts without the need of FEMs. The simulation was compared to Neutron Diffraction (ND) residual strain measurements taken at Oak Ridge National Laboratories (ORNL) as well as Synchrotron X-ray Diffraction (XRD) strain data published by the National Institute of Standards and Technology (NIST). The simulation predictions and the experimental data showed excellent agreement for the in-plane strain directions, and general agreement for the out of plane strain component, highlighting an area where further development can be implemented.

42 ENGINEERING↗
DOE OSTI2026

Micromechanical and fatigue in situ synchrotron characterization of an additively manufactured superalloy with porosity

Additive manufacturing (AM) has the potential to transform component production, but its widespread adoption is constrained by defects, such as pores, that compromise structural integrity. Here, this study investigates the influence of porosity on the micromechanical and fatigue response of AM Inconel 718 (IN718), a widely used aerospace superalloy. One baseline specimen with minimal stochastic porosity and another intentionally seeded with lack of fusion (LOF) pores were examined using high-energy X-ray diffraction microscopy (HEDM) and micro-computed tomography during cyclic loading. Fatigue cracks in the LOF specimen initiated more frequently and at lower cycle counts than in the baseline specimen. The number fraction of fatigue cracks that grew was comparatively higher in the LOF specimen. Grain-level metrics, including stress and diffraction spot widths, were quantified using far-field HEDM. Across the thousands of grains detected in both specimens, the pores in the LOF specimen increased the variability of stress and spot width evolution in the azimuthal direction, the latter serving as a surrogate measure of plastic deformation. However, no correlations emerged between these metrics and grain proximity to fatigue crack initiation sites or pores, underscoring the limitations of grain-averaged metrics for predicting fatigue. Nonetheless, the rich dataset reported here provides a foundation for future modeling efforts.

High-energy X-ray diffraction microscopy↗
DOE OSTI2025

Diffusion behavior of lanthanide fission products in bcc Fe cladding: A first-principles study

Fuel-cladding chemical interaction poses significant challenges in nuclear reactors, where fission products generated from nuclear fuel interact with Fe-based cladding materials, potentially compromising their structural integrity. This study investigates the diffusion behavior of lanthanide fission products, Lanthanum (La), Cerium (Ce), Praseodymium (Pr), and Neodymium (Nd), within body-centered cubic (bcc) Fe cladding using the density functional theory, nudged elastic band method, and self-consistent mean field theory. Our results reveal significant vacancy binding energies, particularly with the 1st and 2nd nearest neighbors, which diminish beyond the 5th nearest neighbor, with La exhibiting the strongest binding affinity, followed by Nd, Ce, and Pr. The nudged elastic band calculations indicate significant high barriers for the dissociation of 1st nearest neighbor vacancy-solute pairs for all fission products. The tracer diffusion coefficients of these fission products were derived in an Arrhenius form, with a magnetic correction that accounts for the high-temperature paramagnetic state. The significant trapping effect of vacancies caused by a very dilute concentration of fission products reduces vacancy mobility, potentially leading to modifications in point defect supersaturation, void nucleation, and swelling under irradiation. These represent critical challenges for irradiated cladding materials. The tracer diffusion coefficients indicate that Nd diffuses the fastest, followed by La, Ce, and Pr. Furthermore, this study provides essential insights for understanding fission product transport in cladding materials and informs future design strategies to mitigate fuel-cladding chemical interaction, ultimately enhancing nuclear reactor safety and performance.

Diffusion↗
DOE OSTI2024

Recent and future developments in pultrusion technology with consideration for curved geometries: A review

Herein this paper examined the current state and future developments in pultrusion with particular emphasis on its application in curved part manufacturing. The relationship between factors such as resin chemistry, fiber characteristics, and die geometry that influences the properties of pultruded product were highlighted. Moreover, the specific challenges associated with pultruding curved parts such as the complexities in achieving uniformity and structural integrity in such geometries were discussed. The review emphasized mold design, process improvement, adaptive control systems for precise resin impregnation and material selection to address these challenges. Additionally, the paper suggests the integration of real-time monitoring and data analytics as ways to enhance quality control during curved parts pultrusion. These advancements will help to overcome challenges specific to curved pultrusion and make the process more efficient. Other manufacturing techniques such as filament winding, thermoforming, pulforming were mentioned as alternatives to curved parts pultrusion. The review also explores pultruded variable curvature processes, highlighting some notable patents and article related to this subject matter. Production of pultruded variable curvature parts was seen as a key driver that can shape the future of pultrusion. Finally, the paper anticipates future trends, with sustainability, customization, integration of advanced materials, and development of techniques for pultrusion of composites parts.

42 ENGINEERING↗
DOE OSTI2024

Examining infrared thermography based approaches to rapid fatigue characterization of additively manufactured compression molded short fiber thermoplastic composites

A novel additive manufacturing (AM) methodology combined with a compression molding (CM) process has been developed to optimize the microstructure of short fiber thermoplastic composites (SFTs)with higher fiber alignment and lower porosity, yielding superior stiffness, strength, and structural integrity. Here, the current work examines the efficacy of the ‘passive’ infrared thermography (IRT) techniques for rapid fatigue characterization of SFTs that use the surface temperature evolution during cyclic loading due to self-heating as a fatigue indicator. A comparison of fatigue limits obtained from traditional stress-life (SN) (≈53.1%σ uts ) and IRT (≈54.1%σ uts ) shows a close match. However, the SN curve required 18 specimens and two weeks of continuous cyclic testing, while IRT used three specimens with 5 hours of testing. Thus, the IRT approach provides an accelerated testing framework for rapidly estimating the fatigue limit. Additionally, existing phenomenological approaches to IRT fatigue characterization have been examined.

42 ENGINEERING↗
DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗
DOE OSTI2026

A Full-Induction Magnetohydrodynamics Solver for Liquid Metal Fusion Blankets in Vertex-CFD

Multiphysics modeling of liquid metal fusion blankets, which produce tritium and convert energy of neutrons created via fusion reactions into heat, is crucial for predicting performance, ensuring structural integrity, and optimizing energy production. While traditional blanket modeling of liquid metal flows during normal steady operating conditions commonly employs the inductionless approximation of the magnetohydrodynamics (MHD) equations, transient scenarios, when the plasma-confining magnetic field varies on millisecond time scales, require a full-induction MHD approach that dynamically evolves the magnetic field via the time-dependent induction equation. This paper presents the formulation, implementation, and initial verification of a full-induction MHD solver integrated within the open-source Vertex-CFD framework, which aims to achieve tight multiphysics coupling, a flexible software design enabling easy extension and addition of physics models, and performance portability across computing platforms. The solver utilizes finite element spatial discretization, implicit Runge–Kutta time integration, and an inexact Newton method to solve the resulting discrete nonlinear system, leveraging Trilinos packages for efficient computation. Verification against selected benchmark problems demonstrates accuracy and robustness of the solver. Furthermore, when the solver is applied to an idealized blanket model in 2.5D and full 3D, results obtained with Vertex-CFD are in good agreement with recently published quasi-2D simulations. These findings establish a computational foundation for future simulations of transient MHD phenomena in liquid metal blankets with Vertex-CFD, and open avenues for future extensions and performance optimizations.

Endeve, Eirik [ORNL] (ORCID:0000000312519507)↗
DOE OSTI2025

Borate-assisted alkaline extraction of hemicellulose from switchgrass with enhanced structural stability and purity

Valorization of non-cellulosic polysaccharides is crucial for enhancing the economic competitiveness of biorefinery processes. In this study, a mixture of boric acid and sodium hydroxide was employed to efficiently extract hemicellulose from holocellulose switchgrass. Borate-assisted alkaline extraction resulted in a higher xylan content (59.5 %) compared to conventional alkaline extraction. Here, the hemicellulose fractions derived from the borate-alkaline treatment exhibited a higher molecular weight (M w = 51.2 kDa) and a relatively lower degree of polydispersity (1.28), indicating improved structural stability. The presence of borate had a protective effect against chain scission, preserving glucuronic acid residues and increasing galactose content. Additionally, borate improved hemicellulose purity, with up to 74.1 % of the extracted hemicellulose being suitable for further enzymatic applications. Extended extraction time further enhanced hemicellulose recovery, reaching 97.9 % under NaOH/boric acid conditions while maintaining structural integrity, as confirmed by SEM, FTIR and 2D HSQC NMR analyses. These findings provide insights into the role of borate in optimizing hemicellulose extraction and improving its potential for bioconversion processes.

Borate alkaline↗
DOE OSTI2024

Specific iron binding to natural sphingomyelin membrane induced by non-specific co-solutes

Sphingomyelin (SPM), a crucial phospholipid in the myelin sheath, plays a vital role in insulating nerve fibers. We hypothesize that iron ions selectively bind to the phosphatidylcholine (PC) template within the SPM membrane under near-physiological conditions, resulting in disruptions to membrane organization. These interactions could potentially contribute to the degradation of the myelin sheath, thereby playing a role in the development of neurodegenerative diseases. We utilized synchrotron-based X-ray spectroscopy and diffraction techniques to study the interaction of iron ions with a bovine spinal-cord SPM monolayer (ML) at the liquid-vapor interface under physiological conditions. The SPM ML serves as a model system, representing localized patches of lipids within a more complex membrane structure. The experiments assessed iron binding to the SPM membrane both in the presence of salts and with additional evaluation of the effects of various ion species on membrane behavior. Grazing incidence X-ray diffraction was employed to analyze the impact of iron binding on the structural integrity of the SPM membrane. Furthermore, our results demonstrate that iron ions in dilute solution selectively bind to the PC template of the SPM membrane exclusively at near-physiological salt concentrations (e.g., NaCl, KCl, KI, or CaCl 2 ) and are pH-dependent. In-significant binding was detected in the absence of these salts or at near-neutral pH with salts. The surface adsorption of iron ions is correlated with salt concentration, reaching saturation at physiological levels. In contrast, multivalent ions such as La 3+ and Ca 2+ do not bind to SPM under similar conditions. Notably, iron binding to the SPM membrane disrupts its in-plane organization, suggesting that these interactions may compromise membrane integrity and contribute to myelin sheath damage associated with neurological disorders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Exceptional radiation resistance of hardened amorphous SiC under high-temperature hydrogen ion implantation

This study provides a compelling comparison of the structural and mechanical responses of single-crystal silicon carbide (sc-SiC), nanocrystalline silicon carbide (nc-SiC), and amorphous silicon carbide (am-SiC) to hydrogen ion implantation at 650 °C across three distinct fluences: low, medium, and high (LF, MF, HF). While both sc-SiC and nc-SiC exhibit blistering, microcracking, and exfoliation, am-SiC remains free of blisters, demonstrating superior resilience. Notably, nc-SiC, with its high density of stacking faults (SFs), requires a higher fluence to initiate blistering compared to sc-SiC. At high fluences, hydrogen accumulation at grain boundaries (GBs) in nc-SiC elevates internal gas pressure, intensifying exfoliation. In sc-SiC, blistering leads to increased hardness, whereas in nc-SiC, the degradation of the SF structure results in a reduction in hardness. In contrast, am-SiC undergoes structural relaxation during irradiation, resulting in a significant increase in hardness while maintaining its structural integrity, with only the formation of nano-sized spherical bubbles observed. Furthermore, these findings highlight the exceptional suitability of am-SiC for nuclear applications, where resistance to radiation-induced microcracking is critical.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Assessment of effective elastic constants of U-10Mo fuel: A multiscale modeling and homogenization study

The significant microstructural changes that U-Mo fuel undergoes during operation degrades its mechanical properties and structural integrity. Microstructural evolution entails the formation, evolution, and redistribution of porosity in conjunction with grain refinement. In the present paper, we employ numerical approaches to assess the impact of the various microstructural features—grains, nanoscale intragranular fission gas bubbles, and mesoscale intergranular voids—on the degradation of elastic constants. Phase-field microstructure models are combined with the asymptotic expansion homogenization technique in order to derive the effective elastic constants as a function of porosity and fission density. Here the results are verified and compared against theoretical bounds. Using this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗