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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Selective Oxidation and Cr Segregation in High-Entropy Oxide Thin Films

High-entropy oxides (HEOs) offer exceptional compositional flexibility and structural stability, making them promising materials for energy and catalytic applications. Here, in this study, we investigate Sr doping effects on B-site cation oxidation states, local composition, and structure in epitaxial La 1–x Sr x (Cr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 )O 3 thin films. X-ray spectroscopies reveal that Sr doping preferentially promotes Cr oxidation from Cr 3+ to Cr 6+ , partially oxidizes Co and Ni, while leaving Mn 4+ and Fe 3+ unchanged. Atomic-resolution scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy shows pronounced Cr segregation, with depletion at the interface and enrichment at the surface, along with partial amorphization in heavily Sr-doped samples. This segregation is likely driven by oxidation-induced migration of smaller, high-valence Cr cations during growth. These findings highlight the critical interplay between charge compensation, local strain, and compositional fluctuations in HEOs, indicating that precise control over growth conditions is critical for tuning their surface composition and electronic structure toward more robust electrocatalyst design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Moiré metrology of energy landscapes in van der Waals heterostructures

The emerging field of twistronics, which harnesses the twist angle between two-dimensional materials, represents a promising route for the design of quantum materials, as the twist-angle-induced superlattices offer means to control topology and strong correlations. At the small twist limit, and particularly under strain, as atomic relaxation prevails, the emergent moiré superlattice encodes elusive insights into the local interlayer interaction. Here we introduce moiré metrology as a combined experiment-theory framework to probe the stacking energy landscape of bilayer structures at the 0.1 meV/atom scale, outperforming the gold-standard of quantum chemistry. Through studying the shapes of moiré domains with numerous nano-imaging techniques, and correlating with multi-scale modelling, we assess and refine first-principle models for the interlayer interaction. We document the prowess of moiré metrology for three representative twisted systems: bilayer graphene, double bilayer graphene and H-stacked MoSe 2 /WSe 2 . Moiré metrology establishes sought after experimental benchmarks for interlayer interaction, thus enabling accurate modelling of twisted multilayers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Chemomechanical modification of quantum emission in monolayer WSe2

Abstract Two-dimensional (2D) materials have attracted attention for quantum information science due to their ability to host single-photon emitters (SPEs). Although the properties of atomically thin materials are highly sensitive to surface modification, chemical functionalization remains unexplored in the design and control of 2D material SPEs. Here, we report a chemomechanical approach to modify SPEs in monolayer WSe 2 through the synergistic combination of localized mechanical strain and noncovalent surface functionalization with aryl diazonium chemistry. Following the deposition of an aryl oligomer adlayer, the spectrally complex defect-related emission of strained monolayer WSe 2 is simplified into spectrally isolated SPEs with high single-photon purity. Density functional theory calculations reveal energetic alignment between WSe 2 defect states and adsorbed aryl oligomer energy levels, thus providing insight into the observed chemomechanically modified quantum emission. By revealing conditions under which chemical functionalization tunes SPEs, this work broadens the parameter space for controlling quantum emission in 2D materials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Directed self-assembly of chiral liquid crystals into biomimetic bouligand structures in thin film

The Bouligand structure, renowned for its helicoidal arrangement and enhanced mechanical properties, has attracted significant research interest for its ability to impart enhanced strength to intrinsically soft materials. Biomimetic approaches have centered on fibrous structures in bulk materials, but translating this architecture into thin-film regime for miniaturized-wearable devices with programmable functions remains challenging. Here, we direct the self-assembly of cholesteric liquid crystals (CLCs) into hierarchical helical structures using chemically patterned surfaces. Alternating surface anchoring regions align uniform lying-down helices at the nanoscale, guiding a secondary microscale helical structure exhibiting both left- and right-handed twists. This mimetic Bouligand structure in CLCs enables optical modulation under applied field and strain with enhanced mechanical response. Simulations reveal the structural evolution from initial Bouligand configuration in LC layers to alternating twist helices. This research provides a basis for designing and manufacturing miniaturized or wearable devices with nanometer-scale precision in regulating electro-optical and mechanical properties. Bouligand structures, which offer strength in natural materials, are of interest but difficult to obtain. Here, the authors report the development of such structures by directed self-assembly of cholesteric single crystals into hierarchical helical structures, with the secondary structure having right and left-handed twists.

Bouligand structure↗
DOE OSTI2020

Experimentally Validated Computational Modeling of Creep and Creep-Cracking for Nuclear Concrete Structures

In a Nuclear Power Plant, one of the most important components is the concrete nuclear reactor cavity, which serves both a structural and protective function as the biological radiation shield. Given that creep has been identified as a major knowledge gap in the assessment of nuclear structures (NUREG/CR-7153), this work helps to further the understanding of creep behavior of massive concrete containment structures for decades to enable safe and long-term operation of these facilities. This project has developed a robust, experimentally validated model to predict creep in nuclear concrete structures for up 60 years using short-term creep data thereby enabling a longer service life of critical facilities and early detection of structural failure. The work presented in this report is a pairing of computational and experimental methods. For the first time, the time temperature superposition (TTS) principle was successfully used to generate a uniaxial creep compliance master curve to predict mortar creep response for up to 22,500 days (nearly 60 years) at a reference temperature of 20°C. These data were used as input into finite element analysis (FEA) codes that use highly realistic random, 3D concrete microstructures from reconstructed coarse limestone aggregates. Finite element analysis performed provides the ability to quickly upscale mortar viscoelastic behavior to long-term concrete creep/relaxation data. A master creep compliance curve, constructed from the TTS principle, spanning 27 years, was used to validate two and a half decades of simulated concrete creep. Concurrently, three different simulated wall specimens were designed to mimic the behavior of post-tensioned concrete nuclear containment facility vessel walls over time as a result of concrete creep. The specimens were designed with different thicknesses, transverse and longitudinal reinforcement ratios, and level of post-tensioning stress. Each specimen contained various instrumentation to measure internal concrete temperature, concrete strain, and post-tensioning strain hourly for over 3 years. The concrete creep model developed in this project, based on the FEA concrete simulations, was applied to simulate the structural-scale experiments of prestressed concrete walls conducted in this project using the Grizzly code. These models can represent the effects of reinforcing and prestressing. Although there are some discrepancies with the experimental data, the model can predict the overall trends of the creep response in these experiments. One of these experimental models was also applied to an extended time to demonstrate how the findings from this study can be used to predict the behavior of actual structures of interest that have been in service for extended periods of time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Lattice-Renormalized Tunneling Models for Superconducting Qubit Materials

We present a lattice-renormalized formalism for configurational tunneling two-level systems (TLS) that overcomes limitations of minimum-energy-path and light-particle models. Derived from the nuclear Hamiltonian, our formulation introduces composite phonon coordinates to capture lattice distortions between degenerate potential wells. This approach resolves deficiencies in prior models and enables accurate computation of tunnel splittings and excitation spectra for hydrogen-based TLS in bcc Nb. Our results bound experimental tunnel splittings and reveal strong anharmonic couplings between tunneling atoms and lattice phonons, establishing a direct link between TLS dynamics and phonon-mediated strain interactions. The formalism further generalizes to multi-level systems (MLS), providing insight into defect-induced decoherence in superconducting qubits and guiding strategies for materials design to suppress TLS-related loss.

Pritchard, P. G. [Northwestern U.]↗
DOE OSTI2021

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 6061-T651 Aluminum Alloy from Plate

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The matters of interest here are the elastic-plastic response and ductile failure behavior of 6061-T651 aluminum alloy under the conditions described above. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of a modular $J_2$ plasticity model with isotropic hardening as well as a ductile failure model. Both included modules that accounted for temperature and strain rate dependence. The models were coupled with an adiabatic heating module to calculate the temperature rise due to the conversion of plastic work to heat. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s as well as four geometries of notched tension specimens and two tests on specimens with shear-dominated deformations. The test data collected allowed the calibration of both the plasticity and the ductile failure models. Most test specimens were extracted from a single piece of plate to maintain consistency. Notched tension tests came from a possibly different plate, but from the same lot. When using the model in structural finite element calculations, element formulations and sizes different from those used to model the test specimens in the calibration are likely to be used. A brief investigation demonstrated that the failure model can be particularly sensitive to the element selection and provided an initial guide to compensate in a specific example.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Role of deformation twinning in fatigue of CrCoNi medium-entropy alloy at room temperature

Here cylindrical specimens of CrCoNi alloy with electropolished surfaces were subjected to constant total strain amplitude low cycle fatigue. The alloy exhibited an initial period of cyclic hardening followed by cyclic softening until failure occurred. At the end of hardening stage at the peak of cyclic stress, well-developed persistent slip markings (PSMs) consisting of extrusions and intrusions were associated with thin deformation twins. A sophisticated experimental workflow was designed to extract information from the surface and the bulk of tested material. A combination of SEM, EBSD, ECCI, FIB and HR-STEM was used to study the internal structure and the surface profiles around the deformation twins, which were produced during the initial period of cyclic loading. Furthermore, localized cyclic plastic strain and stress concentrations near deformation twins led not only to early, well-developed PSMs, but also to the activation of TWIP and TRIP plasticity even at low macroscopic stress amplitudes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Resilient Hydrogels from the Nanoscale to the Macroscale

Biological systems illustrate how a material composed of fragile molecular components can collectively be highly resilient. While the average protein, cell, or even tissue may not last more than a few weeks, many animals and plants live for more than a century. Continual component regeneration and multiple systems to resist mechanical and chemical damage together make this longetivity possible. This project sought to develop biomimetic methods to enable a specific type of material, a hydrogel, to resist damage across multiple scales using distinct, modular damage protection mechanisms. Because hydrogels share many features with biological tissues, they are an ideal substrate for exploring biomimetic strategies for designing resilience and self-repair. We specifically focused in this study on DNA-crosslinked hydrogels, which contain DNA strands that can serve as material to link it together or to control its current state or properties. We investigated how new tools from dynamic DNA nanotechnology could make it possible to actively recover from damage by continually growing and forming a materials shape, or by identifying damage and directing an adaptive response to that damage involving chemical synthesis to reconstruct a structure. We developed embedded molecular sensors able to detect and strain of the gel before damage occurred and react to counteract damage. We also developed methods to continually create shapes and patterns using chemical processes that will allow those patterns to reform when they are damaged. The ability to design resilient materials capable of self-repair has important implications for materials engineering. Instead of designing a material to withstand the worst stresses it may encounter, we could instead design a material to survive under average conditions, but self-repair or reconfigure to resist impending damage. Resilient, self-repairing hydrogels will also have diverse applications such as sensors or actuators.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Suppressing Screening-Current-Induced Strain in a 72-mm-Bore REBCO Insert for a 20-T Magnet: A Numerical Study

Rare-earth barium copper oxide (REBCO) high-temperature superconducting (HTS) magnets are considered a game changer for the capability of generating magnetic fields exceeding 20 T at or above liquid helium temperature, combined with the potential for substantially reduced manufacturing and operational costs. Princeton Plasma Physics Laboratory is dedicated to developing large-bore high-field superconducting magnet systems to support forefront physics research. Here, our current project focuses on a φ72-mm cold-bore REBCO insert comprising 21 dry-wound double-pancake coils, designed to generate at least 8 T when nested within a 12-T outsert magnet. A significant challenge for high-field REBCO magnets is the time-varying-magnetic-field-induced screening currents (SC) in the REBCO conductors, which can cause localized strain and stress concentrations. This paper presents a numerical study of the SC-induced strain in the REBCO insert magnet, confirming that the SC-induced strain can be substantially suppressed by energizing the REBCO insert before the outsert magnets. We discuss and reveal the mechanism behind this reduction. By applying this strategy, we expect to unleash the potential of the REBCO insert magnet to generate up to 12 T in a 12-T background field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Nanoscale Design of Pd-Based Electrocatalysts for Oxygen Reduction Reaction Enhancement in Alkaline Media

Palladium (Pd)-based electrocatalysts have recently emerged as one class of the foremost promising candidates for the oxygen reduction reaction (ORR) in alkaline media due to their excellent ORR activity and durability and lower costs compared with platinum. Insightful design of Pd-based nano-architectures with optimized active surface sites and maximal intrinsic performance is central to promoting the ORR applications. To further accelerate the sluggish ORR kinetics at the cathode of fuel cells and substantially decrease the overall cost of the electrocatalysts, various strategies, including controlled sizes and shapes with selected crystallographic facets, crystal-phase engineering, heteroatom doping, tailored surface strains, and surface engineering by de-alloying, have been extensively developed in the past decade. Here in this review, a brief introduction to the fundamental ORR mechanisms of Pd-based electrocatalysts in alkaline media is presented, followed by a thorough discussion on various strategies for delicately designing high-performance Pd-based catalysts with corresponding examples. Thereafter, the perspectives and new insights into the challenges are outlined, and some emerging research directions related to the rational design and controlled synthesis of Pd-based ORR electrocatalysts are also proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Aerosol-Jet Printed Sensors for Environmental, Safety, and Health Monitoring: A Review

An emergent direct-write approach, aerosol-jet printing (AJP), is gaining attention for the deployment of rapid and affordable microadditively manufactured energy-efficient sensors and printed electronics. AJP enables a broad range of ink viscosities (0.001–1 Pa s) for printing diverse materials ranging from ceramics and metals to polymers and biological matter. Reproducible, high-spatial-resolution features (≈10 µm), and wide standoff distances (1–11 mm) between the nozzle and the substrate facilitate conformal printing of complex geometrical designs on nonplanar—e.g., stepped or curved—surfaces. Here this paper aims to provide a comprehensive overview of state-of-the-art AJP-based sensors (e.g., strain and temperature gauges, biosensors, photosensors, humidity and surface acoustic wave sensors, dielectric elastomer actuators, and motion, smoke, and hazardous gas detectors) and to discuss prospective applications. The drive toward cost-effective devices that are smaller, lighter, and better-performing remains a frontier challenge in the field of printed electronics. Consequently, as AJP becomes increasingly utilized in the high-volume manufacturing of miniaturized active and passive sensors, it opens a pathway for facile large-scale fabrication of devices for a wide range of consumer and industrial applications, including transportation, agriculture, infrastructure, aerospace, national defense, and healthcare.

3-dimensional↗
DOE OSTI2025

A chain stretch-based gradient-enhanced model for damage and fracture in elastomers

Similar to quasi-brittle materials, it has been recently shown that elastomers can exhibit a macroscopically diffuse damage zone that accompanies the fracture process. In this study, we introduce a stretch-based gradient-enhanced damage (GED) model that allows the fracture to localize and also captures the development of a physically diffuse damage zone. This capability contrasts with the paradigm of the phase field method for fracture, where a sharp crack is numerically approximated in a diffuse manner. Capturing fracture localization and diffuse damage in our approach is achieved by considering nonlocal effects that encompass network topology, heterogeneity, and imperfections. These considerations motivate the use of a statistical damage function dependent upon the nonlocal deformation state. From this model, fracture toughness is realized as an output. While GED models have been classically utilized for damage modeling of structural engineering materials (e.g., concrete), they face challenges when trying to capture the cascade from damage to fracture, often leading to damage zone broadening (de Borst and Verhoosel, 2016). This deficiency contributed to the popularity of the phase-field method over the GED model for elastomers and other quasi-brittle materials. Other groups have proceeded with damage-based GED formulations that prove identical to the phase-field method (Lorentz et al., 2012), but these inherit the aforementioned limitations. To address this issue in a thermodynamically consistent framework, we implement two modeling features (a nonlocal driving force bound and a simple relaxation function) specifically designed to capture the evolution of a physically meaningful damage field and the simultaneous localization of fracture, thereby overcoming a longstanding obstacle in the development of these nonlocal strain- or stretch-based approaches. Here, we discuss several numerical examples to understand the features of the approach at the limit of incompressibility, and compare them to the phase-field method as a benchmark for the macroscopic response and fracture energy predictions.

Elastomers↗
DOE OSTI2020

A method for characterization of multiple dynamic constitutive parameters of FRCs

We propose a method to measure multiple dynamic material constitutive parameters of unidirectional fiber reinforced composites (FRCs) in a single experiment. Dynamic short-beam shear (DSBS) experiments were performed on a modified Kolsky compression bar, with integration of high-speed imaging and digital image correlation (DIC). The unidirectional FRCs investigated were S-2 glass fiber reinforced matrix of TGDDM-Jeffamine® D230 with monoamine functionalized partially reacted substructures (mPRS) and commercially available SC-15. Analytical solutions of normal and shear strains of a composite beam were derived based on Timoshenko beam theory, assuming material to be transversely isotropic and have different moduli in tension and compression in each principle material orientation. Tensile and compressive moduli were inversely computed through monitoring normal strain slope when specimen was constantly loaded at a speed of ~7.3 m/s within a small deflection. Non-linear shear stress-strain behavior of the composite was described via Ramberg–Osgood equation. Finite element (FE) analysis was conducted in ABAQUS, simultaneously defining via user subroutine UMAT the transverse isotropy of material, bi-modulus constitutive model, and non-linear shear stress-strain relation. The method proposed in this work was validated by comparing strain distributions computed by FE model and DIC measurements. Comparing with traditional dynamic tensile, compressive, and shear experiments on FRCs, this method significantly simplifies the specimen preparation and design of complicated gripping fixtures for multiple experiments. Here, systematic errors resulting from variations of specimen geometry and dimension, loading direction, and instrumentation are reduced, thereby providing compatible data for numerical studies on impact behavior of composites.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Impact of Backbone Rigidity on the Thermomechanical Properties of Semiconducting Polymers with Conjugation Break Spacers

There remains a lack of fundamental understanding in theroleofbackbonerigidityonthe thermomechanical properties of conjugated polymers. Here, we provide the first holistic approach to understand the fundamental influence of backbone rigidity on an n-type naphthalene diimide-based conjugated polymer, denoted by PNDI-Cx, through insertion of a flexible conjugation break spacer (CBS). CBS lengths are varied from fully conjugated with zero alkyl spacer (PNDI-C0) to a seven- carbon alkyl spacer (PNDI-C 7 ), with the CBS engineered into each repeat unit for systematic evaluation. Solution small-angle neutron scattering and oscillatory shear rheometry were employed to provide the first quantitative evidence of CBS influence over conjugated polymer chain rigidity and entanglement molecular weight (M e ), demonstrating a reduction in the Kuhn length from 521 to 36 Å for fully conjugated PNDI-C0 and PNDI-C6, respectively, as well as a nearly consistent Me of ~15 kDa upon the addition of CBS. Thermomechanical properties, such as elastic modulus and glass-transition temperature, were shown to decrease with an increasing length of CBS. An extraordinary ductility, upwards of 400% tensile strain before fracture, was observed for high-molecular-weight PNDI-C4, which we attribute to a high number of entanglements and disruption of crystallization. Furthermore, the deformation mechanism for PNDI-Cx was studied under strain through X-ray diffraction, polarized UV-vis spectroscopy, and atomic force microscopy. Overall, this work sheds light on the important role of backbone rigidity in designing flexible and stretchable conjugated polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

DONUT: physics-aware machine learning for real-time X-ray nanodiffraction analysis

Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Materials science↗
DOE OSTI2020

Mechanistic basis of oxygen sensitivity in titanium

One of the most potent examples of interstitial solute strengthening in metal alloys is the extreme sensitivity of titanium to small amounts of oxygen. Unfortunately, these small amounts of oxygen also lead to a markedly decreased ductility, which in turn drives the increased cost to purify titanium to avoid this oxygen poisoning effect. Here, we report a systematic study on the oxygen sensitivity of titanium that provides a clear mechanistic view of how oxygen impurities affect the mechanical properties of titanium. The increased slip planarity of Ti-O alloys is caused by an interstitial shuffling mechanism, which is sensitive to temperature, strain rate, and oxygen content and leads to the subsequent alteration of deformation twinning behavior. The insights from our experimental and computational work provide a rationale for the design of titanium alloys with increased tolerance to variations in interstitial content, with notable implications for more widespread use of titanium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2025

DONUT: Physics-aware Machine Learning for Real-time X-ray Nanodiffraction Analysis

SF-25-088 Coherent X-ray scattering techniques are critical for investigating the fundamental structural properties of materials at the nanoscale. While advancements have made these experiments more accessible, real-time analysis remains a significant bottleneck, often hindered by artifacts and computational demands. In scanning X-ray nanodiffraction microscopy, which is widely used to spatially resolve structural heterogeneities, this challenge is compounded by the convolution of the divergent beam with the sample’s local structure. To address this, we introduce DONUT (Diffraction with Optics for Nanobeam by Unsupervised Training), a physics-aware neural network designed for the rapid and automated analysis of nanobeam diffraction data. By incorporating a differentiable geometric diffraction model directly into its architecture, DONUT learns to predict crystal lattice strain and orientation in real-time. Crucially, this is achieved without reliance on labeled datasets or pre-training, overcoming a fundamental limitation for supervised machine learning in X-ray science. We demonstrate experimentally that DONUT accurately extracts all features within the data over 200 times more efficiently than conventional fitting methods.

Zhou, Tao [Argonne National Laboratory (ANL), Argo↗