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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 289 records · Page 16

Scattering insights into shear-induced scission of rod-like micelles

Understanding the scission of rod-like micelles under mechanical forces is crucial for optimizing their stability and behavior in industrial applications. This study investigates how micelle length, flexibility, and external forces interact, offering insights into the design of micellar systems in processes influenced by mechanical stress. Although significant, direct experimental observations of flow-induced micellar scission using scattering techniques remain scarce. Small angle neutron scattering (SANS) is used to explore the shear response of aqueous cetyltrimethylammonium bromide (CTAB) solutions with sodium nitrate. Rheological tests show shear thinning with no shear banding, ensuring a uniform flow field for reliable interpretation of scattering data. As shear rate increases, the scattering spectra show angular distortion, which is analyzed using spherical harmonic decomposition to characterize flow-induced scission and micelle orientation under shear. Two analysis steps are used: a model-independent spectral eigendecomposition reveals a decrease in micellar length, while regression analysis quantifies the evolution of the length distribution and mean length with shear rate. Additionally, micelle alignment increases with shear, quantified by the orientational distribution function. In conclusion, these findings provide experimental evidence for flow-induced alignment and scission, offering a new framework for understanding shear-induced phenomena in micellar systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Demonstration of acoustic monitoring for structural health of microreactors: Through use of neural networks and resonant ultrasound spectroscopy

Nuclear microreactors prioritize modularity and portability and are intended to be a cost-effective technology for non-conventional nuclear markets. As such, the development of microreactors into a safe and feasible solution for energy security applications will necessitate the development of non-destructive technologies to monitor the integrity of inaccessible reactors components during operation. This demonstration applies linear and nonlinear acoustic techniques, in combination with machine learning, to detect and classify mechanical changes (stress and damage) in a test article which are broadly representative of potential operating challenges within a functioning microreactor. All necessary data has been collected for this demonstration, with minor experimental issues identified that can be addressed in follow-on work. Motivated by the expected conditions within a functioning microreactor, we have demonstrated our monitoring techniques on a core-block-like test article using an unstructured excitation source that approximates the noisy acoustic environment expected during reactor operation. At all stress states mechanically applied to the test article, a machine learning model using an artificial neural network was able to classify with 100% accuracy whether a 3D laser vibrometry point measurement was made on an intact or artificially defective test article. Further, model predictions about whether the defect interface was rough or smooth were 95% accurate, indicating the ability of acoustic techniques to recover defect characteristics. Resonant ultrasound spectroscopy (RUS) was also applied to the dataset to provide further quantitative insights about material properties. RUS analysis was ultimately hampered by several minor experimental and data issues, limiting results to certain cases for this demonstration. Last, analysis using nonlinear RUS exhibited sensitivity to changing levels of applied stresses for each intact and defective state. As presented in this demonstration, acoustic monitoring exhibits sensitivity to stress changes, which are of concern due to high thermal gradients expected during startup and operation. Further, our techniques distinguish between measurements made on intact and damaged test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Structural Design Variations in Beetle Elytra

Abstract Beetles typically use their protective wing coverings or elytra to shield their membranous hindwings from the environment. Elytra in some terrestrial species have evolved a greater protective role capable of shielding the organism from powerful antagonistic predators. The structure–function relationships of these biological composites identify how architectural and chemical variations of the cuticle are tuned to create light‐weight, impact resistant composites. Specifically, the elytral structures of a tree dwelling beetle capable of flight, Trypoxylus dichotomus , and a terrestrial beetle incapable of flight, Phloeodes diabolicus , are compared to understand how their varied environmental needs forged the elytra to facilitate fight or resist fatal predator strikes. Mechanical and microstructural analysis reveals P . diabolicus has a harder, stiffer elytra that incorporate through‐thickness fibers to resist greater mechanical stresses imposed by bending and puncture. Conversely, the elytra of T . dichotomus have a compliant structure with large voids that facilitates localized deformation. Variations in flexural strength and puncture resistance remain attributed to P . diabolicus possessing a thicker cuticle with a greater degree of cross‐linking and an increased amount of endocuticular layers. These findings may provide useful insight into the design and manufacturing of composite materials for use in light‐weight or energy‐absorbing applications.

Rivera, Jesus↗

A Morphologically Stable Li/Electrolyte Interface for All-Solid-State Batteries Enabled by 3D-Micropatterned Garnet

Morphological degradation at the Li/solid-state electrolyte (SSE) interface is a prevalent issue causing performance fading of all-solid-state batteries (ASSBs). To maintain the interfacial integrity, most ASSBs are operated under low current density with considerable stack pressure, which significantly limits their widespread usage. In this work, a novel 3D-micropatterned SSE (3D-SSE) that can stabilize the morphology of the Li/SSE interface even under relatively high current density and limited stack pressure is reported. Under the pressure of 1.0 MPa, the Li symmetric cell using a garnet-type 3D-SSE fabricated by laser machining shows a high critical current density of 0.7 mA cm –2 and stable cycling over 500 h under 0.5 mA cm –2 . This excellent performance is attributed to the reduced local current density and amplified mechanical stress at the Li/3D-SSE interface. These two effects can benefit the flux balance between Li stripping and creep at the interface, thereby pre-venting interfacial degradation such as void formation and dendrite growth.

3D-micropatterned garnet↗

Domain Wall Patterning and Giant Response Functions in Ferrimagnetic Spinels

Abstract The manipulation of mesoscale domain wall phenomena has emerged as a powerful strategy for designing ferroelectric responses in functional devices, but its full potential is not yet realized in the field of magnetism. This work shows a direct connection between magnetic response functions in mechanically strained samples of Mn 3 O 4 and MnV 2 O 4 and stripe‐like patternings of the bulk magnetization which appear below known magnetostructural transitions. Building off previous magnetic force microscopy data, a small‐angle neutron scattering is used to show that these patterns represent distinctive magnetic phenomena which extend throughout the bulk of two separate materials, and further are controllable via applied magnetic field and mechanical stress. These results are unambiguously connected to the anomalously large magnetoelastic and magnetodielectric response functions reported for these materials, by performing susceptibility measurements on the same crystals and directly correlating local and macroscopic data.

36 MATERIALS SCIENCE↗

Origin of Ferroelectric Phase Stabilization via the Clamping Effect in Ferroelectric Hafnium Zirconium Oxide Thin Films

The presence of the top electrode on hafnium oxide-based thin films during processing has been shown to drive an increase in the amount of metastable ferroelectric orthorhombic phase and polarization performance. This “Clamping Effect,” also referred to as the Capping or Confinement Effect, is attributed to the mechanical stress and confinement from the top electrode layer. However, other contributions to orthorhombic phase stabilization have been experimentally reported, which may also be affected by the presence of a top electrode. In this study, it is shown that the presence of the top electrode during thermal processing results in larger tensile biaxial stress magnitudes and concomitant increases in ferroelectric phase fraction and polarization response, whereas film chemistry, microstructure, and crystallization temperature are not affected. Through etching experiments and measurement of stress evolution for each processing step, it is shown that the top electrode locally inhibits out-of-plane expansion in the HZO during crystallization, which prevents equilibrium monoclinic phase formation and stabilizes the orthorhombic phase. This study provides a mechanistic understanding of the clamping effect and orthorhombic phase formation in ferroelectric hafnium oxide-based thin films, which informs the future design of these materials to maximize ferroelectric phase purity and corresponding polarization behavior.

36 MATERIALS SCIENCE↗

Multifunctional Utilization of Pitch-Coated Carbon Fibers in Lithium-Based Rechargeable Batteries

This work reports carbon fibers as an electrode material and current collector for dual-carbon and lithium-ion batteries. Here, fully graphitic and semigraphitic carbon fibers undergo anion intercalation beyond 4.5 V versus Li/Li + . Symmetric dual-carbon full cells using a pitch-coated fully graphitic carbon fiber mat as both cathode and anode delivers an energy-density of 276 and 322 Wh kg -1 at 342 W kg -1 power density in the voltage range of 3.0–5.0 and 3.0–5.2 V, respectively. On the other hand, nongraphitic carbon fibers do not exhibit anion intercalation up to 5.2 V and can be used as a current collector. They also possess a larger number of Li + storage sites in their randomly oriented microstructure when used as an anode. A lithium-ion full cell with double carbon-coated C-LiFePO 4 loaded on nongraphitic carbon fiber as a cathode and pitch-coated nongraphitic carbon fiber as an anode exhibits 202.6 and 75.2 Wh kg -1 energy density at power densities of 46.75 W kg -1 and 11.7 kW kg -1 , respectively in 2.0–3.5 V range. This pitch-coated carbon fiber-based battery configuration eliminates the need for metal foils and costly fluorinated binders, lowers overall weight of the cell, and is capable of sustaining mechanical stress and thermal shock.

PF6− intercalation↗

Tuned Reactivity at the Lithium Metal–Argyrodite Solid State Electrolyte Interphase

Thin intermetallic Li 2 Te–LiTe 3 bilayer (0.75 µm) derived from 2D tellurene stabilizes the solid electrolyte interphase (SEI) of lithium metal and argyrodite (LPSCl, Li 6 PS 5 Cl) solid-state electrolyte (SSE). Tellurene is loaded onto a standard battery separator and reacted with lithium through single-pass mechanical rolling or transferred directly to SSE surface by pressing. State-of-the-art electrochemical performance is achieved, e.g., symmetric cell stable for 300 cycles (1800 h) at 1 mA cm -2 and 3 mAh cm -2 (25% DOD, 60 µm foil). Cryo-stage focused ion beam (Cryo-FIB) sectioning and Raman mapping demonstrate that the Li 2 Te–LiTe 3 bilayer impedes SSE decomposition. The unmodified Li–LPSCl interphase is electrochemically unstable with a geometrically heterogeneous reduction decomposition reaction front that extends deep into the SSE. Decomposition drives voiding in Li metal due to its high flux to the reaction front, as well as voiding in the SSE due to the associated volume changes. Analysis of cycled SSE found no evidence for pristine (unreacted) lithium metal filaments/dendrites, implying failure driven by decomposition phases with sufficient electrical conductivity that span electrolyte thickness. In conclusion, DFT calculations clarify thermodynamic stability, interfacial adhesion, and electronic transport properties of interphases, while mesoscale modeling examines interrelations between reaction front heterogeneity (SEI heterogeneity), current distribution, and localized chemo-mechanical stresses.

25 ENERGY STORAGE↗

Tailoring Binder Molecular Weight to Enhance Slurry-Cast NMC Cathodes for Sulfide Solid-State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry-cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide-based all-solid-state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li-ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high-voltage NMC cathodes with sheet-type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high-performance all-solid-state batteries.

25 ENERGY STORAGE↗

Review of the Effects of Polymer Binder Properties on Microstructure and Irreversible Volume Growth of Plastic Bonded Explosives Formulations

The rational design of effective polymeric binders for the formulation of plastic-bonded explosives (PBX) is challenging due to their inherent compositional complexity. The composites comprise irregularly shaped energetic material (EM) powders coated with low weight fractions of polymer via non-equilibrium processes such as slurry coating. Defects can deleteriously affect PBX stability and performance: nano- to micrometer-scale voids can act as loci for hot spots, lowering deflagration and detonation temperatures in unpredictable ways. Furthermore, some nominally desirable polymer properties are at odds with each other: e. g. good flow characteristics are desirable for coating and adhesion, but mechanical stiffness is needed to prevent deformation and cracking of PBX under mechanical stress. Good binder adhesion is critical, but the best means to predict and measure adhesion in PBX is not obvious. Experimental methods of determining binder adhesion on model surfaces may not capture polymer structural configurations relevant to deposition during coating. Molecular dynamics-based computational models have predicted key observables in PBX formulation, suggesting that they may be powerful tools for binder selection. In this review, primarily recent (~2006 and later) literature on polymeric binders for insensitive HE (IHE) is surveyed. We focus on how binder properties influence observable PBX properties as resistance to irreversible volume growth and void formation in PBX formulations mainly (but not exclusively) featuring 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) as the EM (e. g. PBX 9502, LX-17 and others). Conclusions from these studies yield useful guidelines for choosing HE binder candidates, as well as for the general design of highly-filled polymer composite materials. Finally, studies describing challenges in PBX formulation with the newer and more energetically dense high explosive, LLM-105, will be discussed.

adhesion↗

Ionic Liquid–Directed Nanoporous TiNb 2 O 7 Anodes with Superior Performance for Fast–Rechargeable Lithium–Ion Batteries

Nanoporous TiNb 2 O 7 (NPTNO) material is synthesized by a sol–gel method with an ionic liquid (IL) as the nanoporous structure directing template. NPTNO exhibits a high reversible capacity of 210 mAh g –1 even at the charging rate of 50 C and an excellent cyclability of half-cell capacity retention of 74% for 1000 cycles at 5 C and LiNi 0.5 Mn 1.5 O 4 -coupled full-cell capacity retentions of 81% and 87% for 1000 cycles at 1 C and 2 C, respectively. The studies of the 1000 cycled NPTNO electrode illustrate that the IL-directed mesoporous structure can enhance the cyclability of NPTNO cells due to the alleviation of repetitive mechanical stress and volume fluctuation induced by the repetitive Li + insertion-extraction processes. The measured Li + diffusion coefficients from the galvanostatic intermittent titration technique suggest that the IL-templating strategy indeed ensures the fast rechargeability of NPTNO cells based on the fast Li + diffusion kinetics. Benefitting from the nanoporous structure, NPTNO with unhindered Li + diffusion pathways achieves a superior rate capability in the titanium-based oxide materials and the best full-cell cyclability in the TNO materials. Furthermore, the templating potential of IL is demonstrated, and the superb electrochemical performance establishes the IL-directed NPTNO as a promising anode candidate for fast-rechargeable LIBs.

25 ENERGY STORAGE↗

Molecular level insight into non-bilayer structure formation in thylakoid membranes: a molecular dynamics study

In oxygenic photosynthetic organisms, the light reactions are performed by protein complexes embedded in the lipid bilayer of thylakoid membranes (TMs). The organization of the bulk lipid molecules into bilayer structures provide optimal conditions for the build-up of the proton motive force (pmf) and its utilization for ATP synthesis. However, the lipid composition of TMs is dominated by the non-bilayer lipid species monogalactosyl diacylglycerol (MGDG), and functional plant TMs, besides the bilayer, contain large amounts of non-bilayer lipid phases. Bulk lipids have been shown to be associated with lumenal, stromal-side and marginal-region proteins and proposed to play roles in the self-assembly and photoprotection of the photosynthetic machinery. Furthermore, it has recently been pointed out that the generation and utilization of pmf for ATP synthesis according to the ‘protet’ or protonic charge transfer model Kell (Biochim Biophys Acta Bioenerg 1865(4):149504, 2024), requires high MGDG content Garab (Physiol Plant 177(2):e70230, 2025). In this study, to gain better insight into the structural and functional roles of MGDG, we employed all atom and coarse-grained molecular dynamics simulations to explore how temperature, hydration levels and varying MGDG concentrations affect the structural and dynamic properties of bilayer membranes constituted of plant thylakoid lipids. Our findings reveal that MGDG promotes increased membrane fluidity and dynamic fluctuations in membrane thickness. MGDG-rich stacked bilayers spontaneously formed inverted hexagonal phases; these transitions were enhanced at low hydration levels and at elevated but physiologically relevant temperatures. It can thus be inferred that MGDG plays important roles in heat and drought stress mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

Optimization of an Impedance-Matched Test Fixture with the Modal Projection Error

Across many industries and engineering disciplines, components and systems are designed and deployed into their operational environment of intended use. It is the desire of the design agency to be able to predict whether their component or system will function in its shock and vibration environments or if it will fail due to mechanical stresses. One method to determine if the component will survive the shock and vibration environments is to expose the component to the operational environment in a laboratory. One difficulty in executing a representative laboratory test is that the component may not have the same boundary condition in the laboratory as in the operational configuration. This paper examines the use of parameterized optimization to design the test fixture in order to better match the operational configuration. Several frequency and modal-based objective functions are examined for the optimization. The study shows that the Modal Projection Error objective function performs the best of the functions studied. The efficacy of the Modal Projection Error is demonstrated with respect to dynamic test fixture design on several analytical and experimental exemplars.

dynamic↗

Enhanced accuracy through ensembling of randomly initialized auto-regressive models for dynamical systems

Computational mechanics simulations using traditional finite element methods (FEM) require prohibitively expensive computational resources for real-time engineering applications, design optimization, and digital twin implementations. While machine learning (ML) surrogate models offer significant computational speedups, autoregressive ML models for time-dependent mechanical systems suffer from error accumulation that compromises long-term prediction reliability - a critical concern for engineering applications where accuracy over extended time horizons is essential for safety and performance assessments. Here, we propose a deep ensemble framework specifically designed to address this challenge in computational mechanics applications, where multiple ML surrogate models with random weight initializations are trained in parallel and their predictions aggregated during inference. This approach leverages statistical diversity to maximize information gain from a fixed set of training data and to mitigate error propagation, while maintaining the computational efficiency that makes ML surrogates attractive for engineering practice. We validate the framework on three representative problems spanning critical areas of computational mechanics: stress field evolution in heterogeneous microstructures under complex loading (relevant to advanced materials design and composite analysis), planetary-scale shallow water dynamics (applicable to environmental and geotechnical engineering), and Gray-Scott reaction-diffusion systems (relevant to mass transport and chemical process engineering). Across all test cases, the ensemble approach demonstrates consistent error reduction of 15-33% compared to individual models. The codes for this work are available on GitHub (https://github.com/Graham-Brady-Research-Group/AutoregressiveEnsemble_SpatioTemporal_Evolution).

autoregressive prediction↗

Spectroscopic evaluation of tribologically-induced changes in surface chemistry of Zr-based bulk metallic glass

Bulk metallic glasses (BMGs) are promising structural materials owing to their high elastic limit and yield strength-to-weight ratio. While BMGs also exhibit attractive tribological properties (e.g., high wear resistance), the scientific basis for this behavior is not yet established. In particular, tribologically-induced changes in surface chemistry upon sliding are still an open topic of research. Here, we evaluated by X-ray photoelectron spectroscopy (XPS) the evolution of the surface chemistry of Vitreloy 105 (a Zr-rich BMG) upon sliding under different contact conditions against a tungsten carbide countersurface. The spectroscopic results indicate that the relative fraction of the metallic elements in the near-surface region is not affected by the sliding speed when the applied contact pressure is lower than 1.37 GPa, while a decrease in metallic zirconium was observed at lower sliding speeds and higher applied contact pressure (i.e., 1.71 GPa). Based on the spectroscopic results, a model is proposed for the effect of mechanical stress on the extent of oxidation of the near-surface region of Zr-based BMGs. In conclusion, the results of this work provide novel insights into the surface phenomena occurring on BMGs upon sliding and add significantly to our understanding of the tribological response of this class of promising structural materials.

Bulk metallic glasses↗

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗

Machine learning in nuclear materials research

Nuclear materials are often demanded to function for extended time in extreme environments, including high radiation fluxes with associated transmutations, high temperature and temperature gradients, mechanical stresses, and corrosive coolants. They also have a wide range of microstructural and chemical makeups, resulting in multifaceted and often out-of-equilibrium interactions. Machine learning (ML) is increasingly being used to tackle these complex time-dependent interactions and aid researchers in developing models and making predictions, sometimes with better accuracy than traditional modeling that focuses on one or two parameters at a time. Conventional practices of acquiring new experimental data in nuclear materials research are often slow and expensive, limiting the opportunity for data-centric ML, but new methods are changing that paradigm. Here we review high-throughput computational and experimental data approaches, especially robotic experimentation and active learning that is based on Gaussian process and Bayesian optimization. We show ML examples in structural materials (e.g., reactor pressure vessel (RPV) alloys and radiation detecting scintillating materials) and highlight new techniques of high-throughput sample preparation and characterizations, and automated radiation/environmental exposures and real-time online diagnostics. Herein, this review suggests that ML models of material constitutive relations in plasticity, damage, and even electronic and optical responses to radiation are likely to become powerful tools as they develop. Finally, we speculate on how the recent trends of using natural language processing (NLP) to aid the collection and analysis of literature data, interpretable artificial intelligence (AI), and the use of streamlined scripting, database, workflow management, and cloud computing platforms that will soon make the utilization of ML techniques as commonplace as the spreadsheet curve-fitting practices of today.

36 MATERIALS SCIENCE↗

Synthesis of hierarchical graphene coated porous Si anode for lithium-ion batteries

The ultra-high capacity and widespread availability of Si materials have resulted in them being the focus of extensive studies to replace the graphite anode. However, the main barriers preventing the Si anodes from large-scale applications are their huge volume change and severe interface reactions in the lithiation/delithiation process, which pulverizes its structure and subsequently deteriorates its cycle life. Here, micrometer-scale porous Si coated with graphene coating (mpSi@G) has been synthesized by using SiO 2 nanoparticles and novel coal-derived humic acid as feedstocks through a magnesiothermic reduction, followed by spray drying and calcination techniques. SEM, Raman, and X-ray absorption analysis demonstrate that the hierarchical graphene shell and micrometer-sized porous Si structure effectively release the Si anode's mechanical stress upon lithiation to achieve good structural stability. Here, the synthesized mpSi@G anode delivers a high initial lithiation capacity of 2974.9 mAh g –1 at 0.1 A g –1 with an initial coulombic efficiency of 70.2 %. Furthermore, the conductive hierarchical graphene network, along with the tight contacts of porous-Si and the graphene shell, contribute to a high capacity of 1109.5 mAh g –1 at a high current density of 5.0 A g –1 , showing excellent rate capability.

25 ENERGY STORAGE↗