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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Anomalous softening of 3D printed elastomeric foam irradiated under compressive strain

Elastomeric foam is an essential component in many industrial and technological settings, primarily as thermal insulators and as positional/mechanical support cushions. In particular, silicone foam is utilized in harsh environments due to exceptional thermal and chemical stability. Under service conditions within certain applications such material gets exposed to a high dosage of gamma radiation, which can permanently alter the material’s structural and mechanical response properties. Most studies on gamma-exposure under inert or oxidative atmosphere indicate hardening of silicone foam, which is attributed to radiation-induced enhancement in chemical cross-linking. Here we report two contrasting effects depending on whether (non-oxidative) radiation exposure is carried out with the foam under zero or finite compressive strain. While in the former case we observe radiation-hardening consistent with previous studies, in the latter case (50% porous foam under 30% uniaxial compression) we see a monotonic decrease in Young’s modulus with increasing dosage, although solvent swelling experiments on the constituent rubber indicate a net increase in cross-link density independent of the state of strain. We quantitatively model all dose-dependent data using the Ogden Hyperfoam strain-energy function within the framework of Tobolsky two-network scheme and attribute the above anomaly to a combined effect of radiation-induced thickness change (compression set) and inherent nonlinearity in the foam’s stress-strain response.

Coarse-grained models↗
DOE OSTI2026

Investigating property-porosity relationships for micro-architected lattice structures

Micro-architected structures are increasingly valued for their light weight and tunable mechanical properties; this class of material includes sheet structures like the Schöen gyroid and beam lattices like the octet. For design purposes, it is critical to understand how to tune the relative density (RD) to obtain desired mechanical properties. This study investigates the mechanical response of Ti-6Al-4V gyroid structures, spanning a broad range of RDs (0.03–0.90), unit cell sizes (1–4 cm), and sheet thicknesses (0.2–7.8 mm). Results demonstrate that the classical Gibson-Ashby power law scaling between RD and modulus and yield stress does not adequately capture the response over a wide range of RDs, nor does it extrapolate correctly to the fully dense solid. Analytical models, in concert with experimental results and high-fidelity finite element calculations, show that the deviation from Gibson-Ashby reflects a transition from structure-dominated to material-dominated behavior. Distinctions are drawn between scaling relationships and property-porosity models, and an analytical model is proposed to better capture the evolution of mechanical properties with RD. These observations are mirrored in other architected topologies, like the octet, and highlight the importance of understanding the relationship between mechanical properties and geometry for design purposes.

Materials science↗
DOE OSTI2024

High-strength 3D printed poly(lactic acid) composites reinforced by shear-aligned polymer-grafted cellulose nanofibrils

This work demonstrates the application of pilot-scale surface functionalization of cellulose nanofibrils (CNFs) by aqueous grafting-through polymerization and subsequent spray drying in 3D printed poly(lactic acid) (PLA) composites. Grafted-CNF composites attain an ultimate tensile strength of 88 ± 3 MPa and a tensile modulus of elasticity of 7.8 ± 1.3 GPa in the printing direction at 20 wt% reinforcement loading. These increases, 42% and 139% over neat PLA, respectively, represent the strongest reported 3D printed CNF/PLA composite to date in the literature. The mechanisms behind these improvements are investigated by comparisons to neat PLA and unmodified spray-dried CNF/PLA controls using melt rheology, dynamic mechanical analysis, and assessment of the reinforcement dispersion. These experiments reveal that improved network formation and shear-induced alignment of the grafted CNFs facilitate the remarkable tensile properties of the printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Surfactant templated biogenic nanoporous silica thermal insulation composite

Carbon-sequestration biogenic insulation materials offer a promising solution for sustainable and energy-efficient buildings. However, minimizing energy-intensive manufacturing processes and ensuring a uniform microstructure are essential to achieve widespread application. In this work, we introduce cetyltrimethylammonium bromide (CTAB) surfactant as both synthesis and dispersion template for nanoporous silica to create biogenic straw-based thermal insulation composites. As the amount of nanoporous silica increases to 72 wt%, the elastic insulation composite dried using the solvent exchange method exhibits a density of 0.058 g cm –3 , a thermal conductivity of 30.3 mW m –1 K –1 and a flexural modulus of 3.96 MPa, while demonstrating materials circularity and fire retardance. The use of CTAB surfactant effectively captures nanoporous silica, preventing its loss during manufacturing and enhancing the homogeneity and dispersion of the silica within the composite. In addition, the results show that the ethanol solvent exchange drying at ambient conditions provides the optimum thermal insulation performance with less energy consumption compared to freeze-drying.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Mechanical and electrical changes in electrochemically active polyimide binders for Li-ion batteries

Polyimide binders are often used in electrodes made with silicon for lithium-ion batteries for their mechanical strength and adhesion, which help mitigate mechanical issues associated with large volumetric expansion. These binders can be electrochemically active, but it is difficult to characterize what physical and chemical changes occur due to a composite electrode with multiple components and processes at play. Here, in this work, we study electrodes consisting only of polyimide binder and conductive carbon, using scanning probe-based techniques—contact resonance, force volume, and scanning spreading resistance microscopy—along with cryo-scanning transmission electron microscopy, electron energy loss spectroscopy, and energy dispersive X-ray spectroscopy. We show that lithium becomes trapped in the binder during cycling and results in large initial capacity losses, the formation of dendrite-like features, column-like domains of significantly increased mechanical modulus, and a slight increase in electronic resistivity.

25 ENERGY STORAGE↗
DOE OSTI2026

Strengthening poly(lactic acid) composites with poly(methyl methacrylate) functionalized flax nanofibrils

Biobased reinforcements for poly(lactic acid) (PLA) are needed for more additive manufacturing applications requiring higher strength and sustainability. Flax nanofibrils (FNFs) produced through mechanical refining were explored as a lower energy alternative to cellulose nanofibril (CNF) reinforcements. To compatibilize the FNFs for the PLA matrix, a grafting-through surfactant free emulsion polymerization (SFEP) was performed to functionalize the FNF surface with poly(methyl methacrylate) (PMMA). FNFs produced using different refining energy were functionalized under varying solid contents in suspension. Polymerizations performed at 0.7 wt% FNFs in water yielded the highest degree of PMMA functionality. These optimal conditions were scaled up and the PMMA modified FNFs melt compounded into PLA yielding a 12% increase in tensile strength and 92% increase in the modulus of elasticity as compared to the original PLA. Interestingly, the FNFs with the lowest refining energy yielded the strongest composites using these methods, surpassing the higher refining energy CNF reinforcements. This increase was attributed to improved dispersion of the FNF reinforcements in the PLA matrix that was enabled by the PMMA coating on the FNF surface preventing interfibrillar adhesion and aggregation within the PLA matrix.

Mulligan, Abigail [University of Maine]↗
DOE OSTI2025

Elucidating the impact of fiber source on polypropylene/hemp composite performance for the automotive industry

Given their high strength-to-weight ratio, there is an ever-increasing volume of plastics being used in the automotive industry as plastics aid in the charge to lightweight vehicles for improved fuel efficiency. However, these plastics are often landfilled at their end-of-life, which has given rise to the demand for sustainable materials and waste management alternatives compared to purely synthetic systems. Natural fiber composites have been explored as a viable material option to reduce the environmental impact of plastic use in automobiles while simultaneously ensuring the part performance is not sacrificed. Herein, we explored the use of hemp/polypropylene (PP) composites in which US-sourced hemp is compared to internationally sourced and industrially available hemp. There appears to be a minimal impact on the composite properties regardless of fiber sourcing, and the addition of a natural filler to the PP matrix results in up to a 367% increase in Young's modulus, 126% increase in heat deflection temperature, and comparable water uptake performance. It should be noted that the natural filler addition does increase density by up to 13% due to the higher density of natural fibers compared to the low-density PP matrix. A modified rule of mixtures calculation revealed that the composite materials produced in this study demonstrated good agreement with analytical modeling. Finally, a screening analysis was performed exploring the transportation of hemp fibers, and the results build a strong case for regionalized manufacturing of automotive parts.

Hubbard, Amber M. [Oak Ridge National Laboratory (↗
DOE OSTI2026

Molecular concentration field design using closed-form steady-state solutions

Control over spatial concentration fields represents a fundamental challenge in designing synthetic biological systems and programmable soft materials. While nature creates morphogen gradients that orchestrate complex developmental processes, synthetic approaches have largely relied on empirical optimization and computationally intensive simulations. Here, we present an analytical framework for steady-state concentration fields generated by finite-sized localized sources in diffusion–degradation systems and derive closed-form solutions for one-, two-, and three-dimensional geometries. By expressing these solutions in dimensionless form, we show that gradient steepness and spatial structure are organized by the Thiele modulus, which captures the competition between diffusion and degradation length scales. The analysis reveals distinct design regimes: in degradation-dominated systems, gradient shape is governed by exponential decay and becomes dimension-independent, whereas in diffusion-dominated systems, gradient magnitude and extent follow dimension-dependent power-law scaling. Building on these results, we introduce a quantitative design strategy that uses threshold-based criteria to program concentration ranges by tuning physically accessible parameters, most directly the production rate, while holding transport and degradation properties fixed. Comparisons with numerical solutions and reported experimental systems demonstrate consistency with the predicted scaling behavior. Together, this work provides a generalizable and physically transparent framework for designing steady-state concentration fields in synthetic biological and soft matter systems, enabling predictive control of gradient-mediated organization without reliance on extensive numerical optimization.

Kim, Dong Woo [Johns Hopkins University, Baltimore↗
DOE OSTI2025

A single-ion-conducting polymer and high-entropy Li-garnet composite electrolyte with simultaneous enhancement in ion transport and mechanical properties

Enabling the lithium metal anode has been the holy grail for improving the energy density for the next generation advanced batteries. Developing electrolytes that will suppress Li dendrite growth and provide sufficient ionic conductivity remains a major challenge in this field. In this study, we develop a polymer–ceramic composite electrolyte for lithium metal batteries. The polymer matrix is a vinyl ethylene carbonate (VEC) based single-ion-conducting polymer electrolyte. The ceramic filler is a Li 7 La 3 Zr 0.5 Nb 0.5 Ta 0.5 Hf 0.5 O 12 high-entropy Li-garnet (HE Li-garnet) ceramic, which is less prone to surface Li 2 CO 3 formation compared to Al-doped Li garnets. The addition of HE Li-garnet leads to a 7-fold increase in the ionic conductivity (8.6 × 10 −5 S cm −1 at 30 °C) compared to the pure polymer, while maintaining a high Li + transference of 0.73. Proton nuclear magnetic resonance and thermogravimetric analysis results suggest that the addition of HE Li-garnet results in a lower degree of polymerization of VEC, leaving more unpolymerized VEC monomers in the matrix, serving as the governing mechanism for conductivity enhancement. The favorable interactions between HE Li-garnet particles and the polymer matrix lead to a stable and well-mixed composite with 2-fold enhancement of storage modulus at 40 °C. The simultaneous ion transport and mechanical property enhancement significantly improves the composite electrolyte's dendrite resistance and cycle life in Li symmetric cells. This work highlights the positive role HE Li-garnet can play in improving polymer electrolytes to enable lithium metal anodes.

Ock, Ji-young [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2026

Valorization of consolidated bioprocessing residues for bioplastics

This study demonstrates an organic solvent-free processing strategy to valorize consolidated bioprocessing (CBP) residues, from switchgrass and poplar biomass, into functional poly(butylene succinate) (PBS)-based biocomposites using high-shear homogenization (HSH). HSH transformed the switchgrass and poplar CBP residues (CBP-R) into fine, uniformly distributed particles and microfibers. The composites of PBS with homogenized switchgrass residues (H-CBP-R-SG) or homogenized poplar residues (H-CBP-R-P) at a 70/30 weight ratio exhibited improved processability and mechanical integrity, with the Young's modulus for the PBS/H-CBP-R-SG and PBS/H-CBP-R-P nearly doubling to 0.66 ± 0.07 GPa and 0.65 ± 0.04 GPa, respectively, compared to neat PBS (0.36 ± 0.02 GPa). Dynamic Mechanical Analysis (DMA) reveals a significant suppression of the tan δ peak magnitude, indicating that HSH-mediated physical activation facilitates stress transfer in composites typical of covalent chemical grafting systems. While the transition to a stiffness-dominated profile reduces ductility, the resulting composites exhibit the dimensional stability and resistance to thermal warping required for high-fidelity FDM 3D printing and injection molding. Beyond material performance, comprehensive techno-economic analysis (TEA) and life cycle assessment (LCA) confirmed that diverting CBP residues into composite products can improve the economic viability of the biorefinery without substantially increasing biorefinery global warming potential (GWP). At a 30 wt% blend ratio, incorporating residuals into PBS yielded a minimum selling price for the composite of $\$4.07$ per kg compared to the conventional bioplastic price of $\$5.00$ per kg. This approach aligns with circular bioeconomy principles by converting waste streams into value-added products. Furthermore, this innovative strategy addresses key challenges in bioplastic development, including cost, compatibility, and performance, while simultaneously advancing waste minimization strategies for sustainable manufacturing systems.

09 BIOMASS FUELS↗
DOE OSTI2025

Egg yolk as a model for gelation: From rheometry to flow physics

Egg yolks are an excellent model for studying sol-gel transitions, particularly the power law viscoelasticity that defines the critical point of gelation. However, prior studies lack comprehensive datasets and fail to visualize flow behavior linked to temperature and time-dependent linear and nonlinear rheology. Here, we present a detailed dataset characterizing egg yolk viscoelasticity across temperature, time, and forcing amplitude using oscillatory shear, step strain, step stress, and constant high strain rate. Novel protorheology visualizations link rheological properties with observable flow behavior. Our findings highlight the nuanced determination of the critical gel point, emphasizing observation timescale dependencies. We compare methods to identify critical temperatures for gelation, including power law viscoelasticity, moduli crossover, diverging zero-shear viscosity, and emerging equilibrium elastic modulus, while visualizing flow consequences near these transitions. Egg yolk is an accessible, realistic, and nontoxic material relevant to the physicist and the chef alike, making it ideal for understanding the rheology of critical gels. By integrating protorheology photos and videos with rigorous rheometric data, we deepen the understanding of critical gels, with broader impacts for studying other materials with sol-gel transitions.

Marsh, Maxwell C. [Department of Mechanical Scienc↗
DOE OSTI2024

Active doping controls the mode of failure in dense colloidal gels

Mechanical properties of disordered materials are governed by their underlying free energy landscape. In contrast to external fields, embedding a small fraction of active particles within a disordered material generates nonequilibrium internal fields, which can help to circumvent kinetic barriers and modulate the free energy landscape. In this work, we investigate through computer simulations how the activity of active particles alters the mechanical response of deeply annealed polydisperse colloidal gels. We show that the “swim force” generated by the embedded active particles is responsible for determining the mode of mechanical failure, i.e., brittle vs. ductile. We find, and theoretically justify, that at a critical swim force the mechanical properties of the gel decrease abruptly, signaling a change in the mode of mechanical failure. The weakening of the elastic modulus above the critical swim force results from the change in gel porosity and distribution of attractive forces among gel particles, while below the critical swim force, the ductility enhancement is caused by an increase of gel structural disorder. Above the critical swim force, the gel develops a pronounced heterogeneous structure characterized by multiple pore spaces, and the mechanical response is controlled by dynamical heterogeneities. We contrast these results with those of a simulated monodisperse gel that exhibits a nonmonotonic trend of ductility modulation with increasing swim force, revealing a complex interplay between the gel energy landscape and embedded activity.

Zhou, Tingtao (ORCID:000000021766719X)↗
DOE OSTI2025

Prediction of carbon nanostructure mechanical properties and the role of defects using machine learning

Graphene-based nanostructures hold immense potential as strong and lightweight materials, however, their mechanical properties such as modulus and strength are difficult to fully exploit due to challenges in atomic-scale engineering. This study presents a database of over 2,000 pristine and defective nanoscale CNT bundles and other graphitic assemblies, inspired by microscopy, with associated stress–strain curves from reactive molecular dynamics (MD) simulations using the reactive INTERFACE force field (IFF-R). These 3D structures, containing up to 80,000 atoms, enable detailed analyses of structure-stiffness-failure relationships. By leveraging the database and physics- and chemistry-informed machine learning (ML), accurate predictions of elastic moduli and tensile strength are demonstrated at speeds 1,000 to 10,000 times faster than efficient MD simulations. Hierarchical Graph Neural Networks with Spatial Information (HS-GNNs) are introduced, which integrate chemistry knowledge. HS-GNNs as well as extreme gradient boosted trees (XGBoost) achieve forecasts of mechanical properties of arbitrary carbon nanostructures with only 3 to 6% mean relative error. The reliability equals experimental accuracy and is up to 20 times higher than other ML methods. Predictions maintain 8 to 18% accuracy for large CNT bundles, CNT junctions, and carbon fiber cross-sections outside the training distribution. The physics- and chemistry-informed HS-GNN works remarkably well for data outside the training range while XGBoost works well with limited training data inside the training range. The carbon nanostructure database is designed for integration with multimodal experimental and simulation data, scalable beyond 100 nm size, and extendable to chemically similar compounds and broader property ranges. The ML approaches have potential for applications in structural materials, nanoelectronics, and carbon-based catalysts.

Winetrout, Jordan J.↗
DOE OSTI2026

Equation of state for Hf, Ta, W, Re, Os, Ir, Pt, and Au to multi-terapascal pressures from density-functional theory

We present the zero-temperature equation of state (pressure dependence of compression) and phase stability predictions for the 5d-transition metals obtained from all-electron density-functional theory (DFT) calculations. The results compare favorably with experiments but extend beyond current experimental capabilities to 10 TPa. Our study reveals phase changes that are explained from the calculated electronic structure. The cubic face-centered and body-centered structures (fcc and bcc), together with two-, three-, and four-layered hexagonal structures, play major roles under compression. The results’ dependence on the electron exchange and correlation in the DFT approach is investigated, and it is shown that the impact of the choice, while significant at lower pressures, diminishes in the terapascal regime. We further illustrate that the normal parabolic trends in atomic volume and bulk modulus with atomic number, due to the occupation of bonding and anti-bonding 5d states, break down at TPa pressures, suggesting drastically different chemical bonding at these extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Non-solvents as physical blowing agents in printable silicone foams

Silicone foams were produced by dispersing an incompatible liquid phase (i.e. a non-solvent) into an uncured, liquid silicone. The formulation and processing parameters were varied to see the effect on porosity and pore morphology. Specifically, two fluorosilanes were added to stabilize the inclusion of fluorinated solvents as blowing agents. As the floruosilane content increased, the void content increased up to about 44 vol. % when the fluorosilane comprised 18 wt. % of the initial formulation. Fumed silica that was treated with a fluorinated silane was also used to try to stabilize the dispersed liquid. While the fumed silica content did not have a strong effect on the total void content, the morphology changed when silica content changed. Various fluorinated solvents with distinct chemical structures were used as the non-solvent and then removed after curing of the silicone. The interaction of the internal non-solvent phase and the silicone phase was expected to influence the porosity. These insights highlight how the manipulation of formulation and processing parameters, focusing on the inclusion of fluorosilanes and fluorinated solvents, contributes to the understanding of how incompatible liquid phases interact with silicone matrices to control porosity and pore morphology. Additionally, these interactions also influenced processability, leading to formulations that could be printed. Higher content of non-solvent inclusions could increase the yield stress and storage modulus of an uncured formulation, leading to the ability to tune intrastrand porosity while a 3D printed architecture could be modified to introduce porosity between the strands. Furthermore, in addition to fluorinated solvents, we also considered non-fluorinated solvents since these may be more industrially relevant in the future. Overall, this approach provides an alternative route to producing porous foams that can be 3D printed, which could be useful for applications like cushioning and protective gear.

physical blowing agent↗
DOE OSTI2025

Self-assembly of wood-based shape memory composites triggered by solar-thermal energy

Transporting and assembling large, complex structures poses significant challenges due to their size, geometry, and cost. Additionally, the installation sites are often inaccessible or hazardous for humans, necessitating self-assembling capabilities in these structures. To mitigate these challenges, we propose using 3D printing materials with shape memory effect (SME) for both transport and construction. This approach involves developing 3D modular components into flat sheets for easier transportation, and then self-assembling into 3D structures on-site using solar energy. To gain a deeper understanding of the factors influencing material memory performance, we have chosen a composite PLA/WF, which is polylactic acid (PLA) with 20 wt% wood flour (WF) for this purpose, leveraging its high tensile modulus at 0.966 GPa, low cost, and sustainability. Printed shapes with this material can maintain a recovery ratio over 90% after 3 cycles. While traditional composites fillers (e.g. glass or carbon fiber) are added to enhance mechanical and thermal properties, the addition of bio-based fillers like WF accomplish similar goals without compromising sustainability. We conducted multiple experiments to demonstrate how environmental conditions (i.e. temperature) maximize the material’s SME. Although still at an early stage, this study provides initial insights into bridging the gap between the small-scale nature of shape memory polymers (SMPs) and their potential for large-scale additive manufacturing, addressing a critical need for efficient and sustainable construction. In the long term, we hope our study contributes to the design vision of utilizing SMPs for transportation, assembly, and deployment of complex structures, providing a new pathway for sustainable construction and transportation of large-scale structures to hard-to-access locations such as disaster-affected areas and remote deserts, etc.

4D printing↗
DOE OSTI2025

Toward machine learning interatomic potentials for modeling uranium mononitride

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale modeling of UN at finite temperatures. We constructed a training set using density functional theory (DFT) calculations that was enriched through an active learning procedure, and two neural network potentials were generated. Both potentials successfully reproduce key thermophysical properties of interest, such as temperature-dependent lattice parameter, specific heat capacity, and bulk modulus. We also evaluated the energy of stoichiometric defect reactions and defect migration barriers and found close agreement with DFT predictions, demonstrating that our potentials can be used for modeling defects in UN. Additional tests provide evidence that our potentials are reliable for simulating diffusion, noble gas impurities, and radiation damage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Altered post-fracture systemic bone loss in a mouse model of osteocyte dysfunction

Femur fracture leads to loss of bone at uninjured skeletal sites, which may increase risk of subsequent fracture. Osteocytes, the most abundant bone cells, can directly resorb bone matrix and regulate osteoclast and osteoblast activity, but their role in systemic bone loss after fracture remains poorly understood. In this study we used a transgenic (TG+) mouse model that overexpresses human B-cell lymphoma 2 (BCL-2) in osteoblasts and osteocytes. This causes enhanced osteoblast proliferation, followed by disruption in lacunar-canalicular connectivity and massive osteocyte death by 10 wk of age. We hypothesized that reduced viable osteocyte density would decrease the magnitude of systemic bone loss after femur fracture, reduce perilacunar remodeling, and alter callus formation. Bone remodeling was assessed using serum biomarkers of bone formation and resorption at 5 d post-fracture. We used micro-computed tomography, high resolution x-ray microscopy, mechanical testing, and Raman spectroscopy to quantify the magnitude of systemic bone loss, as well as changes in osteocyte lacunar volume, bone strength, and bone composition 2 wk post-fracture. Fracture was associated with a reduction in circulating markers of bone resorption in non-transgenic (TG-) animals. TG+ mice exhibited high bone mass in the limbs, greater cortical elastic modulus and reduced post-yield displacement. After fracture, TG+ mice lost less trabecular bone than TG- mice, but conversely TG+ mice exhibited trends toward a lower yield point and reduced femoral cortical thickness after fracture, though these were not statistically significant. Lacunar density was greater in TG+ mice, but fracture did not alter lacunar volume in TG+ or TG- mice. These findings suggest that osteocytes potentially play a significant role in the post-traumatic systemic response to fracture, though the effects differ between trabecular and cortical bone.

60 APPLIED LIFE SCIENCES↗