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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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577 records · Page 16

Hybrid Bio-Based Composites: Enabling Cellulose Nanofiber (CNF) Incorporation into Composites via Macroscale Natural Fiber Carriers

Cellulose nanofibers (CNFs) have significant potential in composites as additives to improve mechanical properties, melt rheology, and more. However, agglomeration of CNFs is a key challenge in composite melt processing as obtaining nano-level dispersion of CNFs often requires cost- and energy-intensive processes (e.g., solvent exchange or freeze drying) due to the strong hornification tendencies of CNF. Herein, we avoid these challenges by using a natural fiber carrier method to integrate CNF into thermoplastic composites. Fibers are co-dried to create a hybrid fiber feedstock for compounding in which natural fibers are decorated with dispersed nanofibers. The hybridized fibers result in up to a 24% increase in tensile strength and up to a 35% increase in Young’s modulus compared to composites only containing natural fibers. The lignocellulosic nanofibers are found to outperform their purely cellulosic counterpart, which is theorized to be due to either an increased propensity for fibrillation of the lignocellulosic fibers or the increased hydrophobicity of the fibers due to the presence of lignin. Surface analysis of fiber feedstocks, via streaming potential measurements and dynamic light scattering (DLS), confirmed a significant change in the feedstock hydrophobicity before and after hybridization. While mild additions of CNF (1 wt.% on the macroscale fiber) do not impact the composite melt viscosity, the viscosity is found to increase at higher CNF loadings (5 wt.% on the macroscale fiber), indicating its utility as a rheology modifier. Lastly, use of these materials as novel feedstocks for medium-scale additive manufacturing in high-fidelity part production was demonstrated.

bio-based

Development of the METMAN Thermal Desktop Human Model for System Integration

Human thermal analysis and model development inform NASA’s space suit development, vehicle/habitat design, and survivability studies. Historically, human thermal models such as the 41-node metabolic man (METMAN) and the Wissler model have been standalone software tools developed with FORTRAN, a programming language known for its high performance in computationally intensive applications. Though efficient, these standalone programs pose challenges to coupled human-system analysis with detailed life support and thermal control subsystem models in other commercial software. This paper describes the conversion of the METMAN human thermal model from a standalone FORTRAN program to a model in Thermal Desktop (Ansys), a commonly used CAD-based simulation software for engineering that specializes in heat transfer, thermal radiation, and fluid flow analysis. This format was chosen to best facilitate model sharing and compatibility, enabling the direct integration of METMAN human thermal analysis with subsystem models across NASA programs and commercial partners.

Elizabeth Thurston

Delamination recycling of multilayer plastic films: Solvent-assisted separation pathways and recovery of solid polyolefins

Multilayer plastic films are excellent packaging materials due to the bound layers of multiple polymers, with each different polymer contributing to the film properties. Desirable properties lead to continuously growing demand for multilayer films. Multilayer plastic films are typically single-use and, as such, their increased production and disposal have led to waste management problems. Multilayer films are not currently recyclable primarily due to the multiple bound polymers. This work advances delamination as a recycling process to separate and sequester valuable polymers from multilayer films, facilitating the incorporation of these polymers into the circular economy. We effect delamination in a physical process that preserves targeted polymers as solid film, hence retaining their embodied energy. This work documents three different pathways of inducing delamination of multilayer films, with appropriate solvents disrupting adhesion between adjacent layers or dissolving a minor component of the film in less than an hour and at temperatures below 90°C, and where all initial polyethylene is maintained in its solid form throughout the process and is recovered at high purity. Solvent-based delamination is exemplified on commercial multilayer films with majority polyethylene (PE), and polyethylene terephthalate (PET) or ethylene vinyl alcohol copolymer (EVOH) or nylon also present. Solvent-based delamination is an energy-efficient and environmentally friendly recycling process that improves upon dissolution-precipitation recycling, since delamination involves very little dissolution and no precipitation, and is superior to pyrolysis which breaks down the polymers, while delamination keeps polymer chains intact. Furthermore, delamination recycling can contribute to the sustainable use of multilayer films as they continue to protect our food and medicine.

Chemical Recycling

Toward an AI-Powered Software Pipeline for Real-Time Tracking and Analysis of Wildfire and Smoke

Real-time tracking of wildfires and smoke is crucial for effective response, minimizing damage, protecting lives, and efficiently managing resources during fire emergencies. We develop a web-based AI-powered pipeline that detects wildfires in aerial video and estimates deployment-relevant behavior metrics, including cumulative burned area, burned-area growth rate, fire spread direction, and smoke dispersion. The system combines a YOLO-based detector with YCbCr-based fire segmentation, HSV-based smoke segmentation, Farneback optical flow, and centroid-based spatiotemporal tracking. Using ground sampling distance (GSD), pixel-level fire masks are converted to physical burned-area measurements by correlating fire pixel counts with camera altitude and tilt angle. We benchmark YOLO variants and non-YOLO baselines (GoogLeNet, CNN, DBN, Autoencoder, U-Net, and AlexNet) on the IEEE FLAME dataset and a newly created aerial frame dataset, Wildfire-DB. Cross-dataset evaluation uses a strict threshold-transfer protocol: decision thresholds are selected on FLAME validation and transferred unchanged to Wildfire-DB to quantify generalization under domain shift. YOLOv6 achieves the strongest cross-dataset frame-level fire detection on Wildfire-DB (ROC-AUC 0.8200, PR-AUC 0.8044, and transferred-threshold F1 0.7596). For tracking-oriented deployment requiring oriented localization, YOLO11-OBB provides the most reliable cross-dataset behavior among OBB-capable models while remaining computationally feasible. To analyze the feasibility of UAV deployment, we further measure inference efficiency using synchronized GPU and CPU power logs on a fixed workload of 1569 frames. YOLO-family models process the video in 5.73–12.47 seconds with net energy of 1247.28–1775.39 J, substantially lower latency and energy than heavier classification and reconstruction baselines. Overall, model optimality depends on operational objectives: YOLOv6 is best for cross-dataset detection robustness, whereas YOL...

Color segmentation

Numerical Investigation of Fluid Flow and Space Charge in Liquid Argon Time Projection Chamber (LArTPC) Detectors

Overview This project focused on developing a high-fidelity numerical framework to simulate the multiphysics environment within Liquid Argon Time Projection Chamber (LArTPC) detectors. The primary objective was to characterize the complex interplay between ion transport, background fluid dynamics, and electric field distortions—a critical factor for the calibration and sensitivity of next-generation High Energy Physics experiments, such as DUNE. Technical Achievements The research successfully yielded a hybrid numerical space-charge solver utilizing a Cell-Centered Finite Volume Method (FVM) for ion transport coupled with a Finite Element Method (FEM) for electric potential. Key accomplishments include: • Verification & Validation: The 3-D solver was rigorously verified against 1-D analytical solutions, demonstrating high numerical accuracy in predicting space-charge-induced field deviations. • Field Distortion Analysis: 3D simulations revealed that space charge effects introduce significant non-uniformities in the electric field. Critically, the research identified that background LAr flow velocities, when comparable to ion drift velocities, markedly exacerbate these distortions. • Technology Transfer: The resulting source code and comprehensive user manuals were successfully transferred to collaborators at Fermilab, providing a portable computational tool for the broader scientific community. Challenges and Future Directions While the space-charge solver achieved all performance metrics, the integrated fluid dynamics modeling encountered convergence challenges stemming from the extreme 200-fold disparity in length scales between the detector's 37 mm inlet pipes and the 8-meter global domain. To address this, the project has identified a clear technical pivot toward Hierarchical Geometric Adaptive Mesh Refinement (HG-AMR). By implementing an h-type refinement strategy with hanging nodes, future iterations of this solver will be capable of resolving localized high-gradient inlet flows without the prohibitive computational costs of regular grids. This advancement, combined with data-driven uncertainty quantification based on MicroBooNE-style calibration, will enable the precise modeling of detector responses in large-scale cryogenic environments where direct measurement remains difficult. Impact The computational tools developed under this award provide a foundation for enhancing the energy resolution and spatial reconstruction of noble liquid detectors. By bridging the gap between theoretical fluid dynamics and experimental field calibration, this work supports the DOE’s mission to advance the frontiers of neutrino physics and dark matter detection.

42 ENGINEERING

Impact of Inertia, Friction, and Backlash upon Force Control in Telemanipulation

The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors.

Neil A Duffie

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS

Material Properties and Modeling of Room Temperature Vulcanizing Silicone

Room Temperature Vulcanizing silicone (RTV) is a high-temperature adhesive that has successfully been used as a gap-filler between Thermal Protection System (TPS) tiles for heatshields on numerous missions. It is also used to bond instrumentation plugs such as temperature and pressure sensors into the heatshields. While RTV has been traditionally assumed to be a non-porous and non-ablating material, numerous experiments have shown that RTV pyrolyzes and becomes highly porous as it is heated. Heating RTV has also shown swelling, or intumescence, which can pose unique problems that lead to roughness induced boundary-layer transition, surface oxide formation and contamination of heat shield sensors. Therefore, it is crucial to understand and model the intumescence phenomenon of RTV. As data for RTV material properties is limited, the first step in modeling RTV is to collect material properties such as pyrolysis mass-loss, microstructure change, virgin and char porosity, etc. which was performed in our initial study. Additionally, thermomechanical properties such as Young’s modulus and Poisson ratio are required for modeling the intumescence of RTV, which were taken from literature and the coefficient of thermal expansion was collected using in-situ heating and Micro Computed Tomography (µ-CT) in previous studies. Finally, numerous other properties such as pyrolysis gas properties, virgin and char thermal conductivity and specific heat were compiled from previous experiments and literature into a material database that can be used for simulations. In Porous Material Analysis Toolbox based on OpenFOAM (PATO) [4], structural mechanics coupled with material response was used for simulating the intumescence of RTV as it is heated. However, since the permeability of the material is very low, the pyrolysis gas creates an internal pressure build-up as the material is being heated, significantly contributing to the deformation of the material. To correctly characterize this phenomenon, additional physics models were implemented into PATO's stress analysis solver, and results were compared with RTV dilatometry test data as a preliminary verification case. Future work will include experiments of RTV at the Plasmatron X facility and the in-situ heating cell with µ-CT, and improvement of simulation tools to more accurately model RTV intumescence.

PATO

Heat exposure and maternal stress: evidence from the GRAPHS pregnancy cohort in Ghana

Heat exposure has been linked to psychosocial stress, an established antecedent of perinatal depression; however, evidence on heat-related stress during pregnancy in sub-Saharan Africa remains limited. We analyzed psychosocial stress scores and covariate data from the Ghana Randomized Air Pollution and Health Study, linking daily maximum and minimum shaded wet bulb globe temperature (WBGT) metrics to participants’ stress scores derived from the Crisis in Family Systems-Revised Life Events Questionnaire. We evaluated associations using ordinal logistic regression of pregnancy-average and trimester-average exposures and distributed lag non-linear models (DLNMs) to assess time-varying associations across gestation. Higher average maximum WBGT exposure across pregnancy was associated with increased odds of higher psychosocial stress; each 1 °C increase in maximum WBGT was associated with 64% higher odds of belonging to a higher stress category (OR = 1.64; 95% CI = 1.17–2.31; p = 0.0040). In trimester-average models, higher first-trimester maximum WBGT was also associated with higher stress (OR = 1.44; 95% CI = 1.15–1.81; p = 0.0014). DLNMs suggested that relatively cooler daily maximum WBGT values (25th percentile) were associated with decreased odds of stress in early pregnancy, whereas extreme daily maximum WBGT values (99th percentile) showed a pattern consistent with increased odds of stress in mid-to-late gestation. These findings highlight gestational windows in which heat exposure may influence stress, emphasizing the need for further research into underlying mechanisms and effective interventions to protect maternal mental health in heat-vulnerable settings.

White, Lewis [Columbia University] (ORCID:00090005

Geospatial modeling of near subsurface temperatures of the contiguous United States for assessment of materials degradation

Abstract Understanding subsurface temperature variations is crucial for assessing material degradation in underground structures. This study maps subsurface temperatures across the contiguous United States for depths from 50 to 3500 m, comparing linear interpolation, gradient boosting (LightGBM), neural networks, and a novel hybrid approach combining linear interpolation with LightGBM. Results reveal heterogeneous temperature patterns both horizontally and vertically. The hybrid model performed best achieving a root mean square error of 2.61 °C at shallow depths (50–350 m). Model performance generally decreased with depth, highlighting challenges in deep temperature prediction. State-level analyses emphasized the importance of considering local geological factors. This study provides valuable insights for designing efficient underground facilities and infrastructure, underscoring the need for depth-specific and region-specific modeling approaches in subsurface temperature assessment.

Science & Technology - Other Topics

Impact of Crystalline Phases on Low-Activity Waste Glass Durability: Insights from PCT and VHT

During vitrification of nuclear wastes, slow cooling along the container centerline promotes crystalline phase formation, which can alter residual glass composition and reduce chemical durability. This study investigates the effects of crystalline phases on the chemical durability of low-activity waste (LAW) borosilicate glasses using the product consistency test (PCT) and vapor hydration test (VHT) on container centerline cooled (CCC) samples. A preliminary model (R2 = 0.88) was developed to predict CCC PCT responses based on glass composition, PCT data from quenched glasses, and measured crystal fractions. Using the latest LAW glass dataset, the feasibility of predictive modeling is evaluated, limitations in current data and methods are identified, and challenges for improving model accuracy are discussed to guide future data collection and model development.

borosilicate glass

High entropy oxides prediction and discovery by the Mixed Enthalpy-Entropy Descriptor

The vast, high-dimensional composition space of high-entropy oxides (HEOs) offers exceptional opportunities for functional materials discovery, yet it also poses a fundamental challenge: the rational and efficient prediction of stable, synthesizable compositions and the corresponding structure–property relationships. Despite growing interest, the field still lacks broadly applicable, physically grounded descriptors capable of navigating various large chemical spaces. Here, we introduce a Mixed Enthalpy–Entropy Descriptor (MEED) that enables rapid, first-principles–based prediction of HEOs synthesizability across diverse chemistries. Using MEED, we perform high-throughput screening of two distinct HEO families: rocksalt oxides and perovskite oxides. The predicted top candidates in each family were experimentally validated. MEED reveals unifying thermodynamic and structural principles governing stability across both chemical compositions and polymorphs, providing mechanistic insight into the formation of high-entropy phases. This work significantly broadens the accessible chemical design space for HEOs and establishes a data-efficient framework for accelerating the discovery of next-generation functional materials.

Yu, Liping [University of Central Florida]

Resources for E-Mobility Program Implementation [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Successful Energy Project Implementation" will explore common challenges in implementing energy projects and learn strategies to turn project plans into reality. Each participant will focus on a local energy project or priority as a cornerstone for their learning throughout the series.This presentation overviews the basics of developing electric mobility projects with emphasis on leveraging the right tools to advance technical scoping and program design.

29 ENERGY PLANNING, POLICY, AND ECONOMY

Columbia Accident Investigation Board Report: Volume One

The Columbia Accident Investigation Board's independent investigation into the February 1, 2003, loss of the Space Shuttle Columbia and its seven-member crew lasted nearly seven months. A staff of more than 120, along with some 400 NASA engineers, supported the Board's 13 members. Investigators examined more than 30,000 documents, conducted more than 200 formal interviews, heard testimony from dozens of expert witnesses, and reviewed more than 3,000 inputs from the general public. In addition, more than 25,000 searchers combed vast stretches of the Western United States to retrieve the spacecraft's debris. In the process, Columbia's tragedy was compounded when two debris searchers with the U.S. Forest Service perished in a helicopter accident. This report discusses the attributes of an organization that could more safely and reliably operate the inherently risky Space Shuttle, but does not provide a detailed organizational prescription. Among those attributes are: a robust and independent program technical authority that has complete control over specifications and requirements, and waivers to them; an independent safety assurance organization with line authority over all levels of safety oversight; and an organizational culture that reflects the best characteristics of a learning organization. This report concludes with recommendations, some of which are specifically identified and prefaced as "before return to flight." These recommendations are largely related to the physical cause of the accident, and include preventing the loss of foam, improved imaging of the Space Shuttle stack from liftoff through separation of the External Tank, and on-orbit inspection and repair of the Thermal Protection System. The remaining recommendations, for the most part, stem from the Board's findings on organizational cause factors. While they are not "before return to flight" recommendations, they can be viewed as "continuing to fly" recommendations, as they capture the Board's thinking on what changes are necessary to operate the Shuttle and future spacecraft safely in the mid- to long-term.

CAIB

High Temperature - Thin Film Strain Gages Based on Alloys of Indium Tin Oxide

A stable, high temperature strain gage based on reactively sputtered indium tin oxide (ITO) was demonstrated at temperatures up to 1050 C. These strain sensors exhibited relatively large, negative gage factors at room temperature and their piezoresistive response was both linear and reproducible when strained up to 700 micro-in/in. When cycled between compression and tension, these sensors also showed very little hysteresis, indicating excellent mechanical stability. Thin film strain gages based on selected ITO alloys withstood more than 50,000 strain cycles of +/- 500 micro-in/in during 180 hours of testing in air at 1000 C, with minimal drift at temperature. Drift rates as low as 0.0009%/hr at 1000 C were observed for ITO films that were annealed in nitrogen at 700 C prior to strain testing. These results compare favorably with state of the art 10 micro-m thick PdCr films deposited by NASA, where drift rates of 0.047%/hr at 1050 C were observed. Nitrogen annealing not only produced the lowest drift rates to date, but also produce the largest dynamic gage factors (G = 23.5). These wide bandgap, semiconductor strain sensors also exhibited moderately low temperature coefficients of resistance (TCR) at temperatures up to 1100 C, when tested in a nitrogen ambient. A TCR of +230 ppm/C over the temperature range 200 C < T < 500 C and a TCR of -469 ppm/C over the temperature range 600 C < T < 1100 C was observed for the films tested in nitrogen. However, the resistivity behavior changed considerably when the same films were tested in oxygen ambients. A TCR of -1560 ppm/C was obtained over the temperature range of 200 C < T < 1100 C. When similar films were protected with an overcoat or when ITO films were prepared with higher oxygen contents in the plasma, two distinct TCR's were observed. At T < 800 C, a linear TCR of -210 ppm/C was observed and at T > 800 C, a linear TCR of -2170 DDm/C was observed. The combination of a moderately low TCR and a relatively large gage factor make these semiconducting oxide films promising candidates for the active strain elements in high temperature thin film strain gages, particularly in applications where static strain measurement is desired.

Otto J Gregory

The Electron‐Density Distribution of UCl 4 and Its Topology from X‐ray Diffraction

Abstract The chemistry of electrons in actinide complexes and materials is still poorly understood and represents a serious challenge and opportunity for experiment and theory. The study of the electron density distribution of the ground state of such systems through X‐ray diffraction represents a unique opportunity to quantitatively investigate different chemical bonding interactions at once, but was considered “almost impossible” on heavy‐atom systems, until very recently. Here, we present a combined experimental and theoretical investigation of the electron density distribution in UCl_ 4 crystals and comparison with the previously reported spin density distribution from polarized neutron diffraction. All approaches provide a consistent picture in terms of electron and spin density distribution, and chemical bond characterization. More importantly, the synergy between experiments and quantum‐mechanical calculations allows to highlight the remarkable sensitivity of X‐ray diffraction to electrons in materials.

Chemistry

High speed laser-induced refractive index change in ophthalmic HEMA hydrogel using a line focus

Laser-induced refractive index change (LIRIC) techniques typically focus femtosecond laser pulses to a tight spot to achieve the high intensities required to alter ophthalmic materials. A line-focus implementation using 800 nm pulses at 1 kHz repetition rate has been shown to greatly increase the effective writing speed of the process, but the high pulse energies used led to nonlinear propagation effects, presenting challenges for the fabrication of ophthalmic correctors. By taking advantage of the lower effective order of multiphoton absorption for 514 nm pulses, power levels may be reduced, allowing overlapped pulse writing. We demonstrate that this allows high-quality phase bars and devices to be made at high speeds.

Manning, Zachary A. [University of Rochester, NY (

PET waste- and bio-derived imine vitrimers for shape-memory, intrinsic flame-retardant, and recyclable carbon fiber composites

Developing circular multifunctional vitrimers and carbon fiber–reinforced polymers (CFRPs) that are simultaneously recyclable, mechanically robust, and intrinsically flame retardant remains a major challenge. Here, in this study, we report multifunctional vitrimers and their carbon fiber–reinforced vitrimer (CFRV) composites, where the vitrimer design integrates closed-loop recyclability, enhanced interfacial adhesion, and intrinsic flame retardancy within a single materials platform. The vitrimer matrix is synthesized from post-consumer polyethylene terephthalate (PET) waste and a vanillin-derived phosphorus-containing crosslinker, forming an imine-based network. The resulting vitrimer resin exhibits high tensile strength, thermal healability, repeated reprocessability, programmable shape memory, and rapid chemical depolymerization under mild conditions. Amine-functionalized carbon fibers significantly improve fiber–matrix interfacial bonding, yielding CFRVs with tensile strengths up to 789 MPa and complete recovery of structurally intact fibers after chemical recycling. The phosphorus-rich aromatic network further imparts intrinsic flame retardancy, enabling self-extinguishing behavior without external additives. This work advances a materials design paradigm for next-generation multifunctional, sustainable vitrimers and CFRVs, while simultaneously addressing the recycling challenges associated with both plastic and CFRP waste.

Bio-derived crosslinker