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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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968 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Enhanced Optical Contrast and Switching in Near‐Infrared Electrochromic Devices by Optimizing Conjugated Polymer Oligo(Ethylene Glycol) Sidechain Content and Gel Electrolyte Composition

Abstract A detailed investigation addressing the effects of functionalizing conjugated polymers with oligo(ethylene glycol) (EG n ) sidechains on the performance and polymer‐electrolyte compatibility of electrochromic devices (ECDs) is reported. The electrochemistry for a series of donor‐acceptor copolymers having near‐infrared (NIR)‐optical absorption, where the donor fragment is 3,4‐ethylenedioxythiophene (EDOT) or an EG n functionalized bithiophene (g2T) and the acceptor fragment is diketopyrrolopyrrole (DPP) functionalized with branched alkyl or EG n sidechains, is extensively probed. ECDs are next fabricated and it is found that EG n sidechain incorporation must be finely balanced to promote polymer‐electrolyte compatibility and provide efficient ion exchange. Proper electrolyte‐cation pairing and polymer structural tuning affords a 2x increase in optical contrast (from 12% to 24%) and >60x reduction in switching time (from 20 to 0.3 s). Atomic force microscopy (AFM)/grazing incidence wide‐angle X‐ray scattering (GIWAXS) characterization of the polymer film morphology/microstructure reveals that an over‐abundance of EG n sidechains generates large polymer crystallites, which can suppress ion exchange. Lastly, time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) indicates sidechain/electrolyte identity does not influence the electrolyte penetration depth into the films, and EG n sidechain inclusion increases electrolyte cation uptake. The material structural design insight and guidelines regarding the polymer‐electrolyte ion insertion/expulsion dynamics reported here should be of significant utility for developing next‐generation mixed ionic‐electronic conducting materials.

Chemistry↗
NASA NTRS1992

Fifth Annual Workshop on Space Operations Applications and Research (Soar 1991), Volume 1

More than 110 papers were presented at this Symposium, sponsored by the U.S. Air Force Phillips Laboratory, the University of Houston-Clear Lake, and NASA JSC. The technical areas covered were Intelligent Systems, Automation and Robotics, Human Factors and Life Sciences, and Environmental Interactions. The U.S. Air Force and NASA programmatic overviews and panel discussions were also held in each technical area. These proceedings, along with the comments and suggestions made by the panelists and keynote speakers, will be used in assessing the progress made in joint USAF/NASA projects and activities. Furthermore, future collaborative/joint programs will also be identified. The symposium proceedings includes papers covering various disciplines presented by experts from NASA, the Air Force, universities, and industry.

Mars missions↗
DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗
NASA NTRS2026

A Study of Space Environment Effect on Highly Thermally Conductive Hybrid Carbon Fiber Polymer Composites

A set of novel highly thermally conductive hybrid carbon fiber (CF) polymer composites has been developed for lightweight thermal radiator applications in space missions. This study investigates the effects of the space environment on these materials following exposure in low-Earth orbit (LEO) during the Materials International Space Station Experiment (MISSE)-17 flight mission, where samples experienced 159 days of combined atomic oxygen (AO), ultraviolet (UV) radiation, high vacuum, space radiation and thermal cycling. Post-flight characterization included weight loss, surface morphology, thermo-optical properties, molecular structures, glass transition temperature, thermal degradation and thermal conductivity analyses. The pyrolytic graphite sheet (PGS) samples exhibited negligible weight loss, stable thermo-optical property, and only minor oxidation signature on the exposed surface. Although AO erosion of the epoxy polymer matrix was evident, carbon nanotube (CNT)-infused PGS/CF epoxy composites retained high thermal emissivity and preserved their high thermal conductivities. These results demonstrate that the novel highly thermally conductive hybrid CF composites possess strong environmental resilience and are promising candidates for lightweight thermal radiators and thermal management components in future space exploration missions.

Space Environment↗
NASA NTRSDate not supplied

Assembly and Integration Status of a High Fidelity Ground Test Bed for the Water Processor Assembly

The Water Recovery System (WRS) is a critical component of life support aboard the International Space Station (ISS) and will play an essential role in future missions beyond Low Earth Orbit (LEO). Its primary functional units – the Urine Processor Assembly (UPA), Brine Processor Assembly (BPA), and Water Processor Assembly (WPA) – must be evaluated for extended operation, dormancy resilience, material obsolescence, and reliability under exploration-driven constraints. Ground testing is vital for developing these technologies and generating statistically relevant reliability assessments, which requires extended runtime under integrated, Flight-like conditions. Currently, no high-fidelity, fully integrated WPA ground test bed exists to support these objectives. To address this gap, NASA is developing a WPA test bed at Marshall Space Flight Center (MSFC) that combines downgraded ISS flight hardware with functionally flight-like components in a cost-effective configuration while maintaining priority hardware investigations. This paper describes the current status of hardware assembly and integration, outlines key challenges such as simulating microgravity effects and mitigating obsolescence, and presents future test objectives including software development, reliability assessments, dormancy studies, and exploration-oriented upgrades.

Water Processor Assembly↗
DOE OSTI2024

Tailoring Ion Transport in Li 3‐3y Ho 1+y Cl 6‐x Br x via Transition‐Metal Free Structural Planes and Charge Carrier Distribution

Abstract Localized atomistic disorder in halide‐based solid electrolytes (SEs) can be leveraged to boost Li + mobility. In this study, Li + transport in structurally modified Li 3 HoCl 6 , via Br − introduction and Li + deficiency, is explored. The optimized Li 3‐3 y Ho 1+ y Cl 6‐ x Br x achieves an ionic conductivity of 3.8 mS cm −1 at 25 °C, the highest reported for holmium halide materials. 6,7 Li nuclear magnetic resonance and relaxometry investigations unveil enhanced ion dynamics with bromination, attaining a Li + motional rate neighboring 116 MHz. X‐ray diffraction analyses reveal mixed‐anion‐induced phase transitions with disproportionate octahedral expansions and distortions, creating Ho‐free planes with favorable energetics for Li + migration. Bond valence site energy analysis highlights preferred Li + transport pathways, particularly in structural planes devoid of Ho 3+ blocking effects. Molecular dynamics simulations corroborate enhanced Li + diffusion with Br − introduction into Li 3 HoCl 6 . Li‐Ho electrostatic repulsions in the (001) plane presumably drive Li + diffusion into the Ho‐free (002) layer, enabling rapid intraplanar Li + motion and exchange between the 2d and 4h sites. Li 3‐3 y Ho 1+ y Cl 6‐ x Br x also demonstrates good battery cycling stability. These findings offer valuable insights into the intricate correlations between structure and ion transport and will help guide the design of high‐performance fast ion conductors for all‐solid‐state batteries.

Chemistry↗
DOE OSTI2026

Dynamics of Radiation Damage Buildup in Ultrathin Hexagonal Boron Nitride Films under Ion Bombardment

Two-dimensional hexagonal boron nitride (hBN) is attractive for several emerging applications. Ion bombardment can be used to modify the hBN properties. However, the understanding of radiation damage buildup in hBN remains limited. Here, we investigate the effects of the dose rate and ion mass on radiation damage buildup by studying 40 nm-thick hBN films bombarded at room temperature with 500 keV 4 He, 15 N, 40 Ar, and 129 Xe ions and comparing with results for ion bombardment of polycrystalline hBN ceramics. Raman spectroscopy is used to quantify damage buildup, and transmission electron microscopy is used for microstructural analysis. Experiments are complemented by molecular dynamics simulations of the formation and evolution of point defects. Lighter ions are found to be more efficient at disordering hBN than heavier ions. This observation points to a critical role of intracascade defect processes. In contrast, a negligible dose rate effect observed suggests limited intercascade defect dynamic annealing processes for these irradiation conditions. These findings provide a fundamental basis for hBN defect engineering.

2D materials↗
DOE OSTI2025

pi-Extended Porphyrins: The Impact of Aromatic Heterocycles on the Properties of the Largely pi-Extended Structures (Final Report_UNT_SC0016766)

Largely π-extended carbon-rich materials represent fascinating yet challenging frontiers in chemistry and materials science as it offers numerous opportunities in molecular electronics. pi-Extended porphyrins possess unique set of electronic and photophysical properties and are very attractive for a wide range of applications. However, the synthesis and functionalization of pi-extended porphyrins had been very challenging. To explore and expand this intriguing research field, it is essential to develop synthetic tools to make them accessible. Funded by the Department of Energy Basic Energy Science, my laboratory addressed these synthetic challenges by developing concise and versatile methods for pi-extended porphyrins. Significant progress has been made in multiple directions, including fusing Polycyclic Aromatic Hydrocarbons (PAH), aromatic heterocycles, antiaromatic component, and cross-conjugated component to porphyrins as well as push-pull porphyrins. The availability of these methods has made it possible to rationally design and synthesize functionalized pi-extended porphyrins. Unprecedented electronic and photophysical properties have been discovered for these pi-extended porphyrins.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Microstructure prediction for Ti-22Al-25Nb in laser powder bed fusion

This work presents a physics-informed framework for predicting solidification morphology and defect susceptibility in additively manufactured Ti–22Al–25Nb across a broad processing space. The framework integrates solidification microstructure selection (SMS) analysis with a single-track defect-based printability map to establish a unified methodology linking processing parameters to both interfacial morphology and manufacturability. Thermal gradients G and solidification rates R are first computed using the Thermo-Calc Additive Manufacturing (TC-AM) module, a finite-interface-dissipation (FID) phase-field (PF) model coupled with CALPHAD method is then employed to systematically distinguish planar and dendritic regimes as functions of $G$ and $R$. By superimposing the printability map onto the morphology projections, a comprehensive process–structure framework is obtained. Across most processing conditions, the predicted microstructure is predominantly dendritic, while planar growth emerges only under selected laser power $P$ and scan speed $v$ combinations. In addition to morphology classification, the framework quantifies the dendritic area fraction and introduces a width-based morphology descriptor to characterize the spatial extent of planar/dendritic regions within the melt pool. It provides mechanistic insight into the interplay between solidification physics and defect formation, offering practical guidance for parameter selection and microstructural control in Ti–22Al–25Nb additive manufacturing (AM).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Fracture‐Resistant and Thermally Insulating Ultrahigh‐Temperature Carbide Foams

Dense ultrahigh‐temperature ceramics (UHTCs) carbides are recognized as potential materials for thermal protection systems (TPS) owing to properties beyond existing structural materials’ capabilities. Recent advances in UHTCs have enabled the development of multiscale porous microstructures. Herein, it is highlighted that the porosity in UHTCs are no longer treated as a defect but as a functional property specifically tailored for thermal insulation. It is a promising solution to design and fabricate bulk UHTC foams via a freeze‐drying (FD) approach followed by calibrated pressureless spark plasma sintering. Herein, monolithic TaC and HfC UHTC foams and their composite show the partial solid–solution formation of (Ta, Hf)C with porosity ≥50%. TaC–HfC foam (≈80–92 N) shows an intermediate load‐bearing capability compared to monolithic TaC (≈120–135 N) and HfC (≈28–35 N) foams, with no evident cracking on the sample surface. The thermal conductivity of partial solid‐solution TaC–HfC foam increases up to fivefold compared to parent UHTC foams. In the results, solid solutions’ efficacy and pores’ unidirectionality in providing thermal insulation to TaC–HfC while maintaining its high‐load bearing capability are illustrated. In conclusion, the developed technique establishes a new paradigm shift in UHTCs, expanding their potential for TPS in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sustainable Production of Biomass‐Derived Graphite and Graphene Conductive Inks from Biochar

Abstract Graphite is a commonly used raw material across many industries and the demand for high‐quality graphite has been increasing in recent years, especially as a primary component for lithium‐ion batteries. However, graphite production is currently limited by production shortages, uneven geographical distribution, and significant environmental impacts incurred from conventional processing. Here, an efficient method of synthesizing biomass‐derived graphite from biochar is presented as a sustainable alternative to natural and synthetic graphite. The resulting bio‐graphite equals or exceeds quantitative quality metrics of spheroidized natural graphite, achieving a RamanI D /I G ratio of 0.051 and crystallite size parallel to the graphene layers (L a ) of 2.08 µm. This bio‐graphite is directly applied as a raw input to liquid‐phase exfoliation of graphene for the scalable production of conductive inks. The spin‐coated films from the bio‐graphene ink exhibit the highest conductivity among all biomass‐derived graphene or carbon materials, reaching 3.58 ± 0.16 × 10 4 S m −1 . Life cycle assessment demonstrates that this bio‐graphite requires less fossil fuel and produces reduced greenhouse gas emissions compared to incumbent methods for natural, synthesized, and other bio‐derived graphitic materials. This work thus offers a sustainable, locally adaptable solution for producing state‐of‐the‐art graphite that is suitable for bio‐graphene and other high‐value products.

Chemistry↗
DOE OSTI2023

Polymer grafted aramid nanofiber reinforces immiscible waste polypropylene/poly(ethylene terephthalate)

Polypropylene (PP) and poly(ethylene terephthalate) (PET) are plastics commonly used for packaging because of their excellent barrier and mechanical properties. The properties of these plastics are often diminished after mechanical recycling, inevitably causing down-cycling. Furthermore, this problem is exacerbated when different kinds of polymers mix. Aramid nanofibers have the potential to improve the mechanical properties of polymers due to their excellent mechanical properties but their poor dispersion in polymers is a challenge. Grafting polymers onto nanofibers can help address this challenge. In this work, different loading levels (1%, 2%, and 5%) of polymer grafted aramid nanofibers (ANFs) are blended with waste PP/PET (90/10), simulating a PP waste stream containing traces of PET contaminants. Scanning electronic microscopy, rheology, and differential scanning calorimetry results show the affinity of PP functionalized aramid nanofibers (PP_ANF) towards the PP matrix. At 1 wt% of the nanofiber, the size of the PET droplets in the PP matrix of the PP_ANF blend range from 0.2 to 2.0 μm while that of unmodified ANF and PET_ANF blends are in the range of 0.1–6.2 and 0.5–7.4 μm, respectively. In summary, polymer grafted ANFs have the tendency of improving properties of its like polymers due to similarity in the grafting polymer and the polymer matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Surface science insight note: A linear algebraic approach to elucidate native films on Fe 3 O 4 surface

Standard materials are often used to obtain spectra that can be compared to those from unknown samples. Spectra measured from these known substances are also used as a means of computing sensitivity factors to allow quantification by X-ray photoelectron spectroscopy (XPS) of less well-defined materials. Spectra from known materials also provide line shapes suitable for inclusion in spectral models which, when fitted to spectra, permit the chemical state for a sample to be assessed. Both types of information depend on isolating photoemission signals from the inelastically scattered signal. In this Insight note, technical issues associated with the use of XPS of as received Fe 3 O 4 powder sample surface are discussed. The Insight note is designed to show how linear algebraic techniques applied to data collected from a sample marketed as pure Fe 3 O 4 powder are used to verify that XPS has been performed on chemistry representative of the sample. The methods described in this Insight note can further be utilized in elucidating complex XPS data obtained from thin films formed or evolved during cyclic/non-steady use of complex (electro)catalyst surfaces, especially in the presence of contaminants.

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

The effect of gamma ray irradiation on few layered MoSe2: A material for nuclear and space applications

In recent years, emerging two-dimensional (2D) materials, such as molybdenum diselenide (MoSe2), have been at the center of attention for many researchers. This is due to their unique and fascinating physicochemical properties that make them attractive in space and defense applications that include shielding harsh irradiation environments. In this study, we examined the effects of gamma (γ) rays at various doses on the structural, chemical, and optical properties of MoSe2 layers. After the samples were exposed to intense gamma radiation (from a 60Co source) with various exposure times to vary the total accumulated dosage (up to 100 kGy), Raman and photoluminescence spectroscopies were used to study and probe radiation-induced changes to the samples. When compared to pristine materials, very few changes in optical properties were typically observed, indicating good robustness with little sensitivity, even at relatively high doses of gamma radiation. The imaging using scanning electron microscopy revealed a number of nano-hillocks that were connected to substrate alterations. X-ray photoelectron spectroscopies revealed that Mo’s binding energies remained the same, but Se’s binding energies blueshifted. We associated this shift with the decrease in Se vacancies that occurred after irradiation as a result of Mo atoms creating adatoms next to Se atoms. When compared to pristine materials, very few changes in optical, chemical, and structural properties were typically observed. These findings highlight the inherent resilience of MoSe2 in hostile radioactive conditions, which spurs additional research into their optical, electrical, and structural characteristics as well as exploration for potential space, energy, and defense applications.

Materials Science↗
DOE OSTI2024

Circumventing data imbalance in magnetic ground state data for magnetic moment predictions

Abstract Magnetic materials play a crucial role in the transition to more sustainable forms of energy and electric vehicles. There is an anticipated shortage in magnetic materials in the future, and as a result there is an urgent need to discover and design new magnetic materials. Computational magnetic material design using density functional theory is daunting because of the challenge in identifying magnetic ground states from a combinatorially large set of possibilities. Machine learning offers a path forward by enabling efficient surrogate models that can more readily enumerate these states, but there is a dearth of training data available, and what is available tends to be imbalanced with too much non-magnetic data. In this work we show that the discrete and previously tackled data imbalance that exists at the level of the magnetic ordering leads to an imbalanced continuous distribution with many zeros when the data is unraveled at the atomic magnetic moment level, which subsequently leads to models with low accuracy for magnetic properties. We mitigate this by using a two-part model framework. Our scheme is able to classify atoms into magnetic and non-magnetic with an F1 score and Matthew’s correlation coefficient (MCC) of ~91% and then to provide an implicit embedding representation that maps directly onto the magnitude of the magnetic moment with a mean absolute error of 0.1 μ B . Beyond screening for new magnetic materials, we demonstrate an additional practical use case of our scheme: the provision of good initial guesses for magnetic moments in first-principles electronic relaxations. Such initialization is shown to lead to faster convergence to configurations that lie closer to the ground state.

Computer Science↗
DOE OSTI2026

Overview of IMPACT Data Acquisition System and Data Reduction Process

This report documents the development of the data acquisition system (DAS) and data reduction methodologies for the Irradiated Material Property Accelerated Characterization Test (IMPACT) experiment at the Advanced Test Reactor (ATR). The IMPACT experiment is designed to enable in-pile measurement of thermal conductivity in metallic nuclear fuels, specifically U-10Zr, using an instrumented thermal conductivity probe. The DAS supports both passive temperature monitoring and active thermal interrogation of the probe through controlled AC and DC excitation. Significant modifications to laboratory-scale systems were required to accommodate the higher resistance paths associated with the in-pile application. Custom electronics and relay-controlled measurement sequencing were developed to enable the measurement and sufficient power delivery to the sensing region. A reduced-order, axisymmetric thermal model based on the thermal quadrupoles method is presented to support data interpretation. This model enables efficient evaluation of transient heat transfer behavior and facilitates solution of the inverse problem required to extract thermal properties from measured signals. Multiple boundary condition formulations are discussed to address varying experimental time scales and geometries. Additionally, machine learning techniques are introduced to support data reduction and improve confidence in inverse solutions. Convolutional neural networks are applied to identify the presence of gas gaps and other evolving geometric features that significantly impact thermal response during irradiation. These efforts contribute to the broader integration of digital twin frameworks and real-time modeling capabilities within the Advanced Fuels Campaign.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗