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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Evaluation of high-temperature properties of binary, eutectic Ni-X alloys (X = B, Ca, Ce, La, Y, Zr)

We investigated the high-temperature behavior of binary eutectic nickel-base alloys with low-solubility elements, towards developing alloys with new combinations of structural and functional (e.g. thermal or corrosion) properties. Based on thermodynamic screening, we cast binary near-eutectic Ni-B, Ni-Ca, Ni-Ce, Ni-La, Ni-Y, and Ni-Zr alloys and characterized their microstructure and high-temperature properties. All alloys (except Ni-Ca) contain a fine eutectic microstructure, containing submicron alternating lamellae of γ-Ni and continuous intermetallic phases. The eutectic microstructure did not significantly coarsen at 700°C (except for Ni-B), but measurably coarsened in all alloys at 900°C, most quickly in Ni-B, followed by Ni-Ce, Ni-La, Ni-Y, and Ni-Zr. Coarsening in these alloys occurs by fault migration; diffusion within the intermetallic, and its interfacial energy, likely influence coarsening kinetics. At room-temperature, all alloys possess negligible ductility due to the continuous, brittle intermetallic. At 700 and 900°C, the Ni-Zr alloy showed the best combination of strength and ductility. Oxidation experiments at 900°C on Ni-Zr and Ni-Ce revealed heavy internal oxidation of the continuous intermetallic phase. Overall, the Ni-Zr alloy showed good high-temperature coarsening resistance and strength, though ductility and oxidation resistance require improvement for use in structural applications. Possible routes for improving alloy properties via additive manufacturing are discussed.

Ekaputra, Clement [ORNL] (ORCID:0000000307166479)↗
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 OSTI2026

Unraveling interphase-driven failure pathways in LiMn0.6Fe0.4PO4/graphite pouch cells

LiMnxFe1−xPO4 (LMFP) is a promising high-voltage, thermally stable, and earth-abundant cathode material, yet its practical application is limited by interphase instability and Mn dissolution. In this work, we systematically evaluate LiMn0.6Fe0.4PO4/graphite pouch cells using three electrolyte formulations including control carbonate electrolyte, control + 2 wt% vinylene carbonate (VC), and control + 2 wt% VC + 1 wt% 1,3,2-dioxathiolane 2,2-dioxide (DTD), to establish how electrolyte composition governs interphase chemistry and long-term degradation. Electrochemical testing shows that both additives are preferentially reduced prior to ethylene carbonate (EC) during cell formation, generating robust cathode-electrolyte interphase (CEI) and solid-electrolyte interphase (SEI) layers that suppress gas evolution and raise the first-cycle coulombic efficiency to 89.3%. Additionally, the dual-additive electrolyte delivers the most stable performance, retaining over 85% capacity after 600 cycles while minimizing impedance growth under long-term cycling at C/3 and 40 °C. Soft X-ray absorption spectroscopy confirms that VC + DTD effectively suppresses electrolyte oxidation at the cathode surface, and micro-X-ray fluorescence shows substantially reduced Mn dissolution and deposition on the graphite anode. Density functional theory simulations further provided insights into the structural and energetic influences of alkoxide species on the cathode surface, proposing a Mn2+ extraction mechanism. The combined experimental and computational findings establish a mechanistic link between electrolyte composition and interphase evolution, highlighting the effectiveness of electrolyte engineering for extending the operational lifetime of LMFP-based lithium-ion batteries.

Chak, Chanmonirath Michael↗
DOE OSTI2025

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗
DOE OSTI2026

Massive neutrinos and interacting dark matter look alike through the lens of lensing

Here, we demonstrate that the suppression in the lensing power spectrum of the cosmic microwave background (CMB) caused by massive neutrinos can be mimicked by dark matter-baryon interactions at the precision of next-generation CMB experiments. Thus, a determination of neutrino masses from the CMB lensing power spectrum may be compromised. We illustrate the degeneracy for a dark matter-proton cross section ∝ $v$ –4 , which arises in the t-channel exchange of an ultralight mediator in the nonrelativistic limit.

cosmological parameters↗
DOE OSTI2022

Quantum Circuits for the Preparation of Spin Eigenfunctions on Quantum Computers

The application of quantum algorithms to the study of many-particle quantum systems requires the ability to prepare wave functions that are relevant in the behavior of the system under study. Hamiltonian symmetries are important instruments used to classify relevant many-particle wave functions and to improve the efficiency of numerical simulations. In this work, quantum circuits for the exact and approximate preparation of total spin eigenfunctions on quantum computers are presented. Two different strategies are discussed and compared: exact recursive construction of total spin eigenfunctions based on the addition theorem of angular momentum, and heuristic approximation of total spin eigenfunctions based on the variational optimization of a suitable cost function. The construction of these quantum circuits is illustrated in detail, and the preparation of total spin eigenfunctions is demonstrated on IBM quantum devices, focusing on three- and five-spin systems on graphs with triangle connectivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Self-Leveling Inks for Printing Ultra-uniform Perovskite Solar Modules by Flexography

The report describes the development of scalable manufacturing methods for high-performance, stable perovskite solar modules using flexographic printing. The project developed self-leveling perovskite inks that exploit Marangoni flows to reduce coating defects and improve large-area film uniformity. Bayesian optimization was integrated with high-throughput photoluminescence mapping and photovoltaic measurements to efficiently optimize ink formulations and printing conditions. The resulting printed perovskite solar cells achieved champion power conversion efficiencies above 21.6%, with median efficiencies exceeding 20% across large device batches. At the module scale, printed devices achieved active-area efficiencies up to approximately 17.3% on 25 cm² substrates. The project also demonstrated improved performance and stability using additively patterned interconnections compared with laser-scribed controls. Overall, the work establishes a data-driven, roll-compatible pathway toward high-throughput, low-capital-cost manufacturing of uniform and stable perovskite photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2026

Programmable Digital Devices used in Advanced Reactors

This paper introduces the concepts of common cause failure, diversity, and defense-in-depth used by the nuclear industry to analyze resilience in reactors. A survey of publicly traded and private companies building advanced reactors and their licensing status is presented. Safety and non-safety systems found in the NuScale Power design are summarized and the likely hardware and software categories used by those systems are enumerated. The importance of industry partners is highlighted. This paper also identifies an alternate path forward without industry partners to advance the knowledge needed to use artificial intelligence to analyze HBOMs and SBOMs to better understand reactor resiliency.

cybersecurity↗
DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗
DOE OSTI2026

Electrochemical Deconstruction of Ortho-Phthalate Plasticizers and Recovery of Plasticizing Moieties

Electrochemical methods for the direct reduction of alkyl esters have been understudied but provide a potential advantage for addressing specific waste streams given that such strategies often require only a minimal chemical profile. One such waste stream that could benefit from electrochemical remediation is poly(vinyl chloride) (PVC) plastics. PVC recycling often faces challenges due to the complexity of such waste. Solvent-based recycling methods pose several advantages for addressing post-use PVC; however, such methods are complicated by the high amounts of toxic legacy plasticizers (ortho-phthalates) present in PVC. A potential solution to addressing such phthalates is to address them electrochemically, coupled with recovery of the resulting valuable products. Presented herein is an optimized electrochemical method for ester activation that is leveraged to separate and recover the aromatic and alkyl components of ortho-phthalate plasticizers. The resulting aliphatic alcohols may be reused to prepare other non-toxic plasticizers. This electro-degradation method is demonstrated on six phthalates that have been identified to pose health concerns in addition to plasticizers recovered from commercial samples of PVC.

di-(2-ethylhexyl) phthalate↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2026

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan↗
DOE OSTI2026

Ecohydrology of urban environments

Urban watersheds include a gradient of highly managed to unmanaged ecosystems that vary in vegetation cover, built and natural drainage systems, and impervious cover. A distinct difference to undeveloped ecosystems is the dominance of material and energy import and export, the disruption of natural catenae, the covariation of soils, terrain and canopy conditions. In this chapter, we discuss the distinct characteristics of urban ecohydrology compared to non-urban systems. We also investigate emergent principles of unmanaged watersheds that underscore the promotion of ecohydrological resilience, and the need to abstract and adapt these principles to support the goal-oriented restoration of impaired urban ecosystems.

42 ENGINEERING↗
DOE OSTI2024

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

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

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗
DOE OSTI1978

An Assessment of the Nevada Test Site for Low-Level Waste Management

This report presents a summary of description information, facilities, and operating practices at the Nevada Test Site. It is concluded that NTS is not only a feasible location for surface and near-surface storage of low-level wastes, but also a potential site for underground storage of higher level wastes.

052002* -- Nuclear Fuels-- Waste Disposal & Storag↗
DOE OSTI2024

Massive red spiral galaxies in SDSS-IV MaNGA survey

ABSTRACT Massive red spiral galaxies (MRSGs) are supposed to be the possible progenitors of lenticular galaxies (S0s). We select a large sample of MRSGs ($M_*\gt 10^{10.5}\rm {\rm M}_{\odot }$) from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) DR17 using the g − r colour versus stellar mass diagram, along with control samples of blue spirals and S0s. Our main results are as follows: (1) After comparing the Sérsic index, concentration parameter, asymmetry parameter distribution, size–mass relation, and Σ1 (stellar mass surface density within the central 1 kpc)−mass relation, we find MRSGs are similar to S0s and have more compact and symmetric structures than blue spirals. MRSGs also resemble S0s in Dn4000, metallicity, Mgb/$\rm \left\langle Fe \right\rangle$, and V/σ radial profile. (2) By using MaNGA 2D spectra data, we separate the spatial regions into inner (R < 0.8Re) and outer (0.8 < R < 1.5Re) regions, and detect residual star formation in the outer regions of MRSGs. (3) When we select a sub-sample of MRSGs with NUV − r > 5, we find that they are completely star formation quenched in both inner and outer regions. Compared to optically selected MRSGs, NUV − r selected MRSGs appear to be more concentrated and have more massive dark matter haloes. The similarities between S0s and MRSGs suggest the possible evolutionary trend between MRSGs and S0s.

Astronomy & Astrophysics↗
DOE OSTI1991

Physical and Operational Status of the Photovoltaic Systems in the Municipality of Pinotepa de Don Luis, Oaxaca, One Year after Their Installation [Estado fisico y operativo de los sistemas fotovoltaicos en el municipio de Pinotepa de Don Luis, Oaxaca un ano despues de su instalacion]

In November 1990, an inspection visit was made to the residential lighting photovoltaic systems that had been installed approximately one year before in the rural communities of the Municipality of Pinotepa de Don Luis, in the State of Oaxaca. The main purpose of the visit was to evaluate the physical and operational status of these systems. The systems typically consist of a photovoltaic module with a capacity of 30 or 35 Watts, an automotive type battery, an indicator of the status of charge of the battery, 3 fluorescent lamps and the corresponding installation, including cables, connection or outlet box and switches. It can be seen that the systems are in good physical condition and do not show any signs of intentionally caused damage. However, the incidence of failures is higher than what had been expected; therefore the operational status of these systems is considered to be below a level that could be accepted, with a tendency to getting worse. The main problem that has been detected is the lack of automatic charge controllers. This problem has caused other important failures. Serious deficiencies were appreciated in the installations, which show evidence of the poor workmanship of the installers. The lack of system standardization is evident, both regarding the components and the installation. As a consequence, there are technical factors which indicate that the installed systems will keep deteriorating at a rate faster than normal, and will stop operating in a short time unless urgent preventive and corrective measures are taken. The attitude of the users with respect to the systems is generally positive. However, there are elements that make the correct operation and maintenance of these systems a very difficult task. The users did not receive any training regarding the best way to operate and take care of their systems, nor any other information in relation to their technical limitations.

14 SOLAR ENERGY↗