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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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DOE OSTI2026

Hydrogen Detection via a Low-Cost Prototype Fiber-Optic Sensing System

The developed low-cost prototype sensing system successfully detects hydrogen concentrations across a wide range, demonstrating immediate feasibility for commercial deployment. Utilizing fiber-optic technology, the system delivers stable, reproducible performance from parts-per-million levels up to 100% pure H2 environments. Environmental and chemical cross-sensitivity evaluations confirm robust selectivity against methane and temperature changes, establishing its readiness for near-term commercialization.

fiber-optic H2 sensor↗

DOE OSTI2026

Physics-aware adaptive checkpointing with shadow systems for nonlinear PDE simulations

Large-scale simulations of nonlinear partial differential equations (PDEs) that exhibit strongly transient behavior and pattern-forming dynamics produce enormous amounts of data, which, even with modern storage systems, cannot be stored for later curation. Current I/O strategies either write dense time series of snapshots, which is often prohibitive in I/O and storage, or store a few checkpoints that enable restart but incur expensive recomputation cost and provide no control over post-restart error growth, especially when lossy compression is used. Moreover, most, if not all, existing strategies take no account of the actual physical state of the system. Here, we present a simple physics-aware I/O framework in which a low-cost shadow system adaptively triggers lossy checkpoints when the shadow system deviates from the fine-scale simulation. The shadow system can be a coarsened replica of the fine-scale simulation that evolves concurrently. This means that checkpoints are taken based on the physical state of the system: fewer checkpoints are triggered when the system is quiescent while more are taken when the system undergoes a rapid change. This type of behavior is observed in many systems such as Brusselator and FitzHugh–Nagumo. We illustrate that our framework maintains stable restarts, keeps fine-scale restart errors bounded by shadow errors, and reconstructs the time history with significantly lower error and storage than interpolating fixed-interval snapshots, with low-cost shadow replay and modest online synchronization overhead.

Gong, Qian [ORNL] (ORCID:0000000235704142)↗

NASA NTRSDate not supplied

Extending mARC II Arc-Jet Test Duration via Design and Implementation of Model System Cooling Sleeve

The mARC II is a 30 kW arc-jet facility at NASA Ames Research Center used to generate high-enthalpy flows for low-cost thermal protection system (TPS) technology development. Sustained operation of downstream instrumentation and material samples is constrained by thermal loading transmitted through the arc-jet test environment, limiting achievable run times and experimental throughput. This work presents the design, integration, and validation of a cooling sleeve implemented on the sweep arm drive motor feedthrough to mitigate thermal accumulation during testing. The addition of the cooling sleeve is a simple, robust upgrade that translates directly into enhanced facility capability by supporting longer run durations, reduced turnaround time, and higher throughput.

sting arm↗

NASA NTRSDate not supplied

Extending mARC II Arc-Jet Test Duration via Design and Implementation of Model System Cooling Sleeve

numerical simulations↗

DOE OSTI2026

Testing and Validation of Wireless Communication Architecture for Heliostat Fields: SIPS Final Report

This work focuses on the development and testing of a low-cost wireless communication system for heliostat fields, enabling significant capital costs reductions for concentrating solar thermal systems. Outputs of this work include a working demonstration of a multi-node communication system, clear reporting of system performance, and technical documentation of system development and architecture for reproducibility. Through this process, an open-source repository was created for manufacturing hardware at ~$30/heliostat. The system includes software for cybersecurity, achieving sub-second communication latencies and derisking of hardware for eventual scale-up to tens of thousands of heliostats. While the system is not currently off-the-shelf ready, there is now a clearly defined pathway for scaling up and completing the commercial development process.

14 SOLAR ENERGY↗

DOE OSTI2026

Spinel high-entropy oxides (FeNiCrMnZnX) 3 O 4 (X = Al, mg) as anode materials for high-performance lithium-ion batteries

To address the high cost, cobalt dependency, and resource constraints typical of conventional high-entropy oxide (HEO) anodes, this study reports the successful synthesis of two Co-free, six-component spinel-type HEOs(FeNiCrMnZnAl) 3 O 4 (HEO-Al) and (FeNiCrMnZnMg) 3 O 4 (HEO-Mg), via a sol-gel method. The distinct effects of Al 3+ and Mg 2+ incorporation on the electrochemical performance and lithium storage kinetics were systematically investigated. XRD, Raman, and TEM characterizations confirm that both materials possess a pure spinel phase, uniform particle size, and homogeneous elemental distribution. Notably, electrochemical evaluations reveal that HEO-Al delivers a superior reversible capacity of 480.7 mAh g −1 after 100 cycles at 0.1 A g −1 , and maintains 354.5 mAh g −1 after 1000 long-term cycles at 1 A g −1 , significantly outperforming HEO-Mg. Kinetic analysis indicates that HEO-Al exhibits lower charge transfer resistance, a higher Li + diffusion coefficient, and a pseudocapacitive contribution of up to 82%. Furthermore, these findings demonstrate that Al substitution effectively optimizes the structural stability and lithium storage kinetics of Co-free HEOs, providing a viable strategy for designing low-cost, highly stable HEO anode systems.

Anode materials↗

DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Solar Heat for Industrial Processes: Integration with Chemical Reactors

The integration of solar thermal systems with chemical reactors has been proposed as part of a larger effort to develop and deploy solar heat for industrial processes (SHIP) technologies. A strong motivation for SHIP processes and technologies is the potential for high thermal efficiency coupled with low-cost thermal energy storage (TES) which can enable commercial deployment of such systems. While there are different ways to categorize SHIP technologies, one important such distinction is between directly irradiated systems and indirect off-sun process driven by a SHIP system. While directly irradiated systems can provide high thermal efficiencies and high fluxes, they usually require complex engineering solutions due to the need for redesigning the established processes and unit operations. In most cases, it is also more challenging to couple such a process to a TES system, losing some of the benefits of SHIP. On the other hand, using a SHIP system to drive an industrial process off-sun can allow better integration with existing process chains, easier TES capabilities, and potential for more applications fitting a specific SHIP technology. However, the integration of SHIP systems with the industrial processes is not fully explored in detail, especially in the case of high-temperature processes such as reforming, cracking, cement manufacturing, and iron/steelmaking. Many of these systems require heating fluxes of >50 kW/m^2, supplied via combustion of hydrocarbons in a fire box and benefitting from radiative heat transfer between the flue gases and the reaction zones. As such, using SHIP systems for such processes is more complex than providing the same thermal input in the form of a heat transfer medium (HTM) entering the reactor, kiln, or furnace. Moreover, in case convective heat transfer using SHIP is envisioned, for example using supercritical CO2 as the HTM from a particle receiver, the thermal integration might be more challenging than initially envisioned: lower heat transfer coefficients and limited approach temperature might require large flow rates, causing a mismatch between the process thermal requirements and the thermal capacity of the SHIP system. In addition, even if the heat exchange between SHIP and reactor is effective, there is still a cold leg HTM at the reaction temperature or slightly below it. Chemical plants usually include a set of heat exchangers, heat recovery steam generators, and even power generation units - in a tightly integrated design - to recover the flue gases which are eventually vented. With SHIP systems mostly operating on a closed HTM loop, bottoming the cold leg is crucial. In this talk, we will present different modeling results for a variety of syngas production reactions, using catalytic and chemical looping processes, and discuss some of the challenges and design considerations for off-sun chemical reactors using SHIP systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Two-Level Sketching Alternating Anderson Acceleration for Complex Physics Applications

We present a novel two-level sketching extension of the Alternating Anderson–Picard (AAP) method for accelerating fixed-point iterations in challenging single- and multiphysics simulations governed by discretized PDEs. Our approach combines a static, physics-based projection that reduces the least-squares (LS) problem to the most informative field (e.g., via Schur-complement insight) with a dynamic, algebraic sketching stage driven by a backward stability analysis under Lipschitz continuity. We introduce inexpensive estimators for stability thresholds and cache-aware randomized selection strategies to balance computational cost against memory access overhead. The resulting algorithm solves reduced LS systems in place, minimizes memory footprints, and seamlessly alternates between low-cost Picard updates and Anderson mixing. Implemented in Julia, our two-level sketching AAP achieves up to 50% time-to-solution reductions compared to standard Anderson acceleration—without degrading convergence rates—on benchmark problems including Stokes, 𝑝-Laplacian, bidomain, and Navier–Stokes formulations at varying problem sizes. These results demonstrate the method’s robustness, scalability, and potential for integration into high-performance scientific computing frameworks. Our implementation is available open source in the AAP.jl library.

Barnafi, Nicolas [University of Chile, Santiago]↗

NASA NTRSDate not supplied

AstroDOME: Standardized, Mass-Produceable, Small NASA Astrophysics Observatories for Big Missions

NASA’s Goddard Space Flight Center is investigating the use of small, commercial off the shelf (COTS) spacecraft to enable breakthrough astrophysics research at radically reduced cost over previous generations of missions. This paper will focus on the Mission Systems perspective of this investigation. It will cover the spacecraft to instrument interface, and lessons learned in early concept payload development. Low-cost COTS spacecraft have proliferated in the last ~5 years. They represent an order of magnitude reduction in the cost of spacecraft bus development and acquisition. They are enabled by the advent of low-cost smallsat launch options in the immediately preceding years, and are seeded by recent distributed and disaggregated missions in other sectors such as telecommunications megaconstellations (e.g. Starlink, OneWeb, Project Kuiper) and ongoing Space Development Agency (SDA) developments. Our study was tasked with developing a standardized, mass-produceable, astrophysics payload which is reconfigurable to different wavelength bands while maintaining a single optics bench design, and a standardized mechanical, electrical, data, and thermal interface to the spacecraft bus, and which may be reconfigured to multiple COTS spacecraft offerings. In this paper we will discuss lessons learned from our case study. We will also present identified keys to mission success for performing cutting edge astrophysics observations while taking advantage of economies of scale with a disaggregated, standardized architecture.

Matthew Marcus↗

DOE OSTI2026

A Modular Accelerator Robotics Framework for AD Robotics

Accelerator tunnels, such as the ones at Fermilab, remain highly radioactive after beam shutoff due to induced radiation from the beam. This residual radiation creates a hazardous environment for manual inspection and repair of beamline components. To minimize worker radiation dose and reduce beam downtime, the AD Robotics Initiative previously built a fleet of low-cost custom mobile robots. However, the custom Python sockets server-client architecture lacked standardization, causing development delays and complicating the integration of new sensors and actuators. Here, we developed a modular system using ROS2 and Docker to standardize the teleoperation and control interfaces. This system was validated by implementing a teleoperation controller with real-time, low-latency, and high-definition video feedback. The aim of this framework is for a new feature or even a robot to be integrated into the system simply by documenting the hardware configuration. Current integration of LiDAR, Odometry, and Depth Cameras provides the foundation for Simultaneous Localization and Mapping (SLAM) tasks. Finally, future work involves integration into the accelerator control system and the attachment of a 6 degree-of-freedom robotic arm for telemanipulation.

Rayyan Khan, M. [Fermilab; Rensselaer Poly.; Unlis↗

DOE OSTI2026

Modular Accelerator Robotics Framework Implementation For Accelerator Inspection

Rayyan Khana, M. [Unlisted, US, IL] (ORCID:0009000↗

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↗

NASA NTRS2026

NASA Weather Balloon Demonstration of an Additively Manufactured Antenna

Additive manufacturing (AM) enables low-cost, lightweight, and geometrically flexible antennas for rapid deployment missions. This work reports a left-hand circularly polarized magneto-electric dipole printed on a Radix dielectric with inkjet silver metallization and demonstrated as a process replacement for NASA weather-balloon RF hardware. By combining substrate fabrication and metallization, AM provides value for unrecoverable or field-replaceable systems. A physics based verification workflow links AM-specific material behavior to electromagnetic performance and yields bounded total, radiation, and mismatch efficiencies. Standard surface-impedance and roughness models failed to reproduce the frequency-dependent radiation loss observed in printed inks, underscoring the need for AM-specific conductor parameterization. Mission testing confirmed TDRSS link closure from NASA’s Columbia Scientific Balloon Facility and validated a repeatable print–measure–fly workflow for bounding RF performance and qualifying AM antennas for field use.

Peter Moschetti↗

NASA NTRSDate not supplied

NASA Weather Balloon Demonstration of an Additively Manufactured Antenna

Peter Moschetti↗

DOE OSTI2026

Integrating Carbon Capture, Utilization, & Sequestration into Chemical Pulp Mills

The U.S. pulp and paper industry presents a unique and largely untapped opportunity for large- scale carbon dioxide removal (CDR). Unlike most industrial sectors, pulp mills rely heavily on biomass, meaning that much of their carbon emissions originate from atmospheric CO₂ that was recently captured by plants. If this biogenic CO₂ can be captured and permanently stored, pulp mills can be transformed from carbon emitters into net carbon removal facilities. This project was motivated by that opportunity and aimed to develop and evaluate integrated, low-cost strategies for capturing, utilizing, and sequestering CO₂ within existing chemical pulping operations. The scope of this work focused on four complementary innovations designed to integrate seamlessly into kraft pulp mill infrastructure: (1) in situ CO₂ capture within the recovery cycle, (2) oxy-fuel retrofitting of the rotary lime kiln to produce a high-purity CO₂ stream, (3) ex situ CO₂ capture and mineralization using pulp mill residues (dregs, grits, and lime mud), and (4) beneficial reuse of these residues as mineral carbonate fertilizers. The project combined process modeling, laboratory experimentation, life cycle assessment (LCA), and field trials to evaluate the technical feasibility, economic viability, and environmental impact of these approaches. The results demonstrate that pulp mills can serve as effective platforms for carbon removal when equipped with integrated carbon capture systems. Process modeling showed that combining sodium spiking with oxy-fuel calcination significantly enhances CO₂ capture efficiency while reducing costs by up to 31% compared to conventional configurations. Experimental work further revealed that calcination behavior in high-CO₂ environments differs substantially from traditional systems, leading to the development of a new kinetic model that predicts reaction rates under these conditions. This model provides essential design guidance for next-generation decarbonized lime kilns. In parallel, the project demonstrated that alkaline mineral residues generated during pulping operations can be repurposed as a sustainable alternative to agricultural lime. Across a wide range of soils in the southeastern United States, these materials performed equivalently to commercial lime in adjusting soil pH while offering lower greenhouse gas emissions and reduced cost. Field and greenhouse studies confirmed that crop and tree growth responses were comparable, supporting their viability as a drop-in replacement. This co-product pathway provides a practical utilization strategy that offsets costs and improves overall system economics. A major contribution of this project is the first comprehensive life cycle assessment of carbon removal in pulp and paper systems across multiple system boundaries. Results show that retrofitted mills can achieve carbon removal efficiencies ranging from 12% to 92%, depending on how the system is defined. This finding highlights a critical issue in carbon accounting: reported performance is highly sensitive to methodological choices. By explicitly quantifying these differences, this work provides valuable guidance for policymakers, carbon registries, and project developers working to standardize carbon removal metrics. From a commercialization perspective, the technologies investigated in this project are well- aligned with existing industrial infrastructure, minimizing the need for entirely new facilities. 3 DE-EE0009413 Industry engagement throughout the project—including collaboration with pulp and paper companies, equipment manufacturers, and carbon removal developers—has accelerated the transition from research to deployment. Notably, a commercial developer is actively pursuing carbon capture projects at pulp mills in the southeastern United States and has cited this research as a contributing foundation. The emergence of voluntary carbon markets and long-term offtake agreements further strengthens the business case for implementation. The broader public benefits of this work are significant. By enabling large-scale carbon removal using existing industrial systems, this approach offers a near-term pathway to reduce atmospheric CO₂ concentrations while supporting domestic manufacturing and rural economies. The reuse of industrial residues as fertilizers reduces reliance on mined materials, lowers costs for farmers, and decreases environmental impacts associated with conventional lime production. In addition, the project has supported workforce development by training graduate students and researchers in carbon capture technologies, helping to build capacity in a critical area of national interest. In conclusion, this project demonstrates that integrated carbon capture, utilization, and sequestration in pulp mills is both technically feasible and economically promising. By combining process innovation, experimental validation, and systems-level analysis, the work advances the understanding of how biomass-based industries can contribute to climate mitigation. The findings provide a strong foundation for commercial deployment and offer a scalable solution for transforming a major U.S. industry into a source of durable carbon removal.

09 BIOMASS FUELS↗

DOE OSTI2026

Enhancing NO Reduction by CO Over NiO/CeO 2 Catalyst by Optimizing the Metal Oxide–Support Interaction

Noble metal catalysts are widely used in three-way catalysts (TWCs) due to their high efficiency, but their scarcity and high cost drive the need for effective, low-cost alternatives. Here, in this work, a series of NiO/CeO 2 catalysts were engineered by modulating the OH content and crystallite size of the CeO 2 support. This approach yielded Ni species ranging from isolated single atoms to small clusters and larger aggregates, with varied NiO/CeO 2 interaction strengths. Evaluation of their performance in NO reduction by CO, CO oxidation, and the water–gas shift reaction revealed that the NiO/CeO 2 -300 catalyst, featuring small CeO 2 crystallites and highly dispersed NiO clusters, delivered superior activity for NO reduction and CO oxidation. It was demonstrated that small NiO clusters, due to their efficient CO adsorption and activation, were more active than Ni single atoms. Furthermore, the presence of water was found to influence the catalyst stability, with NiO clusters less stable than single atoms likely due to the hydroxylation effect leading to the formation of Ni(OH) 2 . Oxygen storage capacity measurements revealed that performance was governed by a combination of CeO 2 crystallite size and the abundance of NiO/CeO 2 interfaces. These findings demonstrated that the catalytic performance of Ni/CeO 2 systems could be maximized by optimizing the Ni nanostructure and its interaction with CeO 2 support, positioning them as a promising, multifunctional nonprecious alternative for three-way catalysis application.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Ensemble Kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics

This paper presents an innovative Reduced-order model (ROM) for merging experimental and simulation data using data assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the ensemble Kalman filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost singular value decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low relative root mean square error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app.

Data Assimilation↗