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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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1,016 records · Page 41

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE

Experimental Effects of Scaling on the Performance of Ion Rockets Employing Electron-Bombardment Ion Sources

A scaling program was undertaken to establish the relations between performance parameters and the size of the electron bombardment ion source. The experimental results of this investigation are the subject of this paper. Two geometrically similar sources, a 5- and a 20-cm-diameter beam source, were scaled from a 10-cm-diameter source to allow a performance comparison to be made. The three ion sources are compared for ion chamber characteristics and overall engine efficiency. The results of the chamber investigations are compared with scaling variations indicated by simple plasma theory. The effects of size on operating limits are also discussed. Mercury was used as the propellant in this investigation.

Power Supply

Battery Cell-to-Pack Scaling Laws for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss-estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft

Cooperative and bifunctional Ga-Ca-Cr 2 O 3 @CaO structured monoliths as versatile platform for reactive capture of CO 2 and its subsequent conversion to ethylene

Cooperative and bifunctional materials (BFMs) that integrate adsorbents and catalysts offer a promising strategy for the reactive capture of CO 2 to produce valuable fuels and chemicals. In this study, we developed structured BFMs via 3D printing that combine CaO as an adsorbent with Ga–Ca–Cr 2 O 3 metal oxides as the catalyst for the reactive capture of CO 2 and its subsequent conversion to C 2 H 4 via the oxidative dehydrogenation of C 2 H 6 (CO 2 -ODHE). Three different Ga–Ca compositions were used to modify the catalyst surface characteristics and enhance C 2 H 4 selectivity. In these formulations, Ga ions stabilize the oxygen lattice of the BFM, while Ca ions interact strongly with Cr to form CaCrO 4 , thereby altering the oxygen species and enhancing the material’s basic properties. Under adsorption–reaction conditions at 600–650 °C, the optimal BFM achieved an excellent C 2 H 4 selectivity of 96.4 %, attributed to a balanced redox process and improved basicity that facilitate efficient C 2 H 6 conversion and rapid desorption of C 2 H 4 without excessive oxidation. Overall, this work provides new insights into the formulation of BFMs monoliths and highlights the critical role of catalytic surface modification in enhancing C 2 H 4 selectivity in the CO 2 -ODHE reactive capture process.

C2H4 production

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)

Considerations for Maritime Nuclear Technologies, Economic Viability and Public Acceptance

The Maritime Nuclear Application Group (MNAG) is a working group convened by the National Reactor Innovation Center at Idaho National Laboratory (INL), the American Bureau of Shipping, and Morgan, Lewis, and Bockius LLP. This report documents an MNAG examination of considerations relevant to implementing nuclear technology in commercial maritime applications. In general, two types of use case are examined: maritime nuclear power plants and nuclear reactors used on board shipping vessels for propulsion and other ship needs. The report finds that there may be economic benefits related to maritime nuclear technologies, including the flexible deployment of maritime nuclear reactors, which would allow them to complement land-based nuclear projects, and operational differences for nuclear cargo ships that may lead to an overall increase in revenue. High-level analyses in this report show that, based on general small modular reactor and microreactor cost estimates developed by INL, maritime nuclear reactors may be economically competitive for electricity production in remote regions and for use in the propulsion of large cargo ships. Besides economic viability, public acceptance will be key to implementing maritime nuclear technologies. The report discusses the public’s current perception of nuclear technologies. Engaging with the public will be important to improving this perception. The report discusses some key benefits and risks associated with maritime nuclear technologies. Benefits include the creation of jobs, the production of reliable energy, and the potential to improve air quality. Risks that concern the public are the potential for radioactive releases during operation and decommissioning, as well as those related to waste management. Communicating the benefits and the risks of maritime nuclear technologies will be essential to improving public perception.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Crewed Space Vehicle Battery Safety Requirements Revision D

The Crewed Space Vehicle Battery Safety Requirements document has been prepared for use by designers of battery-powered vehicles, portable equipment, and experiments intended for crewed spaceflight. The purpose of the requirements document is to provide battery designers with information on design provisions to be incorporated in and around the battery and on the verification to be undertaken to demonstrate a safe battery is provided. The term "safe battery" means that the battery is safe for ground personnel and crew members to handle and use; safe to be used in the enclosed environment of a crewed space vehicle; and safe to be mounted or used in unpressurized spaces adjacent to habitable areas. Battery design review, approval, and certification is required before the batteries can be used for ground operations and be certified for flight.

Russell, Samuel

Material-dependent photon ionizing radiation effects in Si and GaAs PIN diodes: A numerical investigation

We present a finite-element drift-diffusion-Poisson model in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework to compare the radiation response of silicon (Si) and gallium arsenide (GaAs) PIN diodes under high-energy photon irradiation. The model solves coupled carrier continuity and Poisson’s equations with Shockley-Read-Hall recombination, and is verified against standard analytical J-V behavior. Using a simplified 1D geometry with ideal Ohmic contacts, we quantify device response under forward and reverse bias with a 100 MeV photon flux. Under forward bias, Si exhibits markedly greater radiation sensitivity than GaAs, including larger increases in current density, stronger local field and carrier-product perturbations, and higher recombination. Under reverse bias, GaAs shows larger radiation-induced photocurrent and broader current-density peaks near junctions, indicating an advantage for photodetection. Integrated steady-state recombination is consistently higher in Si across voltages. Under periodic photon pulses, GaAs produces higher-amplitude photoresponse and settles more rapidly than Si. These results highlight material-dependent trade-offs for radiation-tolerant, high-speed optoelectronics and provide guidance for selecting PIN architectures in aerospace, nuclear, and high-energy physics environments.

36 MATERIALS SCIENCE

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

Jumpstart Opportunities to Unleash Leadership in Energy Storage (JOULES)

Current-generation Li-ion batteries with cobalt- and nickel-containing cathodes and graphite anodes are approaching performance and cost limits. In this program, 24M Technologies, Inc. (24M) is teaming with the Massachusetts Institute of Technology (MIT) and University of Michigan (UM) to develop low cost and fast charging sodium metal batteries with good low-temperature performance and high energy density, building upon previous work performed under ARPA-E programs. Key achievements include optimization of solid electrolyte and anode current collector, optimized cathode active materials, development of high-performance electrolyte formulations, and integration of these components into full cells. The cell design incorporates (1) an ultra-thick cathode (>9 mAh/cm 2 ) comprising advanced cobalt-free, sodium cathode active material, (2) advanced fast-charging electrolyte (up to 12 mS/cm) developed using machine learning and automated high-throughput screening technology by UM, and (3) ceramic modified separator that enable smooth Na transport and deposition, developed at MIT, enabling a high-energy density anode-free configuration and maximizing the energy density of sodium batteries. The team has successfully combined these approaches to sodium chemistry and paved the way to meeting the fast-charging, high-energy density, and low-cost requirements of next-generation drone, electric vertical take-off and -landing, and electric vehicle batteries. Performance for anode-free sodium cells developed under this program is more powerful than the commercial Li-ion batteries. The final deliverable cell design has achieved over 300 Wh/kg and volumetric energy density above 800 Wh/L (Table 1). Additionally, the team has achieved over (1) a lifetime of 340 cycles, (2) 80% capacity retention at -20 °C (compared 25 °C), and (3) the ability to fast charge to 80% SOC in 20 minutes.

25 ENERGY STORAGE

Nuclear Reactor Heat Extraction for Synthetic Fuel Plants

This report looks at the viability and best approach when producing synthetic fuels using heat and power supplied by advanced nuclear energy systems. The report looks at a low temperature integration pathway with four types of advanced reactors: a pressurized water reactor (PWR), an advanced light water reactor (A-LWR), a sodium fast reactor (SFR), and a high-temperature gas-cooled reactor (HTGR). A failure modes and effects analysis (FMEA) of the coupling system between the nuclear plant and the synthetic fuel systems is performed with the goal of identifying the reliability of such a thermal delivery system. Furthermore, a high temperature pathway is investigated for synfuel coupling to determine if this is more efficient and more cost effective as a coupling approach.

10 - SYNTHETIC FUELS

End-To-End Decentralized Transmission Line Protection in IBR-Dominated Weak Grids Using Interpretable Data-Driven Methods

Traditional transmission line protection relies on predictable synchronous-based fault signatures, which frequently fail under the non-standard, current-limited fault characteristics of Inverter-Based Resources (IBRs). This study investigates how to achieve secure, communication-free fault isolation in IBR-dominated weak grids without relying on opaque, computationally heavy "black-box" machine learning algorithms. To address this, we propose a novel, standalone, and inherently interpretable data-driven protection framework. Unlike centralized methods requiring multi-terminal communication, this decentralized approach relies solely on local measurements using a hierarchical linear-kernel Support Vector Machine (SVM). The methodology decomposes the protection task into four sequential stages that mimic traditional protection elements: fault detection and fault direction identification, fault type classification, zone classification, and location estimation. This multi-stage architecture allows for specialized feature engineering at each stage, combining high computational efficiency with logic traceability. The framework's end-to-end performance was validated via C-code and PSCAD/EMTDC co-simulation, utilizing a real-world utility network and an OEM black-box IBR model. The proposed relay achieves 97.2% overall accuracy and provides a reliable trip decision within a 2.5-cycle window. The results confirm 100% accuracy in fundamental fault detection, reliable zone selectivity across low to moderate fault resistances, and robust security against non-fault transients, proving its immediate viability for integration into commercial numerical relays.

24 POWER TRANSMISSION AND DISTRIBUTION

Deployment and retrieval mechanism redesigned for Spartan spacecraft on the STS

The Spartan Release Engage Mechanism (REM) is a system designed to restrain the Spartan spacecraft during Space Transportation System (STS) launch and landing. The mechanism is designed to allow deployment and retrieval of the Spartan free flyer spacecraft from the shuttle payload bay. Because current Spartan spacecraft payloads are much heavier than payloads intended for the original REM, an extensive redesign, analysis, and test program was necessary. Also, increased emphasis on safety in the post-Challenger era prompted a reevaluation of possible failures. Much of the design effort focused on improving the latch mechanism gearbox. Key concerns were effective gear lubrication, thermal gradients at the gearbox mounts, operation at thermal extremes, and gear-train failure contingencies. Increased concern for reliability led to the design of an Extra Vehicular Activity (EVA) backup latch system.

Greg Galloway

A Probabilistic Model of a Porous Heat Exchanger

This paper presents a probabilistic one-dimensional finite element model for heat transfer processes in porous heat exchangers. The Galerkin approach is used to develop the finite element matrices. Some of the submatrices are asymmetric due to the presence of the flow term. The Neumann expansion is used to write the temperature distribution as a series of random variables, and the expectation operator is applied to obtain the mean and deviation statistics. To demonstrate the feasibility of the formulation, a one-dimensional model of heat transfer phenomenon in superfluid flow through a porous media is considered. Results of this formulation agree well with the Monte-Carlo simulations and the analytical solutions. Although the numerical experiments are confined to parametric random variables, a formulation is presented to account for the random spatial variations.

O P Agrawal

Battery Cell-to-Pack Scaling Trends for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss- estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging

Applications Technology Satellites Battery and Power System Design

A summary of the ATS battery design which is onboard the Applications Technology Satellite (ATS) is provided. The 15 ampere hour nickel cadmium cells were manufactured by Gulton, 19 series connected cells per battery, and there are two batteries in each spacecraft. The operating design life was two years in a synchronous orbit, and a maximum depth of discharge of 50 percent. The design temperature for the batteries in the spacecraft was 0 to 25 C, and the charge control consisted of 1 volt versus temperature on a constant percentage voltage. Also, C/10 current limit, and a commandable trickle charge rate, using C/20 or C/60. The undervoltage was sent across a 9 cell and a 10 cell group, and it was set at one volt average per group on either group.

F E Ford

Diagnostics development for the Electric Propulsion Orbital Platform

We describe the development of the diagnostics systems for the first flight of the Electric Propulsion Orbital Platform (EPOP), which will center around the in-flight characterization of a 1.8 kW hydrogen arcjet system. In particular, we discuss a spacecraft communications experiment involving ground-to-spacecraft communications of the EPOP carrier; electrical probe measurements in the arcjet plume; and spectrally resolved plume imaging measurements of the same plume. The communications experiment is designed to measure small noise on the communications link which results from arcjet operation. The other two measurements primarily serve the purpose of characterization of the plume plasma. These measurements will be compared to similar measurements performed in a ground chamber to establish whether systematic differences exist between ground-based and in-flight performance of the arcjet system.

Wilhelmus M. Ruyten