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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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2,060 records · Page 99

Effects of Multisensory Virtual Reality Nature on Affect, Presence, and Restorativeness

Virtual reality (VR) can provide access to restorative environments and sensory stimulation for individuals in isolated, confined, and extreme environments. We developed a nature-based VR intervention featuring three scenes (Garden, Forest, Beach) and examined the effects of multisensory augmentation with location-based olfactory, wind, and thermal stimuli (VR+OWT). Over a two-week period, fifty-one participants were assigned to a no-intervention control, standard audiovisual VR, or augmented VR (VR+OWT) condition. Data collection included weekly assessments of affect, stress, and cognitive performance; post-VR measures of affect, presence, and perceived restorativeness; and open-ended feedback. Both VR and VR+OWT groups produced immediate and sustained reductions in negative affect with no sustained systematic benefits on cognitive performance. The addition of olfactory, wind, and thermal stimuli enhanced presence for some scenes; however, feedback indicated that sensory mismatches and stimulus intensity occasionally detracted from the experience and may have contributed to lower coherence ratings in the VR+OWT group. In contrast, the perceived restorativeness of the VR environment was driven primarily by scene content (Garden vs Forest vs Beach) rather than the level of sensory stimulation. These findings support the potential of virtual nature to promote well-being and underscore the importance of coherence across sensory modalities for multisensory augmentation.

Virtual Reality Intervention

Hamiltonian switching control of noisy bipartite qubit systems

Abstract We develop a Hamiltonian switching ansatz for bipartite control that is inspired by the quantum approximate optimization algorithm, to mitigate environmental noise on qubits. We demonstrate the control for a central spin coupled to bath spins via isotropic Heisenberg interactions, and then make physical applications to the protection of quantum gates performed on superconducting transmon qubits coupling to environmental two-level-systems (TLSs) through dipole-dipole interactions, as well as on such qubits coupled to both TLSs and a Lindblad bath. The control field is classical and acts only on the system qubits. We use reinforcement learning with policy gradient to optimize the Hamiltonian switching control protocols, using a fidelity objective for specific target quantum gates. We use this approach to demonstrate effective suppression of both coherent and dissipative noise, with numerical studies achieving target gate implementations with fidelities over 0.9999 (four nines) in the majority of our test cases and showing improvement beyond this to values of 0.999 999 999 (nine nines) upon a subsequent optimization by GRadient Ascent Pulse Engineering (GRAPE). We analyze how the control depth, total evolution time, number of environmental TLS, and choice of optimization method affect the fidelity achieved by the optimal protocols and reveal some critical behaviors of bipartite control of quantum gates.

Physics

Mode Multiplexing for Scalable Cavity-Enhanced Operations in Neutral-Atom Arrays

Neutral-atom arrays provide a versatile platform for quantum information processing. However, in large-scale arrays, efficient photon collection remains a bottleneck for key tasks such as fast, nondestructive qubit readout and remote entanglement distribution. We propose a cavity-based approach that enables fast, parallel operations over many atoms using multiple modes of a single optical cavity. By selectively shifting the relevant atomic transitions, each atom can be coupled to a distinct cavity mode, allowing independent simultaneous processing. We present practical system designs that support cavity-mode multiplexing with up to 50 modes, enabling rapid mid-circuit syndrome extraction and significantly enhancing entanglement distribution rates between remote atom arrays. This approach offers a scalable solution to core challenges in neutral-atom arrays, advancing the development of practical quantum technologies.

Aqua, Ziv [Massachusetts Institute of Technology (

Radioactivity of the Moon, Planets, and Meteorites

This paper reviews and summarizes analytical data for the content of natural radioactive elements in meteorites, eruptive terrestrial rocks, and also, in lunar samples returned by Apollo missions and the Luna series of automatic stations. The K-U systematics of samples analyzed in the laboratory are combined with data for orbital gamma-ray measurements for Mars (Mars 5) and with the results of direct gamma-ray measurements of the surface of Venus by the Venera 8 lander. Using information about the radioactivity of solar system bodies and evaluations of the content of K, U, and Th in the terrestrial planets, we examine certain aspects of the evolution of material in the protoplanetary gas-dust cloud and then in the planets of the solar system.

Yu A Surkov

Chapter 21 - Avionics

This Section presents general guidance for flight testing of avionics systems. Due to the complex and ever changing nature of avionics systems, specific detailed test methods and analysis techniques are left to current and future system specific AGARDographs such as references 21-1 and 21-2. This section will provide descriptions of test methods which are generic to most current and future avionics systems. The field of avionics systems was divided into four general categories (autopilot, navigation and communication, offensive, and defensive) and a fifth overall test category of integration. This was accomplished only for the convenience in presenting the material. These categories are not meant to encompass all avionics systems but are intended to be sufficiently general to enable a systematic discussion of the testing of the basic types of avionics systems.

Ron Mahlum

Power performance and loads characterization of laboratory-scale cross-flow rotors fabricated using additive manufacturing

Tidal energy conversion is a relatively new application for additive manufacturing (AM), where the focus has been on fabricating axial-flow turbine blades. AM techniques add material precisely where it is needed, creating more complex shapes with less waste. Cross-flow rotor geometry presents an opportunity for AM to improve rotor performance by fabricating features that cannot be created economically via conventional manufacturing. The challenges associated with using AM in cross-flow design include water resistance and degradation over time while retaining a level of quality equivalent to conventionally machined parts. In this work, AM materials were tested by environmentally conditioning samples in a seawater tank for 5 months, followed by performance and phase-resolved load testing of laboratory-scale rotors in a hydraulic flume. We found that while metals like titanium and Inconel have excellent performance in marine environments, achieving the desired geometry and performance is difficult. Thermoplastics degraded in seawater but were easier to form into desired geometries and could exceed the performance of an aluminum control rotor. Warping and surface finish were significant detractors from AM rotor performance. These results suggest that the primary benefits of using AM for cross-flow rotors is to quickly fabricate and test unconventional rotor geometries.

16 TIDAL AND WAVE POWER

Laser-heated diamond anvil cell synthesis and recovery of metastable MnSb 2 and YbZn 2 for post-synthesis transport studies

The creation and exploration of new materials under extreme pressure–temperature conditions has become increasingly reliant on laser-heated diamond anvil cell (LHDAC) techniques, which provide direct access to previously unexplored regions of multinary phase diagrams. Whereas numerous high-pressure phases have been identified in situ, systematic recovery and post-synthesis physical property characterization of these materials remain significant challenges. In this work, we describe the setup and implementation of an LHDAC-based synthesis and recovery workflow and demonstrate its application to metastable MnSb 2 and YbZn 2 phases. Synchrotron x-ray diffraction and spatial mapping confirm dominant formation of the targeted phases, whereas laboratory-based refinement quantifies phase fractions despite intrinsic microstrain and minor secondary phases. High-pressure transport measurements on recovered samples reveal pressure-tunable electronic instabilities in both systems. In MnSb 2 , pressure suppresses two high-temperature magnetic ordering anomalies, observed in transport, by ∼5 GPa and, for higher pressures, induces a new low-temperature feature that increases with further pressure increase. In hexagonal high-pressure YbZn 2 , an electronic reconstruction emerges at ∼11 GPa, characterized by semiconducting-like behavior from ∼30 to 300 K and a broad low-temperature coherence crossover near 30 K. Our results establish LHDAC synthesis not only as a structural discovery tool but also as an experimental platform for investigating correlated quantum states stabilized far from equilibrium thermodynamic conditions.

Huyan, S. [Iowa State University, Ames, IA (United

Geochemical Zoning and Early Differentiation in the Moon

The volatile elements (e.g., Rb, Pb, Tl, Bi, Cs) seem to have been depleted at the time of lunar accretion. Accordingly, it may be assumed that the moon initially accreted from refractory material. The good correlation between volatile/involatile element ratios (e.g., Cs/U, K/La, K/Zr) in both highland and maria samples means that element distribution in lunar crustal rocks is not governed by volatility differences. This and other evidence encourages the view that the moon was accreted homogeneously. A consequence of homogeneous accretion theories is that very efficient large-scale element fractionation is required to account both for the high near-surface concentrations of refractory elements (e.g., Th, U, REE, Zr, Ba, etc.) and for the Ca-Al-rich crust.

S R Taylor

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

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY

NASA’s SLS (Space Launch System) Rocket Ready for Artemis II Lunar Mission

In early 2026, NASA will launch the Artemis II mission, an approximately 10-day long lunar mission that will fly three NASA astronauts and one CSA (Canadian Space Agency) astronaut on a free-return trajectory around the Moon, following a one-day checkout of their Orion spacecraft in Earth orbit. The mission will be the first to launch astronauts aboard NASA’s Orion spacecraft and on top of the agency’s SLS (Space Launch System) rocket. The mission will also deploy four 12U CubeSats as secondary payloads from the Orion stage adapter, following Orion separation and departure. The payloads, developed by four of NASA’s international partners, will perform a variety of science and technology investigations. The SLS and Orion for the mission are currently stacked in the Vehicle Assembly Building (VAB) at NASA’s Kennedy Space Center in Florida and are undergoing final preparations to rollout to Launch Pad 39B for a tanking test before launch. In addition to preparations for the Artemis II mission, significant progress is being made on the SLS for the Artemis III mission, which is targeted to return astronauts to the lunar surface no later than 2029. Major components of the core stage and solid rocket boosters are already at NASA Kennedy undergoing build-up for the mission. Data from the Artemis II launch and mission, as well as progress to subsequent missions, as available, will be presented.

Bruce Askins

Li Stripping Behavior of Anode‐Free Solid‐State Batteries Under Intermittent‐Current Discharge Conditions

Anode‐free manufacturing holds promise to enable high energy densities and lower Lithium (Li)‐metal solid‐state batteries (LMSSBs). Nevertheless, in contrast to thick Li foil (>50 µm), the stripping capacity of in situ‐formed Li (10–30 µm) is limited due to diminished creep flow, resulting in reduced accessible capacity. This study explores the correlation between stripping capacity and surface roughness of garnet Li 7 La 3 Zr 2 O 12 (LLZO) solid electrolyte. The results reveal that stripping capacity can be enhanced through the surface modification of solid electrolytes. Additionally, this study scrutinizes the stripping behavior of in situ Li under intermittent‐current discharge conditions, which are more relevant to the operational conditions of electric vehicles (EVs). It is demonstrated that, when compared to constant‐current stripping, intermittent‐current stripping effectively suppresses void formation and enhances the stripping capacity of in situ Li by 40%. It is considered that the intermittent current inhibits the accumulation of Li vacancies, thereby delaying the void formation. These findings provide valuable insights into the development of high‐performance anode‐free LMSSBs for EVs.

25 ENERGY STORAGE

Design Strategies Based on Electronic Interactions for Effective Catalysts in Lithium–Sulfur Batteries

Abstract Lithium–sulfur batteries (LSBs) are considered promising next‐generation batteries due to their high energy density (>500 W h kg −1 ). However, LSBs exhibit an unsatisfactory energy density (<400 W h kg −1 ) and cycle life (<300 cycles) because of the shuttle effect caused by soluble lithium polysulfide (LiPS) intermediates and the sluggish conversion reaction kinetics caused by insulating sulfur (S 8 ) and lithium sulfide (Li 2 S). Although various types of catalysts, including metal‐based compounds to single‐atom catalysts, have been reported to address these issues, most catalysts exhibited limited catalytic activity under practical lean electrolyte conditions (<5 µL mg −1 ). A comprehensive understanding of the synthetic strategy and catalytic mechanism of catalysts is essential for their design, but understanding the electronic effects of the catalysts and LiPS is more important. Furthermore, the electronic design of these catalysts is not well understood. In this review, we introduce the catalytic mechanisms in LSBs and discuss catalyst design strategies in terms of electronic effects on the interactions between reactants and catalysts, with a primary focus on heterogeneous catalytic systems. We additionally consider how the electronic property of homogeneous systems, particularly redox mediators, affects catalytic behavior under lean electrolyte conditions and propose future research directions for catalyst development in LSBs.

Chemistry

NASA’s SLS (Space Launch System) Rocket Ready for Artemis II Lunar Mission

In early 2026, NASA will launch the Artemis II mission, an approximately 10-day long lunar mission that will fly three NASA astronauts and one CSA (Canadian Space Agency) astronaut on a free-return trajectory around the Moon, following a one-day checkout of their Orion spacecraft in Earth orbit. The mission will be the first to launch astronauts aboard NASA’s Orion spacecraft and on top of the agency’s SLS (Space Launch System) rocket. The mission will also deploy four 12U CubeSats as secondary payloads from the Orion stage adapter, following Orion separation and departure. The payloads, developed by four of NASA’s international partners, will perform a variety of science and technology investigations. The SLS and Orion for the mission are currently stacked in the Vehicle Assembly Building (VAB) at NASA’s Kennedy Space Center in Florida and are undergoing final preparations to rollout to Launch Pad 39B for a tanking test before launch. In addition to preparations for the Artemis II mission, significant progress is being made on the SLS for the Artemis III mission, which is targeted to return astronauts to the lunar surface no later than 2029. Major components of the core stage and solid rocket boosters are already at NASA Kennedy undergoing build-up for the mission. Data from the Artemis II launch and mission, as well as progress to subsequent missions, as available, will be presented.

Bruce R Askins

Optical transparency of LiF (100) shock compressed to ∼360 GPa

High-purity [100] lithium fluoride (LiF) is the most widely used optical window in dynamic compression experiments due to its wide bandgap and well-characterized mechanical response. Recent plate-impact experiments established the [100] LiF Hugoniot to ∼230 GPa and demonstrated shock-induced melting onset at 182 GPa with complete melting by 195 GPa; theoretical models predict LiF optical transparency to nearly 900 GPa. To experimentally examine the optical transparency of [100] LiF at higher pressures and in the liquid state, laser-driven shock experiments were performed at peak stresses ranging from 223 to 363 GPa. Optical response was examined by measuring the particle velocity histories at the Kapton/LiF interface using laser interferometry at 532 and 1550 nm wavelengths; in-material particle velocities were obtained using established refractive-index corrections. Continuous photonic Doppler velocimetry fringes were observed across the entire stress range, demonstrating that LiF remains transparent to 1550 nm light throughout the multi-megabar regime investigated. At 532 nm, fringe visibility depended on the reflector coating: aluminum mirrors provided signals to ∼235 GPa, while gold mirrors extended this limit to 270.5 GPa, indicating that the shorter-wavelength response is likely sensitive to experimental configuration rather than to the loss of LiF transparency. Continued optical transparency to at least 360 GPa indicates that shock-melted LiF does not display bandgap closure over the stress range explored. Furthermore, these results provide direct experimental constraints on the high-pressure optical response and establish LiF (100) as a robust optical window material for laser-driven dynamic compression experiments approaching 400 GPa.

Renganathan, P. [Argonne National Laboratory (ANL)

Transforming Windows from Energy Liabilities to Zero-Energy Assets: Next-Generation Solutions for Buildings

Windows have traditionally contributed to a building's HVAC load, but they can also become a source of net energy gain or even operate as zero-energy components. For heating applications, highly insulating windows can harness more solar heat than the energy lost through them, transforming windows from energy liabilities to assets. Dynamic glazings provide further benefits by regulating solar heat gain, reducing cooling loads in summer and heating demands in winter. This simulation study focuses on developing the next generation of zero-energy windows (ZEW) for residential new construction. Through annual energy simulations across climate zones 1-8, ZEW performance benchmarks were established based on current code-level buildings, and we've identified the regions where meeting ZEW standards are most achievable. This work evaluates both static and dynamic window technologies, assessing their effects on annual energy use and cost. Key findings demonstrate that ZEW performance is achievable across diverse climate zones, with specific regional requirements. Most climate zones from 3-8 can achieve ZEW with specific configurations, while some warm climates (1-2) appear challenging for ZEW implementation. Climate zones 4-6 consistently allow for zero energy window implementation, offering multiple pathways through either static or dynamic window technologies. Colder climate zones (7-8) ZEW products allow for higher SHGC values while requiring low U-values.

Yu, Lili

Machine Learning for Predicting Team Functioning in HERA Missions

Team functioning is integral to success in future long term space exploration missions. Proactively detecting declines in team functioning can mitigate conflict and ensure mission success. This project developed a speech-based artificial intelligence (AI) system that unobtrusively predicts degradation in team functioning, including performance and cohesion, in the Human Exploration Research Analog (HERA) Campaigns 4 and 5. The AI system conducted automated analysis of the prosodic (tone of voice) and linguistic (language content) components of speech, modeling interpersonal dynamics at both the turn-taking and day-wide levels. We investigated team functioning via observing structured interactions (i.e., multi-mission space exploration vehicle-extra vehicular activity [MMSEV-EVA], team interaction battery [TIB]) and unstructured interactions before the MMSEV-EVA task. We developed machine learning models to predict team functioning (objective task accuracy, self reported team efficacy and self reported team cohesion) by analyzing OpenSmile acoustic features, linguistic descriptors extracted via the linguistic inquiry and word count (LIWC) dictionary, and semantic embeddings. In the TIB, static models using logistic regression and random forests were not able to predict task accuracy, but predicted team efficacy and cohesion during both the decision making and relational tasks to a moderate level (60-70%). Majority voting on the individual turns to predict day long team efficacy further increased accuracies (70-80%). Finally, long short-term memory (LSTM) models showed the best performance across all variables (80-91%), including task performance. In the MMSEV-EVA, static models achieved an accuracy of 60% with majority voting, which increased to 80% through the incorporation of mission day as a variable, accounting for the learning effect. A key finding across both tasks was the "team-dependent" nature of these interactions; models achieved much higher accuracy when trained on prior days of the same team's data rather than attempting to generalize across entirely different teams, with even 1-2 days of prior data per team achieving 5-15% improvement over team-independent models. In addition, the incorporation of pre-task data from the same team also improves model performance, e.g., incorporating data from the decision-making task of the TIB, which preceded the relational task, improved the prediction of team efficacy and cohesion during the latter. We compared model performance when trained on machine-generated data compared to data that had been further corrected by human annotators. Overall, models trained on human-corrected data exhibited a modest improvement in performance, particularly when acoustic features were used. We found no significant correlation between word error rate (WER) and model accuracy (r(55) = -0.08, p = 0.51), but model’s accuracy was significantly higher for medium/high quality transcription (0.74 (SD = 0.48)) compared to the low-quality group (0.64 (SD = 0.36)) (t(63)=2.82, p = 0.006). Based on these, several design recommendation emerge, that could inform Standards at NASA. Models predicting team functioning should incorporate at least one to two days of historical interaction data, include brief pre-task discussions, and explicitly model temporal learning effects, especially for longer operational tasks. Minimum quality standards for automated speech-processing pipelines are needed, given the performance gains observed with manually corrected acoustic data. Finally, systems should leverage both acoustic features and language embeddings in complementary ways, with modality choices and fusion strategies tailored to mission context, task demands, and data quality requirements.

Shrivatsa Mishra

Unveiling field-transverse spin anisotropy in the spin liquid candidate α-RuCl3 via spin Hall magnetoresistance

α-RuCl3 has emerged as a possible candidate for a quantum spin liquid (QSL) that promises exotic quasiparticles relevant for fault-tolerant quantum computation. Here, we report spin-sensitive transport measurements using a proximal spin Hall metal, platinum (Pt), to probe magnetic moments in the insulator α-RuCl3. We observe spin Hall magnetoresistance (SMR), where both the transverse and longitudinal resistivities exhibit angular oscillations between the in-plane magnetic field and the current, driven by the interplay between the spin Hall effect in Pt and local magnetic moments in α-RuCl3. These oscillations occur from 1.5 to 18 T, covering the zigzag antiferromagnetic, putative QSL, and supposedly partially field-polarized phases. The phase of the SMR oscillations suggests that the local moments, whether static or fluctuating, develop spin anisotropy with a quantization axis in-plane and largely transverse to the magnetic field across all fields from 1.5 to 18 T. Temperature dependence indicates that the spin anisotropy operates at an energy scale similar to that of the reported QSL signatures in α-RuCl3.

Idzuchi, Hiroshi [Tohoku University, Japan]