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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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At least 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Preflight and In-Flight Exercise Conditions for Astronauts on the International Space Station

The physiological demands of spaceflight require astronauts to have certain physical abilities. They must be able to perform routine and off-nominal physical work during flight and upon re-entry into a gravity environment to ensure mission success, such as an Extra Vehicular Activity (EVA) or emergency egress. To prepare the astronauts for their mission, a Wyle Astronaut Strength Conditioning and Rehabilitation specialist (ASCR) works individually with the astronauts to prescribe preflight strength and conditioning programs and in-flight exercise, utilizing Countermeasure Systems (CMS) exercise hardware. PURPOSE: To describe the preflight and in-flight exercise programs for ISS crewmembers. METHODS: Approximately 2 years before a scheduled launch, an ASCR is assigned to each astronaut and physical training (PT) is routinely scheduled. Preflight PT of astronauts consists of carrying out strength, aerobic and general conditioning, employing the principles of periodization. Exercise programs are prescribed to the astronauts to account for their individual fitness levels, planned mission-specific tasks, areas of concern, and travel schedules. Additionally, astronauts receive instruction on how to operate CMS exercise hardware and receive training for microgravity-specific conditions. For example, astronauts are scheduled training sessions for the International Space Station (ISS) treadmill (TVIS) and cycle ergometer (CEVIS), as well as the Advanced Resistive Exercise Device (ARED). In-flight programs are designed to maintain or even improve the astronauts pre-flight levels of fitness, bone health, muscle strength, power and aerobic capacity. In-flight countermeasure sessions are scheduled in 2.5 h blocks, six days a week, which includes 1.5 h for resistive training and 1 h for aerobic exercise. CONCLUSIONS: Crewmembers reported the need for more scheduled time for preflight training. During flight, crewmembers have indicated that the in-flight exercise is sufficient, but would like more reliable and capable hardware.

Guilliams, Mark E.↗
DOE OSTI2023

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Designing the PR100 Study: Puerto Rico Grid Resilience and Transition to 100% Renewable Energy

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phaseout of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040 as established in Act 17. [1] To meet these goals and support widespread end-use electrification, the territory must explore how renewable energy and other generation technologies can be developed with energy storage, distributed generation, distribution control, electric vehicles, and energy efficient and responsive loads in each of Puerto Rico's cities and communities. To support Puerto Rico in reaching its renewable energy goals; help ensure energy system resilience against future extreme weather events; improve energy justice; and provide inputs to LUMA Energy's walk, jog, and run approach in its coordinated planning roadmap, the U.S. Department of Energy, National Renewable Energy Laboratory, Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory and Sandia National Laboratories propose to evaluate 100% renewable energy pathways through an integrated analysis process. This talk will present steps in designing a two-year study entitled Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy (PR100). [1] U.S. Energy Information Administration (EIA). 2020. Puerto Rico Territory Energy Profile.

100% renewable energy↗
DOE OSTI2020

Direct Evidence of Charge Transfer upon Anion Intercalation in Graphite Cathodes through New Electronic States: An Experimental and Theoretical Study of Hexafluorophosphate

Graphite intercalation compounds continue to be central to technologies for electrochemical energy storage from anodes in established Li-ion batteries to cathodes in beyond Li-ion concepts paired with multivalent anodes. When used as a cathode, graphite intercalates a variety of anions with PF 6 - being among the most common. Paired with Li intercalation at the anode, the corresponding dual carbon battery yields high energy and power densities. Given the available choice of anions as intercalants, it is important to elucidate how the graphite structure accommodates them in order to tailor the molecular species to maximize charge and reversibility. However, the changes in electronic structure of the host graphite lattice upon anion intercalation are poorly understood compared to cations, which represent a fundamentally different reaction. Herein, PF 6 -intercalated graphite has been studied using techniques sensitive to electronic structure, namely, X-ray Raman spectroscopy (XRS), X-ray absorption near-edge spectroscopy (XANES), and X-ray emission spectroscopy (XES). Complementary full-potential, all-electron density functional theory calculations yielded excellent agreement with the spectra, thus providing insight into charge compensation in the graphite lattice. In particular, a pre-$π^*$ feature emerged in XRS/XANES, which is direct evidence of the removal of charge from the host lattice to compensate the intercalated anions, leading to an overall lowering of the Fermi energy level. This is expected to be characteristic of many intercalants in anion-intercalated graphite. The unambiguous identification of the origin of the pre-$π^*$ spectral feature, which is frequently seen in graphitic systems, is of broad interest to the spectroscopy of graphitic systems beyond the practical implications of anion-induced changes in the electronic properties for real devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗
DOE OSTI2020

Biomimetic composite architecture achieves ultrahigh rate capability and cycling life of sodium ion battery cathodes

Sodium ion batteries are an emerging candidate to replace lithium ion batteries in large-scale electrical energy storage systems due to the abundance and widespread distribution of sodium. Despite the growing interest, the development of high-performance sodium cathode materials remains a challenge. In particular, polyanionic compounds are considered as a strong cathode candidate owing to their better cycling stability, a flatter voltage profile, and stronger thermal stability compared to other cathode materials. Here, we report the rational design of a biomimetic bone-inspired polyanionic Na3V2(PO4)3-reduced graphene oxide composite (BI-NVP) cathode that achieves ultrahigh rate charging and ultralong cycling life in a sodium ion battery. At a charging rate of 1 C, BI-NVP delivers 97% of its theoretical capacity and is able to retain a voltage plateau even at the ultra-high rate of 200 C. It also shows long cycling life with capacity retention of 91% after 10 000 cycles at 50 C. The sodium ion battery cells with a BI-NVP cathode and Na metal anode were able to deliver a maximum specific energy of 350 W h kg−1 and maximum specific power of 154 kW kg−1. In situ and postmortem analyses of cycled BI-NVP (including by Raman and XRD spectra) HRTEM, and STEM-EELS, indicate highly reversible dilation–contraction, negligible electrode pulverization, and a stable NVP-reduced graphene oxide layer interface. The results presented here provide a rational and biomimetic material design for the electrode architecture for ultrahigh power and ultralong cyclability of the sodium ion battery full cells when paired with a sodium metal anode.

25 ENERGY STORAGE↗
DOE OSTI2022

ECRAM Materials, Devices, Circuits and Architectures: A Perspective

Abstract Non‐von‐Neumann computing using neuromorphic systems based on two‐terminal resistive nonvolatile memory elements has emerged as a promising approach, but its full potential has not been realized due to the lack of materials and devices with the appropriate attributes. Unlike memristors, which require large write currents to drive phase transformations or filament growth, electrochemical random access memory (ECRAM) decouples the “write” and “read” operations using a “gate” electrode to tune the conductance state through charge‐transfer reactions, and every electron transferred through the external circuit in ECRAM corresponds to the migration of ≈1 ion used to store analogue information. Like static dopants in traditional semiconductors, electrochemically inserted ions modulate the conductivity by locally perturbing a host's electronic structure; however, ECRAM does so in a dynamic and reversible manner. The resulting change in conductance can span orders of magnitude, from gradual increments needed for analog elements, to large, abrupt changes for dynamically reconfigurable adaptive architectures. In this in‐depth perspective, the history of ECRAM, the recent progress in devices spanning organic, inorganic, and 2D materials, circuits, architectures, the rich portfolio of challenging, fundamental questions, and how ECRAM can be harnessed to realize a new paradigm for low‐power neuromorphic computing are discussed.

Talin, A. Alec↗
DOE OSTI2026

Observation of Iso-Symmetric Structural and Lifshitz Transitions in Quasi-One-Dimensional CrNbSe 5

Chalcogenides-rich transition metal compounds host a rich landscape of emergent quantum phenomena that are intimately governed by their quasi-onedimensional chemical-bonding frameworks and their response to external perturbations such as pressure. Here, we report a pressure-induced iso-symmetric structural transition in the quasi-one-dimensional compound CrNbSe 5 , in which the electronic ground state is controlled not by symmetry breaking but by a continuous reorganization of local bonding interactions. Applied pressure reversibly tunes CrNbSe 5 between semiconducting and semimetallic states, enabling access to low- and high-carrier electronic regimes through direct modulation of metal−chalcogen bonding. High-pressure singlecrystal X-ray diffraction directly resolves the evolution of Cr−Se and Nb−Se bond distances, coordination polyhedra, and connectivity, revealing a fully reversible semimetal−semiconductor−semimetal transition driven by gradual yet cooperative bond rearrangements within a preserved crystallographic symmetry. In contrast to chemical substitution, which irreversibly alters composition and introduces disorder, pressure acts as a clean, continuous control parameter that reshapes the bonding landscape without disrupting structural symmetry. These results establish CrNbSe 5 as a model system for electronically driven phase switching via tunable chemical bonding, highlighting iso-symmetric bond reorganization as a powerful design principle for pressure-controlled electronic and spintronic functionalities.

Compression↗
DOE OSTI2020

Numerical simulation of an atmospheric pressure plasma jet with coaxial shielding gas

A two-dimensional ( r, z ) numerical simulation of the discharge characteristics of an atmospheric pressure plasma jet (APPJ), with coaxial shielding gas, was performed. The helium working gas flowed in a central capillary tube, engulfing a needle electrode powered by 13.7 MHz radio frequency sinusoidal voltage. The N 2 shielding gas flowed in the annular space of a coaxial tube. These gases emerged, in laminar flow, in a 78%N 2 -21%O 2 -1%Ar dry air ambient. The characteristics of the APPJ with shielding gas were compared to those of the APPJ without shielding gas. The nitrogen shielding gas hindered the diffusion of oxygen and argon from the ambient air into the helium jet. With the shielding gas present, more nitrogen penetrated into the helium core, causing a shorter plasma ‘plume’. The flow rates of the working and shielding gas, critically affected the gas temperature, and in turn the discharge characteristics. For a He flow of 2 standard liters per minute (slm), switching on the nitrogen shielding gas flow (at 4.5 slm) reduced the on-axis O 2 and Ar mole fractions from 3.9 × 10 - 4 to 6.8 × 10 - 5 and from 1.9 × 10 - 5 to 3.3 × 10 - 6 , respectively, at an axial distance of 3 mm downstream of the nozzle. The radial profiles of the mole fractions of the ambient gases were monotonically and strongly decreasing towards the system axis, for short axial distances from the nozzle (~1 mm), but became progressively flatter at longer distances from the nozzle (3 mm and 5 mm). Simulation predictions captured the salient features of experimental data of ambient species mole fractions in the plasma jet, and the 706 nm optical emission intensity profiles of the He 3 3 S excited state.

Physics↗
NASA NTRS1986

The dynamics of magnetically trapped fluids. I - Implications for umbral dots and penumbral grains

A study of the magnetohydrodynamic system in which a nonmagnetized fluid in a gravitational field is surrounded by a fluid carrying a vertical magnetic field is presented. It is pointed out that this study can throw some light on the fine-structural features of a sunspot. The equilibrium configuration of the field-free fluid is a tapering column ending at an apex. The regions away form the apex can be studied by the slender flux tube approximation. A scheme developed to treat the apex indicates that, just below the apex, the radius of the tapering column opens up with a 3/2 power dependence on the depth below the apex. If the internal pressure of the field-free fluid is increased, the apex rises, and a static equilibrium may not be possible beyond a limit if the magnetic pressure drops quickly above a certain height. The nature of steady-flow solutions beyond this limit is investigated. Under conditions inside a sunspot, a column of field-free gas is found to rise with a velocity of about 100 km/hr. If umbral dots and penumbral grains are interpreted as regions where the field-free gas ultimately emerges, a very natural explanation of most of their observed properties is obtained.

Choudhuri, A. R.↗
DOE OSTI2022

Investigation of INL Site Implementation of ARG-US

The Packaging Certification and Life Cycle Management department at Argonne National Laboratory (ANL) developed a suite of monitoring systems collectively referred to here as ARG-US. ARG-US is used to provide necessary data for nuclear facility and system operation and maintenance. ARG-US has been previously demonstrated in hot cells, radioactive material (RAM) storage areas, and RAM shipment trucks. It has also been installed directly on RAM storage and shipment containers. ARG-US offers some unique advantages over other commercially available systems by using wireless data connections, battery power supplies, and customizable monitoring methods. Idaho National Laboratory (INL) has been tasked with investigating applications for ARG-US at INL site facilities, which are operated by several different contractors. The initial investigation scope centered on CPP-603 Wet & Dry Fuel Storage Facility in relation to the upcoming DOE Spent (SNF) Packaging Demonstration. The investigation has been led by the Used Fuel Management Department in the Nuclear Science and Technology Directorate. This investigation is expected to recommend processes or facilities at the INL site at which to implement ARG-US systems. INL has engaged local site technical and oversite representatives, security, nuclear safeguards, and program management to identify good candidates for ARG-US test implementations. INL has identified high-level goals for any INL site implementation of ARG-US: provide unique testing environments, prompt development of new monitoring methods/techniques for the ARG-US suite, and acquire useful monitoring for the user facility. To these ends, INL suggests 3 program areas for further investigation: CPP-603 Fuel Handling Cave (FHC), legacy mixed waste storage systems at Idaho Nuclear Technology & Engineering Center (INTEC) known as the “tank farm”, and periodic and emergency environmental monitoring. This progress report relates activities undertaken in this investigation, describes the preliminary areas of interest for limited scope ARG-US testing or implementation, and relays expected actions needed to complete the task scope. This report offers an opportunity to the program sponsor, technical leads at ANL, and INL site representatives to give feedback on the initial assessment and make recommendations on the forthcoming activities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Active magnetic regenerative cooling with smaller magnets

Magnetocaloric heat pumping near room temperature, a.k.a. magnetic cooling, relies on the active regenerator cycle to achieve functional temperature spans and realize economic and societal benefits promised by this emerging solid-state cooling technology. The cycle itself depends upon synchronizing oscillating flow of a heat transfer fluid through a solid porous active material matrix, or the refrigerant, with periods when the refrigerant is in the highest available (field-on) and in nearly zero (field-off) magnetic fields to accomplish heat transfer. With this in mind, in this work we analyze varying flow and magnetic field wave forms and the timing between when the fluid is pumped and when the magnetic field is turned on and off. We demonstrate that the volume and the cost of permanent magnet generating the field changes can be cut nearly in half with little to no effect on the device temperature span and cooling power normalized by the refrigerant mass.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Activated penetrant dynamics in glass forming liquids: size effects, decoupling, slaving, collective elasticity and correlation with matrix compressibility

In this work, we employ the microscopic self-consistent cooperative hopping theory of penetrant activated dynamics in glass forming viscous liquids and colloidal suspensions to address new questions over a wide range of high matrix packing fractions and penetrant-to-matrix particle size ratios. The focus is on the mean activated relaxation time of smaller tracers in a hard sphere fluid of larger particle matrices. This quantity also determines the penetrant diffusion constant and connects directly with the structural relaxation time probed in an incoherent dynamic structure factor measurement. The timescale of the non-activated fast dissipative process is also studied and is predicted to follow power laws with the contact value of the penetrant–matrix pair correlation function and the penetrant–matrix size ratio. For long time penetrant relaxation, in the relatively lower packing fraction metastable regime the local cage barriers are dominant and matrix collective elasticity effects unimportant. As packing fraction and/or penetrant size grows, much higher barriers emerge and the collective elasticity associated with the correlated matrix dynamic displacement that facilitates penetrant hopping becomes important. This results in a non-monotonic variation with packing fraction of the degree of decoupling between the matrix and penetrant alpha relaxation times. The conditions required for penetrant hopping to become slaved to the matrix alpha process are determined, which depend mainly on the penetrant to matrix particle size ratio. By analyzing the absolute and relative importance of the cage and elastic barriers we establish a mechanistic understanding of the origin of the predicted exponential growth of the penetrant hopping time with size ratio predicted at very high packing fractions. A dynamics-thermodynamics power law connection between the penetrant activation barrier and the matrix dimensionless compressibility is established as a prediction of theory, with different scaling exponents depending on whether matrix collective elasticity effects are important. Quantitative comparisons with simulations of the penetrant relaxation time, diffusion constant, and transient localization length of tracers in dense colloidal suspensions and cold viscous liquids reveal good agreements. Multiple new predictions are made that are testable via future experiments and simulations. Extension of the theoretical approach to more complex systems of high experimental interest (nonspherical molecules, semiflexible polymers, crosslinked networks) interacting via variable hard or soft repulsions and/or short range attractions is possible, including under external deformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2002

Space and Terrestrial Photovoltaics: Synergy and Diversity

A historical view of the research and development in photovoltaics from the perspective of both the terrestrial and the space communities is presented from the early days through the '70s and '80s and the '90s and beyond. The synergy of both communities in the beginning and once again in the present and hopefully future are highlighted, with examples of the important features in each program. The space community which was impressed by the light-weight and reliability of photovoltaics drove much of the early development. Even up to today, nearly every satellites and other scientific space probe that has been launched has included some solar power. However, since the cost of these power systems were only a small fraction of the satellite and launch cost, the use of much of this technology for the terrestrial marketplace was not feasible. It was clear that the focus of the terrestrial community would be best served by reducing costs. This would include addressing a variety of manufacturing issues and raising the rate of production. Success in these programs and a resulting globalization of effort resulted in major strides in the reduction of PV module costs and increased production. Although, the space community derived benefit from some of these advancements, its focus was on pushing the envelope with regard to cell efficiency. The gap between theoretical efficiencies and experimental efficiencies for silicon, gallium arsenide and indium phosphide became almost non-existent. Recent work by both communities have focused on the development thin film cells of amorphous silicon, CuInSe2 and CdTe. These cells hold the promise of lower costs for the terrestrial community as well as possible flexible substrates, better radiation resistance, and higher specific power for the space community. It is predicted that future trends in both communities will be directed toward advances through the application of nanotechnology. A picture is emerging in which the space and terrestrial solar cell communities shall once again share many common goals and, in fact, companies may manufacture both space and terrestrial solar cells in III-V materials and thin film materials. Basic photovoltaics research including these current trends in nanotechnology provides a valuable service for both worlds in that fundamental understanding of cell processes is still vitally important, particularly with new materials or new cell structures. It is entirely possible that one day we might have one solar array design that will meet the criteria for success in both space and on the Earth or perhaps the Moon or Mars.

Bailey, Sheila↗
DOE OSTI2022

Considerations for Hydride Moderator Readiness in Microreactors

The emergence of microreactor technology has helped to drive supporting nuclear materials qualification and acceptance processes. One essential component in these small reactors is a solid moderator, which typically consists of metal hydride and cladding. While the behavior and performance of metal-hydride moderators go back to early advanced reactor development for nuclear-powered aviation and space propulsion, there remains a knowledge gap in the understanding of hydrogen transport–related phenomena and irradiation performance for hydride moderators. This impacts the acceptance/qualification of hydride moderators for microreactors. The goal of this technical note is to lay out a potential path forward for advanced moderator qualification and acceptance for designers and developers of microreactors. The proposed approach has benefited from a model microreactor core with the design parameters of a hydride moderator. Based on the model core and design parameters, a simple chart was developed for the major challenges of hydride moderators where potential incidents, causes, effects, and resolutions are described. The relation between the offered resolutions and the maturity of the metal-hydride moderator technology was emphasized using technological readiness. Technological readiness levels (TRLs) were clustered to three sets: physical phenomena related, reactor irradiations, and system demonstration. Some essential needs to fill the knowledge gaps are discussed for physical phenomena–related TRLs. For reactor irradiations, the importance of identifying goals and priorities is stressed to reach certain TRLs. For system demonstration, it is noted that metal-hydride moderator qualification must comply with the overall microreactor design.

36 MATERIALS SCIENCE↗
NASA NTRS1998

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

Wong, Wee Ling↗