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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Structure and Reactivity of Binuclear Cu Active Sites in Cu-CHA Zeolites for Stoichiometric Partial Methane Oxidation to Methanol

Aluminosilicate zeolites exchanged with copper ions facilitate partial methane oxidation (PMO) to methanol in stoichiometric oxidation and reduction cycles, yet the identities of active Cu sites and details of the reaction mechanism remain debated. Here, we use the high-symmetry chabazite (CHA) zeolite framework as a model support to probe the relationship between bulk composition, Cu speciation, and response to various oxidizing and reducing treatments. Density functional theory and first-principles thermodynamics combined with statistical models reveal that Cu speciation and composition depend strongly on Al configuration and external gas conditions. Cu-CHA samples were synthesized to survey broad regions of Si/Al and Cu/Al composition space and framework Al proximity. Characterization by in situ X-ray absorption and UV–visible spectroscopy during exposure to different oxidation conditions reveal that the extent of Cu oxidation is sensitive to activation conditions and thus that both kinetic and thermodynamic factors influence Cu oxidizability in a given material. Similar characterizations during CO reduction reveal that CO titrates Cu 2+ in amounts suggesting the presence of both O- and O 2 -bridged species. In contrast, CH 4 and autoreduction (He) treatments reduce similar but smaller numbers of Cu sites than CO, implicating O 2 -bridged Cu dimers as a potential common intermediate in the former reduction pathways. Furthermore, a systematic increase in methanol yields (per Cu) in stoichiometric PMO cycles increase with the fraction of binuclear O x -bridged Cu sites suggests these species as active sites, as depicted in an updated PMO reaction mechanism.

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

Exploring the Structure–Function Relationship in Iridium–Cobalt Oxide Catalyst for Oxygen Evolution Reaction across Different Electrolyte Media

Renewable hydrogen generation from water electrolysis offers a viable path to decarbonization if the costs can be reduced. The iridium-based anode catalyst is one of the most expensive components in electrolyzers. We propose reducing iridium usage by substituting Ir with Co, a more affordable metal, in the mixed oxide phase to enhance the catalytic activity while minimizing Ir consumption. A modified surfactant-assisted Adams fusion synthesis technique was developed as a scalable method for producing IrCo oxide nanoparticles. The synthesized material outperforms the commercial baseline, iridium oxide with carbon (IrOx_C), in both acidic and alkaline media. Acid etching (IrCo_ae) further enhances activity by selectively removing Co to expose more active sites. IrCo_ae achieved a significantly lower overpotential at 10 mA/cm 2 compared to IrOx_C, with reductions of approximately 18% under acidic conditions and 14% under alkaline conditions. This work demonstrates that the proposed synthesis method enables efficient Ir utilization and can be adapted to enhance catalyst stability for renewable hydrogen production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Influence of thermal treatment on structure and catalytic performance of ceria-zirconia supported copper oxide (CuO x /Ce y Zr 1-y O 2 ) catalysts for CO oxidation

Copper oxide (CuO x ) supported on ceria-zirconia (Ce y Zr 1-y O 2 , y = 1.0, 0.5, 0.0) catalysts were investigated to elucidate the effects of thermal treatment on their physicochemical properties and catalytic performance in carbon monoxide (CO) oxidation. Here, the catalysts were synthesized via a one-pot chemical vapor deposition (OP-CVD) method at 700˚C and 900˚C with controlled Cu loading. Characterization techniques, including synchrotron X-ray diffraction (S-XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), inductively coupled plasma spectroscopy (ICP), and N 2 adsorption-desorption, were implemented to probe the crystalline structure, molecular and electronic structure, oxygen vacancies, specific surface area (SSA) and metal loading. CO oxidation was chosen as a model reaction to explore the structure-catalytic performance relationship. A ∼100% CO conversion was achieved at < 150˚C, particularly with the CuO x /CeO 2 catalyst calcined at 700˚C. In contrast, calcination at 900˚C caused a ∼90% decrease in SSA and a ∼24% increase in T 50 . Activity tests revealed that increasing ZrO 2 content lowered CO oxidation activity despite generating more defect sites. In-situ measurement of the 700 °C calcined samples revealed the presence of stable and unstable defects in CuO x /Ce 0.5 Zr 0.5 O 2 and CeO 2 respectively, which play a key role in the activity of the catalysts. The results highlight that catalytic performance is closely related to the SSA. Furthermore, an optimum calcination temperature favor significant oxygen vacancy formation with required CuO x -support interactions, enhancing redox properties and catalytic performance.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Explainable tokamak-agnostic forecasting of fusion plasma instability via megahertz turbulent fluctuations

Scientific applications of artificial intelligence (AI) often remain limited by device-specific training and unexplained “black-box” approaches, creating fundamental barriers to cross-system generalization. This challenge is critical for nuclear fusion, where future reactors will have limited operational data for AI training. Here, we demonstrate that our neural network, trained solely on megahertz-scale turbulence measurements from one machine (DIII-D), forecasts Type-I edge localized mode (ELM) onsets in a different tokamak (KSTAR) through zero-shot weight transfer following physics-consistent preprocessing without device-specific retraining. Through an explainable AI framework combining gradient-weighted class activation mapping with physics validation, we reveal that our network can internalize physics relationships governing the ELM instabilities rather than memorizing device-specific patterns. The network perceives spatiotemporal features that correlate consistently with independently calculated instability growth rates, magnetohydrodynamic stability limits, and pedestal structure dynamics. Statistical analyses of dimensionally-reduced saliency features reveal the identical triangular features between the saliency representations, instability growth rates, and prediction probability across tokamaks, providing evidence that our forecasting system can show tokamak-agnostic generalization. This work contributes to a foundation for explainable scientific AI systems, where cross-system developments are essential for transcending traditional domain-specific constraints.

AI↗
NASA NTRS1994

Wavelets, period-doubling, and time-frequency localization with application to organization of convection over the tropical western Pacific

In this paper, preliminary results in using orthogonal and continuous wavelet transform (WT) to identify period doubling and time-frequency localization in both synthetic and real data are presented. First, the Haar WT is applied to synthetic time series derived from a simple nonlinear dynamical system- a first-order quadratic difference equation. Second, the complex Morlet WT is used to study the time-frequency localization of tropical convection based on a high-resolution Japanese Geostationary Meteorological Satellite infrared (IR) radiance dataset. The Haar WT of the synthetic time series indicates the presence and distinct separation of multiple frequencies in a period-doubling sequence. The period-doubling process generates a multiplicity of intermediate frequencies, which are manifested in the nonuniformity in time with respect to the phase of oscillations in the lower frequencies. Wavelet transform also enables the detection of extremely weak signals in high-order subharmonics resulting from the period-doubling bifurcations. These signals are either undetected or considered statistically insignificant by traditional Fourier analysis. The Morlet WT of the IR radiance dataset indicates the presence of multiple timescales, which are localized in both frequency and time. There are two regimes in the variation of IR radiance, corresponding to the wet and dry periods. Multiple timescales, ranging from semidiurnal, diurnal, synoptic, to intraseasonal with embedding structures, are active in the wet regime. In particular, synoptic variability is more prominent during the wet phase of an intensive intraseasonal cycle. These are not only consistent with, but also show more details than, previous findings by using other techniques. The phase-locking relationships among the oscillations with different time-scales suggest that both synoptic and intraseasonal variations may be mixed oscillations due to the interaction of self-excited oscillations in the tropical atmosphere and external forcings such as annual and diurnal solar radiation variations. Both examples show that WT is a powerful tool for analysis of phenomena involving multiscale interactions that exhibit localization in both frequency and time. A discussion on the caveats in the use of WT in geophysical data analysis is also presented.

Weng, Hengyi↗
NASA NTRS2004

Lunar and Planetary Science XXXV: Impact-Related Deposits

The session "Impact-Related Deposits" included:Evidence for a Lightning-Strike Origin of the Edeowie Glass; 57Fe M ssbauer Spectroscopy of Fulgurites: Implications for Chemical Reduction; Ca-Metasomatism in Crystalline Target Rocks from the Charlevoix Structure, Quebec, Canada: Evidence for Impact-related Hydrothermal Activity; Magnetic Investigations of Breccia Veins and Basement Rocks from Roter Kamm Crater and Surrounding Region, Namibia; Petrologic Complexities of the Manicouagan Melt Sheet: Implications for 40Ar-39Ar Geochronology; Laser Argon Dating of Melt Breccias from the Siljan Impact Structure, Sweden: Implications for Possible Relationship to Late Devonian Extinction Events; Lunar Impact Crater, India: Occurrence of a Basaltic Suevite?; Age of the Lunar Impact Crater, India: First Results from Fission Track Dating; The Fluidized Chicxulub Ejecta Blanket, Mexico: Implications for Mars; Low Velocity Ejection of Boulders from Small Lunar Craters: Ground Truth for Asteroid Surfaces; Ejecta and Secondary Crater Distributions of Tycho Crater: Effects of an Oblique Impact; Potassium Isotope Systematics of Crystalline Lunar Spherules from Apollo 16; Late Paleocene Spherules from the North Sea: Probable Sea Floor Precipitates: A Silverpit Provenance Unproven; A Lithological Investigation of Marine Strata from the Triassic-Jurassic Boundary Interval, Queen Charlotte Islands, British Columbia, Including a Search for Shocked Quartz; Triassic Cratered Cobbles: Shock Effects or Tectonic Pressure?; Regional Variations of Trace Element Composition Within the Australasian Tektite Strewn Field; Cretaceous-Tertiary Boundary Microtektite-bearing Sands and Tsunami Beds, Alabama Gulf Coastal Plain; Sand Lobes on Stewart Island as Probable Impact-Tsunami Deposits; Distal Impact Ejecta, Uppermost Eocene, Texas Coastal Plain; and Continental Impact Debris in the Eltanin Impact Layer.

Source record↗
NASA NTRS2016

Transgenic Mouse Model for Reducing Oxidative Damage in Bone

Bone loss can occur due to many challenges such age, radiation, microgravity, and Reactive Oxygen Species (ROS) play a critical role in bone resorption by osteoclasts (Bartell et al. 2014). We hypothesize that suppression of excess ROS in skeletal cells, both osteoblasts and osteoclasts, regulates skeletal growth and remodeling. To test our hypothesis, we used transgenic mCAT mice which overexpress the human anti-oxidant catalase gene targeted to the mitochondria, the main site for endogenous ROS production. mCAT mice have a longer life-span than wildtype controls and have been used to study various age-related disorders. To stimulate remodeling, 16 week old mCAT mice or wildtype mice were exposed to treatment (hindlimb-unloading and total body-irradiation) or sham treatment conditions (control). Tissues were harvested 2 weeks later for skeletal analysis (microcomputed tomography), biochemical analysis (gene expression and oxidative damage measurements), and ex vivo bone marrow derived cell culture (osteoblastogenesis and osteoclastogenesis). mCAT mice expressed the transgene and displayed elevated catalase activity in skeletal tissue and marrow-derived osteoblasts and osteoclasts grown ex vivo. In addition, when challenged with treatment, bone tissues from wildtype mice showed elevated levels of malondialdehyde (MDA), indicating oxidative damage) whereas mCAT mice did not. Correlation analysis revealed that increased catalase activity significantly correlated with decreased MDA levels and that increased oxidative damage correlated with decreased percent bone volume (BVTV). In addition, ex-vivo cultured osteoblast colony growth correlated with catalase activity in the osteoblasts. Thus, we showed that these transgenic mice can be used as a model to study the relationship between markers of oxidative damage and skeletal properties. mCAT mice displayed reduced BVTV and trabecular number relative to wildtype mice, as well as increased structural model index in the cancellous tibia. Treatment caused bone loss in wildtype mice, as expected. Treatment also caused deficits in microarchitecture of mCAT mice, although less severe than wildtype mice in some parameters (percent bone volume, structural model index and cortical area). In conclusion, our results indicate that endogenous ROS signaling in both osteoblast and osteoclast lineage cells contributes to skeletal growth and remodeling, and quenching oxidative damage could play a role in bone loss prevention.

transgenic mice↗
DOE OSTI2022

Dissecting Critical Factors for Electrochemical CO 2 Reduction on Atomically Precise Au Nanoclusters

Here, this work investigates the critical factors impacting electrochemical CO 2 reduction reaction (CO 2 RR) using atomically precise Au nanoclusters (NCs) as electrocatalysts. First, the influence of size on CO 2 RR is studied by precisely controlling NC size in the 1–2.5 nm regime. We find that the electrocatalytic CO partial current density increases for smaller NCs, but the CO Faradaic efficiency (FE) is not directly associated with the NC size. This indicates that the surface-to-volume ratio, i.e. the population of active sites, is the dominant factor for determining the catalytic activity, but the selectivity is not directly impacted by size. Second, we compare the CO 2 RR performance of Au 38 isomers (Au 38 Q and Au 38 T) to reveal that structural rearrangement of identical size NCs can lead to significant changes in both CO 2 RR activity and selectivity. Au 38 Q shows higher activity and selectivity towards CO than Au 38 T, and density functional theory (DFT) calculations reveal that the average formation energy of the key *COOH intermediate on the proposed active sites is significantly lower on Au 38 Q than Au 38 T. These results demonstrate how the structural isomerism can impact stabilization of reaction intermediates as well as the overall CO 2 RR performance of identical size Au NCs. Overall, this work provides important structure–property relationships for tailoring the NCs for CO 2 RR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

De novo design of protein structure and function with RFdiffusion

Abstract There has been considerable recent progress in designing new proteins using deep-learning methods 1–9 . Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models 10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence–structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Science & Technology - Other Topics↗
DOE OSTI2022

Data-driven based coordinated smart inverter control for distributed energy resources

Smart inverters (SI) for distributed energy resources (DER) are becoming popular since they have the ability to stabilize as well as restore the voltage and frequency of power systems. Aiming at establishing the mathematical models combined with SI control methods, multiple optimization methods are developed. However, the computational complexity of solving such a mathematical model with various uncertainties limits the real-time application of the SI control. To conquer this challenge, a data-driven-based SI control approach is developed to achieve coordinated control in the high penetration DER system. First, an optimization problem for maximizing the active power generation and minimizing the power loss is designed using the Volt/VAR control. To reduce the time consumption, the recurrent neural network (RNN) is proposed to model the relationship between the uncertainties and control actions during the offline site. The RNN with different sub-structures such as the long short-term memory cell and gated recurrent unit cell are included to enrich the diversity of features. In the last stage, different experiment comparisons, including multiple uncertainties maps and stateof- art machine learning methods, are conducted to verify the effectiveness of the proposed method based on the IEEE 123 bus power system. The results demonstrate that the proposed method can effectively achieve a rapid and coordinated control with a lower error rate.

Qiu, Wei↗
DOE OSTI2021

The Saga of Endocrine FGFs

Fibroblast growth factors (FGFs) are cell-signaling proteins with diverse functions in cell development, repair, and metabolism. The human FGF family consists of 22 structurally related members, which can be classified into three separate groups based on their action of mechanisms, namely: intracrine, paracrine/autocrine, and endocrine FGF subfamilies. FGF19, FGF21, and FGF23 belong to the hormone-like/endocrine FGF subfamily. These endocrine FGFs are mainly associated with the regulation of cell metabolic activities such as homeostasis of lipids, glucose, energy, bile acids, and minerals (phosphate/active vitamin D). Endocrine FGFs function through a unique protein family called klotho. Two members of this family, α-klotho, or β-klotho, act as main cofactors which can scaffold to tether FGF19/21/23 to their receptor(s) (FGFRs) to form an active complex. There are ongoing studies pertaining to the structure and mechanism of these individual ternary complexes. These studies aim to provide potential insights into the physiological and pathophysiological roles and therapeutic strategies for metabolic diseases. Herein, we provide a comprehensive review of the history, structure–function relationship(s), downstream signaling, physiological roles, and future perspectives on endocrine FGFs.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1979

Photovoltaic systems perspective

This paper summarizes the elements of photovoltaic power system and clarifies the terminology currently used. The relationship of system efficiency and cost is described particularly for the Balance of Photovoltaic System (BOPS) area. The current status of the BOPS development activity is described. The photovoltaic systems terminology is found to be on the road to standardization. Power conditioning, energy storage, and support structure are found to be BOPS cost and/or efficiency drivers. Although the current BOPS activity has identified low-cost/high-efficiency components, further development work is necessary.

Sutton, P. D.↗
DOE OSTI2020

Community structure – Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. In this work, we test these assertions using methane (CH 4 )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH 4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Structural dynamics of first-order phase transition in giant magnetocaloric La(Fe,Si) 13 : The free energy landscape

Maximizing the performance of magnetic refrigerators and thermomagnetic energy harvesters is imperative for their successful implementation and can be done by maximizing their operation frequency. One of the features delimiting the frequency and efficiency of such devices is the phase transition kinetics of their magnetocaloric/thermomagnetic active material. While previous studies have described the magnetic component governing the kinetics of the magnetovolume phase transition in La(Fe,Si) 13 giant magnetocaloric materials, a comprehensive description of its structural component has yet to be explored. In this study, in situ synchrotron X-ray diffraction is employed to describe the structural changes upon magnetic field application/removal. Long magnetic field dependent relaxation times up to a few hundred seconds are observed after the driving field is paused. The phase transition is found to be highly asymmetric upon magnetic field cycling due to the different Gibbs energy landscapes and the absence of an energy barrier upon field removal. An exponential relationship is found between the energy barriers and the relaxation times, suggesting the process is governed by a non-thermal activation over an energy barrier process. Such fundamental knowledge on first-order phase transition kinetics suggests pathways for materials optimization and smarter design of magnetic field cycling in real-life devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Mechanochemical Regulation of Oxidative Addition to a Palladium(0) Bisphosphine Complex

Here, we report the effect of force applied to the biaryl backbone of a bisphosphine ligand on the rate of oxidative addition of bromobenzene to a ligand-coordinated palladium center. Local compressive and tensile forces on the order of 100 pN were generated using a stiff stilbene force probe. A compressive force increases the rate of oxidative addition, whereas a tensile force decreases the rate, relative to that of the parent complex of strain-free ligand. Rates vary by a factor of ~6 across ~340 pN of force applied to the complexes. The crystal structures and DFT calculations support that force-induced perturbation of the geometry of the reactant is negligible. The force-rate relationship observed is mainly attributed to the coupling of force to nuclear motion comprising the reaction coordinate. These observations inform the development of catalysts whose activity can be tuned by an external force that is adjusted within a catalytic cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Composition-dependent fracture energy in metallic glasses

The interplay between metallic glasses (MGs) mechanical properties, fracture energy (G), and glass-forming ability (GFA) and their dependence on alloy composition remain poorly understood. Here, we perform molecular dynamics simulations to investigate the intrinsic composition-dependence of G in Cu x Zr 100-x MGs (x = 20, 30, 40, 50, 64). The results indicate that the value of G increases with Cu content. In addition, it is revealed that MGs with higher G values display higher Poisson’s ratio (ν) and GFA, suggesting a close correlation between fracture toughness, mechanical properties, and GFA. This correlation between G, ν and GFA can be understood based on the fragility (m) of supercooled liquids, which is directly related to the structural heterogeneity in MGs. Larger m values are related to dynamic slowdown and supercooled liquid stabilization, which enhance GFA and the formation of pronounced structural heterogeneity, comprised of loosely packed regions that favor β-relaxation and the activation of shear transformation zones. Those concurrently promote the expansion of the plastic zone at the crack tip, enhancing the observed value of G. Furthermore, these simulation results shed light on the intrinsic relationship between fracture toughness, mechanical properties, and alloy composition in MGs.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-situ/operando study of Cu-based nanocatalysts for CO 2 electroreduction using electrochemical liquid cell TEM

The structure of a nanocatalyst during electrocatalytic reactions often deviates from its pristine structure due to intrinsic properties, or physical and chemical adsorption at the catalytic surfaces. Taking Cu-based catalysts for CO 2 electroreduction reactions (CO 2 RR) as an example, they often experience segregation, leaching, and alloying during reactions. With the recent breakthrough development of high-resolution polymer electrochemical liquid cells, in-situ electrochemical liquid cell transmission electron microscopy (EC-TEM) alongside other advanced microscopy techniques, has become a powerful platform for revealing electrocatalysts restructuring at the atomic level. Considering the complex reactions involving electrified solid-liquid interfaces and catalyst structural evolution with intermediates, systematic studies with multimodal approaches are crucial. In this article, we demonstrate a research protocol for the study of electrocatalysts structural evolution during reactions using the in-situ EC-TEM platform. Using Cu and CuAg nanowire catalysts for CO 2 RR as model systems, we describe the experimental procedures and findings. We highlight the platform’s crucial role in elucidating atomic-scale pathways of nanocatalyst restructuring and identifying catalytic active sites, as well as avoiding potential artifacts to ensure unbiased conclusions. Using the multimodal characterization toolbox, we provide the opportunity to correlate the structure of a working catalyst with its performance. Finally, we discuss advancements as well as the remaining gap in elucidating the structural-performance relationship of working catalysts. We expect this article will assist in establishing guidelines for future investigations of complex electrochemical reactions, such as CO 2 RR and other catalytic processes, using the in-situ EC-TEM platform.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Spacelab shaping space operations planning

An up-to-date picture is presented of the organizational structure, the key management personnel, and management relationships of the Spacelab program. Attention is also given to Spacelab's development status and plans for its operations. A number of charts are provided to illustrate the organizational relations. It is pointed out that the parties involved in Spacelab activities must yet resolve questions about ownership of transportation-system elements, payloads, ground support facilities, and data obtained from space missions.

Steven, F. R.↗