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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

The BioHome: A spinoff of space technology

The discussion of the BioHome is prefaced with some information about the work done at the environmental lab over the past 15 years concerning environmental issues related to biological life support such as the use of water hyacinths for wastewater purification, artificial marshes, indoor polluted air revitalization, and the reduction of organic contaminants using a biological system comprised of plants and microorganisms. One of the main concerns, especially with respect to a closed environment, is whether or not these systems are expelling microorganisms into the air. Analyses are being conducted to determine the numbers and types of microbes that are emitted. The BioHome is a 650 sq ft habitat that will enable the evaluation of the efficiency of bioregenerative technology in a closed system. This BioHome system is described and its functions discussed.

Johnson, Anne↗
NASA NTRS1994

Building brains for bodies

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

Brooks, Rodney Allen↗
NASA NTRS1987

UV-B radiation and photosynthetic irradiance acclimate eggplant for outdoor exposure

Treatment of greenhouse-grown eggplant (Solanum melongena L. var. esculentum Nees. 'Burpee's Black Beauty') seedlings with supplemental photosynthetically active radiation from cool-white fluorescent lamps increased growth of plants subsequently transferred outdoors relative to growth of plants that received no supplemental radiation or were shaded to 45% of solar irradiation in the greenhouse before transfer outdoors. Eggplant seedlings transferred outdoors were placed under plastic tarps either to provide relative protection from solar ultraviolet-B (UV-B) radiation (280-315 nm) using Mylar film or to allow exposure to UV-B using cellulose acetate. Protection of seedlings from UV-B radiation resulted in greater leaf expansion than for UV-B-exposed seedlings, but no change in leaf or shoot dry weight occurred after 9 days of treatment. Specific leaf weight increased in response to UV-B exposure outdoors. Exposure of eggplant to UV-B radiation from fluorescent sunlamps in the greenhouse also decreased leaf expansion and leaf and shoot dry weight gain after 5 days of treatment. However, there were no differences in leaf or shoot dry weight relative to control plants after 12 days of UV-B treatment, indicating that UV-B treated plants had acclimated to the treatment and actually had caught up with non-UV-B-irradiated plants in terms of growth.

NASA Program Space Biology↗
NASA NTRS1972

OFO experimental techniques and preliminary conclusions - Is artificial gravity needed during prolonged weightlessness.

The technique of single unit recording from body systems generating electrical pulses coherent with their basic function (CNS, muscles, sense organs) has been proved feasible during the OFO A orbital flight, an automatic physiological experiment. The results of recording 155 hours of orbital flight of pulses from the nerve fibres of four vestibular gravity sensors in two bull frogs indicate that the vestibular organ adjusts to zero g. As all the other biological changes observed during orbit are due to lack of exercise, it is concluded that artificial gravity might not be necessary during prolonged space missions or on low gravity celestial bodies.

Gualtierotti, T.↗
DOE OSTI2025

Mapping Rare Earths and Toxics in E-Waste via Hyperspectral Imaging and Machine Learning

Electronic waste (e-waste) presents a mounting challenge to environmental sustainability due to its complex composition, which includes high-value rare earth elements, hazardous organic compounds, and non-recyclable plastics. Accurate and scalable material classification is essential for enabling efficient resource recovery and safe recycling practices. This study introduces a confidence-aware classification pipeline that combines mid-infrared hyperspectral imaging (HSI), spectral angle mapping (SAM), and iterative machine learning to perform pixel-level material identification across e-waste devices. A curated spectral library encompassing artificial materials (e.g., plastic iron oxide, galvanized metals), minerals (e.g., allanite, hematite), and organic compounds (e.g., benzanthracene, toluene) was used to generate pseudo-labels, each assigned a confidence score based on SAM-derived spectral similarity. High-confidence samples from seven consumer electronics—digital cameras, keyboards, laptop fans, modems, motherboards, TV remotes, and speakers—were iteratively expanded and classified using models such as Support Vector Machine (SVM), Random Forest, Gradient Boosting Classifier, Partial Least Squares Discriminant Analysis (PLSDA) and Logistic Regression. The best-performing classifiers achieved macro F1 scores approaching 1.0. Results revealed widespread plastic content (dominated by plastic iron oxide), the presence of rare earth-bearing minerals like cerium-containing allanite, and pervasive detection of hazardous organics such as benzanthracene. Principal Component Analysis (PCA) visualizations and confusion matrices confirmed high separability and robust classification performance. This methodology enables precise, non-destructive, and scalable classification of heterogeneous e-waste streams. It supports automated, hazard-aware sorting in recycling workflows, facilitating selective recovery of critical materials and compliance with circular economy goals. The confidence-aware framework provides a foundation for real-time deployment in industrial settings, offering significant implications for smart e-recycling infrastructure and policy-driven material stewardship.

Circular economy↗
DOE OSTI2025

Decoding Antenna Behavior in Metal—Organic Frameworks

Metal–organic frameworks (MOFs) define a solid-state platform for developing artificial photosystems. Efficient anisotropic exciton migrations in these frameworks entail “antenna behavior” that can power up the distal interior reaction centers (RC), driving charge separation between donor-acceptor pairs. Reminiscent of the natural light-harvesting complex, such processes can achieve high quantum yield by exploiting the vast interior surface of the porous crystallites. It is important to understand the optimum positioning of the RC site relative to the anisotropic exciton migration path within these frameworks. The efficiency of such antenna behavior is probed here through Stern–Volmer (SV) type analysis with a series of node-anchored redox quenchers, ferrocene-carboxylate, ferrocene acetate, and dinitrobenzoate. Decoding various intrinsic processes, this work constructs a revised SV formalism in solid assembly that hosts ultrafast anisotropic exciton migration to account for the intrinsic exciton hopping rate from the extrinsic electron transfer rate, and the dimension of effective quenching. In conclusion, this transformative understanding can be applied to other relevant solid-state assemblies.

Saha, Bapan [Southern Illinois University, Carbond↗
NASA NTRS1975

Search for and investigation of extraterrestrial forms of life

Correct combinations of remote, analytic, and functional methods and measuring devices for detecting extraterrestrial life are elaborated. Considered are techniques and instruments available both on earth and aboard spacecraft and artificial planetary satellites. Emphasis is placed on the abiogenetic synthesis of organic compounds formed in photosynthesis on Mars.

Rubin, A. B.↗
NASA NTRS1985

Artificial intelligence - NASA

Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

Erickson, J. D.↗
NASA NTRS2016

Perchlorate and Volatiles of the Brine of Lake Vida (Antarctica): Implication for the in Situ Analysis of Mars Sediments

The cold (-13.4 C), cryoencapsulated, anoxic, interstitial brine of the 27 m-thick ice of Lake Vida (Victoria Valley, Antarctica) contains 49 microgram L-1 of perchlorate and 11 microgram L-1 of chlorate. Lake Vida brine (LVBr) may provide an analog for potential oxychlorine-rich subsurface brine on Mars. LVBr volatiles were analyzed by solid-phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) with two different SPME fibers. With the exception of volatile organic sulfur compounds, most other volatiles observed were artifacts produced in the GC injector when the thermal decomposition products of oxychlorines reacted with reduced carbon derived from LVBr and the SPME fiber phases. Analysis of MilliQ water with perchlorate (40 microgram L-1) showed low level of organic artifacts, reflecting carbon limitation. In order to observe sample-derived organic compounds, both in analog samples and on Mars, the molar abundance of reduced carbon in a sample must exceed those of O2 and Cl2 produced during decomposition of oxychlorines. This suggests that the abundance of compounds observed by the Sample Analysis at Mars (SAM) instruments in Sheepbed samples (CB-3, CB5, and CB6) may be controlled by an increase in the reduced-carbon/oxychlorine ratio of these samples. To increase chances of in situ detection of Martian organics during pyrolysis-GC-MS, we propose that the derivatization agents stored on SAM may be used as an external source of reduced carbon, increasing artificially the reduced-carbon to perchlorate ratio during pyrolysis, allowing the expression of more abundant and perhaps more diverse Martian organic matter.

Mars analog experiment↗
DOE OSTI2025

Control of Energy Transport and Transduction in Photosynthetic Down-Conversion (Final Technical Report)

The research conducted under this contract focused on three areas related to control of energy transport and transduction in natural and synthetic light harvesting systems: (1) experimental and theoretical studies exploring the use of ultrafast laser pulse shaping to manipulate the initially excited states of multi-chromophore biological light harvesting networks and influence the early time energy transfer and electronic and vibrational relaxation pathways, (2) fundamental theoretical developments aimed at computing and analyzing the dynamics of excitations of complex heterogeneous environments and nano structures, and (3) joint experimental and theoretical design studies of artificial light harvesting materials exploring the influence of incorporating different types of organic layers in low dimensional lead halide perovskite materials on their hot carrier relaxation dynamics, and theoretical studies of the design of nano structured light harvesting antenna systems. These research projects supported the training of three theoretical and computational graduate students, one experimental graduate student, and one experimental post-doctoral researcher. The research has been published in seven peer reviewed papers and presented at several international meetings and workshops.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1989

The reusable reentry satellite: A new capability for NASA - A vehicle for international cooperation

NASA's LifeSat program, which is designed to study biological systems, is described. The program is also designed to understand how living organisms respond to microgravity as low as 0.00001 G, various levels of artificial gravity up to 1.5 G, and cosmic radiation. Modules to be developed for LifeSat missions include specialized modules to support animals, plants, cells, and tissues.

Ballard, Rodney W.↗
NASA NTRS2002

Artificial cells: prospects for biotechnology

A variety of techniques can now be used to alter the genome of a cell. Although these techniques are very powerful, they have limitations related to cost and efficiency of scale. Artificial cells designed for specific applications combine properties of biological systems such as nanoscale efficiency, self-organization and adaptability at relatively low cost. Individual components needed for such structures have already been developed, and now the main challenge is to integrate them in functional microscopic compartments. It will then become possible to design and construct communities of artificial cells that can perform different tasks related to therapeutic and diagnostic applications.

Review↗
NASA NTRS1995

An Overview of ANN Application in the Power Industry

The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.

artificial neural networks ANN electric power syst↗
NASA NTRS2001

Artificial Cells: Prospects for Biotechnology

A variety of techniques can now be used to alter the genome of a cell. Although these techniques are very powerful, they also have limitations related to cost and efficiency of scale. Artificial cells designed for specific applications combine properties of biological systems such as nano-scale efficiency, self-organization and adaptability at relatively low cost. Individual components needed for such structures have already been developed, and now the main challenge is to integrate them in functional microscopic compartments. It will then become possible to design and construct communities of artificial cells that can perform different tasks related to therapeutic and diagnostic applications.

Pohorille, Andrew↗
NASA NTRS2022

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning↗
DOE OSTI2026

Functionalized Metal–Organic Framework Thin Films for Stable and Efficient Electrochemical Water Oxidation under Near-Neutral Conditions

The development of molecularly modified metal− organic frameworks (MOFs) for electrochemical water oxidation has emerged as a promising strategy for efficient artificial photosynthesis. In this study, a ruthenium-based water oxidation catalyst (WOC) was incorporated into the UiO-67 framework, forming RuM−UiO-67 films grown directly on conductive FTO substrates. These modified films demonstrate efficient water oxidation activity at near-neutral pH (pH 6), operating at a low overpotential of ∼600 mV. The catalyst exhibits a turnover frequency (TOF) of (0.32 ± 0.02) s −1 at 1.5 V versus the normal hydrogen electrode (NHE) in buffered solution (pH 6) for the oxygen evolution reaction. Notably, incorporation into the MOF results in a 12-fold increase in electroactive surface coverage compared to a monolayer of the same catalyst on bare FTO. Faradaic efficiency analysis revealed incomplete conversion to O 2 , and follow-up iodometric analysis confirmed the formation of H 2 O 2 as a competing two-electron oxidation product during electrocatalysis. These results highlight the utility of MOF-based architectures for maximizing the catalyst accessibility and stability under electrochemical water oxidation conditions.

catalysts↗
DOE OSTI2025

Chemical classification program synthesis using generative artificial intelligence

Accurately classifying chemical structures is essential for cheminformatics and bioinformatics, including tasks such as identifying bioactive compounds of interest, screening molecules for toxicity to humans, finding non-organic compounds with desirable material properties, or organizing large chemical libraries for drug discovery or environmental monitoring. However, manual classification is labor-intensive and difficult to scale to large chemical databases. Existing automated approaches either rely on manually constructed classification rules, or are deep learning methods that lack explainability. This work presents an approach that uses generative artificial intelligence to automatically write chemical classifier programs for classes in the Chemical Entities of Biological Interest (ChEBI) database. These programs can be used for efficient deterministic run-time classification of SMILES structures, with natural language explanations. The programs themselves constitute an explainable computable ontological model of chemical class nomenclature, which we call the ChEBI Chemical Class Program Ontology (C3PO). We validated our approach against the ChEBI database, and compared our results against deep learning models and a naive SMARTS pattern based classifier. C3PO outperforms the naive classifier, but does not reach the performance of state of the art deep learning methods. However, C3PO has a number of strengths that complement deep learning methods, including explainability and reduced data dependence. C3PO can be used alongside deep learning classifiers to provide an explanation of the classification, where both methods agree. The programs can be used as part of the ontology development process, and iteratively refined by expert human curators.

Artificial Intelligence↗