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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tunable and Degradable Dynamic Thermosets from Compatibilized Polyhydroxyalkanoate Blends

Polyhydroxyalkanoates (PHAs) are versatile, biobased polyesters that are often targeted for use as degradable thermoplastic replacements for polyolefins. Given the substantial chemical diversity of PHA, their potential as cross-linked polymers could also enable similar platforms for reversible, degradable thermosets. In this work, we genetically engineered Pseudomonas putida KT2440 to synthesize poly(3-hydroxybutyrate-co-3-hydroxyundecenoate) (PHBU), which contains both 3-hydroxybutyrate and unsaturated 3-hydroxyundecenoate components. To reduce the brittleness of this polymer, we physically blended PHBU with the soft copolymer poly(3-hydroxydecanonate-co-3-hydroxyundecenoate) in mass ratios of 1:3, 1:1, and 3:1. Upon observing varying degrees of immiscibility by scanning electron microscopy, we installed dynamic boronic ester cross-links via thiol–ene click chemistry, which resulted in compatibilized dynamic thermoset blends ranging in hard, medium, and soft rubber or elastomer thermomechanical profiles. These dynamic thermoset blends were subjected to controlled biological degradation experiments in freshwater conditions, achieving timely mass loss despite the cross-linked architectures. Overall, this work highlights a two-component platform for the production of degradable and reprocessable dynamic thermoset blends suitable for several classes of cross-linked polymer technologies from tailored, biological PHA copolymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Using Coordinated, Multi-Agent Platforms for Dynamic Ocean Worlds Science

Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.

Distributed Systems↗
DOE OSTI2024

Small Money Agile Research and Technology Transitions (SMARTT)

The Energy and Environment Directorate’s (EED’s) applied energy mission aligns with the larger DOE mission to ensure America’s security and prosperity by addressing its energy, environmental and nuclear challenges through transformative science and technology solutions. This Small Money Agile Research & Technology Transitions (SMARTT) LDRD project provided EED with the flexibility to leverage PNNL staff and capabilities to rapidly explore new scientific concepts and deliver initial proof-of-concept studies for innovative new technologies that aligned with the goals of DOE’s Applied Energy Offices. Concepts that were successful were further developed through sponsor funding and private-sector partnership, or through follow-on LDRD investment.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Transformational Challenge Reactor Safety Design and Radionuclide Retention Strategy

An integrated safety design and radionuclide (RN) retention strategy is developed to support the Transformational Challenge Reactor (TCR) demonstration. This demonstration aims to showcase viability for rapid deployment of a novel reactor by leveraging the advances in materials, manufacturing, and computational sciences through a highly integrated and agile design and development approach. This strategy provides a logical description and understanding of how RNs are contained within the facility. Rather than discussing fission product barriers individually between separate design and safety basis reports, this paper provides a consistent description and narrative to better facilitate regulatory interactions and focus safety design efforts. The principal barriers credited include the various coating layers in the tristructural isotropic (TRISO) fuel particle, the silicon carbide (SiC) matrix hosting the particles within the fuel element, the helium pressure boundary, and the confinement system. The choice and assumed performance of the credited barriers are highly conservative, which is a direct reflection of the low hazard that the TCR demonstration presents and the need to simplify and focus the safety review process accordingly. However, the strategy and the associated framework are generalized and may be adopted and tailored to support other advanced reactor demonstration efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2005

Science operations interfaces for Mars surface exploration

The Science Activity Planner (SAP) is the science planning tool used for the Mars Exploration Rover (MER) mission. This paper begins with an overview of the software developed for MER and how it was used for science downlink analysis and activity planning.

distributed operations↗
NASA NTRS2011

Development of the Advanced Energetic Pair Telescope (AdEPT) for Medium-Energy Gamma-Ray Astronomy

Progress in high-energy gamma-ray science has been dramatic since the launch of INTEGRAL, AGILE and FERMI. These instruments, however, are not optimized for observations in the medium-energy (approx.0.3< E(sub gamma)< approx.200 MeV) regime where many astrophysical objects exhibit unique, transitory behavior, such as spectral breaks, bursts, and flares. We outline some of the major science goals of a medium-energy mission. These science goals are best achieved with a combination of two telescopes, a Compton telescope and a pair telescope, optimized to provide significant improvements in angular resolution and sensitivity. In this paper we describe the design of the Advanced Energetic Pair Telescope (AdEPT) based on the Three-Dimensional Track Imager (3-DTI) detector. This technology achieves excellent, medium-energy sensitivity, angular resolution near the kinematic limit, and gamma-ray polarization sensitivity, by high resolution 3-D electron tracking. We describe the performance of a 30x30x30 cm3 prototype of the AdEPT instrument.

Hunter, Stanley D.↗
DOE OSTI2025

Open-Source and FAIR Research Software for Proteomics

Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms, predictive models, and workflows, but the field faces challenges, including the increasing complexity of mass spectrometry data, limited reproducibility due to proprietary software, and difficulties integrating with other omics disciplines. Closed-source, platform-specific tools exacerbate these issues by restricting innovation, creating inefficiencies, and imposing hidden costs on the community. Open-source software (OSS), aligned with the FAIR Principles (Findable, Accessible, Interoperable, Reusable), offers a solution by promoting transparency, reproducibility, and community-driven development, which fosters collaboration and continuous improvement. In this manuscript, we explore the role of OSS in computational proteomics, its alignment with FAIR principles, and its potential to address challenges related to licensing, distribution, and standardization. Drawing on lessons from other omics fields, we present a vision for a future where OSS and FAIR principles underpin a transparent, accessible, and innovative proteomics community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI‐Powered Mass Spectrometry and Multiomics Integration

The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS‐based “omics” research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range of domains, from health to environment and industrial biotechnology. Beginning with an overview of key challenges inherent in MS software pipelines, this personal perspective explores how AI‐driven solutions can address them to enhance data processing, integration and interpretation. It proposes a paradigm shift in molecular identification and quantitation algorithms, leveraging AI to enable holistic interpretation of MS‐based multiomics data. While centered on MS‐based omics, this holistic AI‐driven paradigm is also critical for connecting dynamic biochemical changes to genomics and transcriptomics contexts, reinforcing the integrative value of MS in multiomics research. Ultimately, this AI‐driven approach could enhance efficiency, accuracy, and molecular breadth of coverage, deepening our systems‐level understanding of biological processes and accelerating a myriad of biodiscoveries.

47 OTHER INSTRUMENTATION↗
NASA NTRS2007

Science Archives in the 21st Century: A NASA LAMBDA Report

Lambda is a thematic data center that focuses on serving the cosmic microwave background (CMB) research community. LAMBDA is an active archive for NASA's Cosmic Background Explorer (COBE) and Wilkinson Microwave Anisotropy Probe (WMAP) mission data sets. In addition, LAMBDA provides analysis software, on-line tools, relevant ancillary data and important web links. LAMBDA also tries to preserve the most important ground-based and suborbital CMB data sets. CMB data is unlike other astrophysical data, consisting of intrinsically diffuse surface brightness photometry with a signal contrast of the order 1 part in 100,000 relative to the uniform background. Because of the extremely faint signal levels, the signal-to-noise ratio is relatively low and detailed instrument-specific knowledge of the data is essential. While the number of data sets being produced is not especially large, those data sets are becoming large and complex. That tendency will increase when the many polarization experiments currently being deployed begin producing data. The LAMBDA experience supports many aspects of the NASA data archive model developed informally over the last ten years-that small focused data centers are often more effective than larger more ambitious collections, for example; that data centers are usually best run by active scientists; that it can be particularly advantageous if those scientists are leaders in the use of the archived data sets; etc. LAMBDA has done some things so well that they might provide lessons for other archives. A lot of effort has been devoted to developing a simple and consistent interface to data sets, for example; and serving all the documentation required via simple 'more' pages and longer explanatory supplements. Many of the problems faced by LAMBDA will also not surprise anyone trying to manage other space science data. These range from persuading mission scientists to provide their data as quickly as possible, to dealing with a high volume of nuisance (spam) messages. Because so many data center problems and solutions are common across individual data centers and disciplines it would be very valuable to establish some new systems of communication - such as informal email lists for administrators and developers. But resources are very limited, so new timeconsuming and inefficient mechanisms - like too-frequent and too-structured meetingsshould be avoided. Although there are great advantages to being small, agile and independent, there are also some areas where science data centers within and without NASA could be better coordinated - for the assignment of persistent identifiers; to encourage the early adoption of useful standards and technologies; etc. Some super-structure to facilitate such coordination might be beneficial as long as it doesn't begin to control the other work of the archives, and become a "methodology police". In this respect the CCSDS "Reference Model for an Open Archive Information System" is a little worrying. It may be that the closer a data center gets to following such a detailed prescription, the less effective it will become. It is much better to have an informal coordination process than a bureaucratic straight-jacket.

Butterworth, P.↗
DOE OSTI2024

2023 Project Peer Review Report

The Bioenergy Technologies Office (BETO) within the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy supports the research, development, and demonstration (RD&D) of technologies aimed at mobilizing domestic renewable carbon resources for the reduction of greenhouse gas emissions across the U.S. economy. BETO systematically prioritizes RD&D into technology opportunities across a range of emerging scientific breakthroughs and technology readiness levels in the subprogram areas illustrated in Figure 1. This approach supports a diverse portfolio while developing the most promising and widely applicable technologies, testing technologies as integrated processes, and demonstrating integrated processes to support scale-up. These technologies will use a broad variety of renewable carbon resources to produce increasing volumes of biofuels and bioproducts. More information on BETO’s mission, goals, and strategic approaches can be found in the Bioenergy Technologies Office Multi-Year Program Plan. The biennial Peer Review process enables external stakeholders to provide feedback on the responsible use of taxpayer funding and develop recommendations for the most efficient and effective ways to accelerate the development of a bioenergy industry. This report includes the results of the Project Peer Review meeting held on April 3–7, 2023, in Denver, Colorado.

09 BIOMASS FUELS↗
DOE OSTI2020

Correction to Norm-conserving pseudopotentials and basis sets to explore Lanthanide chemistry in complex environments

Correction was made to the funding and acknowledgment: Funding V.-A.G. was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Chemical Sciences, Geosciences, and Biosciences Division. R.R. and M.-T.N. were supported by the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory (PNNL) CheMSR Agile Investment. PNNL is operated by DE-AC05-76RLO01830. J.-B.L. and J.L. were supported by the National Natural Science Foundation of China (Nos. 21433005, 91645203, and 21590792). D.C.C. was supported by Research and Innovation at the University of Nevada, Reno. ACKNOWLEDGMENTS The research was performed using resources available through Research Computing at Pacific Northwest National Laboratory (PNNL), Tsinghua National Laboratory for Information Science and Technology and the Computational Chemistry Laboratory under Tsinghua Xuetang Talents Program, and University of Nevada, Reno High Performance Computing. J.- B.L. and J.L. acknowledge discussions with Dr. Yang-Gang Wang (Southern University of Science and Technology).

Lu, Jun-Bo↗
DOE OSTI2025

Algorithms and file structures to extend and enhance liquid chromatography and ion mobility mass spectrometry workflows (CRADA Final Report)

The purpose of this project was to continue supporting customizations of algorithms and raw data file structures to enhance software workflows for liquid chromatography (LC), mass spectrometry (MS) and ion mobility mass spectrometry (IM-MS)-based protein and metabolite characterization. PNNL worked with Agilent to design, implement, evaluate, and demonstrate new algorithms and integrated them as functionalities into the PNNL-PreProcessor software. The project augmented PNNL’s capabilities to analyze complex proteomics and metabolomics samples. These capabilities are directly beneficial to DOE and PNNL efforts to characterize and analyze these compounds in microbial and plant communities. The project assisted Agilent in further developing improved instrument-software solutions combining liquid chromatography and ion mobility with mass spectrometry for widespread applications in life sciences and other fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2001

The Future of Instrument Technology for Space-based Remote Sensing

The current paradigm for space-based remote sensing relies upon frequency-specific measurements in pre-defined orbits with fixed or narrowly variable apertures. The suites of Earth observing instruments currently deployed or planned for deployment within the next 3 years typify this paradigm. To enable NASA's Earth Science vision, the future paradigm of remote sensing must employ frequency-agile measurements capable of multi-scene observations. Real-time, autonomous adaptive sensing and taskability will be critical. Advanced capabilities will include: (1) Miniaturized observatories. (2) Robust, compact instrument architectures. (3) Miniaturized/programmable components. (4) Aperture synthesis. (5) Deployable apertures. (6) Low cost production.

Peri, Frank↗
NASA NTRS2018

NASA's EOSDIS Near Term Challenges

Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, the ESDIS Project has had to evolve EOSDIS continually over the past three decades. However, many challenges remain. One near-term challenge is the enormous quantity of new data that will need to be managed by the EOSDIS. With the upcoming launch of the latest NASA missions coupled with existing operational missions and field campaigns, EOSDIS can expect to handle as much as 50 petabytes of data per year. In perspective, this is twice the size of the current existing archive, which took over 21 years to collect. Another continuing challenge is the disparate requirements of a diverse science community. Maintaining rigorous long-term data preservation, supporting ease of discovery and access, incorporating user feedback, enabling reanalysis/ reprocessing, and agile integration of new data sources, continue to be the Project's objectives.

Remote Sensing↗
NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗
NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗