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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 109 records · Page 6

Research Development and Partnership Pilot (RDPP): Developing plans and partnerships for incorporating tree reproduction to understand Earth system change

The goals for this Research Development and Partnership Pilot (RDPP) proposal were to i) learn about Department of Energy (DOE) research and use the PI’s expertise on patterns and environmental drivers of tree reproduction as a basis to make connections with individuals and research groups at DOE National Laboratories, and ii) to develop plans and form partnerships that will both enhance the PI’s research. The objectives of the proj ect were for the PI to i) participate in the Department of Energy's Office of Science program in Biological and Environmental Research training and outreach activities, ii) conduct directed fact-finding on Earth and Environmental Systems Sciences Division (EESSD) research projects and new partnerships with individuals and groups at National Laboratories, ii) conduct meetings with potential collaborators at National Laboratories to discuss EESSD-relevant research ideas, and iv) to develop a plan for future research efforts. During the period of the award, the objectives of the proposal were met, as the PI attended Environmental System Sciences meetings, American Geophysical Union meetings, SPRUCE experiment meetings, and visited the Oak Ridge National Lab. These activities led to increased understanding of the research being conducted by DOE scientists and the PI had meetings with potential collaborators to develop future research plans that leverage expertise at DOE and the research interests of the PI to increase understanding of the role of tree reproduction in future carbon allocation and in tree regeneration models in boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Understanding Defect Activation and Kinetics in Next Generation CdTe Absorbers

This project investigated the role of defects and dopants in cadmium telluride (CdTe) solar cells to improve efficiency and long-term stability. Advanced X-ray microscopy and spectroscopy techniques were used to map composition, identify defect structures, and measure charge collection at the nanoscale. These experimental results were combined with computational modeling to understand how dopants such as copper and arsenic interact with other elements during processing. The study found that many dopants become electrically inactive due to the formation of complexes with chlorine and oxygen, limiting carrier concentration and device performance. It also showed that selenium, used to enhance efficiency, can migrate within the material during both manufacturing and operation, altering local structure and potentially affecting stability. The project developed new diagnostic and analysis tools for studying photovoltaic materials and provided a mechanistic understanding of key performance limitations. These insights support the development of more efficient, stable, and cost-effective CdTe solar technologies for large-scale energy deployment.

14 SOLAR ENERGY↗

Understanding the connections between grain growth and flux expulsion in low RRR niobium SRF cavities

The SRF community has shown that high temperature annealing can improve the flux expulsion of niobium cavities during cooldown. The required temperature will vary between cavities and different batches of material, typically around 800 C and up to 1000 C. However, for niobium with a low residual resistance ratio (RRR), even 1000 C is not enough to improve its poor flux expulsion. The purpose of this study is to observe the grain growth behavior of low RRR niobium coupons subjected to high temperature annealing to identify the mechanism for improving flux expulsion in low RRR cavities. We anneal the low RRR material up to 1200 C to understand the limits of flux expulsion performance. We observe that low RRR material experiences less grain growth than high RRR when annealed at the same temperature. We search for the limitations to grain growth in low RRR material and develop a diagnostic based on grain structure to determine the appropriate recipe for good flux expulsion. The results of this study have the potential to unlock a new understanding on SRF materials and enable the next generation of high Q/high gradient surface treatments.

Howard, K. [Chicago U.]↗

Data and Code for Understanding Generative AI Content with Embedding Models

This repository contains code for the experiments in the paper "Understanding Generative AI Content with Embedding Models". Constructing high-quality features is critical to any quantitative data analysis. While feature engineering was historically addressed by carefully hand-crafting data representations based on domain expertise, deep neural networks (DNNs) now offer a radically different approach. DNNs implicitly engineer features by transforming their input data into hidden feature vectors called embeddings. For embedding vectors produced by foundation models -- which are trained to be useful across many contexts -- we demonstrate that simple and well-studied dimensionality-reduction techniques such as Principal Component Analysis uncover inherent heterogeneity in input data concordant with human-understandable explanations. Of the many applications for this framework, we find empirical evidence that there is intrinsic separability between real samples and those generated by artificial intelligence (AI).

Vargas, Max [Pacific Northwest National Laboratory↗

Decoding the κ Opioid Receptor (KOR): Advancements in Structural Understanding and Implications for Opioid Analgesic Development

The opioid crisis in the United States is a significant public health issue, with a nearly threefold increase in opioid-related fatalities between 1999 and 2014. In response to this crisis, society has made numerous efforts to mitigate its impact. Recent advancements in understanding the structural intricacies of the κ opioid receptor (KOR) have improved our knowledge of how opioids interact with their receptors, triggering downstream signaling pathways that lead to pain relief. This review concentrates on the KOR, offering crucial structural insights into the binding mechanisms of both agonists and antagonists to the receptor. Through comparative analysis of the atomic details of the binding site, distinct interactions specific to agonists and antagonists have been identified. These insights not only enhance our understanding of ligand binding mechanisms but also shed light on potential pathways for developing new opioid analgesics with an improved risk-benefit profile.

60 APPLIED LIFE SCIENCES↗

Making a Monkey out of Human Immunodeficiency Virus/Simian Immunodeficiency Virus Pathogenesis: Immune Cell Depletion Experiments as a Tool to Understand the Immune Correlates of Protection and Pathogenicity in HIV Infection

Understanding the underlying mechanisms of HIV pathogenesis is critical for designing successful HIV vaccines and cure strategies. However, achieving this goal is complicated by the virus’s direct interactions with immune cells, the induction of persistent reservoirs in the immune system cells, and multiple strategies developed by the virus for immune evasion. Meanwhile, HIV and SIV infections induce a pandysfunction of the immune cell populations, making it difficult to untangle the various concurrent mechanisms of HIV pathogenesis. Over the years, one of the most successful approaches for dissecting the immune correlates of protection in HIV/SIV infection has been the in vivo depletion of various immune cell populations and assessment of the impact of these depletions on the outcome of infection in non-human primate models. Here, we present a detailed analysis of the strategies and results of manipulating SIV pathogenesis through in vivo depletions of key immune cells populations. Although each of these methods has its limitations, they have all contributed to our understanding of key pathogenic pathways in HIV/SIV infection.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding EV Charging Pain Points Through Deep Learning Analysis

Current and potential electric vehicle (EV) owners express concerns about the charging infrastructure, mentioning non-functional chargers, prolonged charging times, inconvenient charger locations, long wait times, and high costs as major barriers. Addressing these issues often requires analyzing actual vehicle charging data, which is typically proprietary and inconsistent due to diverse standards and protocols. To understand and improve the EV charging experience, customer reviews are typically used to identify common customer pain points (CPPs). However, there is not a comprehensive method to map customer reviews to a standardized set of CPPs. In collaboration with the National Charging Experience (ChargeX) Consortium, this study bridges these gaps by proposing a Systematic Categorization and Analysis of Large-scale EV-charging Reviews (SCALER) framework. SCALER is an integrated, deep learning framework that segments, actively labels, analyzes, and classifies EV charging customer reviews into six CPP categories. To test its effectiveness, we used SCALER to analyze over 72,000 reviews from customers charging various EV models on different networks across the United States. SCALER achieves a classification accuracy of 92.5%, with an F1 score exceeding 85.7%. By demonstrating real-world applications of SCALER, we enhance the industry’s ability to understand and address CPPs to improve the EV charging experience.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Detonation transfer understanding applied to aerospace problems

Summary of the findings obtained from a two-year investigation aimed at a quantitative understanding of explosive stimulus transfer. It is felt that the improved understanding achieved on detonation transfer mechanisms will make possible better output tests and specifications, and should result in improved detonators and initiation methods.

Schimmel, M. L.↗

Global Observations and Understanding of the General Circulation of the Oceans

The workshop was organized to: (1) assess the ability to obtain ocean data on a global scale that could profoundly change our understanding of the circulation; (2) identify the primary and secondary elements needed to conduct a World Ocean Circulation Experiment (WOCE); (3) if the ability is achievable, to determine what the U.S. role in such an experiment should be; and (4) outline the steps necessary to assure that an appropriate program is conducted. The consensus of the workshop was that a World Ocean Circulation Experiment appears feasible, worthwhile, and timely. Participants did agree that such a program should have the overall goal of understanding the general circulation of the global ocean well enough to be able to predict ocean response and feedback to long-term changes in the atmosphere. The overall goal, specific objectives, and recommendations for next steps in planning such an experiment are included.

Source record↗

Understanding the high pressure properties of molecular solids and molecular surfaces deposited on hetrogeneous substrates

Work directed toward understanding the high pressure properties of molecular solids and molecular surfaces deposited on hetrogeneous substrates is reported. The motivation, apart from expanding our basic knowledge about these systems, was to understand and predict the properties of new materials synthesized at high pressure, including pressure induced metallic and superconducting states. As a consequence, information about the states of matter of the Jovian planets and their satellites, which are natural high pressure laboratories was also provided. The work on molecular surfaces and finite two and three dimensional clusters of atoms and molecules was connected with the composition and behavior of planetary atmospheres and on the processes involved in forming surface layers, which is vital to the development of composite materials and microcircuitry.

Etters, R. D.↗

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗

Hypothesis integration in image understanding systems

The goal of this research is to develop a robust control strategy for constructing image understanding systems (IUS). This paper proposes a general framework based on the integration of related hypotheses. Hypotheses are regarded as predictions of the occurrences of objects in the image. Related hypotheses are clustered together. A composite hypothesis is computed for each cluster. The goal of the IUS is to verify the hypotheses. We constructed an image understanding system, SIGMA, based on this framework and demonstrated its performance on an aerial image of a suburban housing development.

Hwang, Vincent Shang-Shouq↗

Understanding natural language for spacecraft sequencing

The paper describes a natural language understanding system, START, that translates English text into a knowledge base. The understanding and the generating modules of START share a Grammar which is built upon reversible transformations. Users can retrieve information by querying the knowledge base in English; the system then produces an English response. START can be easily adapted to many different domains. One such domain is spacecraft sequencing. A high-level overview of sequencing as it is practiced at JPL is presented in the paper, and three areas within this activity are identified for potential application of the START system. Examples are given of an actual dialog with START based on simulated data for the Mars Observer mission.

Katz, Boris↗

Current understanding and issues on electron beam injection in space

The status of the physics understanding involved in electron beam injection in space is reviewed. The paper examines our understanding of beam plasma interactions and their associated wave and energized particle spectra of the processes involved in the beam plasma discharge, and of the vehicle charge neutralization. 'Strawman' models are presented for comparison with experimental observations.

Papadopoulos, K.↗

Toward a computational theory for motion understanding: The expert animators model

Artificial intelligence researchers claim to understand some aspect of human intelligence when their model is able to emulate it. In the context of computer graphics, the ability to go from motion representation to convincing animation should accordingly be treated not simply as a trick for computer graphics programmers but as important epistemological and methodological goal. In this paper we investigate a unifying model for animating a group of articulated bodies such as humans and robots in a three-dimensional environment. The proposed model is considered in the framework of knowledge representation and processing, with special reference to motion knowledge. The model is meant to help setting the basis for a computational theory for motion understanding applied to articulated bodies.

Mohamed, Ahmed S.↗

Toward an understanding of global change: Initial priorities for US contributions to the International Geosphere-Biosphere Program

A limited number of high-priority research initiatives are recommended for early implementation as part of the U.S. contribution to the preparatory phase of the International Geosphere-Biosphere Program. The recommendations are based on the committee's analysis of the most critical gaps in the scientific knowledge needed to understand the changes that are occurring in the earth system not being addressed by existing programs. The report articulates a number of important key issues and interactions that characterize global change in the geosphere-biosphere system on time scales of decades to centuries; identifies the knowledge that is the most urgently needed to improve understanding of those issues and interactions; and formulates initial priorities for initial U.S. contributions to the IGBP, recognizing the contributions of other ongoing and proposed programs.

Source record↗

Recent progress in understanding the eruptions of classical novae

Dramatic progress has occurred in the last two decades in understanding the physical processes and events leading up to, and transpiring during the eruption of a classical nova. The mechanism whereby a white dwarf accreting hydrogen-rich matter from a low-mass main-sequence companion produces a nova eruption has been understood since 1970. The mass-transferring binary stellar configuration leads inexorably to thermonuclear runaways detected at distances of megaparsecs. Summarized here are the efforts of many researchers in understanding the physical processes which generate nova eruptions; the effects upon nova eruptions of different binary-system parameters (e.g., chemical composition or mass of the white dwarf, different mass accretion rates); the possible metamorphosis from dwarf to classical novae and back again; and observational diagnostics of novae, including x ray and gamma ray emission, and the characteristics and distributions of novae in globular clusters and in extragalactic systems. While the thermonuclear-runaway model remains the successful cornerstone of nova simulation, it is now clear that a wide variety of physical processes, and three-dimensional hydrodynamic simulations, will be needed to explain the rich spectrum of behavior observed in erupting novae.

Shara, Michael M.↗

Image understanding and the man-machine interface II; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

Image understanding concepts and models, image understanding systems and applications, advanced digital processors and software tools, and advanced man-machine interfaces are among the topics discussed. Particular papers are presented on such topics as neural networks for computer vision, object-based segmentation and color recognition in multispectral images, the application of image algebra to image measurement and feature extraction, and the integration of modeling and graphics to create an infrared signal processing test bed.

Barrett, Eamon B.↗