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At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

An open experimental database for exploring inorganic materials

The use of advanced machine learning algorithms in experimental materials science is limited by the lack of sufficiently large and diverse datasets amenable to data mining. If publicly open, such data resources would also enable materials research by scientists without access to expensive experimental equipment. Here, we report on our progress towards a publicly open High Throughput Experimental Materials (HTEM) Database (htem.nrel.gov). This database currently contains 140,000 sample entries, characterized by structural (100,000), synthetic (80,000), chemical (70,000), and optoelectronic (50,000) properties of inorganic thin film materials, grouped in >4,000 sample entries across >100 materials systems; more than a half of these data are publicly available. This article shows how the HTEM database may enable scientists to explore materials by browsing web-based user interface and an application programming interface. This paper also describes a HTE approach to generating materials data, and discusses the laboratory information management system (LIMS), that underpin HTEM database. Finally, this manuscript illustrates how advanced machine learning algorithms can be adopted to materials science problems using this open data resource.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Increasing Discovery and Usability of Earth Science Satellite Data with My NASA Data

For 20 years, the My NASA Data project at NASA Langley Research Center has developed innovative approaches to increase the use of NASA’s satellite data by learners. My NASA Data offers a variety of authentic Earth Science datasets and a data visualization tool, eliminating the need for educators and/or learners to obtain specialized knowledge of GIS data formats and software to access and use authentic Earth Science data. While there is no shortage of available data, as federal government agencies such as NASA house petabytes of freely accessible Earth Science datasets, much of the data are only available for download and visualization in specialized formats and software, limiting their accessibility to educators and learners, especially those in primary and secondary school. Using the Google Earth Engine platform, the My NASA Data team has recently reinvented their data visualization tool, called the Earth System Data Explorer (ESDE). The ESDE gives users the capability to explore over 60 Earth Science satellite datasets in a multitude of formats such as maps, graphs, and data table Its new and improved user interface design was developed based on the preferences of educators, whom the My NASA Data project has over 20 years’ experience working with. Earth Science and GIS Subject Matter Experts (SMEs) structured the data in a professional and scientific manner. During Fiscal Year 2023, the My NASA Data website received over 1 million digital engagements, with over one-third being visitors to the data visualization tool. These metrics highlight the interest in a visualization tool that is simple and free to use with reliable and trusted datasets. The ESDE empowers users to readily relate and analyze NASA Earth Science data within their area of interest. The team used a user-centered design (UCD) framework to receive and incorporate feedback into the application’s design. Core requested features include the ability to create time series graphs, comparative analysis of maps, and download the data as CSV file. Responses indicate that advances in data visualization tools such as the ESDE make authentic Earth Science data more accessible. This presentation will cover how the My NASA Data project develops tools to enhance data discovery and accessibility, as well as how SME and user suggestions are incorporated.

Desiray Wilson↗
NASA NTRS2011

Space Weathering Impact on Solar System Surfaces and Planetary Mission Science

We often look "through a glass, darkly" at solar system bodies with tenuous atmospheres and direct surface exposure to the local space environment. Space weathering exposure acts via universal space-surface interaction processes to produce a thin patina of outer material covering, potentially obscuring endogenic surface materials of greatest interest for understanding origins and interior evolution. Examples of obscuring exogenic layers are radiation crusts on cometary nuclei and iogenic components of sulfate hydrate deposits on the trailing hemisphere of Europa. Weathering processes include plasma ion implantation into surfaces, sputtering by charged particles and solar ultraviolet photons, photolytic chemistry driven by UV irradiation, and radiolytic chemistry evolving from products of charged particle irradiation. Regolith structure from impacts, and underlying deeper structures from internal evolution, affects efficacy of certain surface interactions, e.g. sputtering as affected by porosity and surface irradiation dosage as partly attenuated by local topographic shielding. These processes should be regarded for mission science planning as potentially enabling, e.g. since direct surface sputtering, and resultant surface-bound exospheres, can provide in-situ samples of surface composition to ion and neutral mass spectrometers on orbital spacecraft. Sample return for highest sensitivity compOSitional and structural analyses at Earth will usually be precluded by limited range of surface sampling, long times for return, and high cost. Targeted advancements in instrument technology would be more cost efficient for local remote and in-situ sample analysis. More realistic laboratory simulations, e.g. for bulk samples, are needed to interpret mission science observations of weathered surfaces. Space environment effects on mission spacecraft and science operations must also be specified and mitigated from the hourly to monthly changes in space weather and from longer term (e.g., solar cycle) evolution of space climate. Capable instrumentation on planetary missions can and should be planned to contribute to knowledge of interplanetary space environments. Evolving data system technologies such as virtual observatories should be explored for more interdisciplinary application to the science of planetary surface, atmospheric, magnetospheric, and interplanetary interactions.

Cooper, John F.↗
DOE OSTI2026

Soil metagenomics umbrella narrative

Implementing accessible, authentic research experiences in introductory courses is challenging, particularly at institutions serving diverse student populations. To address this gap, we developed and deployed a Course-based Undergraduate Research Experience (CURE) focused on plant-microbe interactions in General Biology II at Northeastern Illinois University (NEIU), a minority-serving institution with a diverse student body. Students grew sugar beets (Beta vulgaris), extracted DNA from the rhizoplane, and used the Department of Energy Systems Biology Knowledgebase (KBase) for bioinformatic analysis to compare microbial relative abundance in fertilized versus unfertilized soil. Over five semesters, the CURE engaged 103 students and leveraged the intuitive KBase platform to make complex sequencing data accessible. Pre/post-course survey data revealed significant increases in student self-assessed research skills, including the ability to explain results and determine the types of data to collect. Furthermore, students reported significant gains in confidence related to experimental design and hypothesis development, alongside a strong increase in familiarity with KBase. Informal faculty feedback indicated high student engagement and appreciation for the real-world connections (e.g. food systems, agriculture, and health). This scalable, low-cost model effectively integrates data science tools into the foundational curriculum, demonstrating a potent strategy for boosting research skills and broadening participation in authentic scientific inquiry among diverse undergraduate students.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

A Simple, Scalable, Script-based Science Processor

The production of Earth Science data from orbiting spacecraft is an activity that takes place 24 hours a day, 7 days a week. At the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC), this results in as many as 16,000 program executions each day, far too many to be run by human operators. In fact, when the Moderate Resolution Imaging Spectroradiometer (MODIS) was launched aboard the Terra spacecraft in 1999, the automated commercial system for running science processing was able to manage no more than 4,000 executions per day. Consequently, the GES DAAC developed a lightweight system based on the popular Per1 scripting language, named the Simple, Scalable, Script-based Science Processor (S4P). S4P automates science processing, allowing operators to focus on the rare problems occurring from anomalies in data or algorithms. S4P has been reused in several systems ranging from routine processing of MODIS data to data mining and is publicly available from NASA.

Lynnes, Christopher↗
NASA NTRS1999

Chandra Interactive Analysis of Observations

The Chandra X-R-ay Observatory has been launched on July 23 1999. The first public release of the Chandra data analysis system, CIAO (Chandra Interactive Analysis of Observations) will be available in the near future. The XMM Science Survey Consortium is considering the possibility of using the whole or parts of CIAO to analyse observations from the XMM satellite and during the meeting we will give presentations and demonstrations of parts of CIAO, including the new GUIs developed for "FirstLook" analysis, data filtering and browsing; SHERPA, the multi-dimensional, multi-missions modelling and fitting application; CHIPS, the Chandra Imaging and Plotting System; generic data manipulation tools and other applications.

Fruscione, Antonella↗
DOE OSTI2026

Data-Driven Discovery and Experimental Validation of Solvent Polarity Effects on Conjugated Polymer Solution-to-Film Assembly Pathways

Understanding how solvent properties influence the solution-to-film assembly of conjugated polymers remains a critical challenge due to the complex and intertwined nature of polymer–solvent interactions. In this study, we integrate a data-driven framework with experimental validation to identify key parameters influencing the assembly and performance of poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno[3,2-b]thiophene)] (DPP-DTT) in organic field-effect transistors (OFETs). A machine learning (ML) approach identified the normalized Reichardt polarity parameter (E T N ) as a significant descriptor correlated with DPP-DTT hole mobility (μ). Systematic DPP-DTT devices fabricated using solvents across a wide E T N range revealed that higher E T N solvents yield enhanced μ. To elucidate the structural origins of high μ, we conducted comprehensive analyses using UV–vis–NIR spectroscopy and grazing incidence wide angle X-ray scattering (GIWAXS) measurements. The results revealed that films processed from high E T N solvents exhibit reduced paracrystallinity. By analyzing the solution-state behavior using optical microscopy and solution WAXS, we revealed polymer solubility differences in the various solvents and associated distinct polymer assembly pathways, elucidating why the high E T N solvent produces long-range ordered films. Notably, the high E T N solvent shows a pronounced preference for liquid-crystal (LC)-mediated assembly, providing a mechanistic explanation for the enhanced structural order. Therefore, these results demonstrate that solvent polarity, as evaluated by E T N , serves as an important parameter that plays a significant role in the DPP-DTT assembly pathway and resultant solid-state morphology. This work provides a strategy for integrating data science with experiments to identify critical parameters associated with complex polymer systems and helps guide rational process design for high-performance organic electronics.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The UCAR Africa Initiative: Recent insights, challenges, and opportunities to foster collaborative research for environmental sustainability

Africa is increasingly being exposed to the negative impacts of climate and environmental change, while having less capacity to respond compared to other continents. The vulnerability partially results from unprecedented demographic growth, urbanization, and industrialization. However, the continent has still largely been underserved by the broader Earth System Science (ESS) community, as evidenced by the limited amount of ESS data and research that cover Africa compared to other areas of the world. Here we present the recent University Corporation for Atmospheric Research (UCAR) Africa Initiative that aims to enhance environmental sustainability in Africa by fostering international collaborative research partnerships co-led by African scientists. Specifically, we outline urgent challenges and opportunities identified through an international workshop in six areas of ESS namely (1) air quality and health, (2) weather, (3) climate, (4) land and water, (5) social science perspectives, and (6) developing equitable collaboration and sustainable infrastructure. We highlight examples of successful partnerships and conclude with recommendations to advance collaborative, actionable ESS research that addresses Africa’s critical environmental challenges.

African weather and land variability↗
DOE OSTI2020

Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1985

Hyperspectral Image Analysis Program

Information on imaging spectrometry is given in the forms of outlines, graphs, and charts. Topics covered include impacts on science users, program objectives, expert systems for imaging spectrometry, and imaging spectrometer data analysis methods.

Source record↗
NASA NTRS1987

Voyager-Neptune telemetry - The DSN 70 meter antenna upgrade

The Deep Space Network (DSN) is responsible for the acquisition of in-situ science and engineering measurements and navigation data from spacecraft exploring the Solar System. Key characteristics of the DSN design approach, the costs to upgrade performance over the past several decades, and some fundamental constraints on performance are discussed. The specific 70-meter upgrade task and the resulting overall benefits to Voyager-Neptune and the mission set are addressed.

Hall, Justin R.↗
NASA NTRS1991

Technology 2000, volume 1

The purpose of the conference was to increase awareness of existing NASA developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. There were sessions on the following: Computer technology and software engineering; Human factors engineering and life sciences; Information and data management; Material sciences; Manufacturing and fabrication technology; Power, energy, and control systems; Robotics; Sensors and measurement technology; Artificial intelligence; Environmental technology; Optics and communications; and Superconductivity.

Source record↗
NASA NTRS1991

Hubble Space Telescope communications and data handling

The communications and data handling system of the HST are described in detail. Consideration is given to observation scheduling, commanding, telemetry, scientific data collection, spacecraft data handling systems, and the use of the TDRSS and NASCOM data network. The science instruments control and data handling subsystem is presented in schematic form.

Lesko, John↗
NASA NTRS1990

The NASA Geostationary Earth Observatory - A status report

The design concept of the NASA Geostationary Earth Observatory (GEO), which is the geostationary component of the NASA Mission to Planet Earth program, is discussed together with the science goals, the mission objectives, the platform concept, the data and information system, and the instrument complement of the GEO. The instruments proposed for GEO will include a geostationary microwave precipitation radiometer, a geostationary atmospheric profiler, a geostationary earth processes spectrometer, an advanced lightning mapper, a high-resolution earth processes imager, an operational instrument suite, a solar constant monitor and a spectrum monitor, a geostationary earth climate sensor, and a trace gas imager. Current technology and engineering studies indicate that GEO will be ready for launch by the year 2000.

Koczor, Ronald J.↗
NASA NTRS1991

Data archiving

The viewgraphs of a discussion on data archiving presented at the National Space Science Data Center (NSSDC) Mass Storage Workshop is included. The mass storage system at the National Center for Atmospheric Research (NCAR) is described. Topics covered in the presentation include product goals, data library systems (DLS), client system commands, networks, archival devices, DLS features, client application systems, multiple mass storage devices, and system growth.

Pitts, David↗
NASA NTRS1997

Feasibility of NASA TT&C via Commercial Satellite Services

This report presents the results of a study to identify impact and driving requirements by implementing commercial satellite communications service into traditional National Aeronautics and Space Administration (NASA) space-ground communications. The NASA communication system is used to relay spacecraft and instrument commands, telemetry and science data. NASA's goal is to lower the cost of operation and increase the flexibility of spacecraft operations. Use of a commercial network offers the opportunity to contact a spacecraft on a nearly "on-demand" basis with ordinary phone calls to enable real time interaction with science events.

Mitchell, Carl W.↗
NASA NTRS1999

High Data Rate Instrument Study

The High Data Rate Instrument Study was a joint effort between the Jet Propulsion Laboratory (JPL) and the Goddard Space Flight Center (GSFC). The objectives were to assess the characteristics of future high data rate Earth observing science instruments and then to assess the feasibility of developing data processing systems and communications systems required to meet those data rates. Instruments and technology were assessed for technology readiness dates of 2000, 2003, and 2006. The highest data rate instruments are hyperspectral and synthetic aperture radar instruments which are capable of generating 3.2 Gigabits per second (Gbps) and 1.3 Gbps, respectively, with a technology readiness date of 2003. These instruments would require storage of 16.2 Terebits (Tb) of information (RF communications case of two orbits of data) or 40.5 Tb of information (optical communications case of five orbits of data) with a technology readiness date of 2003. Onboard storage capability in 2003 is estimated at 4 Tb; therefore, all the data created cannot be stored without processing or compression. Of the 4 Tb of stored data, RF communications can only send about one third of the data to the ground, while optical communications is estimated at 6.4 Tb across all three technology readiness dates of 2000, 2003, and 2006 which were used in the study. The study includes analysis of the onboard processing and communications technologies at these three dates and potential systems to meet the high data rate requirements. In the 2003 case, 7.8% of the data can be stored and downlinked by RF communications while 10% of the data can be stored and downlinked with optical communications. The study conclusion is that only 1 to 10% of the data generated by high data rate instruments will be sent to the ground from now through 2006 unless revolutionary changes in spacecraft design and operations such as intelligent data extraction are developed.

Schober, Wayne↗
NASA NTRS2002

NASA's Living with a Star Program: The Geospace Mission Concept

NASA has initiated the Living with a Star Program (LWS) to develop the scientific understanding to address the aspects of the Connected Sun-Earth system that affect life and society. A goal of the program is to bridge the gap between science, engineering, and user application communities. This will enable future science, operational, and commercial objectives in space and atmospheric environments by improving engineering approaches to the accommodation and/or mitigation of the effects of solar variability on technological systems. Three program elements are the Science Missions; a Theory, Modeling, and Data Analysis program; and a Space Environment Testbeds program. Because many of the effects of solar variability on humanity are observed in Geospace regions of space, the science research for all three elements of the LWS Program have significant components in Geospace regions.

Barth, Janet L.↗