The NASA Discovery STARDUST Project
The NASA Discovery STARDUST Project, a comet particle sample return mission, has been in flight for over 1 year and during this time period has operated all flight instrumentation.
NASA Discovery STARDUST↗
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Results for “discovery”
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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The NASA Discovery 5, Genesis Mission
Genesis is the NASA Discovery 5 mission to solar wind return samples to the Earth for analyses in terrestrial laboratories. This will significantly increase our knowledge of the chemical and isotopic composition of the solar system.
sample return Genesis NASA Discovery 5 solar wind↗
Knowledge Discovery and Data Mining: An Overview
The process of knowledge discovery and data mining is the process of information extraction from very large databases. Its importance is described along with several techniques and considerations for selecting the most appropriate technique for extracting information from a particular data set.
data mining knowledge discovery data search↗
Knowledge Discovery in Large Image Databases: Dealing with Uncertainties in Ground Truth
This paper discusses the problem of knowledge discovery in image databases with particular focus on the issues which arise when absolute ground truth is not available.
knowledge discovery databases absolute ground trut↗
The Discovery of 1992 QB subscript 1
This paper describes the discovery of QB subscript 1, which is in an orbit beyond Pluto.
discovery orbit beyond Pluto↗
KDD-93: Progress and Challenges in Knowledge Discovery in Databases
Interest in Knowledge Discovery in Databases (KDD) continues to increase, driven by the rapid growth in the number and size of large databases and the applicaitons-driven demand to make sense of them.
database design database knowledge discovery datab↗
Resolving requirements discovery in testing and operations
This paper describes the results of an investigation into requirements discovery during testing and operations.
requirements discovery requirements evolution defe↗
Veva Discovery Mission to Venus: Exploration of Volcanoes and Atmosphere
VEVA (Venus Exploration of Volcanoes and Atmosphere) is a potential Discovery mission.
Venus Discovery aerobot balloon sonde↗
Radar Follow-up of Spaceguard Discoveries: Imaging and Astrometry
Radar is a very powerful groundbased technique for post-discovery reconnaissance of NEOs and is likely to play a central role in investigating these fantastic worlds during the foreseeable future. Delay- Doppler measurements are orthogonal to optical angle measurements, typically have a fractional precision between 10^-5 and 10^-9, and consequently are invaluable for refining orbits and prediction ephemerides.
Spaceguard Discoveries↗
Intelligent resource discovery using ontology-based resource profiles
Successful resource discovery across heterogeneous repositories is strongly dependent on the semantic and syntactic homogeneity of the associated resource descriptions. Ideally, resource descriptions are easily extracted from pre-existing standardized sources, expressed using standard syntactic and semantic structures, and managed and accessed within a distributed, flexible, and scaleable software framework.
XML↗
Automated Knowledge Discovery from Simulators
In this paper, we explore one aspect of knowledge discovery from simulators, the landscape characterization problem, where the aim is to identify regions in the input/ parameter/model space that lead to a particular output behavior. Large-scale numerical simulators are in widespread use by scientists and engineers across a range of government agencies, academia, and industry; in many cases, simulators provide the only means to examine processes that are infeasible or impossible to study otherwise. However, the cost of simulation studies can be quite high, both in terms of the time and computational resources required to conduct the trials and the manpower needed to sift through the resulting output. Thus, there is strong motivation to develop automated methods that enable more efficient knowledge extraction.
landscapes↗
STARDUST: Discovery's InterStellar Dust and Cometary Sample Return Mission
The STARDUST Discovery mission will collect samples of cometary and interstellar dust and return them to Earth. The Jet Propulsion Laboratory provides project management with Lockheed Martin Astronautics as the spacecraft industrial partner. STARDUST management is aggressively pursuing cost control through the use of Total Quality Management principles, specifically operating in a Project Engineering and Integration Team that
STARDUST↗
Data Science and the Knowledge Discovery Adventure
This talk will cover the important steps involved in the data science and knowledge discovery process: • Initial fact gathering (interview domain experts, review reports, articles, state-of-the-art) • Identify the problem (prediction, classification, statistical analysis, etc.) • Survey supporting data sources • Understand the data (numerical, categorical, text, sampling rate, data quality issues, etc.) • Selecting relevant features and sources • Acquire the data (set up agreements with the data stewards, APIs to download, etc.) • Merge data sources (temporal, spatial, common key, other ontologies...) • Feature Engineering (non linear domain knowledge or physics-based relationships) • Build data processing pipeline (may need to tap into data stream, develop parallel processing algorithm, federated learning etc.) • Build model and test (tune hyper-parameters, cross validation.) • Analyze/Validate results (do the results make sense. Does it answer the original question). • Deploy/Publish (Monitor and assess benefits)
Data science↗
Does the way we do science foster discovery?
Freedom to explore the unknown is key to scientific discovery. Maximizing modern individualistic measures of scientific productivity like citations and number of publications may impede the progress of science as a whole.
discovery↗
Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)
The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.
HAO↗
Tailoring Molecular Space to Navigate Phase Complexity in Cs-Based Quasi-2D Perovskites via Gated-Gaussian-Driven High-Throughput Discovery
Cesium-based quasi-2D halide perovskites (HPs) offer promising functionalities and low-temperature manufacturability, suited to stable tandem photovoltaics. However, the chemical interplays between the molecular spacers and the inorganic building blocks during crystallization cause substantial phase complexities in the resulting matrices. To successfully optimize and implement the quasi-2D HP functionalities, a systematic understanding of spacer chemistry, along with the seamless navigation of the inherently discrete molecular space, is necessary. Herein, by utilizing high-throughput automated experimentation, the phase complexities in the molecular space of quasi-2D HPs are explored, thus identifying the chemical roles of the spacer cations on the synthesis and functionalities of the complex materials. Furthermore, a novel active machine learning algorithm leveraging a two-stage decision-making process, called gated Gaussian process Bayesian optimization is introduced, to navigate the discrete ternary chemical space defined with two distinctive spacer molecules. Through simultaneous optimization of photoluminescence intensity and stability that “tailors” the chemistry in the molecular space, a ternary-compositional quasi-2D HP film realizing excellent optoelectronic functionalities is demonstrated. Finally, this work not only provides a pathway for the rational and bespoke design of complex HP materials but also sets the stage for accelerated materials discovery in other multifunctional systems.
36 MATERIALS SCIENCE↗
Biocatalyst discovery and design for plastics deconstruction: A multi‐scale perspective
Plastic waste accumulation poses significant environmental challenges due to a lack of economical solutions for the molecular deconstruction of diverse synthetic polymers. Biological‐based degradation offers promise but is hindered by the crystallinity, hydrophobicity, and additive complexity of plastics, which restrict biocatalyst access and activity. To address these problems, we propose a multi‐scale framework that combines detailed materials characterization, optimization of plastic‐biomolecular interfacial interactions, and enhancement of biocatalytic kinetics to develop effective plastic‐deconstructing enzymes. This approach leverages principles from reaction kinetics, transport and interfacial phenomena, and enzyme engineering to systematically address barriers across diverse plastic types. Our framework aims to accelerate the discovery and optimization of biocatalysts capable of scalable, selective, and efficient deconstruction of plastic waste. These advances hold potential to enable sustainable biological recycling and upcycling pathways, contributing to global efforts in mitigating plastic pollution and promoting circular material economies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Targeted Chemical Looping Materials Discovery by an Inverse Design
Chemical looping with oxygen uncoupling (CLOU) materials is actively sought for combustion of carbonaceous materials to achieve complete conversion and capture of carbon dioxide. These materials may play a vital role in reducing atmospheric carbon via negative carbon output. However, there is no one‐size‐fits‐all approach as different operating conditions and feedstocks may require different CLOU materials. As a result, the exploration and discovery of high‐performance CLOU materials can be a slow process. To address this challenge, a high‐throughput inverse machine learning workflow that identifies optimum materials from perovskite oxides for a given set of targets is developed—temperature and Gibbs free energy of oxygen formation. The model is trained on high‐throughput density functional theory calculations of CLOU materials and inverts the materials design process using a genetic algorithm to produce realistic substituted SrFeO 3‐δ compositions as output. Using the inverse model, it is able to identify several interesting new families of CLOU materials: Sr 1‐ x A x Fe 1‐ y B y O 3‐δ (e.g., A = Ca or K; B = Mg, Bi, Mn, Ni, Co, Cu, or Zn). These materials have shown promising properties, and some of them even outperform the benchmark material in terms of oxygen release kinetics under relevant CLOU operating conditions.
36 MATERIALS SCIENCE↗