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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 73 records · Page 4

A Grassroots Network and Community Roadmap for Interconnected Autonomous Science Laboratories for Accelerated Discovery

Scientific discovery is being revolutionized by AI and autonomous systems, yet current autonomous laboratories remain isolated islands unable to collaborate across institutions. We present the Autonomous Interconnected Science Lab Ecosystem (AISLE), a grassroots network transforming fragmented capabilities into a unified system that shorten the path from ideation to innovation to impact and accelerates discovery from decades to months. AISLE addresses five critical dimensions: (1) cross-institutional equipment orchestration, (2) intelligent data management with FAIR compliance, (3) AI-agent driven orchestration grounded in scientific principles, (4) interoperable agent communication interfaces, and (5) AI/ML-integrated scientific education. By connecting autonomous agents across institutional boundaries, autonomous science can unlock research spaces inaccessible to traditional approaches while democratizing cutting-edge technologies. This paradigm shift toward collaborative autonomous science promises breakthroughs in sustainable energy, materials development, and public health.

Ferreira da Silva, Rafael [Oak Ridge National Labo↗

Collaborative, Data-Intensive Science Key to Science & Commerce Challenges

This article coincides with the release of "Data-Intensive Science," co-edited by Dr. Kerstin Kleese van Dam. In the piece, Dr. Kleese van Dam explains how data-intensive science has the potential to transform not only how we do science but how quickly we can translate scientific progress into complete solutions, policies, decisions and, ultimately, economic success. In the article, she states it is clear that nations that can most effectively transform tons of scientific data into actionable knowledge are going to be the leaders in the future of science and commerce and how creating the required new insights for complex challenges cannot be done without effective collaboration. Because many science domains already are unable to explore all of the data they collect (or which is relevant to their research), progress in collaborative, data-intensive science is crucial toward unlocking the potential of big data.

99 GENERAL AND MISCELLANEOUS↗

Physical Sciences Vistas: Perspectives on Excellence in Mission-Focused Science, Technology, and Engineering at Los Alamos Laboratory (Issue 1, 2020)

This is the first 2020 issue of Physical Sciences Vistas, with a focus on “excellence in mission-focused science, technology, and engineering.” Excellence in mission-focused ST&E comprises one of the four elements of the Laboratory Agenda, focusing on sustaining and enhancing LANL’s science base. This issue highlights the diverse efforts of personnel in our Physical Sciences Directorate (ALDPS) to enhance science, technology, and engineering at the Laboratory. As we reflect on work at the Laboratory, mostly from our homes due to COVID-19, it is gratifying to see the important, diverse contributions to ST&E across ALDPS.

36 MATERIALS SCIENCE↗

SCIENCE PLAN AND PROGRESS REPORT FOR THE TERRESTRIAL ECOSYSTEM SCIENCE – SCIENTIFIC FOCUS AREA (TES SFA)

Climate Change Science Institute, Environmental Sciences Division, Biological Sciences Division, Oak Ridge National Laboratory. Submitted to the Terrestrial Ecosystem Science, Biological and Environmental Research Program, DOE Office of Science. February 27, 2015. Principal Investigators: Paul J. Hanson and Daniel M. Ricciuto. Oak Ridge National Laboratory

54 ENVIRONMENTAL SCIENCES↗

Contribution of corresponding member of the USSR Academy of Sciences Ye. A. Korovin to the science of international space law. Anniversary of corresponding member of the USSR Academy of Sciences, Professor Ye. A. Korovin

The Soviet Union's participation in the solution of international legal problems as space flights became possible is reviewed with emphasis on the efforts of the most prominent Soviet international lawyer. Some of the professor's 230 writings are highlighted.

Zhukov, G. P.↗

Imaging Science Panel. Multispectral Imaging Science Working Group joint meeting with Information Science Panel: Introduction

The state-of-the-art of multispectral sensing is reviewed and recommendations for future research and development are proposed. specifically, two generic sensor concepts were discussed. One is the multispectral pushbroom sensor utilizing linear array technology which operates in six spectral bands including two in the SWIR region and incorporates capabilities for stereo and crosstrack pointing. The second concept is the imaging spectrometer (IS) which incorporates a dispersive element and area arrays to provide both spectral and spatial information simultaneously. Other key technology areas included very large scale integration and the computer aided design of these devices.

Source record↗

Enhancing the Payload Development Process for Lunar Gateway and Lunar Surface Science & Exploration: Space Biology Beyond Low-Earth-Orbit Instrumentation and Science Series (BLISS) Science Working Group 2023-2024 Annual Report

Space biology BLEO research is inherently driven by the differences between the LEO and BLEO environments, which can be broadly characterized by the five-hazard “RIDGE” paradigm (Radiation, Isolation, Distance, Gravity, Environment, e.g., similar to Figure 2 in (1)). Thus, the envisioned goals over the next decade will include using the cislunar and lunar surface environments to (A) characterize deep-space environments including biological effects of radiation and other stressors, (B) gain experience from isolation of very small groups in very small enclosures, (C) learn to compensate for distance from Earth via in situ resource utilization (ISRU) and bioregenerative life support, (D) gain assurance that all aspects of deep-space exploration can proceed in altered or artificial gravity environments, (E) develop essential adaptation scenarios for the built (e.g., low pressure) and external (e.g., temperature extremes, dust) environments.

Biology↗

MultiSector Dynamics: Advancing the Science of Complex Adaptive Human-Earth Systems

The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce. Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.

Reed, Patrick↗

Big Data: Next-Generation Machines for Big Science

Addressing the scientific grand challenges identified by the US Department of Energy’s (DOE’s) Office of Science’s programs alone demands a total leadership-class computing capability of 150 to 400 Pflops by the end of this decade. The successors to three of the DOE’s most powerful leadership-class machines are set to arrive in 2017 and 2018—the products of the Collaboration Oak Ridge Argonne Livermore (CORAL) initiative, a national laboratory–industry design/build approach to engineering nextgeneration petascale computers for grand challenge science. These mission-critical machines will enable discoveries in key scientific fields such as energy, biotechnology, nanotechnology, materials science, and high-performance computing, and serve as a milestone on the path to deploying exascale computing capabilities.

High-performance computing↗

Basic Research Needs in The Science of Scientific Software Development and Use: Investment in Software is Investment in Science

Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them are often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. Increased investment, especially in the characterization and improvement of how scientific software is developed and used, is important for sustaining and improving the impact of software as the scope and complexity of scientific efforts expand. Without this investment, we face the risk of diminishing returns on our software investments because the demands for increased functionality, usability, reliability, and more will not be sufficiently met. The US Department of Energy Office of Science (DOE/SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. For many years, DOE/SC software investments have provided tremendous value to the scientific community. We want to continue and further improve the value of DOE/SC software efforts by using a scientific approach to understanding and improving how scientific software is developed and used. In December 2021, the DOE/SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific-Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, which built on insights from 124 pre-workshop position papers, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: Software has become an essential part of modern science, impacting discoveries, policy, and technological development. To maintain and improve confidence in science delivered via software, we must improve the processes and tools that help us create and use software, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work.

97 MATHEMATICS AND COMPUTING↗

Science Goal Driven Observing: A Step Towards Maximizing Science Returns and Spacecraft Autonomy

While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. Also, the new generation of space-based telescopes will generate data at an unprecedented rate. Yet, while on-board data processing and storage capability will increase rapidly, bandwidth for downloading data will not increase as fast and can become a significant cost of a science program. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will not meet the science goals, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the observatory can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download them at a reduced resolution its overall efficiency will be dramatically increased. We are investigating and developing tools for a science goal monitoring (SGM) system. The SGM will have an interface to help capture higher-level science goals from the scientists and translate them into a flexible observing strategy that SGM can execute and monitor. SGM will then monitor the incoming data stream and interface with data processing systems to recognize significant events. When an event occurs, the system will use the science goals given it to reprioritize observations, and react appropriately and/or communicate with ground systems - both human and machine - for confirmation and/or further high priority analyses.

Jones, Jeremy↗

Science Goal Driven Observing: A Step Towards Maximizing Science Returns and Spacecraft Autonomy

In the coming decade, the drive to increase the scientific returns on capital investment and to reduce costs will force automation to be implemented in many of the scientific tasks that have traditionally been manually overseen. Thus, spacecraft autonomy will become an even greater part of mission operations. While recent missions have made great strides in the ability to autonomously monitor and react to changing health and physical status of spacecraft, little progress has been made in responding quickly to science driven events. The new generation of space-based telescopes/observatories will see deeper, with greater clarity, and they will generate data at an unprecedented rate. Yet, while onboard data processing and storage capability will increase rapidly, bandwidth for downloading data will not increase as fast and can become a significant bottleneck and cost of a science program. For observations of inherently variable targets and targets of opportunity, the ability to recognize early if an observation will not meet the science goals of variability or minimum brightness, and react accordingly, can have a major positive impact on the overall scientific returns of an observatory and on its operational costs. If the observatory can reprioritize the schedule to focus on alternate targets, discard uninteresting observations prior to downloading, or download them at a reduced resolution its overall efficiency will be dramatically increased. We are investigating and developing tools for a science goal monitoring (SGM) system. The SGM will have an interface to help capture higher-level science goals from scientists and translate them into a flexible observing strategy that SGM can execute and monitor. SGM will then monitor the incoming data stream and interface with data processing systems to recognize significant events. When an event occurs, the system will use the science goals given it to reprioritize observations, and react appropriately and/or communicate with ground systems - both human and machine - for confirmation and/or further high priority analyses.

Koratkar, Anuradha↗