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At least 343 records · Page 19

Improved Acquisition and Reconstruction for Wavelength-Resolved Neutron Tomography

Wavelength-resolved neutron tomography (WRNT) is an emerging technique for characterizing samples relevant to the materials sciences in 3D. WRNT studies can be carried out at beam lines in spallation neutron or reactor-based user facilities. Because of the limited availability of experimental time, potential imperfections in the neutron source, or constraints placed on the acquisition time by the type of sample, the data can be extremely noisy resulting in tomographic reconstructions with significant artifacts when standard reconstruction algorithms are used. Furthermore, making a full tomographic measurement even with a low signal-to-noise ratio can take several days, resulting in a long wait time before the user can receive feedback from the experiment when traditional acquisition protocols are used. In this paper, we propose an interlaced scanning technique and combine it with a model-based image reconstruction algorithm to produce high-quality WRNT reconstructions concurrent with the measurements being made. The interlaced scan is designed to acquire data so that successive measurements are more diverse in contrast to typical sequential scanning protocols. The model-based reconstruction algorithm combines a data-fidelity term with a regularization term to formulate the wavelength-resolved reconstruction as minimizing a high-dimensional cost-function. Using an experimental dataset of a magnetite sample acquired over a span of about two days, we demonstrate that our technique can produce high-quality reconstructions even during the experiment compared to traditional acquisition and reconstruction techniques. In summary, the combination of the proposed acquisition strategy with an advanced reconstruction algorithm provides a novel guideline for designing WRNT systems at user facilities.

47 OTHER INSTRUMENTATION↗

The CHIMERAS project: design framework for the Collisionless HIgh-beta Magnetized Experiment Researching Astrophysical Systems

From the near-Earth solar wind to the intracluster medium of galaxy clusters, collisionless, high-beta, magnetized plasmas pervade our universe. Energy and momentum transport from large-scale fields and flows to small-scale motions of plasma particles is ubiquitous in these systems, but a full picture of the underlying physical mechanisms remains elusive. The transfer is often mediated by a turbulent cascade of Alfvénic fluctuations as well as a variety of kinetic instabilities; these processes tend to be multi-scale and/or multi-dimensional, which makes them difficult to study using spacecraft missions and numerical simulations alone. Meanwhile, existing laboratory devices struggle to produce the collisionless, high ion beta (β i ≳ 1), magnetized plasmas across the range of scales necessary to address these problems. As envisioned in recent community planning documents, it is therefore important to build a next generation laboratory facility to create a β i ≳ 1, collisionless, magnetized plasma in the laboratory for the first time. A working group has been formed and is actively defining the necessary technical requirements to move the facility towards a construction-ready state. Recent progress includes the development of target parameters and diagnostic requirements as well as the identification of a need for source-target device geometry. As the working group is already leading to new synergies across the community, we anticipate a broad community of users funded by a variety of federal agencies (including National Aeronautics and Space Administration, Department of Energy and National Science Foundation) to make copious use of the future facility.

astrophysical plasmas↗

APS Science 2020 (Vol. 2)

The U.S. Department of Energy's Advanced Photn Source (APS) is one of the world’s most productive x-ray light source facilities. Each year, the APS provides high-brightness x-ray beams to a diverse community of more than 5,000 researchers in materials science, chemistry, condensed matter physics, the life and environmental sciences, and applied research. Researchers using the APS produce over 2,000 publications each year detailing impactful discoveries, and solve more vital biological protein structures than users of any other x-ray light source research facility. APS x-rays are ideally suited for explorations of materials and biological structures; elemental distribution; chemical, magnetic, electronic states; and a wide range of technologically important engineering systems from batteries to fuel injector sprays, all of which are the foundations of our nation’s economic, technological, and physical well-being. The APS occupies an 80-acre site on the Argonne campus, about 25 miles from downtown Chicago, Illinois. It shares a site with the Center for Nanoscale Materials and the Advanced Protein Characterization Facility.

01 COAL, LIGNITE, AND PEAT↗

The Manned Space Platform as an evolutionary means to achieve a permanent manned orbital operations facility

An evolutionary approach to permanently manned on-orbit facilities is discussed, and it is noted that the Science and Applications Manned Space Platform, which is the first step in this evolution, can be based primarily on existing and currently planned hardware. It is shown how by upgrading the systems capabilities of the Spacelab modules, the platform can be reconfigured to provide a permanent manned research and operations facility. The facility can grow in size and capability to accommodate increases in user requirements, more experiment modules, and larger crews and to provide additional power and heat rejection. It is noted that the Growth-Permanently Manned Facility can be used for science activities and/or to support various operations functions such as space construction, servicing and maintaining space systems, and vehicle assembly.

Schwartz, J. M.↗

Delivering real-time multi-modal materials analysis with enterprise beamlines

Contemporary advancements in low-cost automation and computation, reduced barrier to entry in developing artificial intelligence/machine learning (AI/ML), and increased ability to represent complex materials in digital form have led to a number of accelerated materials discovery platforms. However, many of these approaches operate with completely rigid vertical integration in an isolated feedback loop using limited modalities. In order to make a substantial impact on discovering new energy materials, AI-driven experiments must operate collaboratively with each other and researchers and over multiple measurement modalities. Herein, we describe the potential for an “internet of things” approach to self-driving enterprise beamlines that merges core information technologies, robotics, and multi-modal AI. The approach will enable full utility of light sources, collaborate effectively with other remote materials acceleration platforms, and help stride toward the world’s energy future.

36 MATERIALS SCIENCE↗

Project Assessment for Biological and Environmental Research: Report from the BER Advisory Committee

The construction, operation, and stewardship of large-scale scientific user facilities and cutting edge capabilities have been integral to the mission of the U.S. Department of Energy (DOE) Office of Science from its earliest days. To help identify and prioritize new or upgraded facilities critical to scientific innovation over the next 10 years, the Office of Science director issued a charge to the federal advisory committees of six of its program offices in December 2023, including the Biological and Environmental Research (BER) program. The charge letter (see p. ii) asked the advisory committees to: 1. Consider what new or upgraded facilities will be necessary to position the Office of Science at the forefront of scientific discovery. 2. Deliver a short letter report describing each facility in terms of two criteria: (a) the potential to contribute to world-leading science in the next decade and (b) the readiness for construction.

99 GENERAL AND MISCELLANEOUS↗

Direct Data Distribution From Low-Earth Orbit

NASA Lewis Research Center (LeRC) is developing the space and ground segment technologies necessary to demonstrate a direct data distribution (1)3) system for use in space-to-ground communication links from spacecraft in low-Earth orbit (LEO) to strategically located tracking ground terminals. The key space segment technologies include a K-band (19 GHz) MMIC-based transmit phased array antenna, and a multichannel bandwidth- and power-efficient digital encoder/modulate with an aggregate data rate of 622 Mb/s. Along with small (1.8 meter), low-cost tracking terminals on the ground, the D3 system enables affordable distribution of data to the end user or archive facility through interoperability with commercial terrestrial telecommunications networks. The D3 system is applicable to both government and commercial science and communications spacecraft in LEO. The features and benefits of the D3 system concept are described. Starting with typical orbital characteristics, a set of baseline requirements for representative applications is developed, including requirements for onboard storage and tracking terminals, and sample link budgets are presented. Characteristics of the transmit array antenna and digital encoder/modulator are described. The architecture and components of the tracking terminal are described, including technologies for the next generation terminal. Candidate flights of opportunity for risk mitigation and space demonstration of the D3 features are identified.

Budinger, James M.↗

The 1990 annual statistics and highlights report

The National Space Science Data Center (NSSDC) has archived over 6 terabytes of space and Earth science data accumulated over nearly 25 years. It now expects these holdings to nearly double every two years. The science user community needs rapid access to this archival data and information about data. The NSSDC has been set on course to provide just that. Five years ago the NSSDC came on line, becoming easily reachable for thousands of scientists around the world through electronic networks it managed and other international electronic networks to which it connected. Since that time, the data center has developed and implemented over 15 interactive systems, operational nearly 24 hours per day, and is reachable through DECnet, TCP/IP, X25, and BITnet communication protocols. The NSSDC is a clearinghouse for the science user to find data needed through the Master Directory system whether it is at the NSSDC or deposited in over 50 other archives and data management facilities around the world. Over 13,000 users accessed the NSSDC electronic systems, during the past year. Thousands of requests for data have been satisfied, resulting in the NSSDC's sending out a volume of data last year that nearly exceeded a quarter of its holdings. This document reports on some of the highlights and distribution statistics for most of the basic NSSDC operational services for fiscal year 1990. It is intended to be the first of a series of annual reports on how well NSSDC is doing in supporting the space and Earth science user communities.

Green, James L.↗

Developing and Distributing HEP Software Stacks with Spack

The Computational Science and AI Directorate at Fermilab is using Spack to support the development efforts of a large number of scientific programmers, in many independent projects and experiments. While independent, these projects share many dependencies. They are typically under continuous and fairly rapid development. They have to support deployment on diverse hardware. This is a different context than is typical for the management of HPC software, where Spack was born. To support our community, we have created a model that enables users to develop code with greater efficiency than is possible with Spack’s current development facilities. In this talk we will present: - a brief introduction to the science we support (particle physics) - how the code we work with is naturally organized into several layers of packages - how we are using Spack to manage those layers - how we leverage the layering to provide efficient support for developers, using our Spack extension “MPD”. - some suggestions for changes or additions to Spack to make such work easier.

Knoepfel, Kyle J. [Fermilab]↗

MODIS-HIRIS ground data systems commonality report

The High Resolution Imaging Spectrometer (HIRIS) and Moderate Resolution Imaging Spectrometer (MODIS) Data Systems Working Group was formed in September 1988 with representatives of the MODIS Data System Study Group and the HIRIS Project Data System Design Group to collaborate in the development of requirements on the EosDIS necessary to meet the science objectives of the two facility instruments. A major objective was to identify and promote commonality between the HIRIS and MODIS data systems, especially from the science users' point of view. A goal was to provide a base set of joint requirements and specifications which could easily be expanded to a Phase-B representation of the needs of the science users of all EOS instruments. This document describes the points of commonality and difference between the Level-II Requirements, Operations Concepts, and Systems Specifications for the ground data systems for the MODIS and HIRIS instruments at their present state of development.

Han, D.↗

Conceptual design for the space station Freedom modular combustion facility

A definition study and conceptual design for a combustion science facility that will be located in the Space Station Freedom's baseline U.S. Laboratory module is being performed. This modular, user-friendly facility, called the Modular Combustion Facility, will be available for use by industry, academic, and government research communities in the mid-1990's. The Facility will support research experiments dealing with the study of combustion and its byproducts. Because of the lack of gravity-induced convection, research into the mechanisms of combustion in the absence of gravity will help to provide a better understanding of the fundamentals of the combustion process. The background, current status, and future activities of the effort are covered.

Source record↗

Leveraging ARM Data to Improve Models for Predictive Understanding of Energy and Security Challenges

Extreme weather and natural hazards can disrupt the energy sector, affecting demand, generation, transmission, distribution, consumption and operational planning at regional and national scales. These disruptions stem from a broad range of atmospheric phenomena, including winter storms, freezing rain, wet snow loading, severe convection, flooding and landslides, wildfires, prolonged heat, and drought. Many of these same phenomena can also affect national security through impacts to transportation and infrastructure. To support the U.S. Department of Energy (DOE) focus on energy resilience and national security, the Atmospheric Radiation Measurement (ARM) User Facility is uniquely positioned to contribute measurement data, analyses, and modeling frameworks that can significantly improve predictive understanding of these hazards to mitigate their effects. To explore this opportunity, ARM convened a two-part virtual workshop in November 2025. The workshop engaged interdisciplinary experts in atmospheric science, energy systems, modeling, and operations. The goal of the meeting was to engage with these interdisciplinary experts to address three questions: • What are examples of atmospheric processes that represent significant risks to energy security or national security and where are those risks greatest? • What measurements or measurement strategies would improve ARM’s capacity to address these issues? • How can ARM and users of the ARM facility better work with the Energy Exascale Earth System Model (E3SM) and multi-sector modeling communities to apply ARM data to improving E3SM simulations of these phenomena? Participants were asked to submit white papers ahead of the meeting to initiate thinking on these themes and to help organize discussions. Workshop sessions were then organized around themes identified in the white papers. First from the white papers and then through subsequent discussions, workshop participants identified many examples that address the three questions listed above. Participants called out energy system vulnerabilities to weather phenomena such as the impact of freezing rain, strong winds, and excessive heat on power grids. They also noted the effects that weather phenomena could have on energy demand or supply (e.g., through effects of extreme temperatures). They called out security vulnerabilities such as impacts to crops from aerosol-borne pathogens and risks to industry due to melting permafrost in the Arctic. In all, over a dozen meteorological phenomena were linked to energy or security vulnerabilities. For many of the identified phenomena, participants pointed out where ARM was well poised to address issues (e.g., through measurements of cloud microphysics to inform studies of freezing rain) but also noted needs for additional measurements or modified measurement strategies. For example, adaptive scanning of severe weather would be valuable for probing winter storms or severe convection. Participants pointed out the value in integrating external observations with ARM measurements and with applying artificial intelligence (AI) to ARM observation analysis and they advocated for using model simulations to help optimize measurement strategies through Observing System Simulation Experiments (OSSEs). It was clear from the workshop that there are many ways that ARM observations can be used to mitigate energy and security concerns, but meeting participants were also asked to identify what they considered to be the greatest opportunities by ranking issues pertaining to the three workshop questions. This was accomplished through a survey administered to participants between the two virtual sessions. The highest-priority phenomena identified were winter storms, severe convection, and arctic processes. Discussion in the second session, therefore, focused primarily on these three areas, which were most fully developed in exploring ARM opportunities. Nevertheless, it was also clear that ARM has opportunities to contribute to all the identified topics. This report describes the workshop, including input from discussion and white papers (Sections 2 and 3) and a list of priority recommendations (section 4). Many other ideas for ARM contributions are discussed in individual white papers (Appendix D).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗

Space station: Cost and benefits

Costs for developing, producing, operating, and supporting the initial space station, a 4 to 8 man space station, and a 4 to 24 man space station are estimated and compared. These costs include contractor hardware; space station assembly and logistics flight costs; and payload support elements. Transportation system options examined include orbiter modules; standard and extended duration STS fights; reusable spacebased perigee kick motor OTV; and upper stages. Space station service charges assessed include crew hours; energy requirements; payload support module storage; pressurized port usage; and OTV service facility. Graphs show costs for science missions, space processing research, small communication satellites; large GEO transportation; OVT launch costs; DOD payload costs, and user costs.

Source record↗

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A field programmable gate array-based timing and control system for the dynamic compression sector

A field programmable gate array (FPGA)-based timing and trigger control system has been developed for the Dynamic Compression Sector (DCS) user facility located at the Advanced Photon Source (APS) at Argonne National Laboratory. The DCS is a first-of-its-kind capability dedicated to dynamic compression science. All components of the DCS laser shock station—x-ray choppers, single-shot shutter, internal laser triggers, and shot diagnostics—must be synchronized with respect to the arrival of x rays in the hutch. An FPGA synchronized to the APS storage ring radio frequency clock (352 MHz) generates trigger signals for each stage of the laser and x-ray shutter system with low jitter. The developed FPGA-based control system was the first system used to control the laser and the shutter system since its commissioning, and it has been developing since then to improve the timing jitter. The system is composed of a Zynq FPGA, a debug card, line drivers, and a power supply. The delay and offsets of the trigger signals can be adjusted by using a user-friendly graphical user interface with high precision. Here, the details of the system architecture, timing requirements, firmware, and software implementation along with the performance evaluation are presented in this paper. The system offers low timing jitter (15.5 ps rms) with respect to the APS 352 MHz clock, suitable for the 100 ps (FWHM) x-ray bunch duration at the APS.

47 OTHER INSTRUMENTATION↗

Observational data from uncrewed systems over Southern Great Plains

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of data sets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center and made publicly available to the user community https://adc.arm.gov/discovery/#/results/s::sgp*U3 and https://adc.arm.gov/discovery/#/results/s::sgp*tbs. These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This manuscript describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.

54 ENVIRONMENTAL SCIENCES↗

Facile Integration of Robots into Experimental Orchestration at Scientific User Facilities

Integration of robots into scientific user facilities, such as the National Synchrotron Light Source II, improves their efficiency and capacity. Many such facilities use the opensource Bluesky project for experimental control and orchestration. However, there remains an open challenge in deploying robotic solutions at these facilities that are reconfigurable, extensible, and compatible with pre-existing software infrastructure. Herein, we introduce a framework that uses the Robotic Operating System 2 (ROS2) and Bluesky to provide extensible robotic applications, while working under the operational constraints of a large-scale user facility. We demonstrated this framework by integrating a robotic arm to pick and place a sample holder at a beamline, recording a 90% repeatability rate. This provides the groundwork for further new robotics applications at large-scale scientific user facilities that depend on Bluesky.

36 MATERIALS SCIENCE↗