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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗
DOE OSTI2023

The Next-Generation Ecosystem Experiment Arctic Rainfall Simulator: a tool to understand the effects of changing rainfall patterns in the Arctic

Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R 2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Specialized Plant Growth Chamber Designs to Study Complex Rhizosphere Interactions

The rhizosphere is a dynamic ecosystem shaped by complex interactions between plant roots, soil, microbial communities and other micro- and macro-fauna. Although studied for decades, critical gaps exist in the study of plant roots, the rhizosphere microbiome and the soil system surrounding roots, partly due to the challenges associated with measuring and parsing these spatiotemporal interactions in complex heterogeneous systems such as soil. To overcome the challenges associated with in situ study of rhizosphere interactions, specialized plant growth chamber systems have been developed that mimic the natural growth environment. This review discusses the currently available lab-based systems ranging from widely known rhizotrons to other emerging devices designed to allow continuous monitoring and non-destructive sampling of the rhizosphere ecosystems in real-time throughout the developmental stages of a plant. We categorize them based on the major rhizosphere processes it addresses and identify their unique challenges as well as advantages. We find that while some design elements are shared among different systems (e.g., size exclusion membranes), most of the systems are bespoke and speaks to the intricacies and specialization involved in unraveling the details of rhizosphere processes. We also discuss what we describe as the next generation of growth chamber employing the latest technology as well as the current barriers they face. We conclude with a perspective on the current knowledge gaps in the rhizosphere which can be filled by innovative chamber designs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Jupiter Laser Facility Annual Report, FY 2025

Dear JLF community, I cannot believe I am now entering my third year as JLF director — time definitely flies when you are having fun! FY25 was another pivotal year for the Jupiter Laser Facility, marked by both scientific achievement and growing visibility for our community. Building on the successful reopening and refurbishment of the facility, we continued to demonstrate how JLF drives innovation in high energy density and fusion energy science, laser technology, and workforce development. Across Janus, Titan, and COMET, users executed a diverse portfolio of experiments, from dynamic compression and opacity measurements to laser plasma interactions, laboratory astrophysics, and advanced diagnostics. These efforts are highlighted in this report, including the development of new probes that capture the time evolution of plasmas on a single shot, and diagnostics and platforms that are already impacting experiments at NIF and other large facilities. JLF continues to serve as both a testbed for new ideas and a bridge to larger scale campaigns. FY25 also showcased the broader role of JLF within the Laboratory and the national HED science ecosystem. The NIF JLF User Groups Meeting in February brought nearly 180 participants to Livermore and highlighted the scientific progress made during JLF’s first full year of renewed operations. JLF research and users were recognized with Director’s Institutional Awards and Early and Mid Career awards, underscoring the quality and impact of the work performed here. Our team also contributed prominently to national conversations about laser safety, plasma physics, and inertial fusion energy through invited talks, conferences, and professional society leadership. JLF’s integration with LaserNetUS deepened this year as well. We launched a new technical exchange program across LaserNetUS facilities and kicked it off with a JLF team visit to the BELLA Center at Lawrence Berkeley National Laboratory. These exchanges are strengthening operations, sharing best practices, and improving the user experience across the network. Filming for the LaserNetUS “Behind the Scenes” series and participation in the annual LaserNetUS meeting further increased the visibility of our facility and our users. At the same time, JLF continues to play a central role in ambitious new programs, such as the Big Aperture Thulium laser effort funded through one of the DOE Office of Science Microelectronics Science Research Centers, which will use JLF infrastructure to explore next generation high rep rate lasers for EUV and x-ray source development. A core part of our mission remains training the next generation of scientists. In FY25, we welcomed another cohort of summer students, who joined experimental teams on Titan and presented their research at LLNL’s student poster symposium and national inertial fusion energy meetings. JLF users and early career scientists showcased their work at conferences across the country, highlighting experiments performed at the facility. These hands on experiences, and the mentoring provided by our staff and user teams, are central to JLF’s identity as a true user facility. Finally, FY25 reinforced JLF’s role as a focal point for partnerships and outreach. We hosted visits from international collaborators, science leaders, and we shared the story of the facility through venues such as the Big Ideas Lab podcast. These interactions help connect our work to a broader scientific and policy audience and open new pathways for collaboration. As we look ahead, the combination of refurbished hardware, new capabilities like STILETTO and enhanced short pulse performance on Titan, strong partnerships across LLNL and LaserNetUS, and a growing user community positions JLF for an even more ambitious program in the coming years. I am deeply grateful to our technical and operations staff for their dedication, to our LLNL partners for their continued support, and to our users for bringing bold, creative ideas to the facility. I look forward to more experiments, capabilities, partnerships, and groundbreaking science in the years to come! With brightest regards, Félicie Albert, JLF Director.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Workshop Report: Rural Electric Cooperative Distributed Energy Resource Business Model Development Workshops

The United States' energy future is being shaped by decades of technology innovation, rapidly changing consumer requirements, and governmental focus on securing reliable, low-cost energy sources. With expanded electrification and increased emphasis on grid reliability coupled with the heightened complexity and risks associated with transmission infrastructure, the use of distributed energy resources (DERs) is more commonly being considered a safe, efficient, and cost-effective way to maintain grid resilience and reliability. Amidst improvements in performance, decreasing costs, and unprecedented federal policy support for DERs, electric cooperatives are considering new opportunities to use these assets to ensure secure and reliable operations for millions of customers. In light of these developments, a series of workshops were held to collaborate on the development of business models for DERs in rural electric cooperative ecosystems. The first workshop was held July 11, 2024, at the Tri-State Generation and Transmission Association Inc. headquarters in Westminster, Colorado (hereafter referred to as the "Tri-State Workshop"). The second workshop was hosted by PNGC Power on Oct. 9, 2024, in Portland, Oregon (hereafter referred to as the "PNGC Power Workshop"). These workshops convened representatives from G&Ts, distribution cooperatives,2 the energy industry, the financial community, the U.S. government, national and regional organizations, and national laboratories to share perspectives on the unique needs, challenges, and opportunities that they face as DERs are further integrated into the grid. The workshops were designed to address the following objectives: (1) develop the enabling attributes of electric cooperative DER business models, (2) explore pathways for generating community benefits from these assets, and (3) identify technical challenges and market risks for DERs in rural electric cooperative service territories. This report outlines key findings and major themes identified by workshop participants that federal agencies, G&Ts, distribution cooperatives, and other entities can consider to advance electric cooperative DER business models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness.

multi-scale modeling↗
DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Livewire: A Model Platform for Data Quality Assessment and AI Readiness Across DOE Missions

High-quality, well-governed data is essential for accelerating discovery and achieving operational excellence across DOE and national laboratory missions. The Livewire Data Platform is a DOE-supported platform that offers automated assessments of data quality, standardization, provenance, and Artificial Intelligence (AI) readiness. It allows researchers and data practitioners to systematically and easily evaluate datasets against established governance criteria and prepare them for advanced analytics. Livewire addresses critical challenges in DOE's data ecosystem with integrated capabilities for metadata validation, provenance tracking, and schema alignment. This platform's automated workflows assist users in identifying data quality gaps, enhancing interoperability between datasets collected from various stakeholders, and ensuring compliance with DOE data standards, all while reducing manual curation efforts. Additionally, we will discuss its AI readiness framework, which is being developed to prepare datasets for training models, developing advanced analytic tools, and machine learning applications. Using some of the more than one hundred tabular datasets on Livewire, processed with this open-source methodology, we will demonstrate how Livewire can serve as a model for scalable, standards-driven data management. This approach provides a pathway to leverage existing and future datasets within the DOE, boosting innovation and efficiency across national laboratories.

33 - ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2014

Antenna Technology for 3-D Wide Swath Imaging Supporting ACE

A fundamental goal for the National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) is to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack of understanding of aerosol-cloud interactions. As part of the mission instrument suite, the ACE Science Working Group has recommended a dual-frequency radar comprised of a fixed-beam 94 GHz (W-band) radar and a wide-swath 35 GHz (Ka-band) imaging radar. Our ACE radar architecture addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (>100 km) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflector/reflectarray and b) a Ka-band AESA feed module. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost while enabling wide-swath imaging at Ka-band. This presentation describes the approach used to develop the reflectarray surface and plans for its TRL maturation.The dual-frequency antenna is comprised of a primary cylindrical reflector/reflectarray surface illuminated by a fixed W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat) and a Ka-band AESA line feed. The AESA feed design leverages state-of-the-art GaN transmit/receive (T/R) MMICs with high RF output power, high power added efficiency and low noise figure. The innovative reflectarray surface provides beam focusing at W-band, but it is transparent at Ka-band.

RAdar Antenna↗
NASA NTRSDate not supplied

LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal

We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.

Life Sciences↗
DOE OSTI2024

Integrating quantum computing resources into scientific HPC ecosystems

Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era’s inherent external noise issues. Here, this paper discusses the integration of QC as a computational accelerator within classical scientific high-performance computing (HPC) systems. By leveraging a broad spectrum of simulators and hardware technologies, we propose a hardware-agnostic framework for augmenting classical HPC with QC capabilities. Drawing on the HPC expertise of the Oak Ridge National Laboratory (ORNL) and the HPC lifecycle management of the Department of Energy (DOE), our approach focuses on the strategic incorporation of QC capabilities and acceleration into existing scientific HPC workflows. This includes detailed analyses, benchmarks, and code optimization driven by the needs of the DOE and ORNL missions. Our comprehensive framework integrates hardware, software, workflows, and user interfaces to foster a synergistic environment for quantum and classical computing research. This paper outlines plans to unlock new computational possibilities, driving forward scientific inquiry and innovation in a wide array of research domains.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

A daily, 250 m and real-time gross primary productivity product (2000–present) covering the contiguous United States

Abstract. Gross primary productivity (GPP) quantifies the amount of carbon dioxide (CO2) fixed by plants through photosynthesis. Although as a key quantity of terrestrial ecosystems, there is a lack of high-spatial-and-temporal-resolution, real-time and observation-based GPP products. To address this critical gap, here we leverage a state-of-the-art vegetation index, near-infrared reflectance of vegetation (NIRV), along with accurate photosynthetically active radiation (PAR), to produce a SatelLite Only Photosynthesis Estimation (SLOPE) GPP product for the contiguous United States (CONUS). Compared to existing GPP products, the proposed SLOPE product is advanced in its spatial resolution (250 m versus >500 m), temporal resolution (daily versus 8 d), instantaneity (latency of 1 d versus >2 weeks) and quantitative uncertainty (on a per-pixel and daily basis versus no uncertainty information available). These characteristics are achieved because of several technical innovations employed in this study: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR. (2) SLOPE couples highly efficient and pragmatic gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRV (SANIRV) dataset. (3) SLOPE couples a temporal pattern recognition approach with a long-term Cropland Data Layer (CDL) product to predict dynamic C4 crop fraction. Through developing a parsimonious model with only two slope parameters, the proposed SLOPE product explains 85 % of the spatial and temporal variations in GPP acquired from 49 AmeriFlux eddy-covariance sites (324 site years), with a root-mean-square error (RMSE) of 1.63 gC m−2 d−1. The median R2 over C3 and C4 crop sites reaches 0.87 and 0.94, respectively, indicating great potentials for monitoring crops, in particular bioenergy crops, at the field level. With such a satisfactory performance and its distinct characteristics in spatiotemporal resolution and instantaneity, the proposed SLOPE GPP product is promising for biological and environmental research, carbon cycle research, and a broad range of real-time applications at the regional scale. The archived dataset is available at https://doi.org/10.3334/ORNLDAAC/1786 (download page: https://daac.ornl.gov/daacdata/cms/SLOPE_GPP_CONUS/data/, last access: 20 January 2021) (Jiang and Guan, 2020), and the real-time dataset is available upon request.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The 200 Gbps Challenge: Imagining HL-LHC analysis facilities

The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Framework for a Digital Documented Safety Analysis

This framework is developed to progress the digital implementation of digital tools applied to the DOE authorization process, with future applications to NRC SAR development/review, to accelerate the design and review processes of advanced nuclear reactors. The engineering design and licensing process for nuclear reactors is currently burdened by a document-based approach that leads to duplications and errors due to a lack of traceability among numerous static documents. Changes to design information require labor-intensive manual tracing through these documents, creating a high potential for human error. The adoption of a digital ecosystem, utilizing a digital thread to link various aspects of project design and analysis, promises dynamic documentation generation, automatic updates, and error reduction. Model Based Definition (MBD) and Product Lifecycle Management (PLM) tools are central to this digital transformation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits

Mycorrhizal fungi are mutualists that play crucial roles in nutrient acquisition in terrestrial ecosystems. Mycorrhizal symbioses arose repeatedly across multiple lineages of Mucoromycotina, Ascomycota, and Basidiomycota. Considerable variation exists in the capacity of mycorrhizal fungi to acquire carbon from soil organic matter. Here, we present a combined analysis of 135 fungal genomes from 73 saprotrophic, endophytic and pathogenic species, and 62 mycorrhizal species, including 29 new mycorrhizal genomes. This study samples ecologically dominant fungal guilds for which there were previously no symbiotic genomes available, including ectomycorrhizal Russulales, Thelephorales and Cantharellales. Our analyses show that transitions from saprotrophy to symbiosis involve (1) widespread losses of degrading enzymes acting on lignin and cellulose, (2) co-option of genes present in saprotrophic ancestors to fulfill new symbiotic functions, (3) diversification of novel, lineage-specific symbiosis-induced genes, (4) proliferation of transposable elements and (5) divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Determination of fluorine distribution in shark teeth by laser-induced breakdown spectroscopy

Quantifying the chemical composition of fast-growing hard tissues in the environment can shed valuable information in terms of understanding ecosystems both prehistoric and current. Changes in chemical composition can be correlated with environmental conditions and can provide information about the organism's life. Sharks can lose 0.1 to 1.1 teeth/day, depending on species, which offers a unique opportunity to record environmental changes over a short duration of time. Shark teeth contain a biomineral phase that is made up of fluorapatite [Ca 5 (PO 4 ) 3 F], and the F distribution within the tooth can be correlated to tooth hardness. Typically, this is determined by bulk acid digestion, energy-dispersive X-ray spectroscopy (EDS), or wavelength-dispersive spectroscopy. Here we present laser-induced breakdown spectroscopy (LIBS) as an alternative and faster approach for determining F distribution within shark teeth. Using a two-volume laser ablation chamber (TwoVol3) with innovative embedded collection optics for LIBS, shark teeth were investigated from sand tiger (Carcharias Taurus), tiger (Galeocerdo Cuvier), and hammerhead sharks (Sphyrnidae). Fluorine distribution was mapped using the CaF 603 nm band (CaF, Β 2 Σ + → X 2 Σ + ) and quantified using apatite reference materials. In addition, F measurements were cross referenced with EDS analyses to validate the findings. Distributions of F (603 nm), Na (589 nm), and H (656 nm) within the tooth correlate well with the expected biomineral composition and expected tooth hardness. This rapid methodology could transform the current means of determining F distribution, particularly when large sample specimens (350 mm 2 , presented here) and large quantities of specimens are of interest.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Technology Development for 3-D Wide Swath Imaging Supporting ACE

The National Academy of Sciences Decadal Survey (DS) Aerosol-Cloud-Ecosystems Mission (ACE) aims to advance our ability to observe and predict changes to the Earth's hydrological cycle and energy balance in response to climate forcing, especially those changes associated with the effects of aerosol on clouds and precipitation. ACE is focused on obtaining measurements to reduce the uncertainties in current climate models arising from the lack in understanding of aerosol-cloud interactions. As part of the mission instrument suite, a dual-frequency radar comprised of a fixed-beam 94 gigahertz (W-band) radar and a wide-swath 35 gigahertz (Ka-band) imaging radar has been recommended by the ACE Science Working Group.In our 2010 Instrument Incubator Program project, we've developed a radar architecture that addresses the challenge associated with achieving the measurement objectives through an innovative, shared aperture antenna that allows dual-frequency radar operation while achieving wide-swath (100 kilometers) imaging at Ka-band. The antenna system incorporates 2 key technologies; a) a novel dual-band reflectorreflectarray and b) a Ka-band Active Electronically Scanned Array (AESA) feed module. The dual-band antenna is comprised of a primary cylindrical reflectorreflectarray surface illuminated by a point-focus W-band feed (compatible with a quasi-optical beam waveguide feed, such as that employed on CloudSat); the Ka-band AESA line feed provides wide-swath across-track scanning. The benefits of this shared-aperture approach include significant reductions in ACE satellite payload size, weight, and cost, as compared to a two aperture approach. Four objectives were addressed in our project. The first entailed developing the tools for the analysis and design of reflectarray antennas, assessment of candidate reflectarray elements, and validation using test coupons. The second objective was to develop a full-scale aperture design utilizing the reflectarray surface and to detail specific requirements and trades for the Ka-band AESA line feed. As part of the third objective a subscale antenna, similar to the full-scale aperture design, was developed, integrated, and flown with the Cloud Radar System during the 2014 Integrated Precipitation and Hydrology Experiment. The fourth and ongoing objective entails developing a GaN MMIC (Gallium Nitride Monolithic Microwave Integrated Circuits) power amplifier for use in the Ka-band AESA. An overview of the progress made on this project and a look ahead at the 2013 IIP (Instrument Incubator Program) award selection will be presented.

Antenna↗
DOE OSTI2022

The Land–Sea Connection: Insights Into the Plant Lineage from a Green Algal Perspective

The colonization of land by plants generated opportunities for the rise of new heterotrophic life forms, including humankind. A unique event underpinned this massive change to earth ecosystems—the advent of eukaryotic green algae. Today, an abundant marine green algal group, the prasinophytes, alongside prasinodermophytes and nonmarine chlorophyte algae, is facilitating insights into plant developments. Genome-level data allow identification of conserved proteins and protein families with extensive modifications, losses, or gains and expansion patterns that connect to niche specialization and diversification. Here, we contextualize attributes according to Viridiplantae evolutionary relationships, starting with orthologous protein families, and then focusing on key elements with marked differentiation, resulting in patchy distributions across green algae and plants. We place attention on peptidoglycan biosynthesis, important for plastid division and walls; phytochrome photosensors that are master regulators in plants; and carbohydrate-active enzymes, essential to all manner of carbohydratebiotransformations. Together with advances in algal model systems, these areas are ripe for discovering molecular roles and innovations within and across plant and algal lineages.

Plant Sciences↗