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DOE OSTI2024

Spin-Controllable Dynamics in Defect-Engineered Carbon Nanotubes as Single Photon Emitters: Data-Driven Modeling and Computations

Quantum technologies, such as quantum computing and sensing, require efficient single-photon emission (SPE) sources that operate at room temperature in telecom wavelengths. While several materials can serve as SPE sources, no single platform meets all the criteria for efficiency, ambient operation, and scalability. Single-walled carbon nanotubes (SWCNTs) with covalently attached molecules offer a promising solution. Their SPE can be easily tuned via modifications of the SWCNT's diameter, chirality, and bonded molecules, enabling emission across near-IR to telecom wavelengths at ambient conditions. However, to fully realize the potential of SWCNTs and unlock their quantum capabilities, a deeper understanding of how structural defects from molecular adducts affect their emission and competing photoexcited processes is essential. To address this gap in our knowledge, this project combined quantum chemistry calculations with data-driven methods of cheminformatics (QSAR) and machine learning (ML). The developed computational approaches have provided several design strategies for covalent functionalization of SWCNTs to improve their optical response. The collaboration with Los Alamos National Lab (LANL) enabled direct comparison of computational and experimental data, facilitating method validation. This partnership was enhanced through access to LANL's Center for Integrated Nanotechnologies (CINT) utilizing User Facility Program and summer internships, which provided three NDSU graduate students with hands-on experience at LANL. The outcomes of this project included (1) Advancing the current stage of computational methods in accurate modeling of non-adiabatic spin-dependent photoexcited dynamics and its applicability to nanosystems consisting of thousands of atoms, realized as open-access codes linked to existing DFT-based software; (2) Establishing the relationship between the structure of adducts and SWCNTs and intrinsic excitonic and spin properties of defect states for guiding novel synthetic strategies and experimental probes of chemically functionalized SWCNTs as near-IR emitting materials; (3) Generating virtual libraries of hypothetical functionalized SWCNTs for virtual screening of their chemical structures and optical properties, leveraging new functionalities of SWCNTs; (4) Offering a unique experience for NDSU graduate students that prepared them for future scientific careers related to materials modeling and big data processing. These results were summarized in 12 published journal papers and 3 recently submitted papers. One of a key finding is that the position of defect sites on the SWCNT surface primarily drives the emission redshift (up to 100 meV), while the polarity of the defect-inducing molecules has a much smaller effect (~10 meV). However, the electron-donating or withdrawing properties of a molecule influence selecting reactivity of defect sites. These insights important for optimizing synthetic protocols for desired emissions in SWCNTs. We also revealed that the interaction between two defects at various positions on the SWCNT enhances the redshift and optical activity of states, favoring strong near-IR emission. This suggests that manipulations in defect concentrations is a promising strategy for controlling efficient emission. Mostly important, the defect position was found controllable by the spin states of photoexcited intermediates: Excited aromatic molecules form ortho defects with SWCNTs at their singlet states in the presence of oxygen, while oxygen-free conditions favor para defects via the triplet-state mechanism. Additionally, a heat-activated [2+2] cycloaddition reaction facilitates divalent defect formation with fewer bonding positions that narrows emission bands. These groundbreaking findings have been experimentally validated and significantly advance our understanding of defect chemistry in SWCNTs. Using a novel encoding technique and 3D-MoRSE descriptors, we developed highly accurate ML/QSAR models to predict both the 3D structure and optical properties of SWCNTs with chemical defects. This model enabled the creation of a virtual library of 125,556 structures, providing new insights into the relationship between SWCNT-defect structure and emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2025

The Pierre Auger Observatory open data

The Pierre Auger Collaboration has embraced the concept of open access to their research data since its foundation, with the aim of giving access to the widest possible community. A gradual process of release began as early as 2007 when 1% of the cosmic-ray data was made public, along with 100% of the space-weather information. In February 2021, a portal was released containing 10% of cosmic-ray data collected by the Pierre Auger Observatory from 2004 to 2018, during the first phase of operation of the Observatory. The Open Data Portal includes detailed documentation about the detection and reconstruction procedures, analysis codes that can be easily used and modified and, additionally, visualization tools. Since then, the Portal has been updated and extended. In 2023, a catalog of the highest-energy cosmic-ray events examined in depth has been included. A specific section dedicated to educational use has been developed with the expectation that these data will be explored by a wide and diverse community, including professional and citizen scientists, and used for educational and outreach initiatives. This paper describes the context, the spirit, and the technical implementation of the release of data by the largest cosmic-ray detector ever built and anticipates its future developments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Tripal, a community update after 10 years of supporting open source, standards-based genetic, genomic and breeding databases

Abstract Online, open access databases for biological knowledge serve as central repositories for research communities to store, find and analyze integrated, multi-disciplinary datasets. With increasing volumes, complexity and the need to integrate genomic, transcriptomic, metabolomic, proteomic, phenomic and environmental data, community databases face tremendous challenges in ongoing maintenance, expansion and upgrades. A common infrastructure framework using community standards shared by many databases can reduce development burden, provide interoperability, ensure use of common standards and support long-term sustainability. Tripal is a mature, open source platform built to meet this need. With ongoing improvement since its first release in 2009, Tripal provides full functionality for searching, browsing, loading and curating numerous types of data and is a primary technology powering at least 31 publicly available databases spanning plants, animals and human data, primarily storing genomics, genetics and breeding data. Tripal software development is managed by a shared, inclusive governance structure including both project management and advisory teams. Here, we report on the most important and innovative aspects of Tripal after 11 years development, including integration of diverse types of biological data, successful collaborative projects across member databases, and support for implementing FAIR principles.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Building a Bilingual Google Earth Engine Dashboard to Increase Accessibility to Long-term Time Series Remote Sensing Data for Monitoring Saline System Changes in Chile’s Atacama Desert

Saline systems, consisting of salt flats, ponds, and marshes, provide vital water resources to wildlife and communities in northern Chile’s Atacama Desert, one of the driest regions in the world. Mining is extensive in the Atacama, which contains 30% of the world’s lithium reserves and is abundant in potassium and boron. The groundwater that feeds into salt marshes and ponds is extracted in large volumes for mining operations, limiting the availability of water for ecosystems. However, identifying long-term and large-scale environmental impacts from local lithium mining on the saline systems is limited by region inaccessibility and terrain variability. Open access satellite imagery and cloud computing technology has made studying Atacama saline systems feasible and allowed for collaboration across different agencies and countries. The NASA DEVELOP Program partnered with Chile’s la Universidad de La Serena and Servicio Nacional de Geología y Minería (SERNAGEOMIN) to create the Saline Analysis Tool (SalT) in Google Earth Engine (GEE). SalT is used to analyze the extent and distribution of remote saline systems in the Atacama from 1986 to the present day. The tool filters Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) data from GEE’s data catalog and creates a single composite image per year for analysis. Additional output analyses include land cover classification, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) raster images that can be displayed on the map interface or exported. The tool can also generate time-lapse videos and charts displaying NDVI, NDWI, and land cover over time. A key feature of the tool is the use of a bilingual graphical user interface to make analysis accessible and customizable to different users’ needs—SalT provides options to select an analysis area, analysis time period, and outputs to display or export. The tool also incorporates new Earth observations as they are added to GEE’s catalog. The ability to easily visualize and analyze long-term remote sensing imagery will enable SERNAGEOMIN and la Universidad de la Serena to continually monitor changes in these saline systems and inform future land management policy.

NASA DEVELOP↗

DOE OSTI2022

A Primer on Phased Array Radar Technology for the Atmospheric Sciences

The scientific community has expressed interest in the potential of phased array radars (PARs) to observe the atmosphere with finer spatial and temporal scales. Although convergence has occurred between the meteorological and engineering communities, the need exists to increase access of PAR to meteorologists. Here, we facilitate these interdisciplinary efforts in the field of ground-based PARs for atmospheric studies. We cover high-level technical concepts and terminology for PARs as applied to studies of the atmosphere. A historical perspective is provided as context along with an overview of PAR system architectures, technical challenges, and opportunities. Envisioned scan strategies are summarized because they are distinct from traditional mechanically scanned radars and are the most advantageous for high-resolution studies of the atmosphere. Further, open access to PAR data is emphasized as a mechanism to educate the future generation of atmospheric scientists. Finally, a vision for the future of operational networks, research facilities, and expansion into complementary radar wavelengths is provided.

47 OTHER INSTRUMENTATION↗

NASA NTRSDate not supplied

Evaluating SAR Radiometric Terrain Correction products: Optimal products for applied users

Operational applications for Synthetic Aperture Radar (SAR) are under development around the world, driven by the free-and-open access of SAR C-band observations that Sentinel-1 of Copernicus has been providing since 2014. Groups like SERVIR, a joint initiative between NASA and USAID, are at the forefront of remote sensing applied uses, and have made many significant contributions to lower the barrier to access, process, and apply SAR for ecosystem services. A takeaway from the SERVIR experience in using SAR is the need to use the appropriate SAR polarimetric product. Radiometric Terrain Correction (RTC) is a key entry-level product for multiple applications that range from ecosystems to hazards. Many software packages exist to create RTC products from SLC or GRD-type Level-1 SAR data, some of which were released only recently, e.g. Interferometric SAR Computing Environment (ISCE) added an RTC module in April 2020. In addition, new versions of open source softwares are expected to address known issues from previous versions, such as Sentinel-1 Toolbox from the European Space Agency (SNAP-7). Despite the growing availability of RTC software solutions, little work has been done to identify differences between RTC products from different softwares. And to address the question, which open-source software produces the most accurate RTC product? This work evaluates Sentinel-1 RTC products created with three different softwares and approaches, including SNAP-7, ISCE-2, and a pseudo RTC product derived from GEE. The GAMMA-derived RTC product, a known optimal RTC and implemented by Alaska Satellite Facility (ASF), is used as a reference. Time series stacks over ten different sites representing varied terrain and ecosystems are evaluated. Products are evaluated for geolocation quality, absolute radiometric calibration, and for the fidelity of the radiometric terrain flattening. The results provide direct guidance and recommendations about the quality of the RTC products obtained from open source methods. This understanding is key to develop operational applications that rely on SAR Sentinel-1 data that need affordable and scalable solutions.

Africa Flores-Anderson↗

DOE OSTI2021

Arabidopsis bZIP11 Is a Susceptibility Factor During Pseudomonas syringae Infection

The induction of plant nutrient secretion systems is critical for successful pathogen infection. Some bacterial pathogens (e.g., Xanthomonas spp.) use transcription activator-like (TAL) effectors to induce transcription of SWEET sucrose efflux transporters. Pseudomonas syringae pv. tomato strain DC3000 lacks TAL effectors yet is able to induce multiple SWEETs in Arabidopsis thaliana by unknown mechanisms. Because bacteria require other nutrients in addition to sugars for efficient reproduction, we hypothesized that Pseudomonas spp. may depend on host transcription factors involved in secretory programs to increase access to essential nutrients. Bioinformatic analyses identified the Arabidopsis basic-leucine zipper transcription factor bZIP11 as a potential regulator of nutrient transporters, including SWEETs and UmamiT amino acid transporters. Inducible downregulation of bZIP11 expression in Arabidopsis resulted in reduced growth of P. syringae pv. tomato strain DC3000, whereas inducible overexpression of bZIP11 resulted in increased bacterial growth, supporting the hypothesis that bZIP11-regulated transcription programs are essential for maximal pathogen titer in leaves. Our data are consistent with a model in which a pathogen alters host transcription factor expression upstream of secretory transcription networks to promote nutrient efflux from host cells. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Biochemistry & Molecular Biology↗

DOE OSTI2024

Reference Design Cases for Floating Offshore Wind Arrays

Given the immature nature of the Floating Offshore Wind (FLOW) industry, there is a need for reference FLOW farm designs to allow researchers and technology developers to study the behavior of floating wind turbine systems, without having to design every part of those systems or without having to get access to a wide range of information that is often confidential. The International Energy Agency (IEA) Wind Task 49 is facilitating research collaboration on the integrated design of Floating Offshore Wind Arrays (FOWA), and will develop several reference FOWAs to facilitate R&D activities of the floating wind community and efficient scale change of the floating wind industry (from pilot farms to commercial ones). This paper will outline the key design considerations the task has identified for the sustainable deployment of large-scale FOWAs. The aim is to prepare a comprehensive overview of the different elements that impact the design of FOWA to support the development of best practices for FOWA design. The paper will also present three baseline reference design cases that are being prepared for shallow, intermediate and deep water sites. The final designs will be made open access including the engineering and cost inputs to accelerate further innovation, research and the deployment of FOWAs.

array layout↗

NASA NTRSDate not supplied

Dissemination of Global Flood Severity and Surface Water Mapping using Remote Sensing Data to Global Stakeholders

Flooding is a natural event that occurs frequently with high severity worldwide, responsible for significant societal and economic impacts. Disaster managers face significant challenges managing essential information for preparedness, response, and recovery efforts. The development of an open access, global flood alerting system for effective identification of flood impacted areas, classification of potential impacts, and the formulation of effective emergency response measures requires the incorporation of a wide variety of flood models and remote sensing data sources from multiple platforms. NASA is currently funding projects focused on flood forecasting, post-event flood mapping, flood depth estimation and pre-event flood severity estimation using Earth observation (EO) datasets and derived flood products. A new initiative in the Disasters Program is underway to disseminate flood products from different hydrologic models and sensors to global stakeholders via Pacific Disaster Center’s DisasterAWARE®, NASA’s Disasters Mapping Portal and potentially other mechanisms. This initiative focuses on improving response capacity and use of EO products in near real-time by a broader community for resource planning in case of extreme events. As part of this initiative, we have deployed Model of Models (MoM) – an open-source ensemble approach, that integrates outputs from hydrologic models and EO data from optical imagery to assess flood severity daily at sub-watershed level globally. The MoM output is integrated with the incident event system of DisasterAWARE to generate flood severity risk and flood impact boundaries, which are disseminated via the DisasterAWARE platform to different stakeholders globally for decision-making and response efforts. The next step will focus on using MoM outputs to estimate flood depth and extent mapping using high-resolution Synthetic Aperture Radar imagery, impact assessment using optical imagery and population datasets, and damage estimation using critical infrastructure datasets, which would be disseminated via DisasterAWARE to decision-makers, emergency managers and first responders around the world.

flood↗

DOE OSTI2026

A Comprehensive Calibration Framework for the Northwest River Forecast Center

We present a comprehensive framework developed by the Northwest River Forecast Center for calibrating hydrologically diverse basins. The framework includes models for snow, soil moisture, routing, channel loss, and consumptive use. Data inputs include a wide range of open-access datasets for meteorology, land use, topography, and land cover. The framework uses conceptual hydrologic models to handle basins with various hydrologic regimes including rain-driven and snowmelt-dominated basins. We also develop a flexible automatic calibration system that can handle numerous unobservable model parameters in a computationally efficient manner. A single-basin automatic calibration run can typically be completed on a modern laptop in under 10 min. We found that model performance metrics for this new approach match the quality of the NWRFC's previous labor-intensive manual calibrations. The model performance also rivals that of a state-of-the-art deep learning model at a fraction of the computational cost. This framework presents a new standard for the quality of calibrations possible with lumped conceptual hydrologic models, combining careful data curation, an objective calibration framework, and expert local knowledge. In addition, we have made software packages available for the entire suite of National Weather Service River Forecast System models, including SAC-SMA, SNOW-17, and Lag-K. These modern interfaces are intended to increase accessibility and facilitate future research.

Forecasting↗

DOE OSTI2024

Three-Dimensional Ultrastructure of Arabidopsis Cotyledons Infected with Colletotrichum higginsianum

We used serial block-face scanning electron microscopy (SBF-SEM) to study the host–pathogen interface between Arabidopsis cotyledons and the hemibiotrophic fungus Colletotrichum higginsianum. By combining high-pressure freezing and freeze-substitution with SBF-SEM, followed by segmentation and reconstruction of the imaging volume using the freely accessible software IMOD, we created 3D models of the series of cytological events that occur during the Colletotrichum–Arabidopsis susceptible interaction. We found that the host cell membranes underwent massive expansion to accommodate the rapidly growing intracellular hypha. As the fungal infection proceeded from the biotrophic to the necrotrophic stage, the host cell membranes went through increasing levels of disintegration culminating in host cell death. Intriguingly, we documented autophagosomes in proximity to biotrophic hyphae using transmission electron microscopy (TEM) and a concurrent increase in autophagic flux between early to mid/late biotrophic phase of the infection process. Occasionally, we observed osmiophilic bodies in the vicinity of biotrophic hyphae using TEM only and near necrotrophic hyphae under both TEM and SBF-SEM. Overall, we established a method for obtaining serial SBF-SEM images, each with a lateral ( x-y) pixel resolution of 10 nm and an axial ( z) resolution of 40 nm, that can be reconstructed into interactive 3D models using the IMOD. Application of this method to the Colletotrichum–Arabidopsis pathosystem allowed us to more fully understand the spatial arrangement and morphological architecture of the fungal hyphae after they penetrate epidermal cells of Arabidopsis cotyledons and the cytological changes the host cell undergoes as the infection progresses toward necrotrophy. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Biochemistry & Molecular Biology↗

NASA NTRSDate not supplied

Spaceflight Biospecimen Sharing in Support of Science Discovery and Exploration

For decades, NASA and international partners have flown non-human biological experiments in space to understand the effects of spaceflight and address potential biological hazards. Sending organisms into space is a costly endeavor which makes space-flown biological specimens a valuable resource. To enable maximum scientific return, samples not required by the Principal Investigators are harvested and collected mostly by NASA’s Space Biology Biospecimen Sharing Program. These specimens are collected according to well-established SOPs that maintain quality and integrity. The specimens are then preserved, archived, and made available to the international scientific community through NASA’s Institutional Scientific Collection (ISC) at Ames Research Center (ARC). The ISC-ARC biospecimens and descriptive metadata are findable and accessible for request through the Life Sciences Data Archive (LSDA). The NASA ISC-ARC currently stores over 32,000 specimens from Shuttle, International Space Station, and ground-based investigations (spaceflight analog experiments involving either hindlimb unloading, centrifugation, or partial weight-bearing study designs). Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. The specimens include tissues from many physiological systems including musculoskeletal, neurosensory, reproductive, respiratory, circulatory, and digestive. Tissues are stored at -80°C, -20°C, +4°C, or ambient and preserved in various fixatives. Descriptive metadata is available for all samples. Historically, these tissues have been used for a wide range of analyses, including histology, genomics, and transcriptomics. Plans are underway to expand the ISC-ARC beyond the mostly-rodent contents, to include a space-relevant microbial culture collection including bacteria, fungi, and yeast. This expansion of the ISC-ARC will now involve identifying and standardizing best practices for microbial curations. To ensure safe long-term storage of microbial isolates, a microbiology laboratory will be dedicated for identification, cell culture, and lyophilization. Awarding of tissue to public science investigators has resulted in 33 publications since 2011, with 48 requests being submitted since 2016. Of note, NASA GeneLab has been awarded ISC-ARC biospecimens in the past few years. GeneLab processes the biospecimens to generate various levels of ‘omics’ data, which are published on GeneLab’s open access online platform for bioinformatics analysis and visualization. This has helped a systems biology community grow around the processed-biospecimens’ datasets, resulting in many new publications and insights. Websites: https://www.nasa.gov/ames/research/space-biosciences/isc-bsp ; https://lsda.jsc.nasa.gov/Biospecimen

Ryan T. Scott↗

DOE OSTI2024

Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS

The Marine Algae Industrialization Consortium (MAGIC) was formed to address pressing challenges in the commercialization of microalgae as a source of biofuel. The “Marine Algae Industrialization Consortium (MAGIC): Combining biofuel and high-value bioproducts to meet the RFS” project formally addressed two US Department of Energy Bioenergy Technologies Office (BETO) goals: (1) Model the sustainable supply of 1 million metric tonnes ash free dry weight (AFDW) cultivated algal biomass and (2) Demonstrate valuable co-products produced along with biofuel intermediates to increase value of algal biomass by 30%. To achieve these goals, the project demonstrated and validated high-value co-products to drive down the cost of biofuel by increasing the value of algae “co-products” towards increasing the selling price of total algae biomass as one of the key drivers of economics and adoption. This was accomplished through five core, interdependent tasks including: (1) strain selection to identify and deliver strains for mass culture, (2) mass culture using a hybrid cultivation system and following key operating parameters for downstream applications to provide algae feedstock, (3) recovery and conversion to evaluate two alternative methods to separate dry algae biomass into oil and residuals for downstream testing, (4) product assessment to determine biofuel, aquafeed or poultry feed product efficacy using algae biomass fractions as well as to provide critical performance data for valuation and (5) commercialization to use technoeconomic and life cycle assessments (TEA/LCA) as iterative design and assessment tools including consideration of target markets, competitors, and distribution channels to guide product assessment, development and valuation. A total of 46 peer-review publications, many open-access, provide detail of much of the work carried out and the results of the tasks. Additional reports and presentations provide other technical and public engagement material. At a high level, using a variety of approaches, more than 1000 marine microalgae strains were evaluated to ultimately identify the seven winners that were down-selected to be grown in mass culture. Strain selection demonstrated that there were no ‘super strains’ and that each candidate had strengths and limitations for specific products, growth conditions or operational considerations. Mass culture growth of these seven strains at >5000 L / 29 m 2 scale found that four them were suitable for product assessment. More than 250 kg of biomass was produced across hundreds of pond runs along with thousands of cultivation entries on the growth and biomass characteristics as well as environmental parameters. In the process, dozens of standard operating procedures were generated as was custom software to process and analyze cultivation data. Recovery and conversion of algae biomass demonstrated that a hexane solvent based extraction protocol was most effective at recovering oil (biocrude) from algae and four strains were processed to produce oil and lipid extracted algae (residuals) for downstream testing. Membrane-based oil separation was less successful, but may still be applicable to other commercial applications in the future. Product testing demonstrated that algae biocrude is of high quality and hydrotreating generated numerous fractions of high quality composition for fuel and lubricate based applications. Aquafeed studies performed at a variety of scales showed that both whole and defatted (lipid extracted algae) microalgae were suitable as a feed ingredient, but that the specifics of the fed animal and biochemical composition of the algae are critical factors when determining formulation. Similarly, poultry studies on whole and defatted microalgae generally showed positive outcomes on animal growth and health, with some microalgae providing enhanced nutritional composition of the animal product. Economic and life cycle assessments covered a wide range of possible commercialization and sustainability scenarios. Replacement value, improved product value added, consumer values marketing added valuation and improved animal health were considered as alternatives for microalgae valuation. Using the open pond system, algae productivity was identified as the key driver of commercialization economics, but combination of co-products (e.g. animal feed) with biofuel production substantially increased the total selling price of algae. Modeled microalgae selling price exceeded $\$$1500/tonne and could generate competitive biofuel selling prices below $\$$5 gallon gas equivalents using realistic algal productivities. Short (process scale) and longer (decadal trends) sustainability assessments show that marine microalgae can enhance the sustainability of energy production and lead to other realized benefits in water, fertilizer and land use for other sectors (e.g. agriculture). This project successfully demonstrated all of the components of an end-to-end process from mass microalgae cultivation and dewatering, to recovery and conversion of algae biomass components, to final product demonstration and process valuation; the combined results provide a framework for future commercialization of algae based biofuels.

09 BIOMASS FUELS↗

NASA NTRS2019

GeneLab: A Systems Biology Platform for Omics Analysis

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide the latest in terms of professional state-of-the-art bioinformatics platform for the space biology and radiation community to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare to existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all dataset. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era or on the International Space Station. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗

NASA NTRS2019

NASA GeneLab Space Omics Database: Expanding from Space to Ionizing Radiation Data on the Ground

NASA GeneLab is an open-access repository for omics datasets generated by biological experiments conducted in space or ground experiments relevant to spaceflight (e.g. simulated cosmic radiation, simulated microgravity, bed rest studies). The GeneLab Data Systems (GLDS) version 4.0 will be available on October 1st 2019, and will provide a state-of-the-art bioinformatics platform for the space biology and radiation communities to upload their data into an omics data commons, to process their data with vetted standard workflows and to compare with existing analyses. Started in 2015 as a repository designed to archive omics data from space experiments, GeneLab has expanded its scope to all ionizing radiation omics experiments conducted on the ground and has put considerable effort in providing carefully characterized radiation metadata on all datasets. GeneLab is also providing processed data derived from the raw data covering a large spectrum of omics (genome, epigenome, transcriptome, epitranscriptome, proteome, metabolome) to help users explore important questions: 1) Which genes or proteins are expressed differently in space for various living organisms? 2) What specific DNA mutations or epigenetic changes happen in space or after exposure to ionizing radiation? and 3) How does genetics affect these responses? Processed data available on GeneLab are derived by standard data analysis workflows vetted by hundreds of scientists who volunteered to join one of the four GeneLab Analysis Working Groups (Animal AWG, Plant AWG, Microbe AWG, Multi-Omics AWG). In this presentation, we will discuss how to bridge the gap between irradiation studies performed on earth and biological experiments conducted in space since the early 1990's. We will discuss how radiation dosimetry was estimated for datasets derived from samples collected during the Space Shuttle era on the International Space Station and on other orbiting platforms. Finally, we will address future strategies regarding dose monitoring in future missions into space, inter-agency efforts to unify data under one umbrella, and knowledge dissemination across the radiation research community and the space biology community.

open-science↗

DOE OSTI2023

Battery Charge Curve Prediction via Feature Extraction and Supervised Machine Learning

Real-time onboard state monitoring and estimation of a battery over its lifetime is indispensable for the safe and durable operation of battery-powered devices. In this study, a methodology to predict the entire constant-current cycling curve with limited input information that can be collected in a short period of time is developed. A total of 10 066 charge curves of LiNiO 2 -based batteries at a constant C-rate are collected. With the combination of a feature extraction step and a multiple linear regression step, the method can accurately predict an entire battery charge curve with an error of < 2% using only 10% of the charge curve as the input information. The method is further validated across other battery chemistries (LiCoO 2 -based) using open-access datasets. The prediction error of the charge curves for the LiCoO 2 -based battery is around 2% with only 5% of the charge curve as the input information, indicating the generalization of the developed methodology for predicting battery cycling curves. The developed method paves the way for fast onboard health status monitoring and estimation for batteries during practical applications.

25 ENERGY STORAGE↗

DOE OSTI2020

Insights from 20 years of the Molecule of the Month

For 20 years, Molecule of the Month articles have highlighted the functional stories of 3D structures found in the Protein Data Bank (PDB). The PDB is the primary archive of atomic structures of biological molecules, currently providing open access to more than 150,000 structures studied by researchers around the world. The wealth of knowledge embodied in this resource is remarkable, with structures that allow exploration of nearly any biomolecular topic, including the basic science of genetic mechanisms, mechanisms of photosynthesis and bioenergetics, and central biomedical topics like cancer therapy and the fight against infectious disease. The central motivation behind the Molecule of the Month is to provide a user-friendly introduction to this rich body of data, charting a path for users to get started with finding and exploring the many available structures. The Molecule of the Month and related materials are updated regularly at the education portal PDB-101 (http://pdb101.rcsb.org/), offering an ongoing resource for molecular biology educators and students around the world.

59 BASIC BIOLOGICAL SCIENCES↗