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DOE OSTI2023

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere.

14 SOLAR ENERGY↗

DOE OSTI2025

Understanding and Modeling Pooled Rideshare Acceptance: Influential Factors, Preferred User Experiences, and Implications

Ridesharing allows people to share a vehicle with others traveling in the same direction, which can reduce costs and traffic congestion. Pooled rideshare (PR) services, such as UberX Share and Lyft Shared, offer an economical and environmentally friendly alternative by matching passengers traveling similar routes. However, despite these benefits, PR adoption remains low due to concerns about safety, privacy, and convenience. This research explores the factors influencing PR adoption and provides recommendations to improve user acceptance. A nationwide survey of 5,385 participants across the U.S. was conducted to understand why people choose or avoid PR. The study identified five key factors influencing PR consideration: safety, service experience, privacy, traffic/environment, and time/cost. Additional research examined ways to optimize PR experiences by identifying four critical factors: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. To measure the impact of these factors, a statistical model called the Pooled Rideshare Acceptance Model (PRAM) was developed, providing insights into how each element influences PR adoption. Further analysis using the Pooled Rideshare Acceptance Model Multigroup Analyses (PRAMMA) revealed how demographic characteristics such as age, gender, income, and past rideshare experience shape PR perceptions. Some key findings from the multigroup analyses showed that younger users valued technological features and environmental benefits, while older users prioritized reliability and service transparency. Additionally, privacy concerns were more significant for female users, while convenience was critical for higher-income groups. These results emphasize that a 'onesize-fits-all' approach to PR service design is not effective, highlighting the need for tailored strategies to address different user segments. Further, workshops were conducted with researchers and students to translate the findings into real-world solutions. These workshops and 3 all the statistical analyses led to the development of 95 actionable recommendations. The recommendations focus on key areas such as safety, service reliability, user education, and accessibility, offering tangible improvements to PR services. The insights from this study provide valuable guidance for policymakers, transportation network companies (TNCs), and researchers aiming to make PR services safer, more accessible, and widely accepted. By addressing user concerns, PR can become a more viable transportation option, supporting sustainable urban mobility and reducing reliance on private vehicles. Additionally, these findings emphasize the importance of user-centric service design in encouraging broader PR adoption. Future research should explore evolving trends in PR preferences, technological advancements, and policy changes to ensure continued improvements. By implementing these recommendations, PR services can better align with user expectations, enhance trust in shared mobility, and contribute to a more efficient transportation ecosystem.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Developing a Decision Support Engine to Enable Irrigation Modernization - Poster

Irrigation systems in the United States are some of the oldest continually utilized infrastructure in existence today, with some systems exceeding 100 years in age. They are operated to meet farming demands but are managed through a balance of varying influence: policies limiting water usage, stakeholder interests, and environmental impacts. Irrigation modernization is defined as a set of activities that update and improve existing irrigation systems, including, but not limited to improving water quantity, development of distributed energy resources for surrounding communities, ecosystem services, and improved agricultural yields. Modernizing an existing irrigation system can enable stakeholders to combat changing environmental and population demands but is difficult because the complexity involved in determining the potential benefits and consequences of irrigation modernization is high. We are combining a large amount of various geospatial, tabular, and temporal data with subject matter expertise into a decision support engine that will enable stakeholders to determine the benefits and consequences of irrigation modernization in their irrigation systems. A web-based GIS will allow the user to construct the modifications out of a palette of modernization options, which will be sent to the analytics engine for computations, and back to the web client for a graphical display and comparison of relevant metrics. Our development process involves four phases: 1) identify mechanisms of modernization, 2) identify data requirements, data streams, first principles and applicable algorithms necessary to quantify modernization mechanisms, 3) create ‘modules’ for each modernization mechanism, these modules will form the decision support engine, each capable of performing independently but can also inform other modules when needed, 4) Merge the decision support engine with a user interface, capable of ingesting user inputs and returning insights into the impacts of a modernization project as they relate to economic, environmental, monetary, and energy generation. Once complete, it is our intention that this tool will be fundamental in irrigation modernization projects, providing a strong analytical basis from which stakeholders can quickly make informed decisions regarding project development.

13 HYDRO ENERGY↗

NASA NTRS2024

Passenger-Oriented Total Mobility Using Digital Engineering (PAX Mobility): Opportunity Concept Report (OCR)

NASA aeronautics has an opportunity to unlock a new era of passenger-oriented mobility by developing end-to-end models using passenger-level data that seamlessly integrates aviation into a safe and sustainable transportation ecosystem.

Husni Idris↗

DOE OSTI2022

CABLE Big Idea RDD&D Workshop (Workshop Summary Report)

The U.S. Department of Energy’s (DOE’s) Advanced Manufacturing Office (AMO) held the CABLE Big Idea RDD&D Workshop April 7–9, 2021. The virtual workshop brought together approximately 250 leading scientific and technical experts to gather information on the state of the art in conductivity-enhanced materials and their applications. These stakeholders included scientists, engineers, manufacturers, materials experts, utility companies, and other entities within the conductor material and electrical product manufacturing supply chains. The two main goals of the workshop were to 1) start building and strengthening a research ecosystem around conductivity-enhanced materials and 2) inform AMO’s future portfolio of research, development, demonstration, and deployment (RDD&D) investments and other program activities in the area of conductivity-enhanced materials. CABLE—or Conductivity-enhanced materials for Affordable, Breakthrough Leapfrog Electric and thermal applications—was was established as an Office of Energy Efficiency and Renewable Energy initiative as a result of a competitive internal process to identify and prioritize potentially high-impact research topics. Since then, conductivity-enhanced materials have been identified as an important element of the shift to an electrified and decarbonized industry sector, and CABLE remains a Big Idea. The CABLE effort is led by AMO and supported by eight other offices within DOE. The first major effort under CABLE was the development of several subtopics for DOE’s Small Business Innovation Research/Small Business Technology Transfer (SBIR/STTR) programs in 2020. Another major activity was the launch of the CABLE Conductor Manufacturing Prize in March 2021.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

2024 OES-Environmental 2024 State of the Science Report, Chapter 9: Beyond Single Marine Renewable Energy Devices: A System-wide Effects Approach

Global expansion of renewable energy, including marine renewable energy (MRE) technology development is necessary to mitigate the effects of climate change, facilitate a sustainable transition from carbon-based energy sources, and satisfy national energy security needs using locally produced electricity (European Commission 2022; IPCC 2023; IRENA 2020). As MRE engineering and research continue to focus on designing devices for deployment in nearshore and offshore waters around the world, researchers are also examining potential environmental effects on marine animals, habitats, and ecosystem processes. To date, the focus has been on interactions between small numbers of MRE devices (1-6) and the environment, such as collisions between animals and turbine blades, the effects of underwater noise and electromagnetic field (EMF) emissions, changes in habitats and oceanographic processes, risk of entanglement of animals, and displacement of animals (Boehlert & Gill 2010; Copping & Hemery 2020) (see Chapter 3).

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

NetDuid

SAND2025-00238O The NetDuid library is a software tool that can manage and manipulate DHCP Unique Identifiers (DUIDs) in .NET applications. It simplifies the process of working with DUIDs by offering functionalities such as parsing, constructing, comparing, checking equality, and formatting DUIDs. The library supports various types of DUIDs, making it easier for developers to handle these identifiers in their applications. The program fills a gap in the .NET/C# ecosystem by providing a specialized tool for managing DHCP Unique Identifiers, offering a straightforward and efficient solution for developers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Engelhardt, Robert↗

NASA NTRS2020

Cloud-Computing and Machine Learning in Support of Country-Level Land Cover and Ecosystem Extent Mapping in Liberia and Gabon

Liberia and Gabon joined the Gaborone Declaration for Sustainability in Africa (GDSA), established in 2012, with the goal of incorporating the value of nature intonational decision making by estimating the multiple services obtained from ecosystems using the natural capital accounting framework. In this study, we produced 30-m resolution 10 classes land cover maps for the 2015 epoch for Liberia and Gabon using the Google Earth Engine (GEE) cloud platform to support the ongoing natural capital accounting efforts in these nations. We pro-pose an integrated method of pixel-based classification using Landsat 8 data, the Random Forest(RF) classifier and ancillary data to produce high quality land cover products to fit abroad range of applications, including natural capital accounting. Our approach focuses on a pre-classification filtering (Masking Phase) based on spectral signature and ancillary data to reduce the number of pixels prone to be misclassified; therefore, increasing the quality of the final product. The proposed approach yields an overall accuracy of 83% and 81% for Liberia and Gabon, respectively, out performing prior land cover products for these countries in both thematic content and accuracy. Our approach, while relatively simple and highly replicable, was able to produce high quality land cover products to fill an observational gap in up to date land cover data at national scale for Liberia and Gabon.

Celio de Sousa↗

DOE OSTI2025

Grid Communications: Digital Assurance and Supply Chain Challenges and Emerging Regulation Session Two

The TADA Grid Communications Workshops are designed to strengthen cybersecurity and digital assurance across the energy sector by focusing on secure deployment and management of grid communications technologies. These workshops bring together state energy offices, utilities, and technology suppliers to explore the intersection of communications infrastructure, supply chain risks, and emerging regulatory requirements. Participants will apply Cyber-Informed Engineering (CIE) principles to reduce risks in communications systems, engage with INL’s procurement guidance, and explore future tools. Through scenario-based exercises and peer exchange, attendees will develop risk-based security strategies and actionable compliance roadmaps tailored to their grid communications projects. The workshops also help participants navigate evolving regulatory frameworks such as FEOC rules in the OBBB, NERC CIP-013, and NDAA 2024, while identifying compliance gaps in mixed-technology environments. A key outcome is the formation of a practitioner network with ongoing access to INL expertise and resources, fostering long-term resilience in the digital energy ecosystem. This is Session 2 of 3 (Full Version).

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

DOE OSTI2025

Grid Communications: Cybersecurity and Supply Chain Challenges and Emerging Regulation Session Three

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

NASA NTRSDate not supplied

Utilizing NASA Earth Observations to Evaluate Urban Tree Canopy and Land Surface Temperature for Green Infrastructure Development and Urban Heat Mitigation in Huntsville, AL

Huntsville, Alabama’s population has grown by 10.8% since 2010, due in part to the city’s advancing engineering industry. Rapid urban growth negatively impacts the environment by decreasing tree canopy cover and increasing impervious surface cover, which can intensify the urban heat island effect. To examine the impacts of this urban growth on the environment, the team partnered with the City of Huntsville to utilize Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the International Space Station’s Global Ecosystems Dynamic Investigation (GEDI) and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). The team utilized these Earth observations in combination with ancillary datasets to create a suite of end products to assist in mitigating the effects of extreme heat due to urban expansion and tree canopy loss. Rasters of annual land surface temperature (LST) was calculated in Google Earth Engine from 2010 to 2019. The team derived land cover classes through supervised and threshold classification methods to distinguish trees, other vegetation types, impervious surfaces, and water. From 2010 to 2019, LST increased approximately 4 °F for all census tracts within the city and the total amount of tree cover increases less than 3%. The findings will aid the city in future decision-making processes by indicating areas that would benefit from increased green infrastructure.

Greta Paris↗

DOE OSTI2024

Spatiotemporal Operational Emissions Associated With Light-, Medium-, and Heavy-Duty Transportation Electrification

Not provided.

Engineering↗

DOE OSTI2025

Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations

Title: Warming Permafrost Model Intercomparision Project (WrPMIP): Pan-Arctic Perturbation Warming Simulations Description: WrPMIP Pan-Arctic simulations including historial baseline and two warming simulations. Models were perturbed similarly to known experimental warming trials that have been implemented across the Pan-Arctic over the last several decades. More information about the dataset can be found at the following links: https://warmingpermafrost.nau.edu/ The dataset is available at: https://esgf-node.ornl.gov/search/project=WrPMIP&mip_era=CMIP6&activity_id=WrPMIP

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

On-Demand Column Joining for High Energy Physics

As the Large Hadron Collider (LHC) transitions into the High-Luminosity LHC (HL-LHC) era, the volume of data to be processed is expected to increase significantly. The CMS Experiment currently utilizes various data formats, including AOD, MiniAOD, and NanoAOD, each with different levels of detail and storage requirements. This paper addresses the challenges of data duplication and storage inefficiencies in high-energy physics (HEP) analyses by proposing an on-demand column-joining solution. This approach aims to reduce data duplication by enabling the dynamic combination of NanoAOD data with auxiliary information from larger data tiers, such as MiniAOD. The proposed solution leverages Trino, a high-performance distributed SQL query engine, to perform efficient and scalable data joins. Benchmarks using CMS OpenData demonstrate the feasibility of this approach, showing that it can handle large datasets with low latency. Integration with the scikit-hep ecosystem and the coffea analysis framework is also discussed, highlighting the potential for seamless end-to-end data processing and analysis. Ongoing and future work focuses on expanding benchmarks, integrating ServiceX for data transformation, and exploring the use of native object storage solutions.

Manganelli, Nicholas [Northeastern U.]↗

DOE OSTI2021

Summarizing the interoperabilities between xSDK members

Rapid, efficient production of high-quality, sustainable extreme-scale scientific applications is best accomplished using a rich ecosystem of state-of-the art reusable libraries, tools, lightweight frameworks, and defined software methodologies, developed by a community of scientists who are striving to identify, adapt, and adopt best practices in software engineering. The vision of the xSDK is to provide infrastructure for and interoperability of a collection of related and complementary software elements — developed by diverse, independent teams throughout the high-performance computing (HPC) community — that provide the building blocks, tools, models, processes, and related artifacts for rapid and efficient development of high-quality applications. A primary component, and challenge, of the xSDK is to improve interoperability among software libraries and domain components. This document summarizes the current and planned interoperabilities of the twenty-three xSDK member packages as of March 2021. Additionally, the status of the xSDK example codes that demonstrate and test the interoperabilities within the xSDK is provided.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Utilizing plant synthetic biology to accelerate plant-microbe interactions research

Plant-microbe interactions are critical to ecosystem resilience and substantially influence crop production. From the perspective of plant science, two important focus areas concerning plant-microbe interactions include: 1) understanding plant molecular mechanisms involved in plant-microbe interfaces and 2) engineering plants for increasing plant disease resistance or enhancing beneficial interactions with microbes to increase their resilience to biotic and abiotic stress conditions. Molecular biology and genetics approaches have been used to investigate the molecular mechanisms underlying plant responses to various beneficial and pathogenic microbes. While these approaches are valuable for elucidating the functions of individual genes and pathways, they fall short of unraveling the complex cross-talk across pathways or systems that plants employ to respond and adapt to environmental stresses. Also, genetic engineering of plants to increase disease resistance or enhance symbiosis with microbes has mainly been attempted or conducted through targeted manipulation of single genes/pathways of plants. Recent advancements in synthetic biology tool development are paving the way for multi-gene characterization and engineering in plants in relation to plant-microbe interactions. Here, we briefly summarize the current understanding of plant molecular pathways involved in plant interactions with beneficial and pathogenic microorganisms. Then, we highlight the progress in applying plant synthetic biology to elucidate the molecular basis of plant responses to microbes, enhance plant disease resistance, engineer synthetic symbiosis, and conduct in situ microbiome engineering. Lastly, we discuss the challenges, opportunities, and future directions for advancing plant-microbe interactions research using the capabilities of plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Can Common Pool Resource Theory Catalyze Stakeholder-Driven Solutions to the Freshwater Salinization Syndrome?

Freshwater salinity is rising across many regions of the United States as well as globally, a phenomenon called the freshwater salinization syndrome (FSS). The FSS mobilizes organic carbon, nutrients, heavy metals, and other contaminants sequestered in soils and freshwater sediments, alters the structures and functions of soils, streams, and riparian ecosystems, threatens drinking water supplies, and undermines progress toward many of the United Nations Sustainable Development Goals. There is an urgent need to leverage the current understanding of salinization’s causes and consequences–in partnership with engineers, social scientists, policymakers, and other stakeholders–into locally tailored approaches for balancing our nation’s salt budget. In this feature, we propose that the FSS can be understood as a common pool resource problem and explore Nobel Laureate Elinor Ostrom’s social-ecological systems framework as an approach for identifying the conditions under which local actors may work collectively to manage the FSS in the absence of top-down regulatory controls. We adopt as a case study rising sodium concentrations in the Occoquan Reservoir, a critical water supply for up to one million residents in Northern Virginia (USA), to illustrate emerging impacts, underlying causes, possible solutions, and critical research needs.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Maya Forest Water Resources II: Mapping Inundation Below the Forest Canopy in the Maya Tri-National Forest

To monitor seasonal flooding within the tri-National Maya Forest the team completed the methodology started by the Summer 2021 term to analyze changes in inundation dynamic throughout 2017. The team analyzed inundation dynamics in Google Earth Engine (GEE) using Earth observation products from the Landsat 8 Operational Land Imager (OLI), Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) 2, and International Space Station (ISS) Global Ecosystem Dynamics Investigation LiDAR (GEDI). The team improved the landcover classification using the Random Forest algorithm in GEE by adding canopy height data derived from GEDI, elevation and slope data from Copernicus, and additional multi-spectral band ratios from Landsat 8. The pixel-based land cover classification produced an overall accuracy of 88%. Experiments measuring inundation extent using L-band SAR included comparing results with a priori knowledge, topography datasets, and auxiliary datasets. We iteratively tested and found threshold values for identifying forested inundation using the ratio for HH divided by HV. The resulting methodology and products helped end users from Belize’s Land Information Center (LIC) and Forest Department, Guatemala’s Center for Monitoring and Evaluation (CEMEC), and Mexico’s El Colegio de la Frontera Sur (ECOSUR) manage land and water resources and protect communities.

Stephanie Jiménez↗