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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The future of fungi: threats and opportunities

The fungal kingdom represents an extraordinary diversity of organisms with profound impacts across animal, plant, and ecosystem health. Fungi simultaneously support life, by forming beneficial symbioses with plants and producing life-saving medicines, and bring death, by causing devastating diseases in humans, plants, and animals. With climate change, increased antimicrobial resistance, global trade, environmental degradation, and novel viruses altering the impact of fungi on health and disease, developing new approaches is now more crucial than ever to combat the threats posed by fungi and to harness their extraordinary potential for applications in human health, food supply, and environmental remediation. To address this aim, the Canadian Institute for Advanced Research (CIFAR) and the Burroughs Wellcome Fund convened a workshop to unite leading experts on fungal biology from academia and industry to strategize innovative solutions to global challenges and fungal threats. This report provides recommendations to accelerate fungal research and highlights the major research advances and ideas discussed at the meeting pertaining to 5 major topics: (1) Connections between fungi and climate change and ways to avert climate catastrophe; (2) Fungal threats to humans and ways to mitigate them; (3) Fungal threats to agriculture and food security and approaches to ensure a robust global food supply; (4) Fungal threats to animals and approaches to avoid species collapse and extinction; and (5) Opportunities presented by the fungal kingdom, including novel medicines and enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Private, public, and bottled drinking water: Shared contaminant-mixture exposures and effects challenge

Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

DICER: Data Intensive Computing Environment and Runtime for Evaluating Unprecedented Scale of Geospatial-Temporal Human Mobility Data

With the significant increase in sources and volume of human mobility data through commercial data vendors as well as microsimulation of cities, the scale of geospatial-temporal data to analyze and assess for mobility characterization has grown to the level of Big Data. There are mobility related commercial organizations deploying scalable computing, but often the system architecture, workflow, and intermediate processing components are not fully disclosed in relevant scope. Current research literature has a notable lack of studies demonstrating architectures and workflows for human mobility analytics that are implemented on a TeraByte scale of geospatial-temporal data. In this context, this paper presents a hyperscale-level system solution named DICER (Data Intensive Computing Environment and Runtime) for processing and analytics of geospatial-temporal data at big data scale. Although the cluster computing architecture of DICER with Apache Spark job running on Kubernetes cluster is not new, there are innovations in the workflow, hierarchical processing logic, and a wide range of intermediate preprocessing and mobility metrics calculation. We have performed case studies to validate the effectiveness of DICER system solution by performing detailed analytics and assessment of human mobility microsimulation output at three different scopes and scale, including a usecase with 16.97 TeraByte and 259.2 Billion rows of data. In addition, we have presented another case study of utilizing DICER to perform the same mobility processing and comparative analytics on large-scale commercially available geospatial-temporal data. All these case studies validate the efficiency and usefulness of DICER in computing population mobility characteristics from geospatial-temporal trajectory data at an unprecedented scale (not only just data volume, but also combination of: number of user entities, temporal frequency, spatial resolution, data duration).

De, Debraj↗
DOE OSTI2023

Tackling Grand Challenges in Wind Energy through a Socio-Technical Perspective

Wind power has an important role to play in tackling climate change. Key challenges in wind energy science and innovation must be overcome to increase the penetration and capability of this technology. However, the success of these efforts heavily depends on how society engages with the development of wind power infrastructure. Consequently, grand challenges exist in both technical and social domains, yet little research has made substantial efforts in connecting them. Here we review the social science and humanities literature on wind energy to illustrate the social dimensions of previously identified technical challenges. We suggest that a socio-technical lens enables an interdisciplinary approach to overcome the prevalent tendency of silo thinking in wind energy research and use it to explore socio-technical grand challenges related to the design, planning, development, operational and end-of-life phases of wind energy. Finally, we provide an outlook for research, practice and innovation, including an interdisciplinary and socio-technical research agenda for wind energy science, renewable energy developments and science policy in general.

end-of-life↗
DOE OSTI2022

Automated Metadata Extraction: Challenges and Opportunities

Proper application of the FAIR data principles is what separates a vibrant data ecosystem, in which research data are frequently shared and reused, from a lifeless data graveyard. Automated metadata extraction systems have been proposed as a means of bolstering the findability, interoperability, and reusabil- ity of data repositories with little or no human intervention. These extraction systems mine metadata by crawling a repository and applying lightweight extractors that, for various types of file (e.g., image, CSV file), extract or synthesize relevant attributes. In practice, however, the automated creation of generally useful metadata is fraught with challenges. Data consumers may have different perspectives as to what metadata representations are useful, the standards for recording metadata tend to change over time, and the software model for processing updates can introduce unnecessary human and computational effort. Thus, generalizing extraction for a broad audience of data consumers is a difficult and relatively unsolved problem.In this work, we explore these challenges faced by extraction systems in the context of constructing our own extraction system for science data. We first define the metadata extraction problem and provide context to the issues faced in generalizing metadata. Additionally, we identify potential research directions to help alleviate many of these challenges for all automated extraction systems. Ultimately, this work represents a first step in designing ubiquitous metadata extraction systems that can maximize the value of research data while minimizing the human efforts required in doing so.

Skluzacek, Tyler↗
DOE OSTI2021

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Mind the gaps! Climate scientists should heed lessons in collaborative storytelling from William Shakespeare

Abstract To co‐produce locally relevant climate knowledge, climate scientists are engaging in new collaborations—with stakeholders and with scholars in the humanities, arts, and social sciences. In our work as a Shakespeare scholar‐turned‐public‐humanist and a climate scientist, we have created a methodology that allows researchers and communities to co‐produce knowledge by co‐producing narratives. We combine principles from emerging climate “storylines” research with collaborative storytelling inspired by William Shakespeare's plays and theatrical practices. Shakespeare's plays spark collaborations and interpretations, in part, because of how Shakespeare leaves gaps in the narrative. These gaps allow others to enter as collaborators, creating a “cognitive ecology” that fosters knowledge and action among all engaged. Integrating these methods into climate storyline‐making offers a radical paradigm: it upends the scientist's role as the focal storyteller and expert, and fosters, instead, partnership, equity, and a co‐exploration of multiple uncertainties. It is time for researchers to cede control to a cognitive ecology of collaborative action. This article is categorized under: Trans‐Disciplinary Perspectives > Humanities and the Creative Arts

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Concentrations and Health Implications of As, Hg, and Cd and Micronutrients in Rice and Emissions of CH 4 From Variably Flooded Paddies

Abstract The flooded soil conditions under which rice is typically grown are beneficial for boosting yield and decreasing herbicide inputs but may pose a food safety and environmental health risk. Flooded soils lead to reducing conditions and anaerobic metabolisms of soil microorganisms, which mobilizes arsenic from soil into soil solution, where it can be absorbed by rice roots and transported to grain. These conditions also promote the production and emission of methane (CH 4 )—a potent greenhouse gas. To evaluate how water management affects metal(loid) grain concentrations and CH 4 emissions, we conducted a 2‐year field study in which rice paddy water was managed under a range of soil redox conditions that spanned from flooded to non‐flooded. We observed that growing rice under less flooded conditions decreased CH 4 emissions and concentrations of grain total As, grain inorganic As, grain total Hg, and grain inorganic Hg relative to flooded conditions, with more reductions observed as conditions were drier; grain organic As and Hg (MeHg) species also decreased with drier conditions particularly in Year 1. However, the driest conditions tested led to a 50%–97% increase in grain Cd concentrations that exceeded the CODEX limit and grain yield reductions as high as 25% and 40% in Year 1 and 2, respectively. While concentrations of toxic metal(loid)s could be manipulated by water management, micronutrient concentrations were similar or decreased with drier conditions, potentially increasing grain Cd bioaccessibility to humans. Because practices for rice water management are gaining momentum, more research should monitor grain Cd levels along with micronutrients.

Environmental Sciences & Ecology↗
DOE OSTI2026

An agentic artificially intelligent X-ray scientist

Executing experimental tasks in both normal research laboratories and large-scale scientific facilities often requires extensive human supervision and remains a key challenge on the path to fully autonomous, artificial intelligence (AI)-driven science. Here we demonstrate a large language model-driven agent that autonomously performs X-ray sample alignment on a synchrotron beamline by planning actions, executing instrumental commands, interpreting observations and iterating towards experimental goals. Based on existing large language models with structured tool-use via the model context protocol, our AI X-ray scientist was guided and tested using an in-house-built virtual experimental setup that mirrors a six-circle diffractometer at an operational synchrotron beamline. The agentic workflow developed in the virtual environment was directly deployed on a real beamline, where it correctly identified reference reflections and determined the orientation matrix, an essential first step in any type of single-crystal scattering experiment. Our AI X-ray scientist responded effectively to unexpected experimental conditions, demonstrating adaptive problem-solving and readiness for addressing practical experimental situations. Our study provides a step towards autonomous operation across diverse experimental environments at large-scale scattering facilities.

Chen, Zhantao (ORCID:0000000319543868)↗
DOE OSTI2022

A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry

Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Bacterial Secondary Metabolite Biosynthetic Potential in Soil Varies with Phylum, Depth, and Vegetation Type

Microbes produce specialized compounds to compete or communicate with one another and their environment. Some of these compounds, such as antibiotics, are also useful in medicine and biotechnology. Historically, most antibiotics have come from soil bacteria which can be isolated and grown in the lab. Though the vast majority of soil bacteria cannot be isolated, we can extract their genetic information and search it for genes which produce these specialized compounds. These understudied soil bacteria offer a wealth of potential for the discovery of new and important microbial products. Here, we identified the ability to produce these specialized compounds in diverse and novel bacteria in a range of soil environments. This information will be useful to other researchers who wish to isolate certain products. Beyond their use to humans, understanding the distribution and function of microbial products is key to understanding microbial communities and their effects on biogeochemical cycles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Flicker: A review of temporal light modulation stimulus, responses, and measures

Flicker has been an important lighting system consideration for over a century. More precise terms are temporal light modulation (TLM) as the stimulus, and responses to TLM as the unwanted visual, cognitive, or physiological consequences. As lighting technology evolved, different forms of TLM emerged, and so did responses to them. Today, some LED systems – encompassing the LED, driver, and control – can result in TLM causing severe unwanted effects, while other LED systems produce no unwanted effects at all. LED systems can deliver a much wider range of luminous waveforms than conventional lighting systems, some exhibiting very high modulation depths. More than any light source before, they can elicit perceptions of the phantom array. Direct flicker effects at modulation frequencies less than about 80 Hz and the stroboscopic effect at frequencies greater than 80 Hz are fairly well understood, but the phantom array effect needs more exploration and characterisation. This review focuses on the technology and research history that led to current metrics for quantifying TLM and human responses to TLM. Notably, visually impaired individuals may exhibit alterations in their response to TLM, but such a discussion is beyond the intent of this review. Thus, the focus is on individuals with normal visual function.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Reverse engineering (RE) analysts struggle to address critical questions about the safety of binary code accurately and promptly, and their supporting program analysis tools are simply wrong sometimes. The analysis tools have to approximate in order to provide any information at all, but this means that they introduce uncertainty into their results. And those uncertainties chain from analysis to analysis. We hypothesize that exposing sources, impacts, and control of uncertainty to human binary analysts will allow the analysts to approach their hardest problems with high-powered analytic techniques that they know when to trust. Combining expertise in binary analysis algorithms, human cognition, uncertainty quantification, verification and validation, and visualization, we pursue research that should benefit binary software analysis efforts across the board. We find a strong analogy between RE and exploratory data analysis (EDA); we begin to characterize sources and types of uncertainty found in practice in RE (both in the process and in supporting analyses); we explore a domain-specific focus on uncertainty in pointer analysis, showing that more precise models do help analysts answer small information flow questions faster and more accurately; and we test a general population with domain-general sudoku problems, showing that adding "knobs" to an analysis does not significantly slow down performance. This document describes our explorations in uncertainty in binary analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Geant4 Visualization

Geant4 offers versatile visualization tools to study detector geometry, particle trajectories, and hits. These tools support both interactive and batch modes (e.g., vis.mac). With a unified interface, Geant4 integrates various graphics systems such as G4VisExecutive, OpenGL, Qt, HepRApp, DAWN, VTK, and ToolsSG. Advanced examples, including the ICRP145 Human Phantoms and the gMocren tool, highlight its applications in medical research and simulation and as well as radiation protection and shielding studies. These features make Geant4 a robust framework for exploring particle interactions and supporting domain-specific use cases.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Modeling Sepsis: Establishment and Validation of a 72-Hour Swine Model of Penetrating Abdominal Trauma

Background/Objectives: Fecal peritonitis following penetrating abdominal trauma is a serious condition that often results in sepsis and organ failure. The aim of our study was to develop a novel conscious porcine model of sepsis and organ dysfunction caused by multiple penetrating injuries to the small and large intestines. Methods: Twelve female Yorkshire pigs (average weight 50.6 ± 6.5 kg) were divided into two groups: Penetrating Abdominal Trauma (PAT) (n = 8) and Control (n = 4). All surgical procedures were performed under anesthesia with adequate analgesia. In the PAT group, the small and large intestines were punctured, and feces mixed with saline were introduced into the abdominal cavity to induce peritonitis. The Control group received sham surgery with only saline solution. The animals were observed in a conscious state over a period of 72 h, vital parameters were recorded, and blood samples were taken regularly. We adapted a pig-specific SOFA score and developed pig-specific SIRS criteria and NEWS2 score to assess organ function. The model was validated by independent investigators. Results: The survival rate in the PAT group was 75%, with an average survival time of 58.5 h, while all animals in the Control group survived to euthanasia. Monitoring showed pathophysiological changes, such as tachycardia, leucopenia, and thrombocytopenia, indicative of sepsis and organ dysfunction. Blinded investigators independently confirmed the model’s validity. Conclusions: A new swine model of penetrating abdominal trauma and sepsis has been successfully developed that demonstrates significant physiological and immunologic changes comparable to human sepsis. This new model provides a realistic platform for future research into sepsis, its diagnostics, and the evaluation of therapeutic strategies.

General & Internal Medicine↗
DOE OSTI2021

The Human Proteoform Project: Defining the human proteome

Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown. We propose here an ambitious initiative to define the human proteome, that is, to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented along with a call for improved technologies in a two-pronged strategy to the Human Proteoform Project.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Report for the ASCR Workshop on Visualization for Scientific Discovery, Decision-Making, and Communication

Visualization—the use of visual elements to explore data, form hypotheses, or convey conclusions—is an integral part of the scientific process. Starting from an initial exploration of new data to illustrating outcomes for the general public, visualization is one of the most intuitive and powerful modes of communication. With the explosion of new data sources and types, unprecedented volumes of data, and new technologies, such as virtual reality (VR) and artificial intelligence (AI), visualization has become increasingly essential but also ever more challenging. The Department of Energy’s (DOE) Office of Advanced Scientific Computing Research (ASCR) sponsored a Basic Research Needs workshop in January 2022 to understand the major opportunities and grand challenges in visualization tools and technologies for scientific computing as well as for DOE-relevant applications and goals in general. The workshop identified five priority research directions (PRDs) for visualization to support scientific discovery, decision making, and communication. The first three PRDs describe interconnected research themes addressing the need for new techniques to deal with complex data, uncertainty, and interpretability (PRD 1); the need for scalable and interoperable software stacks (PRD 2); and the challenges and opportunities inherent in new technologies, such as VR, cloud, or exascale computing (PRD 3). The remaining two PRDs describe foundational research themes that recognize the potential of visualizations to provide equitable access to information and to strengthen the scientific discourse (PRD 4); and the need to consider human factors when designing visualizations (PRD 5). Collectively, these PRDs form the pillars for a coherent, long-term research and development strategy in Visualization for Scientific Discovery, Decision-Making, and Communication in the context of the Office of Science’s mission scope.

97 MATHEMATICS AND COMPUTING↗