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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗
DOE OSTI2024

The need for carbon-emissions-driven climate projections in CMIP7

Abstract. Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), for both idealized model experiments and climate projections of different emissions scenarios. We argue that although this approach was practical to allow parallel development of Earth system model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth system models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy, and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently calculated in integrated assessment models (IAMs) during scenario development with only the net carbon emissions passed to the ESM. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use and projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon–climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular, sources and sinks of methane and nitrous oxide) and process-based representation of carbon removal options. These developments will allow three primary benefits: (1) resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts, (2) scenario modeling of the range of possible future climate states including Earth system processes and feedbacks that are increasingly well-represented in ESMs, and (3) optimal utilization of the strengths of ESMs in the wider context of climate modeling infrastructure (which includes simple climate models, machine learning approaches and kilometer-scale climate models).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease

Significance Microfluidics is an important in vitro platform to gain insights into mechanics of blood flow and mechanisms of pathophysiology of human diseases. Extraction of 3D fields in microfluidics with dense cell suspensions remains a formidable challenge. We present artificial-intelligence velocimetry (AIV) as a general platform to determine 3D flow fields and a microaneurysm-on-a-chip to simulate blood flow in microaneurysms in patients with diabetic retinopathy. AIV is built on physics-informed neural networks that integrate seamlessly 2D images from microfluidic experiments or in vivo observations with physical laws to estimate full 3D velocity and stress fields. AIV could be integrated into imaging technologies to automatically infer key hemodynamic metrics from in vivo and in vitro biomedical images.

42 ENGINEERING↗
DOE OSTI2024

Experiments and Project-Based Enhancements for STEM Learning: Preprint

Motivating k-12 students to pick a career in science, technology, engineering, and mathematics (STEM) is an effort that requires consistent attention. At different points in time, STEM educators need to pivot themselves and update educational materials to consistently motivate the next generation of k-12 students to enter into STEM careers. Once they enter undergraduate education, universities need to motivate their undergraduates students to consider graduate studies to ensure qualified human resources can be developed for research, and teaching. We present in this paper, our work on developing STEM materials for k-12 students targeting grid integration of hydrogen assets. This paper also presents our work on leveraging open source distribution system model, digital real time simulation tool to create projects for undergraduate students and motivate their interest in research topics, and enter into graduate level education.

electro-magnetic transients↗
DOE OSTI2021

Bio-inspired strategies for next-generation perovskite solar mobile power sources

Smart electronic devices are becoming ubiquitous due to many appealing attributes including portability, long operational time, rechargeability and compatibility with the user-desired form factor. Integration of mobile power sources (MPS) based on photovoltaic technologies with smart electronics will continue to drive improved sustainability and independence. With high efficiency, low cost, flexibility and lightweight features, halide perovskite photovoltaics have become promising candidates for MPS. Realization of these photovoltaic MPS (PV-MPS) with unconventionally extraordinary attributes requires new ‘out-of-box’ designs. Natural materials have provided promising designing solutions to engineer properties under a broad range of boundary conditions, ranging from molecules, proteins, cells, tissues, apparatus to systems in animals, plants, and humans optimized through billions of years of evolution. Applying bio-inspired strategies in PV-MPS could be biomolecular modification on crystallization at the atomic/meso-scale, bio-structural duplication at the device/system level and bio-mimicking at the functional level to render efficient charge delivery, energy transport/utilization, as well as stronger resistance against environmental stimuli (e.g., self-healing and self-cleaning). In this paper, we discuss the bio-inspired/-mimetic structures, experimental models, and working principles, with the goal of revealing physics and bio-microstructures relevant for PV-MPS. Here the emphasis is on identifying the strategies and material designs towards improvement of the performance of emerging halide perovskite PVs and strategizing their bridge to future MPS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Design and Implementation of Smart Buildings: A Review of Current Research Trend

The building sector is one of the largest contributors to the world’s total energy use and greenhouse gas emissions. Advancements in building energy technologies have played a critical role in enhancing the energy sustainability of the built environment. Extensive research and new techniques in energy and environmental systems for buildings have recently emerged to address the global challenges. This study reviews existing articles in the literature, mostly since 2000, to explore technological advancement in building energy and environmental systems that can be applied to smart homes and buildings. This review study focuses on an overview of the design and implementation of energy-related smart building technologies, including energy management systems, renewable energy applications, and current advanced smart technologies for optimal function and energy-efficient performance. To review the advancement in building energy-related technologies, a systematic review process is adopted based on available published reviews and research types of articles. Review-type articles are first assessed to explore the current literature on the relevant keywords and to capture major research scopes. Research-type papers are then examined to investigate associated keywords and work scopes, including objectives, focuses, limitations, and future needs. Throughout the comprehensive literature review, this study identifies various techniques of smart home/building applications that have provided detailed solutions or guidelines in different applications to enhance the quality of people’s daily activities and the sustainability of the built environmental system. This paper shows trends in human activities and technology advancements in digital solutions with energy management systems and practical designs. Understanding the overall energy flow between a building and its environmentally connected systems is also important for future buildings and community levels. This paper assists in understanding the pathway toward future smart homes/buildings and their technologies for researchers in related research fields.

renewable system integration↗
DOE OSTI2024

ChatGPT and Other Large Language Models for Cybersecurity of Smart Grid Applications

Cybersecurity breaches targeting electrical substations constitute a significant threat to the integrity of the power grid, necessitating comprehensive defense and mitigation strategies. Any anomaly in information and communication technology (ICT) should be detected for secure communications between devices in digital substations. This paper proposes large language models (LLMs), e.g., ChatGPT, for the cybersecurity of IEC 61850-based communications. Multi-cast messages such as generic object oriented system events (GOOSE) and sampled values (SV) are used for case studies. The proposed LLM-based cybersecurity framework includes, for the first time, data pre-processing of communication systems and human-in-the-loop (HITL) training (considering the cybersecurity guidelines recommended by humans). The results show a comparative analysis of detected anomaly data carried out based on the performance evaluation metrics for different LLMs. A hardware-in-the-loop (HIL) testbed is used to generate and extract a dataset of IEC 61850 communications.

ChatGPT↗
DOE OSTI2020

Enabling human–infrastructure interfaces for inspection using augmented reality

Decaying infrastructure maintenance cost allocation depends heavily on accurate and safe inspection in the field. New tools to conduct inspections can assist in prioritizing investments in maintenance and repairs. The industrial revolution termed as “Industry 4.0” is based on the intelligence of machines working with humans in a collaborative workspace. Contrarily, infrastructure management has relied on the human for making day-to-day decisions. New emerging technologies can assist during infrastructure inspections, to quantify structural condition with more objective data. However, today’s owners agree in trusting the inspector’s decision in the field over data collected with sensors. If data collected in the field is accessible during the inspections, the inspector decisions can be improved with sensors. New research opportunities in the human–infrastructure interface would allow researchers to improve the human awareness of their surrounding environment during inspections. This article studies the role of Augmented Reality (AR) technology as a tool to increase human awareness of infrastructure in their inspection work. The domains of interest of this research include both infrastructure inspections (emphasis on the collection of data of structures to inform management decisions) and emergency management (focus on the data collection of the environment to inform human actions). This article describes the use of a head-mounted device to access real-time data and information during their field inspection. The authors leverage the use of low-cost smart sensors and QR code scanners integrated with Augmented Reality applications for augmented human interface with the physical environment. This article presents a novel interface architecture for developing Augmented Reality–enabled inspection to assist the inspector’s workflow in conducting infrastructure inspection works with two new applications and summarizes the results from various experiments. The main contributions of this work to computer-aided community are enabling inspectors to visualize data files from database and real-time data access using an Augmented Reality environment.

Maharjan, D.↗
DOE OSTI2020

Enabling Deformable and Stretchable Batteries

Abstract Deformable energy storage devices are needed to power next‐generation wearable electronics that interface intimately with human skin. Currently, deformable energy storage devices demonstrate poor performance compared to their rigid lithium‐ion counterparts, forcing wearable manufacturers to design their devices around bulky battery compartments. However, technological advances to create deformable batteries at the component and device level have yielded continuous improvement in stretchable batteries over the last five years. In this Essay, the major strategies at the component and device level that have been successfully employed to create stretchable batteries are reviewed. The outstanding challenges facing deformable energy storage are also discussed, namely, energy density, packaging, delamination, device integration, and manufacturing. This Essay will give researchers who are interested in contributing to the development of deformable batteries a cursory understanding of the most successful strategies to date, and provide insights into the most important directions to pursue in the future.

Mackanic, David G.↗
DOE OSTI2021

Portable Industrial Control Systems Simulator (Final Report)

Industrial Control Systems (ICS) are more integrated than they have ever been before, but also the division between IT (Information Technology) and OT (Operational Technology) is becoming a grey area. As the integration of IT and OT occurs more often, cyber attack will also increase. Cyber attacks on Critical Infrastructure can be highly detrimental to society, notably via compromised Industrial Control Systems (ICS). Virtual and physical simulation has been used in medical fields, mathematics, architecture, aeronautics, space, and many more. Virtualization & Simulation in a lab environment is ideal because there is a need for the ability to test theories and designs is a safe and cost-effective way without risking equipment damage or, more importantly, human life. Furthermore, OT and ICS are some of the most difficult systems to use for research and development. They are either committed to operations or widely expensive to set up in a life-like environment. Virtualization and simulation will allow these otherwise accessible systems to be a test bed for the training, development, and research of SRNL customers or engineers and scientists at SRNL. This will allow the testbed to fit into a small form factor and interact with a simulator with minimum hardware components for easy transports and replication effort within the environment.

42 ENGINEERING↗
DOE OSTI2023

Unraveling complex causal processes that affect sustainability requires more integration between empirical and modeling approaches

Scientists seek to understand the causal processes that generate sustainability problems and determine effective solutions. Yet, causal inquiry in nature–society systems is hampered by conceptual and methodological challenges that arise from nature–society interdependencies and the complex dynamics they create. Here, we demonstrate how sustainability scientists can address these challenges and make more robust causal claims through better integration between empirical analyses and process- or agent-based modeling. To illustrate how these different epistemological traditions can be integrated, we present four studies of air pollution regulation, natural resource management, and the spread of COVID-19. The studies show how integration can improve empirical estimates of causal effects, inform future research designs and data collection, enhance understanding of the complex dynamics that underlie observed temporal patterns, and elucidate causal mechanisms and the contexts in which they operate. These advances in causal understanding can help sustainability scientists develop better theories of phenomena where social and ecological processes are dynamically intertwined and prior causal knowledge and data are limited. The improved causal understanding also enhances governance by helping scientists and practitioners choose among potential interventions, decide when and how the timing of an intervention matters, and anticipate unexpected outcomes. Methodological integration, however, requires skills and efforts of all involved to learn how members of the respective other tradition think and analyze nature–society systems.

42 ENGINEERING↗
DOE OSTI2020

Remote Radiation Sensing Using Aerial and Ground Platforms

Remote sensing of ionizing radiation has a significant role in waste management, nuclear material management and nonproliferation, and radiation safety. Robotic platforms can surpass the number of tasks that are achieved by humans. With this technique, the operator's radiation exposure can be decreased. Remote sensing allows for the evaluation and monitoring of radiological contamination. Gamma-ray and neutron sensors were integrated onto the robotic platforms. This approach allows for the radiation sensor data to be dynamically tracked and mapped thus enabling further analysis of the radiation flux in temporal and spatial domains. The goal is to complete scheduled tasks while the robot is being irradiated. To achieve this, electronic components must be shielded and radiation hardened. CZT Detector: Cadmium Zinc Telluride (CZT) detector technology has been a promising solution for gamma-ray and x-ray measurements. Detector data is transferred to the Odroid minicomputer that controls and powers the module via the USB. Robot Operating System (ROS) was utilized for data acquisition and data fusion. The Mariscotti method was employed for the spectrum analysis. A function was programmed in ROS for the automatic identification of photopeaks. CLYC Detector: A Cs{sub 2}LiYCl{sub 6}:Ce{sup 3+} (CLYC) detector was used for simultaneous medium-resolution gamma-ray measurements and neutron counting. A 2.54 cm diameter photomultiplier tube (PMT) was equipped with a high voltage supply and a miniature digitizer. Gamma-ray excitation: fast core-to-valence luminescence (CVL) with 1 ns decay constant, and prompt Ce{sup 3+} emission with 50 ns decay constant. Neutron excitation: slow cerium self-trapped excitation (Ce{sup 3+} STE), 1000 ns decay constant. Radiation Source Localization: Maximum Likelihood Estimation (MLE) and gradient-based methods were used to locate the position of a radiation source based on measured radiation intensities. Multi-Particle Transport Code FLUKA: Estimation of radiation damage of the electronic components is important in order to optimize the robot's operational time while it is irradiated. Displacement per atom (DPA) represents the radiation damage in materials exposed to the ionizing radiation. Various shielding layers of different thickness t were analyzed (< 5% statistical error). The model of the controller of the UAS was designed in FLUKA. Conclusion: CZT and CLYC detectors were integrated onto the robotic platforms. Radiation source localization and contour mapping using robotic platforms were studied. Functions for data analysis and fusion were developed in ROS. FLUKA code was utilized to analyze DPA values. Layers of low-density and high-density materials were used to shield the UAS electronics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Genomic insights into the origin, domestication and diversification of Brassica juncea

Despite early domestication around 3000 BC, the evolutionary history of the ancient allotetraploid species Brassica juncea (L.) Czern & Coss remains uncertain. Here, we report a chromosome-scale de novo assembly of a yellow-seeded B. juncea genome by integrating long-read and short-read sequencing, optical mapping and Hi-C technologies. Nuclear and organelle phylogenies of 480 accessions worldwide supported that B. juncea is most likely a single origin in West Asia, 8,000–14,000 years ago, via natural interspecific hybridization. Subsequently, new crop types evolved through spontaneous gene mutations and introgressions along three independent routes of eastward expansion. Selective sweeps, genome-wide trait associations and tissue-specific RNA-sequencing analysis shed light on the domestication history of flowering time and seed weight, and on human selection for morphological diversification in this versatile species. Our data provide a comprehensive insight into the origin and domestication and a foundation for genomics-based breeding of B. juncea.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Novel additive manufacturing for plasma facing materials ‐ creating a research pathway for minority students

This project addresses two critical and intertwined challenges in fusion energy, namely the shortage of a broadly trained scientific workforce and the lack of scalable manufacturing solutions for plasma-facing components (PFCs). Through a collaboration among Florida International University (FIU), Miami Dade College (MDC), and Purdue University, the project established structured, reproducible educational and research pathways that recruit and advance students from institutions historically outside the fusion energy enterprise, building the human capital that this field urgently needs. The project integrates the complementary research strengths of FIU and Purdue to investigate flash sintering as a transformative processing route for tungsten-based PFCs. Unlike conventional sintering approaches, flash sintering offers rapid densification at significantly reduced thermal budgets, making it a compelling candidate for fabricating complex tungsten geometries that must withstand extreme plasma-facing environments. Systematic experimental and modeling efforts will elucidate the fundamental mechanisms governing microstructure evolution, grain boundary chemistry, and thermomechanical response during flash sintering — knowledge that is presently lacking but essential for translating this technology into reliable manufacturing practice. The convergence of workforce development and cutting-edge manufacturing research positions this project to deliver measurable, durable impact: a pipeline of fusion-ready researchers cultivated through expanded institutional partnerships, and a validated materials processing framework that accelerates domestic readiness for next-generation fusion reactor construction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Elimination of human rabies in Goa, India through an integrated One Health approach

Dog-mediated rabies kills tens of thousands of people each year in India, representing one third of the estimated global rabies burden. Whilst the World Health Organization (WHO), World Organization for Animal Health (OIE) and the Food and Agriculture Organization of the United Nations (FAO) have set a target for global dog-mediated human rabies elimination by 2030, examples of large-scale dog vaccination programs demonstrating elimination remain limited in Africa and Asia. We describe the development of a data-driven rabies elimination program from 2013 to 2019 in Goa State, India, culminating in human rabies elimination and a 92% reduction in monthly canine rabies cases. Smartphone technology enabled systematic spatial direction of remote teams to vaccinate over 95,000 dogs at 70% vaccination coverage, and rabies education teams to reach 150,000 children annually. An estimated 2249 disability-adjusted life years (DALYs) were averted over the program period at 526 USD per DALY, making the intervention ‘very cost-effective’ by WHO definitions. This One Health program demonstrates that human rabies elimination is achievable at the state level in India.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

JUST-R metrics for considering energy justice in early-stage energy research

We report achieving sustainable decarbonization of the energy sector requires implementing and improving energy technologies while simultaneously managing sources of social inequity in the energy system. Centering energy justice, which has "the goal of achieving equity in both the social and economic participation in the energy system, while also remediating social, economic, and health burdens on those historically harmed by the energy system," in the transition to clean energy has become an increasingly urgent priority for social scientists, policymakers, and community activists alike. However, late-stage consideration of social impacts of energy technologies may result in identifying inequities only after substantial time, money, and effort have been expended on research and development (R&D). This issue is exemplified by concerns over environmental and human health impacts related to cobalt in lithium-ion batteries, which has spurred research into alternatives only after decades of R&D and the establishment of supply chains, infrastructure, and markets for cobalt-containing chemistries. Other examples include issues with land use and resource consumption related to first-generation biofuel feedstocks as well as occupational hazards and pollution associated with photovoltaics manufacturing. In all these cases, subsequent R&D to improve technologies or processes cannot undo the effects already experienced. Incorporating energy justice from the earliest stage of R&D will enable more just technology implementation, but integrating justice considerations into early-stage research is a challenge due to a lack of tools to assess and manage them. To fill this gap, we center early-stage research to develop the Justice Underpinning Science and Technology Research (JUST-R) metrics framework - energy justice metrics specifically targeted at early-stage researchers to assess their work on an immediate timescale. By applying these metrics to a case study focused on materials for next-generation photovoltaics, we highlight potential benefits and barriers to implementing this framework in early-stage research and discuss necessary institutional and individual actions needed for researchers to effectively leverage the tool to incorporate justice-focused criteria into R&D decision making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Can exascale computing and explainable artificial intelligence applied to plant biology deliver on the United Nations sustainable development goals?

Human population growth and accelerated climate change necessitate agricultural improvements using designer crop ideotypes (idealized plants that can grow in niche environments). Diverse and highly skilled research groups must integrate efforts to bridge the gaps needed to achieve international goals toward sustainable agriculture. Given the scale of global agricultural needs and the breadth of multiple types of omics data needed to optimize these efforts, explainable artificial intelligence (AI with a decipherable decision making process that provides a meaningful explanation to humans) and exascale computing (computers that can perform 1018 floating-point operations per second, or exaflops) are crucial. Accurate phenotyping and daily-resolution climatype associations are equally important for refining ideotype production to specific environments at various levels of granularity. In this article, we review advances toward tackling technological hurdles to solve multiple United Nations Sustainable Development Goals and discuss a vision to overcome gaps between research and policy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Integrating N -glycan and CODEX imaging reveal cell-specific protein glycosylation in healthy human lung

Identifying cell-specific glycan structures in human lungs is critical for understanding the chemistry and mechanisms that guide cell–cell and cell–matrix interactions and determining nuanced functions of specific glycosylation. Our dual-modality omics platform, which uses matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to profile glycan chemistry at 50 μm × 50 μm scale, combined with co-detection by indexing (CODEX) to provide cell identification from the exact same tissue section, is a significant step in this direction. It enabled us to detect, differentiate, and reveal chemical properties of N-glycans in the various cell types of a human lung, suggesting the cell-specific function of distinct carbohydrate moieties. This innovative technological combination bridges the gap between the specific protein glycosylation and their cellular origin, paving the way for targeted studies in the lungs and many other human tissues where glycans mediate cell–cell recognition events.

Veličković, Dušan [Pacific Northwest National Labo↗