Search NASA⌕ Search

SEARCH · Search NASA

Results for “Education and Training”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Final Reports of the 2019 Los Alamos National Laboratory Computational Physics Student Summer Workshop

The Los Alamos National Laboratory Computational Physics Workshop is intended to educate select students in problems of computational physics, while exciting them about problems of particular interest to LANL. The long term goal is to train a cadre of future researchers with strong connections to LANL and both interest and expertise in the problems LANL faces. This year’s workshop ran from June 10 – August 16, 2019 and once again attracted a phenomenal group of students, whose work is presented in the following pages. The students worked with LANL staff mentors in teams of two, doing original research. In addition, they attended a lecture series focusing on both the basics and the cutting edge challenges of computational physics (Table 1). A new item this year was a modification to our Meet LANL series of brown-bag lunch session, moving from focusing on individual researchers to panel presentations from the different groups within XCP. As always, the mentors were drawn from across disciplines and divisions. Projects looked physics ranging from quantum interactions, up to solar system development.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Establishment of a Nationwide Plasma Science and Fusion Energy Certification and Apprenticeship Programs

Here we propose the establishment of a national Plasma Science and Fusion Energy training program that will combine professional development certification courses with hands-on apprenticeship opportunities. The program should be developed by a collaboration of stakeholders (academia, national laboratories, and industry) and should offer pathways for students from community colleges (CCs), minority-serving institutions (MSIs), high school graduates, and veterans. We argue that certification courses offer fast and flexible discipline-specific education that can be rapidly translated into marketable skills through hands-on apprenticeship opportunities. Furthermore, we first list major findings and recommendations related to the fusion workforce and discuss how to address them through the establishment of the proposed training program. We then highlight the appropriateness of this format for engagement with CCs, MSIs, high schools, and veteran employment services. In the final section, we provide a strategy for the establishment of the program, along with a tentative timeline and projected costs.

Certification↗
DOE OSTI2022

Assessment of Knowledge, Attitudes, and Practices Toward Ticks and Tickborne Disease among Healthcare Professionals Working in Schools in New York and Maryland

Healthcare Professionals Working in Schools (HPWS) are responsible for providing health services to students and play a role in providing education to prevent illnesses, including tickborne diseases (TBD). Providing TBD education to children has been shown to increase prevention behaviors and knowledge of TBD symptoms, but little is known regarding the current state of TBD awareness among HPWS. In spring 2019 we conducted a cross-sectional knowledge, attitudes, and practices (KAP) survey of HPWS in two states with a high incidence of Lyme disease (LD) to inform design of TBD prevention programs. The survey queried general knowledge of TBDs, school practices regarding TBDs, and availability of TBD resources. Overall, higher confidence, experience, risk perception, prior training on TBD, and more years employed as a HPWS were independently associated with knowledge of LD transmission, symptoms, and correct tick removal practices. State and local health departments should consider prioritizing engagement with HPWS to provide educational opportunities about tickborne diseases.

Nursing↗
DOE OSTI2025

The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies

The Artificial Intelligence Ontology (AIO) is a systematization of artificial intelligence (AI) concepts, methodologies, and their interrelations. Developed via manual curation, with the additional assistance of large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing a comprehensive framework that encompasses both technical and ethical aspects of AI technologies. The primary audience for AIO includes AI researchers, developers, and educators seeking standardized terminology and concepts within the AI domain. We use the term “branches” for classes, and their subclasses, in our ontology that are subclasses of owl:Thing. AIO contains eight branches: Bias, Layer, Machine Learning Task, Mathematical Function, Model, Network, Preprocessing, and Training Strategy, each designed to support the modular composition of AI methods and facilitate a deeper understanding of deep learning architectures and ethical considerations in AI. AIO uses the Ontology Development Kit (ODK) for its creation and maintenance, with its content being more easily updated through AI-driven curation support. This approach not only ensures the ontology's relevance amidst the fast-paced advancements in AI but also significantly enhances its utility for researchers, developers, and educators by simplifying the integration of new AI concepts and methodologies. The ontology's utility is demonstrated through the annotation of AI methods data in a catalog of AI research publications and the integration into the BioPortal ontology resource, highlighting its potential for cross-disciplinary research. The AIO ontology is open source and is available on GitHub ( https://w3id.org/aio/ ) and BioPortal ( https://bioportal.bioontology.org/ontologies/AIO ).

Joachimiak, Marcin P. [Biosystems Data Science Dep↗
DOE OSTI2024

Isotope Production Education and Research via a Systematic Study of Photo-nuclear Reaction Yields and Excitation Functions

A new collaboration between the New Mexico Institute of Mining and Technology, Idaho State University, and Idaho National Laboratory builds the domestic workforce in isotope production and related science and technologies by conducting research and education programs related to photo-nuclear reactions. Workforce development was identified by the Department of Energy’s Office of Science in the Reaching a New Energy Sciences Workforce (RENEW) program that seeks to engage underrepresented university students in isotope production activities. This collaboration includes coursework development, student training, and isotope production research utilizing photo-nuclear reactions at electron linear accelerators. Bremsstrahlung-weighted excitation functions and cross-sections will be measured and the use of nanomaterials to exploit kinematic recoil reactions will be investigated. Students will be hosted at the Idaho National Laboratory where mentors will provide opportunities to explore careers in nuclear science and technology. This presentation regards the ongoing progress of the research and education objectives of the collaboration that was performed under the Office of Science Isotopes Program under award number D000-22-2765.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

5G integrated edge computing platform for efficient component monitoring in coal-fired power plants

This project developed a cutting-edge 5G-integrated edge computing framework to enhance operational efficiency and reliability in coal-fired power plants through real-time component monitoring and anomaly detection. The initiative focused on leveraging distributed machine learning, federated learning, and 5G-based dynamic network slicing to support scalable, fault-tolerant monitoring environments to meet the operational requirements in industrial control systems. With a Distributed Edge Computing Service (DECS) orchestration, this project enabled federated learning at edge for condition monitoring and introduced adaptive client selection strategies to minimize communication overhead. Scalable distributed training was achieved using the Horovod framework, thus enhancing performance across edge nodes. In the realm of 5G networking, the project designed and deployed reconfigurable, QoS-aware network slicing tailored for operational technology (OT) environments, integrating software-defined networks to bolster cyber-resilience and enabling dynamic slicing for federated learning workloads. A significant milestone was the development of a virtualized ICS environment with 5G core integration—which allowed elastic and fault tolerant distributed training on real-world datasets such as NASA Bearings, Hydraulic Systems, and TEP. To broaden the impact of the project, a TRL-3 virtualized ICS testbed for research and education was designed. This project engaged several graduate and undergraduate students to conduct research on the cutting-edge technology, and it resulted in one PhD dissertation, one MS thesis, and over 14 peer-reviewed publications. With the support of this project students also participated in national cybersecurity competitions to improve their professional development skills.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Achieving GPT-4o level performance in astronomy with a specialized 8B-parameter large language model

AstroSage-Llama-3.1-8B is a domain-specialized natural-language AI assistant tailored for research in astronomy, astrophysics, cosmology, and astronomical instrumentation. Trained on the complete collection of astronomy-related arXiv papers from 2007 to 2024 along with millions of synthetically-generated question-answer pairs and other astronomical literature, AstroSage-Llama-3.1-8B demonstrates remarkable proficiency on a wide range of questions. AstroSage-Llama-3.1-8B scores 80.9% on the AstroMLab-1 benchmark, greatly outperforming all models—proprietary and open-weight—in the 8-billion parameter class, and performing on par with GPT-4o. This achievement demonstrates the potential of domain specialization in AI, suggesting that focused training can yield capabilities exceeding those of much larger, general-purpose models. AstroSage-Llama-3.1-8B is freely available, enabling widespread access to advanced AI capabilities for astronomical education and research.

AI assistant↗
DOE OSTI2026

Data-Driven Modeling and Control of Systems with Plasma-Surface Interactions (Final Technical Report)

This final technical report summarizes the activities and accomplishments in the period from February 2023 thru January 2026. The objective of the proposed research is to investigate the physical mechanisms and processes underlying the formation of structures and patterns in systems with plasma-surface interactions. In the past decades, there have been extensive studies on the interaction of glow discharges, dielectric barrier discharges, and arc discharges with confining or intervening surfaces. The advancement of the understanding of these phenomena is not only of fundamental scientific interest and relevance to the knowledge of the plasma state, but also with profound implications in various technological applications. The research will integrate theoretical, computational, and experimental work within an innovative framework of data assimilation, i.e., optimally combining model predictions with measurements. The scientific merit of this research has three aspects. Firstly, it extends the studies of plasma-surface interactions to systems with insulator surfaces and multi-layer systems, while existing studies are predominantly on electrode surfaces. Secondly, it expects to develop a novel data-driven modeling approach based on data assimilation to enhance the predictive and control capabilities, which could make transformative contributions to basic plasma research. Thirdly, it will shed new light on outstanding problems related to formation of patterns interfacing plasmas. This project also aims to launch an education and outreach initiative at Texas A&M University-Kingsville, a non-R1, minority-serving institution in South Texas. The initiative is structured as a four-tier pyramid. Tier one will be a webinar series for culture and capacity building to inform broader audience in the region about the research fields of plasma science and engineering. Tier two will be the creation and offering of an upper-level undergraduate course on introductory plasma physics, which will help with the recruitment for the upper tiers. On tier three, we will engage and mentor senior design students to conduct work toward the research goal of this project. There will also be a certificate program on general plasma science for undergrad and graduate students, part of which will be lab training at Princeton University. Tier four will be the supervision and mentoring of Ph.D. students. Therefore, this project will systematically expand the talent pipeline, broaden participation from communities historically and geographically underrepresented in DOE SC research portfolio, significantly improve the research and education capacity at the PI’s institution, and contribute to developing a diverse workforce in plasma science and engineering.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Supporting Growth of a Skilled Workforce in the Building Energy Efficiency Industry (Final Technical Report)

The Interstate Renewable Energy Council (IREC), having worked for well over a decade to develop national networks and best practices focused on attracting and training high quality workers for the clean energy industries, sought to address shortfalls in skilled workers who build, retrofit, operate, and maintain energy efficient buildings. Through this project, IREC created and promoted a Green Buildings Career Map (GBCM)—a career awareness and recruitment tool—that seeks to boost the nationwide growth of workers entering the energy efficiency (EE) industry. Working with a team of subject matter experts and our partner organizations—Building Performance Association (BPA), Building Performance Institute (BPI), Community Action Partnership (CAP), and the National Institute of Building Sciences (NIBS)—IREC produced an interactive, engaging career map to attract and motivate individuals into pursuing careers in energy efficiency, and in support of the Weatherization Assistance Program. The GBCM was designed for a broad audience including educators, career advisors, employers, policymakers, workforce professionals, and jobseekers who may otherwise have little or no awareness of the exciting and rewarding opportunities within targeted industry sectors. Most individuals seeking careers do not know about the breadth of careers awaiting them in the built environment and the same is true for most career and guidance counselors, educators, and parents. The GBCM provides this broad audience with a vision of the myriad jobs that could lead to a long-standing career in energy efficiency. The GBCM describes diverse occupations across the EE industry, charts possible progression between those occupations, and identifies the training, skills, and credentials necessary to do them well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Investigation of the Effect of Framework Flexibility on Adsorption in SIFSIX-3-Cu using a Machine-Learned Force Field

Metal-organic frameworks (MOFs) are a promising class of adsorbents. The performance of MOF sorbents relies on high selectivity and low regeneration energy. This work focuses on the use of machine learned force fields (MLFFs) to model adsorption in a flexible MOF, SIFSIX-3-Cu. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies, forces, and stresses, using an iterative sampling scheme combining sampling based on molecular dynamics, Monte Carlo, and geometry optimization to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included in this model. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations using the MLFF predicted adsorption isotherms in good agreement with experimental data for a range of pressures (40 Pa – 104 Pa) in contrast to rigid models, which overpredict CO2 adsorption at low pressures. The improvement was the result of a description of the variability of fluorine-fluorine diagonal distances at adsorption sites. This detailed description of flexibility afforded by the MLFF resulted in more accurate predictions adsorption isotherms when compared to the experimentally measured values. These results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low pressure applications and provide a robust procedure for training MLFF models for MOFs.

Atomistic Simulation↗
DOE OSTI2023

Bishop Paiute Single Family Solar Home Project: Phase 4 (Final Technical Report)

The Bishop Paiute Tribe is committed to energy efficiency, renewable energy, and environmental protection and has a vision to install solar energy systems on all buildings on the Reservation where technically feasible. Through completion of the Bishop Paiute Tribe Residential Solar Program – Phase 4, Bishop Paiute Tribe continued its successful model partnering with non-profit solar installer GRID Alternatives to advance its vision and build energy self-sufficiency on the Bishop Paiute Reservation. The Bishop Paiute Tribe Residential Solar Program – Phase IV deployed 67 kW-AC of new clean, renewable energy through grid-tied, net-metered rooftop solar electric systems installed on a total of 20 (one more than the planned 19) existing owner-occupied, single-family homes for low-income families on the Reservation. This represents nearly 14% of the Reservation’s total “unsolarized” homes. These systems were provided at no cost to the homeowners, who will also receive energy efficiency education to further reduce energy consumption and lower electric bills. GRID led a solar installation for three (3) of the homes where Tribal/community members, were given an opportunity in participating in on-the-roof trainings to gain new skills while installing solar for their low-income community members. Subcontractors through GRID Sub Contractor Partnership Program (GRID SPP) led solar installations for seventeen (17) of the homes. Each installation provided paid employment for a solar trainee trainees hired by the SPP subcontractors as entry level solar installers. It is estimated that the installed 67 kW-AC of solar will produce at least 120,000 kWh/year, displacing at least 30-75% of the 20 homes’ total electricity use for a combined system lifetime electricity cost savings for the low-income homeowners of about $\$$500,000. It is further estimated that the installed renewable energy systems installed will prevent greenhouse gases by about 1,000 tons, equivalent to planting approximately 25,000 trees. Following the successful completed installations, it is expected that the Reservation and surrounding communities will benefit from improved air quality via reduced wood stove use for heating. Cumulatively with other initiatives, the project will result in nearly 40% of the Reservation’s solarizable homes being solarized. Overall, the triple impact of the phase 4 of the Bishop Paiute Tribe Residential Solar Program – Phase 4 is: 1) affordable energy for low-income families; 2) on-site clean energy production, 3) hands on training and paid solar installation work for local tribal/community workers. These impacts will support and grow the Tribe’s energy, economic, environmental, and social self-sufficiency and sovereignty amongst the neediest on the Reservation.

14 SOLAR ENERGY↗
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 OSTI2023

Scaling Up: Growth of the Indy Student Cluster Competition

The Indy Student Cluster Competition (IndySCC) completed its second year of competition, expanding and building upon the fist year. The IndySCC is a fully virtual competition, with a focus on education, and is part of the student program within the Supercomputing (SC) conference series. The competition aims to engage teams who do not get into the in-person, Student Cluster Challenge (SCC) and to build and train inexperienced teams to eventually go on to the SCC. The first year featured 5 teams and in the second year, this grew to 11 accepted teams in 2022. This work aims to provide an update to how the competition has grown, the challenges, and the plans to grow in the future.

Dietz, Dan↗
DOE OSTI2022

Real-time Distribution Simulation and Application Development for Power Systems Education

To help bridge the gap between traditional power system engineering instruction and emerging industry needs, a new set of classroom and research tools are needed. Real-time simulation tools emulating power system control room software present an opportunity to introduce students to the array of operational considerations, technical challenges, and decision-making associated with power system operations. The GridAPPS-D platform is proposed to support coursework and academic research as it provides an open-source platform for simulation, application development, and software integration. The GridAPPS-D platform, simulation capabilities, development environment, and interactive training are discussed in the context of lessons-learned from implementation for undergraduate and graduate students in the US and India. A series of potential GridAPPS-D supported academic capabilities are introduced.

Active distribution networks, open educational res↗
DOE OSTI2026

Mapping the Gap: Analysis of Nuclear Cybersecurity Education in U.S. Universities

The U.S. nuclear sector is undergoing rapid transformation, driven by the expansion of advanced reactors, digital modernization of legacy systems, and increasing interest in nuclear energy to meet AI-fueled energy demands. However, the cybersecurity talent pipeline is not keeping pace with this growth. This paper investigates the significant gap in nuclear cybersecurity education and proposes scalable strategies for colleges to address this critical need by promoting it as a viable and essential career path. Through a multi-institutional landscape analysis of 16 cybersecurity and 12 nuclear engineering programs, we found that nuclear cybersecurity is largely absent from university curricula. Most students are unaware of the field’s existence, and few institutions offer hands-on training or interdisciplinary exposure. This lack of awareness leads to a shortage of specialized talent, forcing nuclear facilities to retrain generalist hires or rely on costly external consultants. We present a framework for early pipeline cultivation grounded in Social Cognitive Career Theory and workforce development principles. Proposed solutions include student-led clubs, guest lectures, modular classroom kits, and summer boot camps. By increasing visibility and access to nuclear cyber content, we aim to break the self-reinforcing cycle of low awareness and limited specialization. This work underscores the critical role of education and advocacy in cultivating early interest and guiding students toward this emerging field. We call on academic institutions, national laboratories, and industry stakeholders to collaborate in establishing nuclear cybersecurity as a distinct and accessible career path within the broader cybersecurity and nuclear engineering ecosystems.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

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

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

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Energy I-Corps Electron Beam (EB) Potential for International Trade of Logs

The purpose of this document is to capture the potential from Fermilab’s “Team EB Treement” at the DOE Energy I-Corps program. Energy I-Corps, a key initiative of the Office of Technology Transitions, pairs teams of researchers with industry mentors for an intensive two-month training where the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. The team was composed prior to the Energy I-Corp program; however, the program was a catalyst for education and information exchange between the team members and stakeholders, customers, and regulators. These exchanges were captured in the evolution of a Business Model Canvas (BMC) and a Value Proposition (VP). The BMC and VP underwent numerous transformations based on feedback from the conversations between members of the team and forest or agriculture industry stakeholders and the program instructors.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Women in Data Science Livermore Datathon 2024

The WiDS Datathon 2024 focuses on a prediction task using a roughly 39k record dataset (split into training and test sets) representing patients and their characteristics (age, race, BMI, zip code), their diagnosis and treatment information (breast cancer diagnosis code, metastatic cancer diagnosis code, metastatic cancer treatments, … etc.), their geo (zip-code level) demographic data (income, education, rent, race, poverty, …etc), as well as toxic air quality data (Ozone, PM25 and NO2) that tie health outcomes to environmental conditions. Each row in the data corresponds a single patient and her Diagnosis Period.

59 BASIC BIOLOGICAL SCIENCES↗