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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Workforce Development Survey Results: Industry, Government Laboratories, Academia, and Recent Graduates

Herein, we describe the results of the survey from the TMS Education committee. The committee designated a subcommittee on Workforce Development to survey professionals in industry/government laboratories (I/G), academia (A), and recent graduates (RG) to gain insights into the alignment of materials science curricula with workforce needs. The survey project began with a charter to explore any disconnects that might exist between university materials curriculum and workforce knowledge, skill, and ability needs for MSE-related careers, and also highlight critical areas of excellence that should be preserved. Focused surveys for each category were developed and received over 150 responses, including 83 responses from industry/government, 40 responses from recent graduates, 29 responses from academia.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Developing and Demonstrating a Lab Method for Quantifying Hair Exposure to Environmental Tobacco Smoke with a Forensic Perspective

Forensic science and chemistry curricula often lack hands-on experimental designs that effectively simulate the impact of environmental tobacco smoke (ETS) or other common elements found at crime scenes, such as marijuana, on trace forensic evidence. Hair, a critical form of trace evidence, offers unique advantages for assessing long-term exposure to environmental pollutants, including ETS. This study presents a novel, noninvasive forensic laboratory module designed to evaluate ETS exposure on various human hair types (untreated, dyed, and bleached). The experimental procedure involved controlled cigarette smoke exposure, followed by analysis using UV−visible spectroscopy, FTIR spectroscopy, and zeta potential measurements. Thirteen students participated in the three-week lab module (three sessions per week). Pre- and postlab assessments were conducted to evaluate learning outcomes. The prelab assessment focused on baseline knowledge of forensic hair analysis, as well as student expectations and confidence. The postlab assessment evaluated knowledge gained, technical insights, application of techniques, self-reflection, conceptual understanding, and practical skill development. This design helped students comprehend the effects of chemical treatments that significantly influence hair’s capacity to adsorb ETS residues by altering its physical and chemical properties. Integration of this experiment into the forensic chemistry curriculum led to measurable gains in student understanding, technical competency, and appreciation for realworld forensic applications. This method offers a valuable teaching and investigative tool for assessing individual ETS exposure in forensic contexts.

FTIR↗
DOE OSTI2022

Development of a Freeze-Dried CRISPR-Cas12 Sensor for Detecting Wolbachia in the Secondary Science Classroom

Training the future synthetic biology workforce requires the opportunity for students to be exposed to biotechnology concepts and activities in secondary education. Detecting Wolbachia bacteria in arthropods using polymerase chain reaction (PCR) has become a common way for secondary students to investigate and apply recombinant DNA technology in the science classroom. Despite this important activity, cutting-edge biotechnologies such as clustered regularly interspaced short palindromic repeat (CRISPR)-based diagnostics have yet to be widely implemented in the classroom. To address this gap, we present a freeze-dried CRISPR-Cas12 sensing reaction to complement traditional recombinant DNA technology education and teach synthetic biology concepts. The reactions accurately detect Wolbachia from arthropod-derived PCR samples in under 2 h and can be stored at room temperature for over a month without appreciable degradation. Here, the reactions are easy-to-use and cost less than $40 to implement for a classroom of 22 students including the cost of reusable equipment. We see these freeze-dried CRISPR-Cas12 reactions as an accessible way to incorporate synthetic biology education into the existing biology curriculum, which will expand biology educational opportunities in science, technology, engineering, and mathematics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

DNABERT-S: pioneering species differentiation with species-aware DNA embeddings

SUMMARY: We introduce DNABERT-S, a tailored genome model that develops species-aware embeddings to naturally cluster and segregate DNA sequences of different species in the embedding space. Differentiating species from genomic sequences (i.e. DNA and RNA) is vital yet challenging, since many real-world species remain uncharacterized, lacking known genomes for reference. Embedding-based methods are therefore used to differentiate species in an unsupervised manner. DNABERT-S builds upon a pre-trained genome foundation model named DNABERT-2. To encourage effective embeddings to error-prone long-read DNA sequences, we introduce Manifold Instance Mixup (MI-Mix), a contrastive objective that mixes the hidden representations of DNA sequences at randomly selected layers and trains the model to recognize and differentiate these mixed proportions at the output layer. We further enhance it with the proposed Curriculum Contrastive Learning (C2LR) strategy. Empirical results on 28 diverse datasets show DNABERT-S's effectiveness, especially in realistic label-scarce scenarios. For example, it identifies twice more species from a mixture of unlabeled genomic sequences, doubles the Adjusted Rand Index (ARI) in species clustering, and outperforms the top baseline's performance in 10-shot species classification with just a 2-shot training. AVAILABILITY AND IMPLEMENTATION: Model, codes, and data are publically available at https://github.com/MAGICS-LAB/DNABERT_S.

Zhou, Zhihan↗
DOE OSTI2025

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗
DOE OSTI2022

Vulnerability Research Development Program Guide v.1

SAND2021-15515 O The Vulnerability Research Development Program (VRDP) Guide is a training program developed to help general purpose computer science staff become independently capable vulnerability researchers. VRDP Guide is both a course description and curriculum for the program. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Salim, Nasser↗
DOE OSTI2024

Comminty Geothermal: Planning and Design of a Heating and Cooling System in Framingham, Massachusetts

These reports, plans, and drawings review the achievements of Home Energy Efficiency Team (HEET) and its partners to plan and design a network of interconnected ground-source heat pump systems, or geothermal network, in an area encompassing multiple environmental justice (EJ) neighborhoods in the City of Framingham, MA. The materials provided in this dataset include, a) stakeholder and design best practices, b) study on optimal method to interconnect geothermal loops, c) guidelines for monitoring and metering, d) operations and maintenance plans, e) permitting guidelines and f) 10-day driller tutorial curriculum. These materials can guide the efficient and ethical design of future geothermal networks nationwide. The capacity of the system is estimated at 217 tons and is designed to provide 100% of heating and cooling needs for the buildings connected to the loop. In this project, 80 boreholes are used as the main thermal resources, the distribution system (or loop) consists of 0.61 miles of an 8-inch single-pipe at ambient temperature, with the capacity to connect 44 buildings, including 13 apartment buildings from the Framingham Housing Authority, one transitional home, one school building and 29 single family homes. While Framingham already has a geothermal network loop that is currently in the commissioning stage, our proposed project is unique because it is the first utility-led expansion loop (2nd loop) project that will connect to an adjacent existing geothermal loop (1st loop) in a pre-existing neighborhood. Both the 1st and 2nd loops are being installed, owned and operated by Eversource Energy, the utility Deployment Partner.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Modern Software Engineering and Research [Slides]

The goals of this teaching workshop are for the learners to leave with a broad view of University curriculum, successes and limitations, and the state of industry; an awareness of grand challenges in software engineering; and an awareness of current approaches to address those challenges.

42 ENGINEERING↗
DOE OSTI2022

NNSA Minority Serving Institute Partnership Program (MSIPP)-- Partnership for Advanced Manufacturing Education and Research (PAMER) (Q1 FY2022 Progress Report)

The following report summarizes the status update during this quarter for the National Nuclear Security Agency (NNSA) initiated Minority Serving Institution Partnership Plan's (MSIPP) project titled, Partnership for Advanced Manufacturing Education and Research (PAMER). In 2016, the National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) targeting Tribal Colleges and Universities (TCUs) to offer programs that will prepare students for technical careers in NNSA’s laboratories and production plants. The MSIPP consortium’s approach is as follows: 1) align investments at the college and university level to develop a curriculum and workforce needed to support NNSA’s nuclear weapon enterprise mission, and 2) to enhance research and education at under-represented colleges and universities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

NNSA Minority Serving Institute Partnership Program (MSIPP)— Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE) (FY22 Q1 Progress Report)

In 2016, the National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) targeting Tribal Colleges and Universities (TCUs) to offer programs that will prepare students for technical careers in NNSA’s laboratories and production plants. The MSIPP consortium’s approach is as follows: 1) align investments at the college and university level to develop a curriculum and workforce needed to support NNSA’s nuclear weapon enterprise mission, and 2) to enhance research and education at under-represented colleges and universities. The first TCU consortium that MSIPP launched was known as the Advanced Manufacturing Network Initiative (AMNI) whose purpose was to develop additive manufacturing (AM) learning opportunities. The AMNI consortium consisted of Bay Mills Community College, Cankdeska Cikana Community College, Navajo Tech University, Salish Kootenai Community College, Turtle Mountain Community College, and United Tribes Technical College. In 2016, the American Indian Higher Education Consortium (AIHEC), the AMNI consortium and the Southwestern Indian Polytechnic Institute (SIPI), in collaboration with Sandia National Labs, using a grant by NNSA hosted the first TCU Advanced Manufacturing Technology Summer Institute (TCU AMTSI). The AMNI consortium will officially end Sept. 2022. However, building on the successes of AMNI, in FY22 NNSA’s MSIPP launched three additional consortiums: (1) the Indigenous Mutual Partnership to Advanced Cybersecurity Technology (IMPACT), which focuses on STEM and cybersecurity, (2) the Advanced Synergistic Program for Indigenous Research in Engineering (ASPIRE), which focuses on STEM and the electrical and mechanical engineering skills set needed for renewable and distributed energy systems, and (3) the Partnership for Advanced Manufacturing Education and Research (PAMER), which focuses on developing and maintaining a sustainable pathway for a highly trained, next-generation additive manufacturing workforce and a corresponding community of subject matter experts for NNSA enterprises. The following report summarizes the status update during this quarter for the ASPIRE program.

42 ENGINEERING↗