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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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DOE OSTI2025

An Experiment with LLMs as Database Design Tutors: Persistent Equity and Fairness Challenges in Online Learning

As large language models (LLMs) continue to evolve, their capacity to replace humans as their surrogates is also improving. As increasing numbers of intelligent tutoring systems (ITSs) are embracing the integration of LLMs for digital tutoring, questions are arising as to how effective they are and if their hallucinatory behaviors diminish their perceived advantages. One critical question that is seldom asked if the availability, plurality, and relative weaknesses in the reasoning process of LLMs are contributing to the much discussed digital divide and equity and fairness in online learning. In this paper, we present an experiment with database design theory assignments and demonstrate that while their capacity to reason logically is improving, LLMs are still prone to serious errors. We demonstrate that in online learning and in the absence of a human instructor, LLMs could introduce inequity in the form of “wrongful” tutoring that could be devastatingly harmful for learners, which we call ignorant bias, in increasingly popular digital learning. We also show that significant challenges remain for STEM subjects, especially for subjects for which sound and free online tutoring systems exist. Based on the set of use cases, we formulate a possible direction for an effective ITS for online database learning classes of the future.

Jamil, Hasan M. (ORCID:0000000231243780)↗
DOE OSTI2025

Pulsar’s Application in Energy Systems: Review of Current Status, Challenges, and Opportunities

To accelerate progress toward the realization of advanced energy systems, this review explores the potential of pulsar technology to create a more stable, economical, and environmentally friendly energy infrastructure. Pulsars, with their precise and reliable timing characteristics, have emerged as a promising tool for enhancing energy systems. This review begins by examining the development history of pulsar technology, shedding light on its evolution and the milestones achieved. It then provides a comprehensive summary of the current state of research, highlighting recent advancements and breakthroughs in this field. It also explores transformative pulsar applications in energy systems, including improved grid stability, advanced energy synchronization, and efficient energy storage management. However, implementing pulsar-related technologies presents significant technical, economic, and operational challenges. This review examines these hurdles and proposes strategies to overcome them, emphasizing the need for innovation, interdisciplinary collaboration, and supportive policies to fully integrate pulsar technologies into sustainable energy systems.

application↗
DOE OSTI2022

Nuclide Inventory Benchmark for BWR Spent Nuclear Fuel: Challenges in Evaluation of Modeling Data Assumptions and Uncertainties

This work discusses challenges and approaches to uncertainty analyses associated with the development of a nuclide inventory benchmark for fuel irradiated in a boiling water reactor. The benchmark under consideration is being developed based on experimental data from the SFCOMPO international database. The focus herein is on how to address missing data in fuel design and operating conditions that are important for adequately simulating the time-dependent changes in fuel during irradiation in the reactor. The effects of modeling assumptions and uncertainties in modeling parameters on the calculated nuclide inventory were analyzed and quantified through computational models developed using capabilities in the SCALE code system. Particular attention was given to the impact of the power history and water coolant density on the calculated nuclide inventory, as well as to the effect of geometry modeling considerations not usually addressed in a nuclide inventory benchmark. These considerations include gap closure, channel bow, and channel corner radius, which do not usually apply to regular reactor operation but are relevant for assessing impacts of potential anomalous operating scenarios.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Current State, Challenges, and Opportunities in Genome-Scale Resource Allocation Models: A Mathematical Perspective

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The Anaerobic Fungi: Challenges and Opportunities for Industrial Lignocellulosic Biofuel Production

Lignocellulose is a promising feedstock for biofuel production as a renewable, carbohydrate-rich and globally abundant source of biomass. However, challenges faced include environmental and/or financial costs associated with typical lignocellulose pretreatments needed to overcome the natural recalcitrance of the material before conversion to biofuel. Anaerobic fungi are a group of underexplored microorganisms belonging to the early diverging phylum Neocallimastigomycota and are native to the intricately evolved digestive system of mammalian herbivores. Anaerobic fungi have promising potential for application in biofuel production processes due to the combination of their highly effective ability to hydrolyse lignocellulose and capability to convert this substrate to H2 and ethanol. Furthermore, they can produce volatile fatty acid precursors for subsequent biological conversion to H2 or CH4 by other microorganisms. The complex biological characteristics of their natural habitat are described, and these features are contextualised towards the development of suitable industrial systems for in vitro growth. Moreover, progress towards achieving that goal is reviewed in terms of process and genetic engineering. In addition, emerging opportunities are presented for the use of anaerobic fungi for lignocellulose pretreatment; dark fermentation; bioethanol production; and the potential for integration with methanogenesis, microbial electrolysis cells and photofermentation.

pretreatment↗
DOE OSTI2021

Engineering Challenges of Solution and Slurry-Phase Chemical Hydrogen Storage Materials for Automotive Fuel Cell Applications

In this work, we present the research findings of the DOE-funded Hydrogen Storage Engineering Center of Excellence (HSECoE) related to liquid-phase and slurry-phase chemical hydrogen storage media and their potential as future hydrogen storage media for automotive applications. Chemical hydrogen storage media other than neat liquid compositions will prove difficult to meet the DOE system level targets. Solid- and slurry-phase chemical hydrogen storage media requiring off-board regeneration are impractical and highly unlikely to be implemented for automotive applications because of the formidable task of developing solid- or slurry-phase transport systems that are commercially reliable and economical throughout the entire life cycle of the fuel. Additionally, the regeneration cost and efficiency of chemical hydrogen storage media is currently the single most prohibitive barrier to implementing chemical hydrogen storage media. Ideally, neat liquid-phase chemical hydrogen storage media with net-usable gravimetric hydrogen capacities of greater than 7.8 wt% are projected to meet the 2017 DOE system level gravimetric and volumetric targets. The research presented herein is a collection of research findings that do not in and of themselves warrant a dedicated manuscript. However, the collection of results do, in fact, highlight the engineering challenges and short-comings in scaling up and demonstrating fluid-phase ammonia borane and alane compositions that all future materials researchers working in hydrogen storage should be aware of.

25 ENERGY STORAGE↗
DOE OSTI2023

A Review on Progress, Challenges, and Prospects of Material Jetting of Copper and Tungsten

Copper (Cu) and tungsten (W) possess exceptional electrical and thermal conductivity properties, making them suitable candidates for applications such as interconnects and thermal conductivity enhancements. Solution-based additive manufacturing (SBAM) offers unique advantages, including patterning capabilities, cost-effectiveness, and scalability among the various methods for manufacturing Cu and W-based films and structures. In particular, SBAM material jetting techniques, such as inkjet printing (IJP), direct ink writing (DIW), and aerosol jet printing (AJP), present a promising approach for design freedom, low material wastes, and versatility as either stand-alone printers or integrated with powder bed-based metal additive manufacturing (MAM). Thus, this review summarizes recent advancements in solution-processed Cu and W, focusing on IJP, DIW, and AJP techniques. The discussion encompasses general aspects, current status, challenges, and recent research highlights. Furthermore, this paper addresses integrating material jetting techniques with powder bed-based MAM to fabricate functional alloys and multi-material structures. Finally, the factors influencing large-scale fabrication and potential prospects in this area are explored.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The Presence of Virus Neutralizing Antibodies Is Highly Associated with Protection against Virulent Challenge in Domestic Pigs Immunized with ASFV live Attenuated Vaccine Candidates

African swine fever virus (ASFV) is currently producing a pandemic affecting a large area of Eurasia, and more recently, the Dominican Republic in the Western Hemisphere. ASFV is a large and structurally complex virus with a large dsDNA genome encoding for more than 150 genes. Live attenuated virus strains can induce protection in domestic swine against disease produced by homologous virulent parental viruses. The roles of the different immune mechanisms induced by the attenuated strains in protection still need to be understood. In particular, the role of ASFV neutralizing antibody in protection still is an important controversial issue to be elucidated. Here we present the development of a novel methodology to detect virus neutralizing antibodies based on the reduction of virus infectivity in a Vero cell adapted ASFV strain. The described method was used to assess levels of virus neutralizing antibodies in domestic swine inoculated with live attenuated ASFV. Results demonstrated a high association between the presence of virus neutralizing antibodies and protection in 84 animals immunized with the recombinant vaccine candidates ASFV-G-Δ9GL/ΔUK or ASFV-G-ΔI177L. To our knowledge, this is the first report demonstrating an association between virus neutralizing antibodies and protection against virulent challenge in such a large number of experimental individuals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Recombinant Vaccine Strain ASFV-G-Δ9GL/ΔUK Produced in the IPKM Cell Line Is Genetically Stable and Efficacious in Inducing Protection in Pigs Challenged with the Virulent African Swine Fever Virus Field Isolate Georgia 2010

We have previously reported that the recombinant African Swine Fever (ASF) vaccine candidate ASFV-G-Δ9GL/ΔUK efficiently induces protection in domestic pigs challenged with the virulent strain Georgia 2010 (ASFV-G). As reported, ASFV-G-Δ9GL/ΔUK induces protection, while intramuscularly (IM), administered at doses of 10 4 HAD 50 or higher, prevents ASF clinical disease in animals infected with the homologous ASFV g strain. Like other recombinant vaccine candidates obtained from ASFV field isolates, ASFV-G-Δ9GL/ΔUK stocks need to be produced in primary cultures of swine macrophages, which constitutes an important limitation in the production of large virus stocks at the industrial level. Here, we describe the development of ASFV-G-Δ9GL/ΔUK stocks using IPKM (Immortalized Porcine Kidney Macrophage) cells, which are derived from swine macrophages. We show that ten successive passages of ASFV-G-Δ9GL/ΔUK in IPKM cells induced small changes in the virus genome. The produced virus, ASFV-G-Δ9GL/ΔUKp10, presented a similar level of replication in swine macrophages cultures to that of the original ASFV-G-Δ9GL/ΔUK (ASFV-G-Δ9GL/ΔUKp0). The protective efficacy of ASFV-G-Δ9GL/ΔUKp10 was evaluated in pigs that were IM-inoculated with either 10 4 or 10 6 HAD 50 of ASFV-G-Δ9GL/ΔUKp10. While animals inoculated with 10 4 HAD 50 present a partial protection against the experimental infection with the virulent parental virus ASFV-G, those inoculated with 10 6 HAD 50 were completely protected. Therefore, as was just recently reported for another ASF vaccine candidate, ASFV-G-ΔI177L, IPKM cells are an effective alternative to produce stocks for vaccine strains which only grow in swine macrophages.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Non-Carbon 2D Materials-Based Field-Effect Transistor Biosensors: Recent Advances, Challenges, and Future Perspectives

In recent years, field-effect transistors (FETs) have been very promising for biosensor applications due to their high sensitivity, real-time applicability, scalability, and prospect of integrating measurement system on a chip. Non-carbon 2D materials, such as transition metal dichalcogenides (TMDCs), hexagonal boron nitride (h-BN), black phosphorus (BP), and metal oxides, are a group of new materials that have a huge potential in FET biosensor applications. In this work, we review the recent advances and remarkable studies of non-carbon 2D materials, in terms of their structures, preparations, properties and FET biosensor applications. We will also discuss the challenges facing non-carbon 2D materials-FET biosensors and their future perspectives.

2D-materials↗
DOE OSTI2025

Can Collaboration Succeed in Siting a Spent Nuclear Fuel Facility in the United States?—A Challenge in Political Sustainability

We examine the U.S. Department of Energy (DOE)’s collaborative process to locate, build, and operate one or more federal consolidated interim storage facilities (FCISFs) for commercial U.S. spent nuclear fuel—instead of continuing to store the material at over 70 nuclear reactor sites. Technocratic siting of nuclear facilities in the U.S., most of which did not involve meaningful public participation, was not successful. We consider increasing pressure to find at least one FCISF site, as well as the critical role of trust in engaging communities and reaching agreement—leading some observers to assert that DOE is in the “trust building business”, not the siting business. We present case studies with the following: (1) illustrating community engagement that led to a more satisfactory outcome than had been anticipated (Fernald); (2) a planned voluntary process that failed to produce an operating CISF (Office of the Nuclear Waste Negotiator); and (3) a site that demonstrates the ongoing need for negotiations to keep a site open and operational (Waste Isolation Pilot Plant). The essay concludes with the observation that a collaboration-based siting effort can succeed in the U.S., but that five main challenges—related to trust and requiring patience—will need to be addressed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

The Role of Synthetic Biology in Atmospheric Greenhouse Gas Reduction: Prospects and Challenges

The long atmospheric residence time of CO 2 creates an urgent need to add atmospheric carbon drawdown to CO 2 regulatory strategies. Synthetic and systems biology (SSB), which enables manipulation of cellular phenotypes, offers a powerful approach to amplifying and adding new possibilities to current land management practices aimed at reducing atmospheric carbon. The participants (in attendance: Christina Agapakis, George Annas, Adam Arkin, George Church, Robert Cook-Deegan, Charles DeLisi, Dan Drell, Sheldon Glashow, Steve Hamburg, Henry Jacoby, Henry Kelly, Mark Kon, Todd Kuiken, Mary Lidstrom, Mike MacCracken, June Medford, Jerry Melillo, Ron Milo, Pilar Ossorio, Ari Patrinos, Keith Paustian, Kristala Jones Prather, Kent Redford, David Resnik, John Reilly, Richard J. Roberts, Daniel Segre, Susan Solomon, Elizabeth Strychalski, Chris Voigt, Dominic Woolf, Stan Wullschleger, and Xiaohan Yang) identified a range of possibilities by which SSB might help reduce greenhouse gas concentrations and which might also contribute to environmental sustainability and adaptation. These include, among other possibilities, engineering plants to convert CO 2 produced by respiration into a stable carbonate, designing plants with an increased root-to-shoot ratio, and creating plants with the ability to self-fertilize. A number of serious ecological and societal challenges must, however, be confronted and resolved before any such application can be fully assessed, realized, and deployed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)

Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Challenge Solutions for a Significant Water Cut Reduction History Match on Heavy Oil Polymer EOR

Milne Point Field is conducting the first-ever active polymer flood pilot program designed to enhance oil recovery (EOR) of heavy oils on the Alaska North Slope (ANS). The experimental field program consists of two pairs of horizontal injection and production wells deployed in an isolated fault block in the Schrader Bluff reservoir. The EOR method combines polymer flooding and low salinity water flooding to improve recovery. Prior average water cut reduction in polymer EOR fields ordinarily ranges between 10% to 15% for most light oil and heavy oil reservoirs. When comparing other field applications, the long-lasting (24 months) and much lower water cut poses a challenge for numerical history matching when applying typical simulation methods. This abstract discusses two practical new approaches used for history matching of the long-lasting ultralow water cut. These new applications include 1) multiple relative permeability curves with J-function incorporation with low endpoints of relative permeability of water (Krw). This approach integrated the permeability differential adjustment in the geometries of horizontal and vertical directions based on geological review. 2) A specific permeability channel strips along with the horizontal or vertical planar assumption. The current history matching results indicate success in achieving an excellent agreement with the field observed low water-cut.

Namie, S.↗
DOE OSTI2025

Near-Term Application Engineering Challenges in Emerging Superconducting Qudit Processors

We review the prospects to build quantum processors based on superconducting transmons and radiofrequency cavities for testing applications in the NISQ era. We identify engineering opportunities and challenges for implementation of algorithms in simulation, combinatorial optimization, and quantum machine learning in qudit-based quantum computers.

Venturelli, Davide [RIACS, Mtn. View] (ORCID:00000↗
DOE OSTI2024

Deep-Learning-Based Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment

Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.

building load forecasting↗
DOE OSTI2021

Vision, challenges and opportunities for a Plant Cell Atlas

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.

59 BASIC BIOLOGICAL SCIENCES↗