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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 253 records · Page 14

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↗

Circular Perspective for Utilization of Industrial Wastewaters via Phytoremediation

Wastewater generated in municipal rendering facilities requires multi-step treatment, but it may also serve as a source of nutrients and water and thus may be valorized before or instead of the necessary wastewater treatment operations. In this work, wastewaters from a composting plant were utilized to support the growth of Miscanthus x giganteus, known as both a remediation plant and an energy biomass source. A pot experiment was established to compare the effects of different wastewater doses (0, 50, 100, and 200 mL per pot per week) on the miscanthus biomass yield, phytoextraction of heavy metals, biomass heat of combustion, and plant condition. The increase in the wastewater dose resulted in increases in both biomass yield (from about 44 to 139%) and biomass heat of combustion (from 7 to 17%) when compared to the control sample, with no adverse effects on plant physiological parameters. The highest concentrations of metals were found in miscanthus grown with the highest dose of wastewaters. It was found that higher wastewater dose correlates to both higher phytoextraction and phytorecovery of metals from plant substrate and wastewaters. The highest metal uptake was identified for Fe (431 mg·pot −1 ), followed by Al, Zn, Mn, Cu, Ni, Cr. The lowest metal uptake was noted for Pb, Co and Cd (0.88, 0.11, and 0.95 mg·pot −1 , respectively). The results indicate that miscanthus can be recommended for industrial wastewater treatment. In addition, due to high absorption efficiency of the substrate components, miscanthus can be used as a remediation tool, e.g., for the ecological stabilization of remediation of metal-polluted soils, especially in municipal facilities like rendering plants. This presents a circular perspective for the valorization of post-fermentation wastewaters with subsequent growth of energy crops, with other potential benefits for the environment, such as soil treatment, absorption of CO 2 , and air purification.

Miscanthus x giganteus↗

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

59 BASIC BIOLOGICAL SCIENCES↗

New Perspectives on the Exoplanet Radius Gap from a Mathematica Tool and Visualized Water Equation of State

Recent astronomical observations obtained with the Kepler and TESS missions and their related ground-based follow-ups revealed an abundance of exoplanets with a size intermediate between Earth and Neptune (1 R ⊕ ≤ R ≤ 4 R ⊕ ). A low occurrence rate of planets has been identified at around twice the size of Earth (2 × R ⊕ ), known as the exoplanet radius gap or radius valley. We explore the geometry of this gap in the mass–radius diagram, with the help of a Mathematica plotting tool developed with the capability of manipulating exoplanet data in multidimensional parameter space, and with the help of visualized water equations of state in the temperature–density (T–ρ) graph and the entropy–pressure (s–P) graph. We show that the radius valley can be explained by a compositional difference between smaller, predominantly rocky planets (<2 × R ⊕ ) and larger planets (>2 × R ⊕ ) that exhibit greater compositional diversity including cosmic ices (water, ammonia, methane, etc.) and gaseous envelopes. In particular, among the larger planets (>2 × R ⊕ ), when viewed from the perspective of planet equilibrium temperature (T eq ), the hot ones (T eq ≳ 900 K) are consistent with ice-dominated composition without significant gaseous envelopes, while the cold ones (T eq ≲ 900 K) have more diverse compositions, including various amounts of gaseous envelopes.

79 ASTRONOMY AND ASTROPHYSICS↗

Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling

AI models are criticized as being black boxes, potentially subjecting climate science to greater uncertainty. Explainable artificial intelligence (XAI) has been proposed to probe AI models and increase trust. In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. Dynamical models are complex but have gained trust because their successes and failures can sometimes be attributed to specific components or sub-models, such as when model bias is explained by pointing to a particular parameterization. We propose three types of understanding as a basis to evaluate trust in dynamical and AI models alike: (1) instrumental understanding, which is obtained when a model has passed a functional test; (2) statistical understanding, obtained when researchers can make sense of the modeling results using statistical techniques to identify input–output relationships; and (3) component-level understanding, which refers to modelers' ability to point to specific model components or parts in the model architecture as the culprit for erratic model behaviors or as the crucial reason why the model functions well. We demonstrate how component-level understanding has been sought and achieved via climate model intercomparison projects over the past several decades. Such component-level understanding routinely leads to model improvements and may also serve as a template for thinking about AI-driven climate science. Currently, XAI methods can help explain the behaviors of AI models by focusing on the mapping between input and output, thereby increasing the statistical understanding of AI models. Yet, to further increase our understanding of AI models, we will have to build AI models that have interpretable components amenable to component-level understanding. We give recent examples from the AI climate science literature to highlight some recent, albeit limited, successes in achieving component-level understanding and thereby explaining model behavior. The merit of such interpretable AI models is that they serve as a stronger basis for trust in climate modeling and, by extension, downstream uses of climate model data.

54 ENVIRONMENTAL SCIENCES↗

FRET-based dynamic structural biology: Challenges, perspectives and an appeal for open-science practices

Single-molecule FRET (smFRET) has become a mainstream technique for studying biomolecular structural dynamics. The rapid and wide adoption of smFRET experiments by an ever-increasing number of groups has generated significant progress in sample preparation, measurement procedures, data analysis, algorithms and documentation. Several labs that employ smFRET approaches have joined forces to inform the smFRET community about streamlining how to perform experiments and analyze results for obtaining quantitative information on biomolecular structure and dynamics. The recent efforts include blind tests to assess the accuracy and the precision of smFRET experiments among different labs using various procedures. These multi-lab studies have led to the development of smFRET procedures and documentation, which are important when submitting entries into the archiving system for integrative structure models, PDB-Dev. This position paper describes the current ‘state of the art’ from different perspectives, points to unresolved methodological issues for quantitative structural studies, provides a set of ‘soft recommendations’ about which an emerging consensus exists, and lists openly available resources for newcomers and seasoned practitioners. To make further progress, we strongly encourage ‘open science’ practices.

59 BASIC BIOLOGICAL SCIENCES↗

Scenarios of a Sustainable Energy Transition: Perspectives from the U.S.

The energy sector has been undergoing a significant transition over the past decade, which was accelerated in 2020 during the COVD-19 pandemic. This presentation provides an overview of energy trends in the U.S., including electricity, oil and gas, coal, and renewables, the impact of the pandemic in 2020, and forecasts for recovery. Scenarios of energy use and future integrated technologies are outlined as near and mid-term approaches. The presentation concludes with potential U.S. policy priorities focused on energy and economic recovery, as well as perspectives on energy planning from the disruptions of 2020. The presentation is part of day-long series of presentations covering post-COVID-19 energy responses in Asia, Australia, Europe, and the United States.

COVID-19↗

Comparative Economic Analysis of Capture, Transport, and Storage from a CO2 Source Perspective

This presentation provides an overview of a study that evaluated multiple carbon capture and storage (CCS) networks within the Central United States using NETL-developed resources and models to assess management options different CO2 source types face from both economic and regional geologic perspectives when capturing, transporting and storing their CO2. It was presented at the Carbon Capture, Utilization, and Storage (CCUS) 2023 conference, organized and presented by the Society of Petroleum Engineers (SPE), American Association of Petroleum Geologists (AAPG), and Society of Exploration Geophysicists (SEG) and held in Houston, Texas, April 25-27, 2023.

Guinan, Allison↗

Carbon Storage and Utilization: Perspective on Water Usage and Opportunities

Disseminate technical and non-technical perspective on the opportunities for water recovery from produced water and CO2 storage in the I-WEST region. Concerned citizens and advocacy groups; farmers and ranchers; tribal, state, city, and county leaders; and project leaders working on water-related initiatives are all encouraged to participate in the workshop. This workshop is an opportunity for regional stakeholders to join the conversation about the challenges and opportunities water presents for energy transition in the Inter- Mountain West.

Vikara, Derek↗

Machine Learning in Nuclear Thermal Hydraulics, Part 2: Opportunities and Perspectives

This paper summarizes the issues in nuclear thermal hydraulics (NTH), mainly from the three named aspects, and illustrates potential opportunities of machine learning (ML) applications in dealing with these issues. These issues are problems in simultaneously realizing computational efficiency and accuracy of system thermal hydraulic (STH) modeling and simulation, uncertainty in the scaling analysis for the best-estimate calculations of transient and accident analysis, and difficulties in optimal data production and usage for the development and assessment of evaluation models. Due to ML uncertainty, data insufficiency, and lack of cognition about how to efficiently incorporate knowledge and data, challenges of adapting ML techniques still exist. Accordingly, several perspectives are proposed to provide insights for ML applications in solving these issues.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Perspective on Solar Energy Materials, Design and Discovery, Defects, Disorder, and Interfaces

The energy transition still faces a daunting math. Currently, more than three quarters of final energy consumption occurs in form of fuels vs less than one quarter in electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, meeting the terawatt challenge requires enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies, for example via solar thermochemical routes. In this presentation, we will review successes and challenges in photovoltaic materials from silicon to CdTe to halide perovskites and potential emerging materials, with a particular perspective on the role of first principles calculations and predictions. Materials design and discovery is evolving to incorporate defects, disorder, and interfaces. These phenomena play also an important role in the thermochemical generation of hydrogen, allowing to utilize synergies between renewable electricity and fuels in computational research. At the same time, machine learning approaches are increasingly geared toward properties of non-ideal materials, for example defect formation, allowing the screening for more complex material behavior as needed for the respective applications.

fuels↗

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.

Alexeev, Yuri↗

Fabrication Lessons Learned of Transportation Packaging from the Perspective of a Design Authority - 20322

This paper presents lessons learned regarding fabricating packaging systems from the perspective of a design authority (DA). Capturing and implementing lessons learned is critical for an organization to reduce systematic project risk and thereby promote the likelihood of project success. This paper defines the design authority as the organization responsible for technical design, resolving technical design issues, quality assurance program, and maintenance of the packaging system license. A package system is defined as the packaging, its contents, and auxiliary equipment. Packages are certified by the NRC under 10 CFR 71[1] for transportation by ground. The following lessons learned subjects are presented in the paper: quality assurance, interpretation of drawing dimensional requirements, execution of manufacturing processes, hardware dimensional inspection, and leakage rate testing. All discrepancies presented in this paper have been resolved as described in the appropriate final data package. All described package systems are in compliance with their Safety Analysis Report (SAR) and certificate of conformance requirements. The intent of this paper is to identify opportunities for improving the outcome of future projects and to mitigate fabrication challenges proactively. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Panel Session 129: Perspectives (US and Non-US) on the Use of Risk and Dose Assessment Tools (R9.3)

This panel focused on various dose and risk assessment tools for assessments, Deactivation and Decommissioning, remediation, and closure of sites of chemical and radioactive wastes. Representatives from the US government agencies, non-US countries and their representative regulatory bodies or authorities, as well as performance/risk assessment practitioners compared and contrasted the various guidance from regulatory agencies and authorities on how tools such as the Preliminary Remediation Goals (PRG) calculator, the Dose Compliance Concentrations (DCC) calculator, and Residual Radioactivity (RESRAD) should be used in support of analyses and decisions for environmental cleanup activities. Panelists with presentations: Cumulative Impact Evaluation: Innovative Tools for Evaluation of Groundwater Protection (Alaa Aly); Superfund Evaluation Process for Alternative Risk and Dose Models (with Focus on EPA and DOE Tools) (Stuart Walker); NRC Staff Perspective on Risk-Informed Approach and Reasonable Safety Assurance in D and D and LLW (Rateb (Boby) Abu Eid)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Panel discussion: Challenges and improvements in accident dose analysis; Regulatory and industry perspective

Full text of publication follows. Design basis accident (DBA) analyses are one of several ways nuclear power plant licensees demonstrate, and the U.S. Nuclear Regulatory Commission (NRC) staff verifies, that the design and location of a nuclear power plant are appropriate and that the protection of health and safety of the public is maintained. In July 2000, the NRC staff issued Regulatory Guide 1.183, 'Alternative Radiological Source Terms for Evaluating Design Basis Accidents at Nuclear Power Reactors' (RG 1.183) [1]. RG 1.183 provides a method acceptable to the NRC staff for complying with the regulatory requirements contained in Title 10 of the Code of Federal Regulation (10 CFR) Section 50.67 (50.67), 'Accident source term' [2]. RG 1.183 also provides assumptions and parameters used to model postulated DBA radiological analyses for light-water reactors (LWR). Since the initial issuance of RG 1.183, the NRC staff and the nuclear power plant licensees have both gained substantial experience with the implementation of 10 CFR 50.67 and RG 1.183. Based on this experience, comments from licensees, the anticipation of licensing advanced LWRs, and new research, the NRC is developing a proposed revision to RG 1.183. This panel discussion will provide a discussion of that proposed revision, its potential impact on existing and future evaluations, and the industry perspective on the revised guidance. References: 1) USNRC, Regulatory Guide 1.183, 'Alternative Radiological Source Terms for Evaluating Design Basis Accidents at Nuclear Power Reactors,' Revision 0, U.S. Nuclear Regulatory Commission, Washington, D.C. (2000), Electronic copies are also available in ADAMS (http://www.nrc.gov/reading-rm/adams.html), under Accession No. ML003716792. 2) U.S. Code of Federal Regulations, Title 10 (Energy), Part 50 (Domestic Licensing of Production and Utilization Facilities), Section 67, (Accident source term), Office of the Federal Register, Washington, DC (1999). (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗

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

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

end-of-life↗