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At least 1,243 records · Page 69

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Controlled environment agriculture: An opportunity to strengthen interagency research collaboration in the US government

Challenges facing food production and agricultural systems are increasingly interconnected with economic, security, health, and equity issues, among others. Threats such as extreme weather, economic volatility, and shrinking water resources and arable land, influence our ability to maintain a safe and resilient food supply. One promising solution to these threats is controlled environment agriculture (CEA). In many cases, CEA can drastically reduce the amount of water and land used in crop production while increasing productivity. Operations may be established in nearly any environment and harvests can take place year-round, supporting food system resiliency and sustainability. CEA sits at the nexus of a number of disciplines and industries, making it well suited for transdisciplinary and multi-institutional research coordination. Herein, authors from multiple US government agencies present CEA as a case study in improving cross-agency research collaboration. The federal government houses a range of scientific expertise and research capabilities, positioning scientists to lead national and global efforts in transdisciplinary, interagency approaches to complex challenges. Navigating cross-agency collaboration can be a challenge, especially coordinating across different scientific disciplines, geographic locations, and funding mechanisms. To enhance multiagency efforts, collaborators could prioritize (i) organizing personnel and resources, (ii) enhancing existing multiagency collaborations, and (iii) focusing on further opportunities for coordination. Adopting these approaches could enable federal researchers to reinforce and advance academic and industry efforts to address current CEA challenges while solidifying the United States as a leader in this arena.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Interdisciplinary research in climate and energy sciences

Due to the complex nature of climate change, interdisciplinary research approaches involving knowledge and skills from a broad range of disciplines have been adopted for studying changes in the climate system as well as strategies for mitigating climate change (i.e., greenhouse gas emissions reductions) and adapting to its impacts on society and natural systems. Harnessing of renewable energy sources to replace fossil fuels is widely regarded as a long-term mitigation strategy that requires the synthesis of knowledge from engineering, technology, and natural and social sciences. In this study, we examine how the adoption of interdisciplinary approaches has evolved over time and in different geographic regions. We conducted a comprehensive literature survey using an evaluation matrix of keywords, in combination with a word cloud analysis, to evaluate the spatiotemporal dynamics of scholarly discourse about interdisciplinary approaches to climate change and renewable energy research and development (R&D). Publications that discuss interdisciplinary approaches to climate change and renewable energy have substantially increased over the last 60 years; it appears, however, that the nature, timing, and focus of these publications vary across countries and through time. Over the most recent three decades, the country-level contribution to interdisciplinary research for climate change has become more evenly distributed, but this was not true for renewable energy research, which remained dominated by the United Sates and a few other major economies. The research topics have also evolved: Water resource management was emphasized from 1990s to 2000s, policy and adaptation were emphasized from the 2000s to 2010 – 2013, while vulnerability became prominent during the most recent years (2010 – 2013). Lastly, our analysis indicates that the rate of growth of interdisciplinary research for renewable energy lags behind that for climate change, possibly because knowledge emanating from climate change science has motivated the subsequent upswing in renewable energy R&D.

54 ENVIRONMENTAL SCIENCES↗

Coupled Thermo-Hydro-Mechanical Processes in Fractured Rocks: Some Past Scientific Highlights and Future Research Directions

Abstract Coupled thermo-hydro-mechanical (THM) processes in fractured rocks have been a topic of intense scientific research for more than 30 years. The present paper takes a look into the past and highlights some scientific advances which are of an unusual “out-of-the-box” nature, and then looks forward and discusses possible directions of future research in this interesting field of study. Concerning future research directions, we see a trend from a focus on coupled THM processes in single fractures or a few interacting fractures, to the study of coupled THM behavior in complex fracture network systems where the fractures act collectively giving rise to local stress concentration points and points of large pressure gradients. Three examples of future research directions are presented. First is an effort towards identifying characterizing parameters of a fracture network that play a direct controlling role in major coupled THM phenomena (such as induced seismicity and flow channeling), rather than parameters of stochastic distributions of fractures in the network. The second example of research direction is accounting for the heterogeneity and hierarchy of fractures in a fault or fracture zone which has been associated with major THM events in a number of geo-energy projects. The third example is at the opposite end of the first; here it is recognized that in some cases, the coupled THM processes in fractured rocks may be controlled dominantly by only a few key bridges. Identification, characterization, and evaluation of these key bridges should be one of the important research directions in the coming days.

58 GEOSCIENCES↗

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Research on Bulk-metallic Glasses and High-entropy Alloys in Peter K. Liaw’s Group and with His Colleagues

Bulk-metallic glasses (BMGs) and high-entropy alloys (HEAs) have attracted extensive attention in the field of metallic materials research for several decades due to their extraordinary properties. Many scientists and researchers have significantly contributed to developing new classes of metallic alloys, such as BMGs and HEAs, for various applications. Liaw’s group and his colleagues have focused on the fundamental understanding of unique features, structures, and properties in BMGs and HEAs as well as the development of new types of metallic materials. Here, we summarized the research work of Liaw’s group and his colleagues by reviewing relevant papers. The goal is to provide an understanding of the current research progression in BMGs and HEAs while further encouraging young and junior researchers to be involved in the field of structural materials research pertaining to these classes of exotic alloy systems.

36 MATERIALS SCIENCE↗

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗

A Review and Perspective of Recent Bio-Oil Hydrotreating Research

The pathway for catalytic hydrodeoxygenation of biomass derived fast pyrolysis oil represents a compelling route for production of liquid transportation fuels. There has been continued progress and advancements in both the public and private research areas towards driving this technology to completion. Published research and patent literature have demonstrated that continued development of HDO as a part of a processes for production liquid transportation using biomass is being advanced for both fuel blend stocks and for refinery intermediates for co-processing. Much of the research has still focused on “quality” metrics around single or groups of unit operations generating partially treated bio-oil streams without assessing upstream and downstream implications. However, there is an encouraging amount of research that is now being targeted and assessed with attempts to understand the impact on the final fuel product, regardless of the route. Much of the most important research is moving towards continuous, industrially relevant processes where data can be generated to adequately inform process and economic modeling. As the technology for producing liquid transportation fuels from pyrolysis/HDO/coprocessing is driving towards commercialization, further research should be prioritized on the basis of impact to a techno-economic analyses.

bio-oil↗

New challenges in oxygen reduction catalysis: a consortium retrospective to inform future research

In this perspective, we highlight results of a research consortium devoted to advancing understanding of oxygen reduction reaction (ORR) catalysis as a means to inform fuel cell science. We demonstrate how targeted collaborations between different institutions from academic, national lab, and industry backgrounds and different scientific disciplines like theory, experiment, and characterization can yield unique insights into fuel cell catalysts. We comment on such insights into material designs for platinum-group-metal alloys, transition metal oxides, and non-traditional materials including metal–organic frameworks; systems that have served as the foundational building blocks for our consortium. We also motivate a renewed focus on catalyst durability in light of emerging technological requirements and paths forward in understanding in situ and operando electrochemical stability. Lastly, we describe new frontiers ORR research can take and how emerging artificial intelligence tools can assist researchers in capturing data, selecting new experiments, and guiding characterization to accelerate the design and discovery of fuel cell catalysts. A main goal of sharing this perspective is to discuss the rationale for our future research plans based on our consortium work. However, we also hope to illustrate both the potential impact of a collaborative strategy with the hopes of inspiring a higher degree of Industry-Academia-National Laboratory collaboration and encourage other centers and consortiums to distill and share their findings in a similar perspective-type article. Together we hope to enable the fuel cell research community to engage in a discussion of strategies for research and accelerated development of catalysts with improved activity and stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Community-Driven Metadata Standards for Agricultural Microbiome Research

Accelerating the pace of microbiome science to enhance crop productivity and agroecosystem health will require transdisciplinary studies, comparisons among datasets, and synthetic analyses of research from diverse crop management contexts. However, despite the widespread availability of crop-associated microbiome data, variation in field sampling and laboratory processing methodologies, as well as metadata collection and reporting, significantly constrains the potential for integrative and comparative analyses. Here we discuss the need for agriculture-specific metadata standards for microbiome research, and propose a list of “required” and “desirable” metadata categories and ontologies essential to be included in a future minimum information metadata standards checklist for describing agricultural microbiome studies. We begin by briefly reviewing existing metadata standards relevant to agricultural microbiome research, and describe ongoing efforts to enhance the potential for integration of data across research studies. Our goal is not to delineate a fixed list of metadata requirements. Instead, we hope to advance the field by providing a starting point for discussion, and inspire researchers to adopt standardized procedures for collecting and reporting consistent and well-annotated metadata for agricultural microbiome research.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗

SU-D-BRD-03: A Gateway for GPU Computing in Cancer Radiotherapy Research

Purpose: Graphics Processing Unit (GPU) has become increasingly important in radiotherapy. However, it is still difficult for general clinical researchers to access GPU codes developed by other researchers, and for developers to objectively benchmark their codes. Moreover, it is quite often to see repeated efforts spent on developing low-quality GPU codes. The goal of this project is to establish an infrastructure for testing GPU codes, cross comparing them, and facilitating code distributions in radiotherapy community. Methods: We developed a system called Gateway for GPU Computing in Cancer Radiotherapy Research (GCR2). A number of GPU codes developed by our group and other developers can be accessed via a web interface. To use the services, researchers first upload their test data or use the standard data provided by our system. Then they can select the GPU device on which the code will be executed. Our system offers all mainstream GPU hardware for code benchmarking purpose. After the code running is complete, the system automatically summarizes and displays the computing results. We also released a SDK to allow the developers to build their own algorithm implementation and submit their binary codes to the system. The submitted code is then systematically benchmarked using a variety of GPU hardware and representative data provided by our system. The developers can also compare their codes with others and generate benchmarking reports. Results: It is found that the developed system is fully functioning. Through a user-friendly web interface, researchers are able to test various GPU codes. Developers also benefit from this platform by comprehensively benchmarking their codes on various GPU platforms and representative clinical data sets. Conclusion: We have developed an open platform allowing the clinical researchers and developers to access the GPUs and GPU codes. This development will facilitate the utilization of GPU in radiation therapy field.

60 APPLIED LIFE SCIENCES↗

Collaborative Visualization: Definition, Challenges, and Research Agenda

Collaborative visualization has emerged as a new research direction which offers the opportunity to reach new audiences and application areas for visualization tools and techniques. Technology now allows us to easily connect and collaborate with one another - in settings as diverse as over networked computers, across mobile devices, or using shared displays such as interactive walls and tabletop surfaces. Any of these collaborative settings carries a set of challenges and opportunities for visualization research. Digital information is already regularly accessed by multiple people together in order to share information, to view it together, to analyze it, or to form decisions. However, research on how to best support collaboration with and around visualizations is still in its infancy and has so far focused only on a small subset of possible application scenarios. The purpose of this article is (1) to provide a clear scope, definition, and overview of the evolving field of collaborative visualization, (2) to help pinpoint the unique focus of collaborative visualization with its specific aspects, challenges, and requirements within the intersection of general computer-supported collaborative work (CSCW) and visualization research, and (3) to draw attention to important future research questions to be addressed by the community. Thus, the goal of the paper is to discuss a research agenda for future work on collaborative visualization, including our vision for how to meet the grand challenge and to urge for a new generation of visualization tools that were designed with collaboration in mind from their very inception.

99 GENERAL AND MISCELLANEOUS↗

The FaceBase Consortium: A comprehensive resource for craniofacial researchers

The FaceBase Consortium, funded by the National Institute of Dental and Craniofacial Research, National Institutes of Health, is designed to accelerate understanding of craniofacial developmental biology by generating comprehensive data resources to empower the research community, exploring high-throughput technology, fostering new scientific collaborations among researchers and human/computer interactions, facilitating hypothesis-driven research, and translating science into improved health care to benefit patients. The resources generated by the FaceBase projects include a number of dynamic imaging modalities, genome-wide association studies, software tools for analyzing human facial abnormalities, detailed phenotyping, anatomical and molecular atlases, global and specific gene expression patterns, and transcriptional profiling over the course of embryonic and postnatal development in animal models and humans. The integrated data visualization tools, faceted search infrastructure, and curation provided by the FaceBase Hub offer flexible and intuitive ways to interact with these multidisciplinary data. In parallel, the datasets also offer unique opportunities for new collaborations and training for researchers coming into the field of craniofacial studies. Here we highlight the focus of each spoke project and the integration of datasets contributed by the spokes to facilitate craniofacial research.

60 APPLIED LIFE SCIENCES↗

COVIDScholar: An automated COVID-19 research aggregation and analysis platform

The ongoing COVID-19 pandemic produced far-reaching effects throughout society, and science is no exception. The scale, speed, and breadth of the scientific community’s COVID-19 response lead to the emergence of new research at the remarkable rate of more than 250 papers published per day. This posed a challenge for the scientific community as traditional methods of engagement with the literature were strained by the volume of new research being produced. Meanwhile, the urgency of response lead to an increasingly prominent role for preprint servers and a diffusion of relevant research through many channels simultaneously. These factors created a need for new tools to change the way scientific literature is organized and found by researchers. With this challenge in mind, we present an overview of COVIDScholar https://covidscholar.org/, an automated knowledge portal which utilizes natural language processing (NLP) that was built to meet these urgent needs. The search interface for this corpus of more than 260,000 research articles, patents, and clinical trials served more than 33,000 users at an average of 2,000 monthly active users and a peak of more than 8,600 weekly active users in the summer of 2020. Additionally, we include an analysis of trends in COVID-19 research over the course of the pandemic with a particular focus on the first 10 months, which represents a unique period of rapid worldwide shift in scientific attention.

60 APPLIED LIFE SCIENCES↗

AmeriFlux FLUXNET-1F US-ORv Olentangy River Wetland Research Park

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ORv Olentangy River Wetland Research Park. This is the FLUXNET version of the carbon flux data for the site US-ORv Olentangy River Wetland Research Park produced by applying the standard ONEFlux (1F) software. Site Description - The ORWRP site is a 21-ha large-scale, long-term wetland campus facility that is owned by Ohio State University. It is designed to provide teaching, research, and service related to wetland and river science and ecological engineering. The site has been developed in several phases: Phase 1 (1992 - 1994) - Construction of two 2.5-acre deepwater marshes and a river water delivery system began, with pumps installed on the floodplain to bring water from the Olentangy River. In May 1994, one wetland was planted with marsh vegetation, while the other remained as an unplanted control; Phase 2 (1994 - 1999) - Development of a research and teaching infrastructure took place with the construction of boardwalks, a pavilion, and a compound. The creation of the 7-acre naturally flooded oxbow was also included; Phase 3 (2000 - 2003) - As a research building was created, three additional wetlands were created in the vicinity of the building, including a stormwater wetland that receives runoff from the roof of the building; Phase 4 - The current phase involves research access to the Olentangy River.

Bohrer, Gil↗

Annual Report FY2011: Establishment of a Laboratory for Biofuels Research at the University of Kentucky

This project is aimed at the development of the biofuels industry in Kentucky by establishing a laboratory to develop improved processes for biomass utilization. The facility is based at the University of Kentucky Center for Applied Energy Research and the Department of Biosystems and Agricultural Engineering, and constitutes an open laboratory, i.e., its equipment is available to other Kentucky researchers working in the area. The development of this biofuels facility represents a significant expansion of research infrastructure, and will provide a lasting resource for biobased research endeavors at the University of Kentucky. In order to enhance the laboratory's capabilities and contribute to on-going biofuels research at the University of Kentucky, initial research at the laboratory has focused on the following technical areas: (i) the identification of algae strains suitable for oil production, utilizing flue gas from coal-fired power plants as a source of CO 2 ; (ii) the conversion of algae to biofuels; and (iii) thermochemical methods for the deconstruction of lignin. Highlights from these activities include a detailed study of bio-oil production from the fast pyrolysis of microalgae (Scenedesmus sp.) and the application of pyrolytic gas chromatography coupled with mass spectrometry (Py-GC-MS) to the characterization of high lignin biomass feedstocks.

09 BIOMASS FUELS↗

Actinide Foil Production for MPACT Research

Sensitive fast-neutron detectors are required for use in lead slowing down spectrometry (LSDS), an active interrogation technique for used nuclear fuel assay for Materials Protection, Accounting, and Controls Technologies (MPACT). During the past several years UNLV sponsored a research project at RPI to investigate LSDS; began development of fission chamber detectors for use in LSDS experiments in collaboration with INL, LANL, and Oregon State U.; and participated in a LSDS experiment at LANL. In the LSDS technique, research has demonstrated that these fission chamber detectors must be sensitive to fission energy neutrons but insensitive to thermal-energy neutrons. Because most systems are highly sensitive to large thermal neutron populations due to the well-known large thermal cross section of 235U, even a miniscule amount of this isotope in a fission chamber will overwhelm the small population of higher-energy neutrons. Thus, fast-fission chamber detectors must be fabricated with highly depleted uranium (DU) or ultra-pure thorium (Th), which is about half as efficient as DU. Previous research conducted at RPI demonstrated that the required purity of DU for assay of used nuclear fuel using LSDS is less than 4 ppm 235U, material that until recently was not available in the U.S. In 2009 the PI purchased 3 grams of ultra-depleted uranium (uDU, 99.99998% 238U with just 0.2 ± 0.1 ppm 235U) from VNIIEF in Sarov, Russia. We received the material in the form of U3O8 powder in August of 2009, and verified its purity and depletion in a FY10 MPACT collaboration project. In addition, chemical processing for use in FC R&D was initiated, fission chamber detectors and a scanning alpha-particle spectrometer were developed, and foils were used in a preliminary LSDS experiment at a LANL/LANSCE in Sept. of 2010. The as-received U3O8 powder must be chemically processed to convert it to another chemical form while maintaining its purity, which then must be used to electro-deposit U or UO2 in extremely thin layers (1 to 2 mg/cm2) on various media such as films, foils, or discs. After many months of investigation and trials in FY10 and 11, UNLV researchers developed a new method to produce pure UO2 deposits on foils using a unique approach, which has never been demonstrated, that involves dissolution of U3O8 directly into room temperature ionic liquid (RTIL) followed by electrodeposition from the RTIL-uDU solution (Th deposition from RTIL had been previously demonstrated). The high-purity dissolution of the U3O8 permits the use of RTIL solutions for deposition of U on metal foils in layers without introducing contamination. In FY10 and early FY11 a natural U surrogate for the uDU was used to investigate this and other techniques. In this research project UNLV will deposit directly from RTIL to produce uDU and Th foils devoid of possible contaminants. After these layers have been deposited, they will be examined for purity and uniformity. UNLV will complete the development and demonstration of the RTIL technology/ methodology to prepare uDU and Th samples for use in constructing fast-neutron detectors. Although this material was purchased for use in research using fast-fission chamber detectors for active inspection techniques for MPACT, it could also contribute to R&D for other applications, such as cross section measurements or neutron spectroscopy for national security

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗