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At least 1,171 records · Page 65

Modeling and Analysis of Space Based Transceivers

This paper presents the tool chain, methodology, and initial results of a study to provide a thorough, objective, and quantitative analysis of the design alternatives for space Software Defined Radio (SDR) transceivers. The approach taken was to develop a set of models and tools for describing communications requirements, the algorithm resource requirements, the available hardware, and the alternative software architectures, and generate analysis data necessary to compare alternative designs. The Space Transceiver Analysis Tool (STAT) was developed to help users identify and select representative designs, calculate the analysis data, and perform a comparative analysis of the representative designs. The tool allows the design space to be searched quickly while permitting incremental refinement in regions of higher payoff.

Moore, Michael S.↗

Accelerating Discovery to Deployment: Argonne's Materials Engineering Research Facility (MERF) and Its Role in Scaling Materials Technologies for Water and Resource Solutions

The U.S. Department of Energy (DOE) national laboratories represent a unique class of government‐owned, contractor‐operated research institutions dedicated to conducting research and development (R&D) related activities that address national priorities, supporting and advancing the DOE mission. They play a vital role in sustaining U.S. innovation capacity, stewarding the nation's technical base, and nurturing science and technologies. In this perspective, we highlight the processing science and scaleup capabilities of the Materials Engineering Research Facility (MERF) at DOE's Argonne National Laboratory to demonstrate how DOE National Laboratories bridge fundamental science and applied technology development to accelerate deployment. Case studies are presented on selective membranes for critical mineral recovery, sensors for per‐ and polyfluoroalkyl substances (PFAS) detection, surface functionalization via atomic layer deposition (ALD) and sequential infiltration synthesis (SIS), and lithium recovery from battery recycling waste streams using a novel electrodialysis process. These examples underscore MERF's role in translating innovative technologies into practical solutions for renewable water and critical resource recovery, which also leverage Argonne's analytical and computational capabilities. This perspective also outlines mechanisms for collaborating with the DOE national laboratories to strengthen partnerships across government, the national laboratories, academia, and industry.

36 MATERIALS SCIENCE↗

Assessing the Predictive Capability of the LIFEIV Nuclear Fuel Performance Code Using Sequential Calibration

This report considers the problem of calibrating a numerical model to data from an experimental campaign (or series of experimental tests). The issue is that when an experimental campaign is proposed, only the input parameters associated with each experiment are known (i.e. outputs are not known because the experiments have yet to be conducted). Faced with such a situation, it would be beneficial from the standpoint of resource management to carefully consider the sequence in which the experiments are conducted. In this way, the resources available for experimental tests may be allocated in a way that best 'informs' the calibration of the numerical model. To address this concern, the authors propose decomposing the input design space of the experimental campaign into its principal components. Subsequently, the utility (to be explained) of each experimental test to the principal components of the input design space is used to formulate the sequence in which the experimental tests will be used for model calibration purposes. The results reported herein build on those presented and discussed in [1,2] wherein Verification & Validation and Uncertainty Quantification (VU) capabilities were applied to the nuclear fuel performance code LIFEIV. In addition to the raw results from the sequential calibration studies derived from the above, a description of the data within the context of the Predictive Maturity Index (PMI) will also be provided. The PMI [3,4] is a metric initiated and developed at Los Alamos National Laboratory to quantitatively describe the ability of a numerical model to make predictions in the absence of experimental data, where it is noted that 'predictions in the absence of experimental data' is not synonymous with extrapolation. This simply reflects the fact that resources do not exist such that each and every execution of the numerical model can be compared against experimental data. If such resources existed, the justification for numerical models would be reduced considerably. The authors note that the PMI is primarily intended to provide a high-level, quantitative description of year-to-year (or version-to-version) improvements in numerical models, where these descriptions can be used as a means of justifying funding requests to support further model development research. It is in this context that the present report should be considered: the availability of data from experimental tests should be viewed as a time-dependent variable, where experiments are added to the calibration suite as resources become available. For the present report, the experimental data is of course already available (permitting demonstration of the proposed methodology). Furthermore, the authors are not proposing this methodology as the answer to the question of how to allocate resources for experimental tests, and readers are directed to [5] and the references contained in Section 1 of [5] for additional information on the subject. However, the strength of this methodology is that it offers a means by which to select the sequence of experiments in a pre-arranged experimental campaign (a situation for which the methods discussed in [5] are less appropriate). The report is organized as follows. Section 2 describes the methodology employed to formulate the sequences of experiments for the calibrations performed for this study. Section 3 then presents the results associated with two sequences; supplementary results are provided in the Appendix. The report then concludes in Section 4 with a brief summary.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ecological connectivity and in-kind mitigation in a regulatory decision framework: A case study with an amphibian habitat specialist

Ecological connectivity is critical to the survival and long-term viability of populations but is often overlooked in regulatory frameworks. We integrated landscape-level processes into a mitigation strategy for impacts to aquatic resources on the U.S. Department of Energy (DOE) Oak Ridge Reservation (ORR) in eastern Tennessee. Wetlands on the ORR, which contain significant breeding populations of the imperiled four-toed salamander (Hemidactylium scutatum) and tubercled rein orchid (Platanthera flava var. herbiola), will be impacted by construction of an environmental waste disposal facility under the Comprehensive Environmental Response, Compensation, and Liability Act of 1980 (CERCLA). Here, we used a modified Kepner-Tregoe decision analysis to select general mitigation options that balanced regulatory requirements and interest group perspectives. We emphasized habitat connectivity through models that prioritized an area's importance to natural area connectivity (centrality) and maintenance of population structure for an affected habitat specialist (four-toed salamanders). We also emphasized in-kind mitigation through the preservation and enhancement of ecologically similar resources and the translocation and establishment of a new subpopulation of four-toed salamanders elsewhere on the ORR. We ultimately released over 500 juvenile salamanders that originated from the impacted site into the chosen mitigation wetlands. By doing so under the constraints of a time-sensitive CERCLA remediation effort and exceeding its substantive requirements, this work underscores feasibility. Ecological connectivity and the conservation of species that are not afforded explicit regulatory processes can be effectively and efficiently integrated into environmental decision-making and land use planning.

54 ENVIRONMENTAL SCIENCES↗

Understanding of catalytic transformation of shale gas and development of catalysts with high activity and selectivity through experimental exploration and theoretical simulation

Catalysis on transition metal oxides is equivalently important in contrast to that on metal catalysts in chemical and energy transformations. Understanding of catalytic reactions on early transition metal oxide catalysts is fundamentally intriguing and of great practical interest in efficient production of chemical and fuel feedstocks. Fundamental understanding of catalysis on transition metal oxide-based catalysts has been lagged behind catalysis on metals due to the complexity of chemistry and structure of surface and bulk of oxide catalysts and their structural flexibility in reactive environment at high temperatures. The funded DOE project explored surface chemistry of a few reducible oxides including CeO 2 - based, Co 3 O 4 -based, and CoO-based which are significant for heterogeneous catalysis. Through in-situ studies using ambient pressure X-ray photoelectron spectroscopy and high pressure scanning tunneling microscopy, we revealed phase transformation, the accompanying changes of surface chemistry and structure, and uncovered their correlations with catalytic activity and selectivity in catalytic reactions including reduction of NO with CO, water-gas shift, and chemical transformations of methane to methanol and acetic acid under mild conditions. Driven by the following two facts, we propose to pursue fundamental understanding of oxidative dehydrogenation of ethane and oxidative coupling of methane on oxide catalysts through both in-situ studies of catalyst surfaces during catalysis and computational studies in the renewal proposal. One driving force is the significance of oxidative dehydrogenation of ethane and oxidative coupling of methane for utilization of earth-abundant, relatively inexpensive energy resource and the urgent needs of efficient chemical processes to generate ethylene from shale gas. The other is that exploration of surface chemistry of oxide catalysts during catalysis has remained challenging though it is critical in deeply understanding catalysis on oxide catalysts and developing oxide-based catalysts toward high selectivity and activity. Therefore, the overall objective of the renewal proposal is to mechanistically understand the oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level through building correlations between surface chemistry of catalysts during catalysis and the corresponding catalytic performances, and thus design catalysts with high selectivity and activity for production of ethylene with the guidance achieved from these fundamental studies. Experiments were designed to explore the influences of electronic states of cations supported on substrate oxides, cations of surface of the substrate oxides, and surface lattice oxygen atoms of the substrate oxides on their catalytic selectivity and activity. Surface chemistry, including oxidation state of the surface monomers and cations of substrate oxides and density of oxygen vacancies during catalysis, will be tracked with AP-XPS during catalysis. A correlation between surface chemistry of these catalysts at different temperatures and their corresponding catalytic selectivity for production of ethylene and activity will be built. Computational studies will calculate adsorption energies of reactant molecules and their dissociated species and intermediates on the catalyst surface, search transition states, and simulate reaction pathway close to experimental studies. By integrating the computational studies into these correlations to be built from experimental studies, fundamental understanding of the catalytic mechanisms of oxidative dehydrogenation of ethane and oxidative coupling of methane at a molecular level will be achieved. With these insights, new catalysts with high selectivity and activity will be developed.

36 MATERIALS SCIENCE↗

Electricity Costs and Carbon Implications for CO 2 -to-Fuels in Selected Locations in 2030

With the growing interest in converting carbon dioxide (CO 2 ) to fuels and products to reduce overall greenhouse gas emissions and extend carbon from biogenic and other sources, the development of carbon capture and utilization (CO2U) technologies and industry is crucial. The Markets, Resources, and Environmental and Energy Justice of CO 2 -to-Fuels Technologies (short title: MarkeRs & EEJ) project supports this goal by assessing the resource and market potential and infrastructure requirements for mid-term (-2030) and long-term (-2050) deployment of CO2U technologies. The overall project analyzes CO2U economic and resource requirements as well as sustainability and environmental and energy justice (EEJ) metrics. This report focuses on short-term (-2030) aspects of the project. It identifies three CO2U locations in the Midwestern United States and quantifies the costs for potential electricity resources and marginal emissions for each site in the near term (e.g., 2030). We focus on four electricity purchase options, including retail rate, physical power purchase agreement (PPA), financial PPA, and real-time pricing (RTP), for each of the three sites and consider potential policies such as production tax credits (PTCs). We also assess time-dependent hourly marginal electricity costs and the marginal emission rates using modeled scenarios from Cambium (Gagnon et al. 2021).The results of the analysis are expected to inform other projects within the U.S. Department of Energy's CO 2 -to-Fuels Consortium, especially the Economics and Sustainability of CO 2 Utilization Technologies with Techno-Economic Analysis and Life Cycle Analysis (TEA/LCA) project, led by Michael Wang of Argonne National Laboratory and Ling Tao of the National Renewable Energy Laboratory. The project results are also expected to inform the investment and technology communities and policymakers at the U.S. Department of Energy, state, and regional levels and guide investment by government and industry in research and development portfolios.

09 BIOMASS FUELS↗

Multi-discipline resource inventory of soils, vegetation and geology

The author has identified the following significant results. Computer classification of natural vegetation, in the vicinity of Big Summit Prairie, Crook County, Oregon was carried out using MSS digital data. Impure training sets, representing eleven vegetation types plus water, were selected from within the area to be classified. Close correlations were visually observed between vegetation types mapped from the large scale photographs and the computer classification of the ERTS data (Frame 1021-18151, 13 August 1972).

Simonson, G. H.↗

Exploring Renewable Energy Opportunities in Select Southeast Asian Countries: A Geospatial Analysis of the Levelized Cost of Energy of Utility-Scale Wind and Solar Photovoltaics

The costs of renewable energy-based electricity generation have fallen precipitously in recent years to levels that are increasingly competitive with traditional generation such as fossil fuel-based generation. As these costs become increasingly competitive, private developers, policymakers, and energy system planners are searching for opportunities to harness high-quality renewable energy resources. Developing economies are setting ambitious targets and exploring how cost-effective, grid-connected renewable energy options can help power economic growth and meet growing electricity demands. This includes the member states of the Association of Southeast Asian Nations (ASEAN) that are determined to reach a target of 23% of renewable energy in the region's total primary energy supply by 2025. A critical gap to identifying opportunities and scaling up renewable energy is the lack of quality data and analyses to support decisions on the investment and deployment of renewables - including wind and solar photovoltaics (PV). This work supports decision making by providing high-quality data and spatial analysis of the cost of utility-scale wind and solar PV generation in select countries of Southeast Asia - specifically, the ASEAN member states. Generation costs are expressed as the levelized cost of energy (LCOE) - a commonly used metric that represents the net present value of the unit cost of electricity during the lifetime of a particular electricity generation technology. This is the first spatial estimate of LCOE for these technologies within the ASEAN member states - providing insights into the roles that renewable energy resource quality and other factors may play in generation costs.

14 SOLAR ENERGY↗

Adaptive gene loss in the common bean pan-genome during range expansion and domestication

The common bean ( Phaseolus vulgaris L.) is a crucial legume crop and an ideal evolutionary model to study adaptive diversity in wild and domesticated populations. Here, we present a common bean pan-genome based on five high-quality genomes and whole-genome reads representing 339 genotypes. It reveals ~234 Mb of additional sequences containing 6,905 protein-coding genes missing from the reference, constituting 49% of all presence/absence variants (PAVs). More non-synonymous mutations are found in PAVs than core genes, probably reflecting the lower effective population size of PAVs and fitness advantages due to the purging effect of gene loss. Our results suggest pan-genome shrinkage occurred during wild range expansion. Selection signatures provide evidence that partial or complete gene loss was a key adaptive genetic change in common bean populations with major implications for plant adaptation. The pan-genome is a valuable resource for food legume research and breeding for climate change mitigation and sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

Upcycling of polyethylene to gasoline through a self-supplied hydrogen strategy in a layered self-pillared zeolite

Conversion of plastic wastes to valuable carbon resources without using noble metal catalysts or external hydrogen remains a challenging task. Here we report a layered self-pillared zeolite that enables the conversion of polyethylene to gasoline with a remarkable selectivity of 99% and yields of >80% in 4 h at 240 °C. The liquid product is primarily composed of branched alkanes (selectivity of 72%), affording a high research octane number of 88.0 that is comparable to commercial gasoline (86.6). In situ inelastic neutron scattering, small-angle neutron scattering, solid-state nuclear magnetic resonance, X-ray absorption spectroscopy and isotope-labelling experiments reveal that the activation of polyethylene is promoted by the open framework tri-coordinated Al sites of the zeolite, followed by β-scission and isomerization on Brönsted acids sites, accompanied by hydride transfer over open framework tri-coordinated Al sites through a self-supplied hydrogen pathway to yield selectivity to branched alkanes. This study shows the potential of layered zeolite materials in enabling the upcycling of plastic wastes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Museomics Dissects the Genetic Basis for Adaptive Seasonal Coloration in the Least Weasel

Abstract Dissecting the link between genetic variation and adaptive phenotypes provides outstanding opportunities to understand fundamental evolutionary processes. Here, we use a museomics approach to investigate the genetic basis and evolution of winter coat coloration morphs in least weasels (Mustela nivalis), a repeated adaptation for camouflage in mammals with seasonal pelage color moults across regions with varying winter snow. Whole-genome sequence data were obtained from biological collections and mapped onto a newly assembled reference genome for the species. Sampling represented two replicate transition zones between nivalis and vulgaris coloration morphs in Europe, which typically develop white or brown winter coats, respectively. Population analyses showed that the morph distribution across transition zones is not a by-product of historical structure. Association scans linked a 200-kb genomic region to coloration morph, which was validated by genotyping museum specimens from intermorph experimental crosses. Genotyping the wild populations narrowed down the association to pigmentation gene MC1R and pinpointed a candidate amino acid change cosegregating with coloration morph. This polymorphism replaces an ancestral leucine residue by lysine at the start of the first extracellular loop of the protein in the vulgaris morph. A selective sweep signature overlapped the association region in vulgaris, suggesting that past adaptation favored winter-brown morphs and can anchor future adaptive responses to decreasing winter snow. Using biological collections as valuable resources to study natural adaptations, our study showed a new evolutionary route generating winter color variation in mammals and that seasonal camouflage can be modulated by changes at single key genes.

Miranda, Inês↗

Industrial biomanufacturing: The future of chemical production

The current model for industrial chemical manufacturing employs large-scale megafacilities that benefit from economies of unit scale. However, this strategy faces environmental, geographical, political, and economic challenges associated with energy and manufacturing demands. We review how exploiting biological processes for manufacturing (i.e., industrial biomanufacturing) addresses these concerns while also supporting and benefiting from economies of unit number. Key to this approach is the inherent small scale and capital efficiency of bioprocesses and the ability of engineered biocatalysts to produce designer products at high carbon and energy efficiency with adjustable output, at high selectivity, and under mild process conditions. The biological conversion of single-carbon compounds represents a test bed to establish this paradigm, enabling rapid, mobile, and widespread deployment, access to remote and distributed resources, and adaptation to new and changing markets.

Science & Technology - Other Topics↗

2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks

Consumption of renewable energy in the United States is the highest in history, contributing to energy security, greenhouse gas reductions, and other social, economic, and environmental benefits. The largest single source of renewable energy is biomass, representing 3.9 quadrillion of 9.6 quadrillion British thermal units (Btu) in 2015 (EIA 2016). Biomass includes agricultural and forestry resources, municipal solid waste (MSW), and algae. For more than a decade, the U.S. Department of Energy (DOE) has been quantifying the potential of U.S. biomass resources, under biophysical and economic constraints, for production of renewable energy and bioproducts. The 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy (BT16) evaluates the most recent estimates of potential biomass that could be available for new industrial uses in the future. BT16 consists of two volumes: Volume 1 (this volume) focuses on resource analysis—projecting biomass potentially available at specified prices. Volume 2 evaluates changes in environmental sustainability indicators— water quality and quantity, greenhouse gas emissions, air quality, soil organic carbon, and biodiversity—associated with select production scenarios in volume 1. The following is a summary of BT16 , volume 1.

09 BIOMASS FUELS↗

Computed Tomography Scanning and Petrophysical Measurements of the Lively Grove #1 Well Core

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core from the Lively Grove #1 Well (API 121892494700), drilled near Marissa, Washington County, Illinois. Core from the well was obtained as part of the Illinois Storage Corridor’s Carbon Storage Assurance Facility Enterprise (CarbonSAFE) project (DE FE0031892). The primary impetus of this work was to capture a detailed digital representation of the core from the Lively Grove #1 Well. The collaboration between the U.S. Department of Energy’s (DOE) NETL and the Illinois State Geological Survey (ISGS) enables other research entities to access information about this potential carbon storage location and Cambro-Ordovician Storage Complex formations of the Illinois Basin. The resultant datasets are presented in this report and can be accessed from NETL’s Energy Data eXchange (EDX) online system. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. Fractures, discontinuities, and millimeter-scale features were readily detectable with the medical CT scanner-acquired images. Imaging with the NETL medical CT scanner was performed on entire cores. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), gamma density, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for potential future analysis. Higher-resolution industrial and micro-CT images were acquired from selected zones along the depth of the core to visualize the structure in higher detail. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; with the resulting macro- and micro-descriptions relevant to many subsurface energy related examinations traditionally performed at NETL.

54 ENVIRONMENTAL SCIENCES↗

HELIOCOMM: Wireless Controls State-of-the-Art Report

This report introduces the concept of wireless controls in heliostat-based concentrating solar thermal power (CSP) systems. Specifically, the need for wireless communications to be implemented within the heliostat-based CSP systems is identified versus the existing approaches that follow wireline connections which suffer from high installation, operation, and maintenance cost. Furthermore, this report analyzes the most recent advances in the field of developing wireless controls in heliostat-based CSP systems, which are highlighted to be in their infancy given the primitive wireless networking solutions that they currently utilize and test. The main contribution of this report is the introduction of a novel HELIOCOMM system that supports the wireless controls in heliostat-based CSP systems by exploiting the next generation networking technology of integrated access and backhaul. Furthermore, the proposed HELIOCOMM system performs an artificial intelligent clustering approach of the heliostats and clusterhead selection and develops an entropy-based routing model to enable the heliostats to communicate with the central station by considering their energy availability and network traffic. Also, towards efficiently exploiting the limited resources in the developed wireless communication system, a resource allocation module is introduced that performs the maximization of the energy efficiency of each heliostat by minimizing its corresponding experienced end-to-end latency to communicate with the central station, while performing an intelligent bandwidth splitting in the access and backhaul wireless links. The overall architecture is presented, and its individual building components are discussed in detail.

14 SOLAR ENERGY↗

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). With its flexible and modular design, hls4ml supports a large number of deep learning frameworks and can target HLS compilers from several vendors, including Vitis HLS, Intel oneAPI and Catapult HLS. Together with a wider eco-system for software-hardware co-design, hls4ml has enabled the acceleration of ML inference in a wide range of commercial and scientific applications where low latency, resource usage, and power consumption are critical. In this paper, we describe the structure and functionality of the hls4ml platform. The overarching design considerations for the generated HLS code are discussed, together with selected performance results.

FOS: Computer and information sciences↗

Regional applicability and potential of salt-gradient solar ponds in the United States. Volume 2: Detailed report

A comprehensive assessment of the regional applicability and potential of salt-gradient solar ponds in the United States is provided. The assessment is focused on the general characteristics of twelve defined geographic regions. Natural resources essential to solar ponds are surveyed. Meteorological and hydrogeological conditions affecting pond performance are examined. Potentially favorable pond sites are identified. Regional thermal and electrical energy output from solar ponds is calculated. Selected pond design cases are studied. Five major potential market sectors are evaluated in terms of technical and energy-consumption characteristics, and solar-pond applicability and potential. Relevant pond system data and financial factors are analyzed. Solar-pond energy costs are compared with conventional energy costs. The assessment concludes that, excepting Alaska, ponds are applicable in all regions for at least two market sectors. Total solar pond energy supply potential in the five market sectors examined is estimated to be 8.94 quads/yr by the year 2000, approximately 7.2% of the projected total national energy demand.

Lin, E. I. H.↗

Computational modeling for the study of multispectral sensor systems and concepts

A computational model of the deterministic and stochastic processes involved in remote sensing is being developed as a tool for studying multispectral sensor systems and concepts. The goal is to improve the efficiency of sensor systems for routine worldwide monitoring of earth resources and the environment. Preliminary computational results are presented for simple models of the natural variability of atmospheric radiative transfer and surface reflectance. These results illustrate the dependence of classification accuracy on the selection of sensor spectral channels and data processing algorithms.

Huck, F. O.↗