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At least 487 records · Page 27

Stack Test Summary for TA-59-0001

The Radioactive Air Emissions Management (RAEM) team performed stack flow characterization tests at Technical Area (TA) 59 Building 0001 Exhaust Stack (ES) 8. These tests were completed in accordance with Title 40 of the Code of Federal Regulations (CFR), Part 61, Subpart H and the American National Standards Institute (ANSI) N13.1-1999 required by the Clean Air Act. Subpart H of the regulation is the National Emission Standards for Hazardous Air Pollutants (NESHAP) for radionuclides, which compliance with is maintained by the REAM team.

54 ENVIRONMENTAL SCIENCES↗

Accelerating Optimal Integration of Energy Efficiency Strategies with Industrialized Modular Construction: Preprint

The National Renewable Energy Laboratory's (NREL's) Industrialized Construction Innovation team first introduced the Industrialized Construction Assessment Framework to achieve affordable, net-zero energy (NZE) modular multifamily buildings in the 2020 ACEEE paper "Integrating Energy Efficiency Strategies with Industrialized Construction for our Clean Energy Future." Since then, NREL has continued to drive the ambitious plan to accelerate optimal integration of energy efficiency strategies during industrialized construction with little or no additional cost, labor, and production time. This follow-on paper introduces the Energy in Modular (EMOD) buildings method and presents NREL's research efforts over the last two years in collaboration with industry, including affordable housing partners. NREL has developed an idealized NZE modular multifamily building design that incorporates five energy efficiency strategies well suited for industrialized construction in factories: (1) envelope thermal control, (2) envelope infiltration control, (3) mechanical, electrical, and plumbing systems, (4) smart controls, and (5) solar plus storage. This paper highlights results from leveraging design for manufacturing and assembly principles, testing, and validation pilots with factory partners; demonstrating pod prototypes in test stand at NREL; and performing simulations. Overall, these research efforts address barriers to whole-building system integration, such as poor installation quality of thermal and air barriers; lack of unitized systems for space conditioning, energy recovery and ventilation, and water heating; problematic on-site installation, commissioning, and configuration of controls; and lack of cost-effective integration for grid-friendly design and emerging technologies. Conclusively, the paper delineates next steps for future work with NREL's partners toward developing a transformational pathway for our clean energy future.

affordable housing↗

Deep Learning for Subsurface Flow: A Comparative Study of U‐Net, Fourier Neural Operators, and Transformers in Underground Hydrogen Storage

Subsurface flow research is essential for the sustainable management of natural resources and the environment. Deep learning (DL) has significantly advanced this field by developing efficient and accurate surrogate models to replace computationally expensive physics‐based simulations. These surrogate models are commonly used to predict the spatiotemporal evolution of state variables, such as gas saturation and reservoir pressure, in heterogeneous geological formations. Despite the various DL models applied to this task, there is a lack of studies systematically comparing their performance. This absence of comparative analysis leads to somewhat arbitrary DL model selection in subsurface flow research, resulting in suboptimal performance and potentially inaccurate predictions. To bridge this gap, we conduct a systematic comparison study of three popular DL architectures—U‐Net, Fourier Neural Operators (FNO), and Segmentation Transformer (SETR)—in surrogate modeling of underground hydrogen storage (UHS). We focus on UHS due to its promise of enhancing clean energy resilience and its cyclic operational conditions that represent common scenarios in various subsurface applications. We evaluate the models based on accuracy, training cost, and inference speed. The comparison shows that U‐Net achieves the highest accuracy, followed by SETR and FNO. Despite its lower accuracy, FNO has the highest inference speed. SETR offers competitive accuracy with the least training memory usage, demonstrating the potential of transformers in learning subsurface flow. Our results provide guidance for selecting DL models for surrogate modeling in a wide range of subsurface flow problems.

42 ENGINEERING↗

Causes of fuel–ablator mix inferred from modeling of monochromatic time-gated radiography of OMEGA cryogenic implosions

Here, we present evidence, in the context of OMEGA cryogenic target implosions, that laser imprint, known to be capable of degrading laser-direct-drive target performance, plays a major role in generating fuel–ablator mix. OMEGA cryogenic target implosions show a performance boundary correlated with acceleration-phase shell stability; for sufficiently low adiabats (where the adiabat is the ratio of the pressure to the Fermi pressure) and high in-flight aspect ratios (IFAR's), the neutron-weighted shell areal density and neutron yield relative to the clean simulated values sharply decline. Direct evidence of Rayleigh–Taylor fuel–ablator mixing was previously obtained using a Si Heα backlighter driven by an ~20-ps short pulse generated by OMEGA EP. The shadow cast by the shell shortly prior to stagnation, as diagnosed using backlit radiographs, shows a softening near the limb, which is evidence of an ablator–fuel mix region for a low-adiabat implosion (α ~ 1.9, IFAR = 14) but not for a moderate adiabat implosion (α ~ 2.5, IFAR = 10). We find good agreement between experimental and synthetic radiographs in simulations that model laser imprint and account for uncertainty in the initial ablator thickness. Furthermore, we further explore the role of other mechanisms such as classical instability growth at the fuel–ablator interface, species concentration diffusion, and long-wavelength drive and target asymmetries.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Model Year 2019 Fuel Economy Guide: EPA Fuel Economy Estimates

The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Model Year 2020 Fuel Economy Guide: EPA Fuel Economy Estimates

The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles.

33 ADVANCED PROPULSION SYSTEMS↗

Renewable Energy for Industrial Environmental Management

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has grown exponentially as they become cost competitive. Simultaneously, industrial and manufacturing processes have been increasingly seeking ways to reduce emissions and operational costs in highly competitive sectors. With these combined drivers of lower cost and reduced environmental impact, renewable energy may become a viable energy provider for industrial processes such as oil and gas, mining, chemical refining, food production, and manufacturing. Renewable energy technologies may also partner with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization, to create cleaner and circular industrial systems for reduced resource use. The Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of the National Renewable Energy Laboratory (NREL) and five universities and others, has been studying to potential for application of clean energy technologies to the heterogenous energy demands in industry. Dr. Jill Engel-Cox will present an overview of NREL and JISEA, the status and potential future of renewable energy technologies, and collaborations with the oil and gas industry and other industrial sectors to improve their environmental performance and reduce operational costs.

ENERGY PLANNING, POLICY, AND ECONOMY↗

The PHASE Project: New Research and Tools to Inform Pollinator Habitat on Utility-Scale Solar

The solar industry is responding to demand for building a clean energy future. At the same time, pollinator declines and habitat losses are resulting in listing consideration for once-common species like monarch butterflies, plus petitions to list bees and other species. How can projects responsibly co-locate pollinator plantings at solar facilities? What ecological and performance benefits can be realized from pollinator plantings? How do developers and owners weigh the costs and challenges of maintaining pollinator plantings and determine the effects it has on power generation, community acceptance, and operations? The Pollinator Habitat Aligned with Solar Energy (PHASE) project is a four-year research project that aims to answer these questions and better support the solar industry in successfully implementing pollinator plantings. This project is funded by the U.S. Department of Energy's Solar Energy Technologies Office. In collaboration with an advisory group composed of industry and technical professionals, the PHASE team developed methodologies to evaluate the impacts of plantings on both biodiversity and the facility operations, including the diversity of plant and insect communities, pollinator services being provided by the site, and the effects of pollinator vegetation on panel temperature and efficiency. The PHASE team also used data to develop tools designed to better support solar industry decision-making on pollinator vegetation including a Pollinator Planting Implementation Manual, a Cost Comparison Tool, a Seed Selection Tool, and Habitat Assessment Module Guidance. Final versions of the four tools will be released this year.

agrivoltaic↗

Investigation of the silicon coated film characteristics on tungsten surface in EAST fusion device

Siliconization using 10 % SiD 4 + 90 % He assisted by ion cyclotron range of frequency discharge (ICRF) or glow discharge (GD) was performed in EAST with full tungsten (W) diverters. It was found that the coated Si film on W sample at a higher baking temperature (160 °C) was smoother than that at a lower baking temperature (60 °C). This was mainly because physically adsorbed gaseous impurities were released at a higher baker temperature. This process improved the adhesion between the film and the surface of W. An increase in the ICRF working power from 20 kW to 40 kW further increased the Si content and the film thickness by 1.5 times. The cleaning efficiency of ICRF on the surface of the W sample before siliconization was higher at 40 kW than that at 20 kW, which facilitated the removal of oxides and other compounds from the surface of W. The ratio of silicon/oxygen (Si/O) and the thickness improved considerably due to greater ionization and deposition of SiD 4 . Additionally, siliconization via GD was more uniform and 1.5 nm thicker than that via ICRF, which was because of the greater working gas pressure, coating duration, and homogeneity in GD. These results might be used as a reference for evaluating the effect of siliconization on plasma performance and its application in fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fouling characterization and treatment of water reuse concentrate with membrane distillation: Do organics really matter

Membrane distillation (MD) for the treatment of concentrated brines has been limited in part by membrane fouling, resulting in subsequent flux decline and membrane wetting. This study provides new insight into the identification of fouling and scaling mechanisms and pretreatment strategies for mitigating flux decline with MD treatment of water reuse reverse osmosis concentrate (ROC). Bench-scale direct contact MD experiments were performed with untreated and pretreated ROC. Biological activated carbon (BAC), chemical water softening, or fluidized bed crystallization reactor coupled with ion exchange (FBCR-IX) were selected as pretreatment strategies to isolate the effects of organic fouling and calcium scaling. Organic and inorganic compounds were analyzed by high-performance liquid chromatography (HPLC) and inductively coupled plasma mass spectrometry (ICP-MS). Calcium ions were found to be the major contributor to flux decline despite the high organic content in the ROC. Minimal organic fouling is likely because the organic matter in the ROC is hydrophilic, limiting hydrophobic-hydrophobic interactions between the organics and the membrane. Furthermore, the water flux declined by 63 % after removing organic compounds by BAC pretreatment, with 60 % of the calcium mass precipitating from the solution. Whereas, the water flux remained constant after removing multivalent ions with fluidized bed crystallization. Cleaning the membrane by acid washing and temperature reversal recovered 73 % and 12 % of the water flux, respectively. The analyses outlined in this study can assist in selecting appropriate fouling and scaling mitigation strategies for water reuse ROC and a wide range of feed solutions used in MD applications.

42 ENGINEERING↗

Incorporation of Ion Transport Chains into Multivariate MOF for Improved Water Oxidation

The climate crisis demands clean energy technologies to cut CO 2 emissions from fossil fuels. Hydrogen fuel cells and solar-driven CO 2 reduction are promising, but both rely on efficient water oxidation. Polypyridyl ruthenium complexes are active catalysts for water oxidation; however, they exhibit poor stability and recyclability. Our group improved performance by embedding these complexes into metal−organic frameworks (MOFs). As water oxidation is pH-dependent, proton management further enhances reactivity. To address the issue, we introduced proton transfer pathways into the MOF structure. Specifically, we incorporated −SO 3 H groups onto the biphenyl linkers of UiO-67 loaded with [Ru(tpy)(dcbpy)OH 2 ]PF 6 catalyst (where tpy = 2,2′:6′,2″-terpyridine; dcbpy = 5,5-dicarboxy-2,2′- bipyridine). The sulfonated MOF exhibited a 2.5-fold increase in oxygen evolution compared to the nonsulfonated analogue. After 1 h of electrolysis, the sulfonated MOF exhibited a turnover number of 25 for oxygen evolution reaction compared to 10 for the native MOF, demonstrating the benefits of built-in proton management.

Catalysts↗

Low-Temperature Electrochemical Wastewater Oxidation

Here, we demonstrated the Clean Sustainable Electrochemical Treatment (CleanSET) process that enables the distributed clean-up of biomass-derived wastewater while simultaneously generating hydrogen (H 2 ). The specific goal of this project is to 1) demonstrate the selective removal of chemical oxygen demand (COD), total carbon (TC), and total nitrogen (TN) of different wastewaters, 2) optimize the electrode composition to improve electrochemical performance, and 3) perform a high-level techno-economic analysis to obtain levelized costs of disposal (LCOD) .

08 HYDROGEN↗

Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study

Background: Currently, the identification of infectious disease re-emergence is performed without describing specific quantitative criteria that can be used to identify re-emergence events consistently. This practice may lead to ineffective mitigation. In addition, identification of factors contributing to local disease re-emergence and assessment of global disease re-emergence require access to data about disease incidence and a large number of factors at the local level for the entire world. This paper presents Re-emerging Disease Alert (RED Alert), a web-based tool designed to help public health officials detect and understand infectious disease re-emergence. Objective: Our objective is to bring together a variety of disease-related data and analytics needed to help public health analysts answer the following 3 primary questions for detecting and understanding disease re-emergence: Is there a potential disease re-emergence at the local (country) level? What are the potential contributing factors for this re-emergence? Is there a potential for global re-emergence? Methods: We collected and cleaned disease-related data (eg, case counts, vaccination rates, and indicators related to disease transmission) from several data sources including the World Health Organization (WHO), Pan American Health Organization (PAHO), World Bank, and Gideon. We combined these data with machine learning and visual analytics into a tool called RED Alert to detect re-emergence for the following 4 diseases: measles, cholera, dengue, and yellow fever. We evaluated the performance of the machine learning models for re-emergence detection and reviewed the output of the tool through a number of case studies. Results: Our supervised learning models were able to identify 82%-90% of the local re-emergence events, although with 18%-31% (except 46% for dengue) false positives. This is consistent with our goal of identifying all possible re-emergences while allowing some false positives. The review of the web-based tool through case studies showed that local re-emergence detection was possible and that the tool provided actionable information about potential factors contributing to the local disease re-emergence and trends in global disease re-emergence. Conclusions: To the best of our knowledge, this is the first tool that focuses specifically on disease re-emergence and addresses the important challenges mentioned above.

60 APPLIED LIFE SCIENCES↗

Cesium intercalation of graphene: A 2D protective layer on alkali antimonide photocathode

Alkali antimonide photocathodes have wide applications in free-electron lasers and electron cooling. The short lifetime of alkali antimonide photocathodes necessitates frequent replacement of the photocathodes during a beam operation. Furthermore, exposure to mediocre vacuum causes loss of photocathode quantum efficiency due to the chemical reaction with residual gas molecules. Theoretical analyses have shown that covering an alkali antimonide photocathode with a monolayer graphene or hexagonal boron nitride protects it in a coarse vacuum environment due to the inhibition of chemical reactions with residual gas molecules. Alkali antimonide photocathodes require an ultra-high vacuum environment, and depositing a monolayer 2D material on it poses a serious challenge. In the present work, we have incorporated a novel method known as intercalation, in which alkali atoms pass through the defects of a graphene thin film to create a photocathode material underneath. Initially, Sb was deposited on a Si substrate, and a monolayer graphene was transferred on top of the Sb film. Heat cleaning around 550–600 °C effectively removed the Sb oxides, leaving metallic Sb underneath the graphene layer. Depositing Cs on top of a monolayer graphene enabled the intercalation process. Atomic force microscopy, Raman spectroscopy, x-ray photoelectron spectroscopy, low energy electron microscopy, and x-ray diffraction measurements were performed to evaluate photocathode formation underneath the monolayer graphene. Our analysis shows that Cs penetrated the graphene and reacted with Sb and formed Cs 3 Sb.

2D materials↗

coloring v.1.0

SAND2024-02435O The software coloring allows applications written in the C++ language to generate publication-quality 2D plots. Its functionality is similar to Microsoft Excel's chart functionality or the Python language's matplotlib package. The value of coloring is that it is written purely in C++ and thus can be compiled on systems where Python is not available and linked into high performance computing software. For drawing shapes onto an image, coloring uses the mathematical definition of quadratic Bezier splines and uses Newton's method to search for the closest point on a spline to a given query point. This is then used to do accurate sub-pixel sampling to get clean, non-pixelated images. For working with the actual plot data, coloring has basic statistical methods such as finding maxima and minima as well as axis scaling such as logarithms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Ibanez, Daniel↗

Tandem particle-slurry batch reactors for solar water splitting (Final Scientific/Technical Report)

Economically, particle slurry reactors are projected to be one of the most promising technologies for solar photoelectrochemical hydrogen production, according to a 2009 techno-economic analysis commissioned by the US DOE and performed by Directed Technologies, Inc. The Fuel Cell Technologies Office’s Multi-Year Research, Development and Demonstration (MYRD&D) goals and targets are to reduce the cost of H 2 produced from renewable sources at the plant gate (i.e. not including delivery, dispensing, or storage) to < $2.00/gge, equivalent to ~$2.00/kg H 2 . Research results from our techno-economic modeling research suggest that this target could be met using particle slurry reactors assuming STH efficiencies in the range of 5 – 10%, materials lifetimes of < 1 year, and nanoparticles that cost up to 20 times more than projected costs of TiO 2 -coated Fe 2 O 3 nanoparticles. Although most large worldwide research efforts directed at solar photoelectrochemical hydrogen production focus on wafer-based designs, the projected lower cost for a particle slurry reactor at these disparate projected STH efficiencies clearly suggests that particle slurry reactors could be a scalable and deployable technology, assuming several challenges are overcome. These major technological challenges include the demonstration of a vertically-stacked-vessel architecture that is capable of operating sustainably while mostly relying on diffusion and natural convection to mix the redox shuttles between the vessels, and the demonstration that photocatalyst particles can operate at an overall 1% STH efficiency or larger when incorporated into this two-vessel design. Our research adds to the understanding of photocatalytic reactors for solar water splitting through numerical modeling results and experimental results. Numerical models were developed to simulate relevant device physics including particle and reactor dimensions which affect optical, transport, and rheological properties, electrocatalytic and photovoltaic properties of particles at various temperatures, and properties of redox shuttles and separators. Moreover, theoretical maximum solar-to-hydrogen efficiencies for ensembles of particles like in photocatalyst reactors were modeled and simulated and shown to equal or exceed those of photoelectrochemical designs under most scenarios. These results help determine constraints on the reactor that will enable more optimal designs for future prototypes. In parallel, experiments were performed to identify the most effective redox shuttles and to empirically validate the numerical models and simulations. Toward the latter, state-of-the-art light-absorbing particles and electrocatalysts were synthesized and characterized physically and photoelectrochemically for water electrolysis and redox chemistry with redox shuttles in the form factor of mesoporous electrodes and free-floating particles. The most promising materials candidates were used in a suspension reactor to evaluate performance toward photocatalytic H 2 production and results from the two measurements were compared. Predominantly, state-of-the-art cocatalyst-modified Rh-doped SrTiO 3 and BiVO 4 particles were further characterized to assess for their ability to perform visible-light-driven H 2 and O 2 evolution, respectively, and results were similar to those reported for the state-of-the-art in the peer-reviewed literature. Outcomes from this work inform the public of the effectiveness and promise of solar photocatalytic water splitting for clean and renewable hydrogen production. This work may also help increase research interest and funding for photocatalysis projects, which will accelerate development of a technology that will benefit the public by generating fuel while emitting few greenhouse gases and pollutants.

08 HYDROGEN↗

Application of electron beam technology to decompose persistent emerging drinking water contaminants: poly- and perfluoroalkyl substances (PFAS) and 1,4 dioxane.

Fermi Research Alliance, LLC (FRA) operates Fermilab under contract with the U.S. Department of Energy and has patents on technologies and applications of a novel mobile electron beam accelerator. A high-power version of this mobile accelerator based on FRA-developed SRF technology is under development at Illinois Accelerator Research Center (IARC) and can enable several new applications that have significant commercial potential. One such application is the e-beam treatment of persistent emerging contaminants in drinking water. The contaminants of concern are poly- and perfluoroalklyl substances (PFAS) and 1,4-dioxine. Both PFAS and 1,4-D are highly resistant to degradation and are not effectively removed by conventional drinking water treatment systems. Existing technologies, such as granular activated carbon (GAC) filters and reverse osmosis (RO) systems do not decompose. The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters. se PFAS, but rather concentrate them either by adsorption (GAC) or membrane rejection (RO). The Center for Clean Water Technology (CCWT) at Stony Brook University (SBU) is in the process of identifying and testing effective technologies to remove PFAS and/or 1,4-D from drinking waters to demonstrate the full-scale application of novel water treatment technologies and is experienced in conducting research to understand treatment performance with a particular focus on 1,4-D and PFAS contamination.

43 PARTICLE ACCELERATORS↗

Nuclear Fuel Cycle and Supply Chain (NFCSC) Technical Monthly September FY-24

AFC hosted the Light Water Reactor (LWR) Fuels Research Workshop and Electric Power Research Institute (EPRI) Collaborative Research on Advanced Fuel Technologies (CRAFT) Meeting September 9-13, 2024. The Department of Energy's (DOE) Advanced Fuels Campaign (AFC) Accident Tolerant Fuel (ATF) program is pivotal in advancing clean energy through collaborative innovation in fuel technology for light water reactors (LWRs). For over a decade, AFC has engaged a wide array of stakeholders—researchers, industry participants, and regulatory bodies—both within the U.S. and internationally to develop ATF technology. This initiative aims to enhance the safety and economic performance of both Pressurized Water Reactors (PWRs) and LWRs. To foster community relationships and disseminate research, AFC initiated annual LWR Fuel workshops in 2024, supplementing ongoing industry-led CRAFT workshops.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗