NEVADA NATIONAL SECURITY SITE DISPOSAL OPERATIONS - VOLUME REPORT FY 2023 - QUARTER ONE
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12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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NEVADA NATIONAL SECURITY SITE WASTE DISPOSAL OPERATIONS - DISPOSAL VOLUME REPORT FY 2022 - QUARTER ONE
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12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NEVADA NATIONAL SECURITY SITE WASTE DISPOSAL OPERATIONS - VOLUME REPORT FY 2025 - QUARTER ONE
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12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NERC MISOPS
This investigation was commissioned by the Office of Electricity of the Department of Energy in response to reviewing the NERC State of Reliability report. The study is an attempt to proactively address electric utility industry needs. “Monitoring, analyzing, and tracking trends in Protection System Misoperations are critical to improve BES reliability. Historically, Protection System Misoperations have exacerbated the severity of most cascading power outages.” The NERC misoperations data shows that unnecessary trips are by far the leading category of reported misoperations and that a majority of misoperations are those of line protection packages. A significant number of misoperations are tied to microprocessor relays. Approximately one quarter of reported misoperations are due to incorrect settings and another one quarter of misoperations are due to relay failures/malfunctions and communication failures.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Metal-Complex Inks for Lower Cost and Improved Passivation for Silicon Photovoltaic Metallization
This contribution introduces the silicon PV community to screen-printable metal-complex inks that potentially will reduce Ag usage in Si PV metallization to one-quarter and costs to one-third that of traditional particle-based pastes while also improving passivation. Metal-complex inks are formulated using a Tollen’s reaction to produce inks with a high percentage of diamminesilver (I) cations (22 wt %) in a solution of acetate and formate anions. When printed and dried, labile ammonia ligands evaporate, leaving behind silver cations which, when reduced by formate anions and acetic acid, plate out silver and silver acetate. When annealed to just 300 °C a dense metallic silver film forms with excellent conductivity, and adhesion to silicon. When compared to traditional particle-based screen-printing pastes, the metal-complex inks are much denser, have higher conductivity, use less Ag, and are a fraction of the cost. Importantly, the inks anneal from 90 – 450 °C allowing for improved passivation schemes compared with fired SiNx. This contribution highlights first experiments on the improved passivation of metallized poly-Si/SiO2 passivated contacts using metal-complex Ag inks.
Young, David L. (ORCID:0000000340970493)↗
Metal-Complex Inks for Lower Cost and Improved Passivation for Silicon Photovoltaic Metallization
This contribution introduces the silicon PV community to screen-printable metal-complex inks that potentially will reduce Ag usage in Si PV metallization to one-quarter and costs to one-third that of traditional particle-based pastes while also improving passivation. Metal-complex inks are formulated using a Tollen's reaction to produce inks with a high percentage of diamminesilver (I) cations (22 wt %) in a solution of acetate and formate anions. When printed and dried labile ammonia ligands evaporate, leaving behind silver cations which, when reduced by formate anions and acetic acid, plate out silver and silver acetate. When annealed to just 300 degrees C a dense metallic silver film forms with excellent conductivity, and adhesion to silicon. When compared to traditional particle-based screen-printing pastes, the metal-complex inks are much denser, have higher conductivity, use less Ag, and are a fraction of the cost. Importantly, the inks anneal from 90 - 450 degrees C allowing for better passivation schemes than fired SiNx. This contribution highlights first experiments on the improved passivation of metallized poly-Si/SiO2 passivated contacts using metal-complex, Ag inks compared with particle-based, fired pastes.
metal-complex ink↗
Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges
Traffic intersections are crucial and challenging nodes in transportation networks where multiple lanes of vehicles and pedestrians converge. About one-quarter of traffic fatalities and about one-half of all traffic injuries in the United States happen at traffic intersections . Effective management of these intersections is important to ensure safety and efficiency of all users - vehicles, pedestrians, cyclists, and vulnerable road users (VRUs). With advancements in sensor perception technologies such as radar, light detection and ranging (lidar), and cameras, traffic intersections are developing into dynamic and data-rich environments. By using these data to create a real-time digital twin, we can enable real-time data-driven decision making and a range of applications such as sharing perception information to connected vehicles (CVs) and connected autonomous vehicles (CAVs), safety affirmative signaling, and curb optimizing to improve efficiency and enhance safety.This paper presents an overview of the concept and examines the challenges involved in implementing an infrastructure-based cooperative perception engine at a traffic intersection. In addition to outlining the physical components, this study also addresses important challenges involved in a multi-sensor system. We present results from deploying the National Renewable Energy Laboratory's (NREL's) Infrastructure Perception and Control (IPC) mobile trailer at a traffic intersection in the city of Colorado Springs, Colorado, USA that employed multiple radars and lidars to capture the data. This study provides necessary practical learning for the Cooperative Driving Automation (CDA) and traffic engineering communities for next-generation infrastructure-based cooperative perception that promises improvements in signal control for optimized traffic flow, among other applications, and documents findings for ongoing research and development efforts in other areas.
ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
Chiral spin liquid and quantum phase transition in the triangular-lattice Hofstadter-Hubbard model
Recent advances in moiré engineering motivate the study of lattice models of strongly correlated electrons subjected to substantial orbital magnetic flux. We analyze the triangular-lattice Hofstadter-Hubbard model at one-quarter flux quantum per plaquette and a density of one electron per site, where a chiral spin liquid phase may exist between weak-coupling integer quantum Hall and strong-coupling 120° antiferromagnetic phases. Here, we use matrix product state methods and analytical arguments to investigate this model compactified to cylinders of finite circumference. We uncover a glide particle-hole symmetry operation which, we argue, is spontaneously broken at the quantum Hall to spin liquid transition on odd-circumference cylinders. We numerically verify the spontaneous symmetry breaking and further demonstrate that this transition is associated with algebraic long-range correlations of various spin-singlet, charge-neutral operators. For even-circumference cylinders, the transition becomes a crossover associated with a large correlation length that grows substantially with circumference. Our findings suggest that in the two-dimensional limit, the transition to a chiral spin liquid phase is continuous and features critical fluctuations of the current.
Divic, Stefan [University of Pennsylvania, Philade↗
Perspective on Solar Energy Materials, Design and Discovery, Defects, Disorder, and Interfaces
The energy transition still faces a daunting math. Currently, more than three quarters of final energy consumption occurs in form of fuels vs less than one quarter in electricity. On the other hand, renewable energy additions come almost exclusively in the form of electricity (dominantly photovoltaics and wind). Thus, meeting the terawatt challenge requires enormous growth in renewables, sufficient to convert excess electricity into fuels, as well as the development of non-electricity based solar fuel technologies, for example via solar thermochemical routes. In this presentation, we will review successes and challenges in photovoltaic materials from silicon to CdTe to halide perovskites and potential emerging materials, with a particular perspective on the role of first principles calculations and predictions. Materials design and discovery is evolving to incorporate defects, disorder, and interfaces. These phenomena play also an important role in the thermochemical generation of hydrogen, allowing to utilize synergies between renewable electricity and fuels in computational research. At the same time, machine learning approaches are increasingly geared toward properties of non-ideal materials, for example defect formation, allowing the screening for more complex material behavior as needed for the respective applications.
fuels↗
The environmental footprint of data centers in the United States
Much of the world's data are stored, managed, and distributed by data centers. Data centers require a tremendous amount of energy to operate, accounting for around 1.8% of electricity use in the United States. Large amounts of water are also required to operate data centers, both directly for liquid cooling and indirectly to produce electricity. For the first time, we calculate spatially-detailed carbon and water footprints of data centers operating within the United States, which is home to around one-quarter of all data center servers globally. Our bottom-up approach reveals one-fifth of data center servers direct water footprint comes from moderately to highly water stressed watersheds, while nearly half of servers are fully or partially powered by power plants located within water stressed regions. Approximately 0.5% of total US greenhouse gas emissions are attributed to data centers. We investigate tradeoffs and synergies between data center's water and energy utilization by strategically locating data centers in areas of the country that will minimize one or more environmental footprints. Our study quantifies the environmental implications behind our data creation and storage and shows a path to decrease the environmental footprint of our increasing digital footprint.
54 ENVIRONMENTAL SCIENCES↗
Membrane Carbonation for 100% Efficient Delivery of Industrial CO 2 Gases
Industrial processes generate about one quarter of all greenhouse gases emissions in the US, about 80% of which is carbon dioxide (CO 2 ). Biological processes are one of the largest natural sinks for atmospheric CO 2 , but the rate of capture is limited by the low concentration in air (~0.04%). Industrial emissions have significantly higher CO 2 concentrations, ranging from 5–80% CO 2 , which can significantly increase the rate of biological CO 2 capture, including many-fold improvements for cultivating microalgae to produce food, fertilizer, and renewable fuel. However, traditional methods for delivering CO 2 to microalgae using bubbling is < 40% efficient, leading to significant residual CO 2 emissions and increased cost. This project developed the Membrane Carbonation (MC) technology to significantly improve the CO 2 delivery efficiency to microalgae from power plant flue gas, wastewater treatment plant anaerobic digesters biogas (Figure 1), and other CO 2 -containing industrial sources.
09 BIOMASS FUELS↗
Anyon superconductivity from topological criticality in a Hofstadter–Hubbard model
We argue that the combination of strong repulsive interactions and high magnetic fields can generate electron pairing and superconductivity. Inspired by the large lattice constants of moiré materials, which make large flux per unit cell accessible at laboratory fields, we study the triangular lattice Hofstadter-Hubbard model at one-quarter flux quantum per plaquette, where previous literature has argued that a chiral spin liquid separates a weak-coupling integer quantum Hall phase and a strong-coupling topologically trivial antiferromagnetic insulator at a density of one electron per site. We argue that topological superconductivity emerges upon doping in the vicinity of the integer quantum Hall to chiral spin liquid transition. We employ exact diagonalization and density matrix renormalization group methods to examine this theoretical scenario and find that electronic pairing indeed occurs on both sides of criticality over a remarkably broad range of interaction strengths. On the chiral spin liquid side, our results provide a concrete model realization of the long-hypothesized mechanism of anyon superconductivity. Our study thus establishes a beyond-Bardeen-Cooper-Schrieffer route to electron pairing in a well-controlled limit, relying crucially on the interplay between electron correlations and band topology.
Hubbard model↗
Continuous Liquid–Liquid Extraction and in-Situ Membrane Separation of Miscible Liquid Mixtures
Separation operations are critical across a wide variety of manufacturing industries and account for about one quarter of all in-plant energy consumption in the United States. Conventional liquid-liquid separation operations require either thermal or chemical treatment, both of which have a large environmental impact and carbon footprint. Consequently, there is a great need to develop sustainable, clean methodologies for separation of miscible liquid mixtures. The greatest opportunities to achieve this lie in replacing high-energy separation operations (e.g., distillation) with low-energy alternatives such as liquid-liquid extraction. One of the primary design challenges in liquid-liquid extraction is to maximize the interfacial area between two immiscible (e.g., polar and non-polar) liquids for efficient mass transfer. However, this often involves energy-intensive methods including ultrasonication, pumping the feed and the extractant through packed columns with high tortuosity, or using a supercritical fluid as an extractant. Emulsifying the feed and the extractant, especially with a surfactant, offers a large interfacial area, but subsequent separation of emulsions can be energy-intensive and expensive. Thus, emulsions are typically avoided in conventional extraction operations. Herein, we discuss a novel, easily scalable, platform separation methodology termed CLEANS (Continuous Liquid-liquid Extraction And iN-situ membrane Separation). CLEANS integrates emulsion-enhanced extraction with continuous, gravity-driven, membrane-based separation of emulsions into a single unit operation. Furthermore, our results demonstrate that the addition of a surfactant and emulsification significantly enhance extraction (by > 250% in certain cases), even for systems where the best extractants for miscible liquid mixtures are known. Utilizing the CLEANS methodology, we demonstrate continuous separation of a wide range of miscible liquid mixtures, including soluble organic molecules from oils, alcohols from esters, and even azeotropes.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
1.4.2.403 - Water Power STEM Workforce Development (Hydro)
As interest in renewable energy grows, water power technologies will continue to play a robust and growing role. However, the industry needs new talent to spur innovation and to support industry needs. With one-quarter of the domestic hydropower workforce retiring in the coming decade, the need to fill the workforce pipeline has never been more critical. The lack of new hydropower development has limited the number of educational programs focused on this sector at all levels of education. NREL has a long track record of working to address educational needs across the renewable energy spectrum. Leveraging this track record, this project brought the Hydropower STEM Portal to water power stakeholders fueled by information from a multitude of sectors, our partnership with the Hydropower Foundation, NEED, and others. The team has also sought to integrate activities with the Bonneville Environmental Foundation, to increase dissemination opportunities and interfaces. The purpose of the portal is to be a one-stop shop to information geared at inspiring the next-generation water power professional. NREL also leverages experience in engaging with stakeholders to understand barriers to technology adoption to identify issues and drivers, provide feedback to the R&D community, work to clarify misperceptions, and inform decisions to facilitate market adoption. The outcome of this work is a more successful and diverse water power industry based on a motivated and better-trained workforce.
ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗
Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Wave
The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production using a single, simulated wave energy conversion device. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel Hydrogen. While the unit supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. For the wave energy, NLR used a wave energy converter model from PacWave. These devices can be equipped with accumulators and pressure relief values to smooth the power output by storing and releasing hydraulic energy. Using a peak power output of 10 MW, the model created two 25-minute profiles: one with and one without the accumulators and pressure relief valves. To down select the profile data from the native resolution of 20 Hz to 1 Hz, NLR took the mean of every 20 data points. NLR experimented with two simulated wave energy power plants: one that peaks at 10 MW, and one that peaks at 5 MW. These profiles were scaled for the physical 1.25 MW electrolyzer by multiplying the original profiles by one eighth and one quarter, respectively. The first profile matches the capacity rating of eight of the 1.25 MW electrolyzers, while the second matches four electrolyzers. Finally, NLR experimented with two settings for the electrolyzer power supply minimum and maximum current ramp rates (gain and slew): 200 and 400 amperes per second. The simulated profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wave electrolysis experiment and is formatted as follows: {technology}-{accumulator?}_{number of 1.25 MW electrolyzers connected}-{electrolyzer ramp rate in amperes/second} For instance, “wavePacWave-Noacc_4-400.zip” represents the 25 minute-long experiment using the PacWave’s wave energy converter model, equipped with no accumulator, connected to four 1.25-MW electrolyzers with their power supplies set to a maximum current ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. An experiment, labeled “characterization_200.zip”, demonstrates the MC250 electrolyzer steady-state response with 30 minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all wave profiles combined into one dataset labeled "combined_wave_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis.
08 HYDROGEN↗
The Effect of Slag Heat Treatment on Ingot Quality during Cold Start Electroslag Remelting
Heat treatments of a commercial 40CaF 2 –30CaO–30Al 2 O 3 slag are explored to study their effect on quality of ingots produced using cold start electroslag remelting (ESR). Reducing heat treatment (or roasting) time or temperature for slag degassing can lead to energy savings as well as longer lifetimes for various components. Heat treatments in vacuum with pressure monitoring and air are investigated along with several temperatures, heating rates, and/or holding times. A research scale ESR furnace is used with steel electrodes. Significant differences in ingot quality, such as the occurrence of pores and a rough sidewall near the bottom of the ingot produced using slag heat treated in air at 580 °C, are observed. Further, adjustments in the heat treatment temperature for heat treatment in air eventually lead to an ingot quality comparable to that obtained using slag degassing in a controlled atmosphere at higher temperatures. Using differential thermal analysis, it is found that moisture is primarily removed from the slag at ≈460 °C and 700 °C. A safe slag roasting temperature is concluded to be 750 °C. Improper slag heat treatment leads to hydrogen concentrations from 8 to 15 ppm in about one‐quarter of the ingot volume.
36 MATERIALS SCIENCE↗
Properties of the new $ \mathcal{N} $ = 1 AdS 4 vacuum of maximal supergravity
The recent comprehensive numerical study of critical points of the scalar potential of four-dimensional N = 8, SO(8) gauged supergravity using Machine Learning software in [1] has led to a discovery of a new N = 1 vacuum with a triality-invariant SO(3) symmetry. Guided by the numerical data for that point, we obtain a consistent SO(3) × Z 2 -invariant truncation of the N = 8 theory to an N = 1 supergravity with three chiral multiplets. Critical points of the truncated scalar potential include both the N = 1 point as well as two new non-supersymmetric and perturbatively unstable points not found by previous searches. Studying the structure of the submanifold of SO(3) × Z 2 -invariant supergravity scalars, we find that it has a simple interpretation as a submanifold of the 14-dimensional Z $3\atop{2}$ -invariant scalar manifold (SU(1, 1)/U(1)) 7 , for which we find a rather remarkable superpotential whose structure matches the single bit error correcting (7, 4) Hamming code. This 14-dimensional scalar manifold contains approximately one quarter of the known critical points. We also show that there exists a smooth supersymmetric domain wall which interpolates between the new N = 1 AdS4 solution and the maximally supersymmetric AdS4 vacuum. Using holography, this result indicates the existence of an N = 1 RG flow from the ABJM SCFT to a new strongly interacting conformal fixed point in the IR.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Surface defects in holographic 5d SCFTs
We use holography to study codimension-2 surface defects in 5d SCFTs engineered by (p, q) 5-brane webs. The three-dimensional defects are realized by D3-branes ending on the brane web. We identify the holographic representation of the defects in Type IIB AdS 6 solutions as probe D3-branes, and study conformal and non-conformal defects which, respectively, preserve one half and one quarter of the supersymmetry. For a sample of 5d SCFTs, including the T N theories, we provide explicit solutions for conformal and non-conformal defects. For the conformal defects we obtain their contribution to the free energy on S 5 .
79 ASTRONOMY AND ASTROPHYSICS↗