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At least 595 records · Page 33

Scale-up study of enhancing algal growth through bioaugmentation with the indole-3-acetic acid producing bacteria Azospirillum brasilense

Algae-based wastewater treatment technologies can recover nutrients while generating algal biomass with diverse application potentials. While numerous bacteria have demonstrated the ability to enhance algal growth through symbiotic relationships in laboratory settings, scaling this benefit to larger applications remains challenging due to complex wastewater conditions and microbe-algae dynamics. This study explores the effectiveness of bioaugmentation with Azospirillum brasilense, a plant growth-promoting bacterium known for producing the phytohormone indole-3-acetic acid (IAA), in boosting algal productivity within an Algaewheel wastewater treatment system. Through a series of experiments conducted at lab-, pilot-, and full-scale levels, we evaluated the impact of bioaugmentation on algal growth and developed a bioaugmentation strategy for an Algaewheel system. The results indicate that a biweekly dosing, achieving a final bioaugmenting cell density of 0.2–4 × 10 9 cells/L, effectively doubles the biomass productivity in a residential subdivision wastewater treatment plant in Northern Illinois. The bacterial production of IAA was the primary mechanism driving this enhancement, as demonstrated by the similar growth and yield improvements observed with chemically supplemented IAA and bioaugmentation across all experimental scales. High-throughput sequencing of 18S rRNA genes revealed that the algal community in the bioaugmented tank exhibited more stable biodiversity than the control. Additionally, bioaugmentation improved nutrient removal efficiency during winter, highlighting its potential to enhance the overall performance and sustainability of algae-based wastewater systems. The developed bioaugmentation and chemical treatment methods offer further operational solutions for managing yield, optimizing biochemical profiles, and enhancing biofuel production potential.

Algae-bacterial symbiotic relationship↗

Energy Analysis of Combi Heat Pump System Configurations for Space Conditioning and Domestic Hot Water Heating in Residential Buildings

Combi heat pump systems, also referred to multifunctional variable refrigerant flow heat recovery (MF-VRFHR) systems, are specifically designed for residential applications to manage both space conditioning and domestic hot water (DHW). They have attracted attention due to their potential for energy conservation through heat recovery. The incorporation of a hot water tank introduces various system configurations, each characterized by distinct pros and cons related to energy efficiency, system stability, and maintenance. Despite this, a critical gap exists as the specific energy performance remains unquantified under diverse operational modes (e.g., heating mode and heat recovery mode). This paper aims to bridge this gap by conducting a comprehensive comparative analysis of two prevalent system configurations while considering feasible proposed control logics. Configuration 1 integrates a separate hot water tank and a refrigerant-to-water heat exchanger (HEX), also known as a Hydro Kit while Configuration 2 incorporates a refrigerant-wrapped hot water tank. To facilitate this analysis, we developed high-fidelity system models for both configurations in Modelica, capturing system dynamics and detailed control sequences effectively. These system models were built upon the TIL library for HVAC equipment components and the Buildings library for residential building thermal load calculations. The validation of the simulation testbed utilized data from experiments conducted in the PNNL lab home for Configuration 1. To establish the simulation testbed for Configuration 2, we extended the modeling setup derived from Configuration 1. This extension specifically involved substituting the separate hot water tank and Hydro Kit with a refrigerant-wrapped hot water tank of similar sizing sourced from an actual product. The simulation analysis of heating-only and heat recovery modes reveals that Configuration 2 not only saves energy and maintains warmer tank temperatures but also demonstrates faster water heating capabilities. This is attributed to decreased energy loss and improved heat transfer. The study encompasses a wide range of scenarios, considering diverse thermal loads and water usage patterns across heating and heat recovery modes. Overall, the comprehensive results indicate that Configuration 2 achieves energy savings ranging from 3.5% to 12.2% compared to Configuration 1, depending on factors such as water usage patterns, thermal loads, and operational modes.

Configuration, Comparison, Multi-functional, Resid↗

PV Degradation Modeling: Applying Geospatial Workflows with "PVDeg"

Accurate degradation modeling is essential for predicting photovoltaic (PV) module performance, estimating longevity and informing design decisions. With degradation rates varying significantly by location, geospatial analysis is critical for PV and broader applications, such as agrivoltaics, weathering and environmental data analysis. This work presents PVDeg, an open-source tool designed for geospatial degradation analysis. PVDeg integrates meteorological data from global sources, including the National Solar Radiation Database (NSRDB) and Photovoltaic Geographical Information System (PVGIS), with degradation models. The toolkit enables users to customize geospatial workflows by integrating weather data, material parameters, and user-defined Python functions. It facilitates accelerated downloads of NSRDB and PVGIS datasets and optimizes geospatial point selection to preserve data density in regions of interest. Additionally, PVDeg provides a local database for storage and spatial queries, supporting large-scale analyses without the need for high-performance computing (HPC) resources. PVDeg provides a foundational workflow that extends its utility beyond PV applications, enabling researchers to analyze geospatial processes across discipline.

14 SOLAR ENERGY↗

The ALS OSMS: Optical Surface Measuring System for high accuracy two-dimensional slope metrology with state-of-the-art x-ray mirrors

We report that to preserve the brightness and coherence of x-rays produced by diffraction-limited-storage-ring (DLSR) and free-electron laser (FEL) light sources, beamline optics must have unprecedented quality. For example, in the case of the most advanced beamlines for the DLSR source under development at the Advanced Light Source (ALS), the ALS-U, we need highly curved x-ray mirrors with surface slope tolerances better than 50-100 nrad (root-mean-square, rms). At the ALS X-Ray Optics Lab (XROL), we are working on the development of a new Optical Surface Measuring System (OSMS) with the required measurement accuracy. The OSMS is capable for the two-dimensional (2D) surface slope metrology over the spatial range from the sub-mm scale to the clear aperture. Usage of different arrangements of the OSMS sensors allows measuring the mirrors in the face-up or side-facing orientation, corresponding to the beamline application. The OSMS translation system and data acquisition software are designed to support multi scan measurement runs optimized for automatic suppression and compensation of instrumental drifts and major angular and spatial systematic errors. Here, we discuss the recent results of the OSMS research and development project. We provide details of the OSMS design and describe results of experimental performance tests of the gantry system. In particular, we show that the system is capable for measurement repeatability with strongly curved mirrors on the level of 20 nrad (rms). The high angular resolution of the OSMS rotational tip-tilt stage is adequate for implementation of instrumental calibration with using the mirror under test as a reference. The achieved measuring accuracy is demonstrated via comparison to metrology with the carefully calibrated Developmental Long Trace Profiler, also available at the XROL.

47 OTHER INSTRUMENTATION↗

Software development infrastructure for the HYBRID modeling and simulation project

One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the whole problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers involved in the project. Thirdly, to exchange documents quickly, a SharePoint directory has been set-up. SharePoint allows teams and organizations to intelligently share, and collaborate on content from anywhere.

97 MATHEMATICS AND COMPUTING↗

Continuous Fiber Bath Treatments at Pilot Scale: A Novel Testbed System

The technical demands on high performance textiles continues to expand, and the research community has answered the call with innovative fiber bath treatments for enhanced properties and sizings for improved composites. However, little translation to greater scale has been demonstrated. To fill this gap, a novel, multifunctional system has been developed to explore polymer fiber treatment methods, the deployment of nanoadditive coatings and other sizings, and smart processing methods at the pilot scale. Continuous tows of fibers can be passed through a temperature-controlled, crossflow bath with an immersion residence time exceeding 2 hours. The modular system is resistant to corrosive solutions, includes additional inline stations for washing and drying after processing, is equipped with a bevy of sensors, pumps, and valves monitored and controlled by a LabView program, and can be fully contained in a standard lab fume hood. This new testbed system, when coupled with high fidelity materials characterization methods, will enable rapid evaluation of new fiber treatment methods at pilot-scale.

36 MATERIALS SCIENCE↗

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

A resettable in-line particle concentrator using AC electrokinetics for distributed monitoring of microalgae in source waters

Green algae have been studied as an important and effective biomarker to indicate water quality due to their sensitivity to toxic agents in freshwater sources. But, conventional methods to monitor algal physiology use a chlorophyll fluorometer whose use is hampered by high-cost, large footprint, and limited sensitivity for practical samples containing low algal concentration. In order to overcome these constraints, we developed a multi-level electrode platform for resettable trapping of algae via AC electro-osmosis (ACEO) and negative dielectrophoresis. Preliminary experiments were performed in freshwater with conductivity of 0.02 S/m. Algal trapping was demonstrated at a low voltage of 2 V. The concentration effect was experimentally verified by measuring the fluorescence intensity of algae and using hemocytometer counting chambers at the inlet and outlet of the multilevel microchannel lab-on-a-chip. An optimal frequency was found for trapping, which agrees with the frequency dependence of ACEO flow velocity. Through-flow rate and electrode dimensions were optimized as well. Trapping efficiencies within the range of 26% - 65% have been obtained. A maximum trapping rate of 182 cells/s was obtained with a flow rate of 20 l/min. Our lab-on-a-chip shows high potential for improving the limit of detection in algal monitoring and enabling the development of a portable, integrated and automated system for monitoring the quality of source drinking waters.

30 DIRECT ENERGY CONVERSION↗

Developing quantitative capabilities for a scanning microwave impedance microscope

Currently no instrument exists to quantitatively measure electrical properties (dielectric constant and conductivity) on sub-micron regions, a capability of extreme importance to measure the functioning of sub-micron structures and devices. In particular, such electrical measurements could support the development and manufacture of advanced energy related materials used in technologies such as photovoltaic cells, fuel cells and advanced batteries, thereby increasing performance and/or lowering production costs. The goal of this project is to develop microwave imaging add-on modules and probes capable of quantitatively measuring the electrical properties of small regions of a material using microwaves. These modules for scanning probe microscopes, such as atomic force microscopes, make use of the near-field interaction between the exciting microwaves and a material and can resolve regions 10 nanometers in size (less than a million atoms) with little perturbation of the material. In Phase 1 commercial probes and modified hardware were used to establish the feasibility of using microwave imaging systems to quantify local permittivity and conductivity. Repeatable measurements that vary in a systematic way with electrical parameters were obtained from a variety of samples. In Phase 2 research prototypes of the needed hardware and probes were developed and their performance against test structures and real-world samples was demonstrated. Result of this research project include demonstration of quantification of both permittivity and doping level at precisions up to 10% using multiple technical approaches. The level of performance and ease of use meets market expectations and the technology and protocols researched under this grant are currently being commercialized. Quantitative capabilities of this sort will provide a key capability to energy related technologies, and to a wide variety of semiconductor, biological, and materials science applications. Applications include both materials research in academic and industrial labs, as well as manufacturing applications. In a manufacturing environment the quantitative measurement and imaging capabilities could be used both as metrology for process control and as a tool for failure analysis and yield improvement.

36 MATERIALS SCIENCE↗

Innovating Distributed Embedded Energy Prize (InDEEP): A Lessons Learned Report

The U.S. Department of Energy's Water Power Technologies Office (WPTO) launched the Innovating Distributed Embedded Energy Prize (InDEEP) in March 2023 to accelerate innovation in Distributed Embedded Energy Conversion Technologies (DEEC-Tec) for ocean wave energy. Administered by the National Laboratory of the Rockies (NLR) with technical support from Sandia National Laboratories (SNL), InDEEP focused on the development of small, distributed, and embeddable energy converters (DEECs) and their integration into scalable DEEC-Tec metamaterials for marine renewable energy applications. Spanning three phases over two years, InDEEP awarded approximately $2.3 million to teams from academia, industry, and startups. Phase I emphasized conceptual design. Phase II moved into the prototyping of individual DEECs. Phase III required integration into functional DEEC-Tec metamaterial prototypes. Across 60 submissions, teams explored a wide range of energy conversion mechanisms - including piezoelectric, variable-capacitance, ionic, and inductive methods. Note, the prize did not include the design nor demonstration of ocean wave energy conversion systems. Rather, the prize only required participants to design and demonstrate individual DEECs and corresponding DEEC-Tec metamaterials. This prize utilized a mix of novel and proven techniques to attract participants from outside marine energy, including an engagement leaderboard, robust recruitment, technical expert mentorship, and a suite of technical trainings. Key insights from the competition emphasized that DEEC-Tec metamaterials must be intentionally designed to produce beneficial emergent behaviors - advantages that go beyond simply combining multiple DEEC units. Top-performing teams showed that thoughtful design of system architecture, coordinated deformation, and systems adaptabilities could unlock meaningful performance gains both at the DEEC system level and DEEC-Tec metamaterial system level. A critical realization was that many DEEC-Tec metamaterials could benefit from being designed to accept lower-frequency energy inputs and shift those into higher-frequencies per each DEEC making up the respective DEEC-Tec metamaterial. Other important takeaways included the need for rigorous and quantitative performance testing, effective integration of power conditioning electronics, and the pivotal role of material science in enabling innovative, adaptive DEEC-Tec-based energy conversion designs. InDEEP also helped establish a growing DEEC-Tec community of practitioners, attracting participants from beyond traditional marine energy sectors. Through a strong support infrastructure, InDEEP fostered early-stage innovation and laid a foundation for future DEEC-Tec-based ocean wave energy conversion solutions - positioning DEEC-Tec as a promising pathway toward scalable, resilient ocean wave energy conversion. Through focused R&D of individual DEECs and their integration into DEEC-Tec metamaterials, alongside a growing, multidisciplinary community catalyzed by InDEEP, there is a strong opportunity to drive a disruptive shift in ocean wave energy conversion design and development. This convergence of novel architectures, emergent behaviors, and collaborative innovation positions DEEC-Tec as a transformative approach, moving the field from rigid, centralized energy conversion-based designs to resilient, modular systems highly adaptable for real-world ocean wave energy conversion applications.

16 TIDAL AND WAVE POWER↗

Variational quantum and neural quantum states algorithms for the linear complementarity problem

Variational quantum algorithms (VQAs) are promising hybrid quantum-classical methods designed to leverage the computational advantages of quantum computing while mitigating the limitations of current noisy intermediate-scale quantum (NISQ) hardware. Although VQAs have been demonstrated as proofs of concept, their practical utility in solving real-world problems—and whether quantum-inspired classical algorithms can match their performance—remains an open question. We present a novel application of the variational quantum linear solver (VQLS) and its classical neural quantum states-based counterpart, the variational neural linear solver (VNLS), as key components within a minimum map Newton solver for a complementarity-based rigid-body contact model. We demonstrate using the VNLS that our solver accurately simulates the dynamics of rigid spherical bodies during collision events. These results suggest that quantum and quantum-inspired linear algebra algorithms can serve as viable alternatives to standard linear algebra solvers for modelling certain physical systems.

neural quantum states↗

Improved high-resolution mapping of phase-matching conditions in second-order nonlinear crystals via imaging

Large-aperture nonlinear crystals for frequency conversion and parametric amplification exhibit spatial variations in phase-matching conditions, which affect the performance of high-power laser systems. We demonstrate significant improvements in speed and resolution to a technique that spatially maps these phase-matching conditions using imaging of the beam resulting from detuned second-harmonic generation. The phase-matching conditions at the pyramidal sector boundary of partially deuterated potassium dihydrogen phosphate (DKDP) are mapped with sub-0.1-mm resolution. We examine the effect of further increases in scan rate on the precision of the technique and demonstrate a scan rate of 0.8 cm 2 per minute at the aforementioned resolution.

Wampler, R. [Univ. of Rochester, NY (United States↗

Performance enhancement of a polymer-electrolyte membrane H2O and CO2 co-electrolysis system for the production of syngas

Co-electrolysis of water and CO 2 to produce hydrogen and CO would provide an alternative pathway to making chemicals and fuels. The process could provide a way to use excess renewable electricity, or could be coupled to nuclear or carbon-based power generation. Opus 12 has overcome barriers to using a proton exchange membrane (PEM) reactor for this reaction by modifying the cathode catalyst layer to enhance simultaneous electrochemical H 2 production and CO 2 reduction. Current reactor performance metrics in terms of selectivity, current density, and applied voltage meet or exceed internal targets. However, the cell lifetime must be extended for a commercial product to be feasible. Through this H2@Scale project, we propose to work with the Weber Group at LBNL to diagnose performance decay mechanisms that currently limit the lifetime of the electrochemical syngas generator. LBNL is host to a number of advanced PEM diagnostic tools and lab scientists have unique experience in exploring performance and lifetime tradeoffs at the component to cell scales. Using the results of this study, the identified limiting mechanisms will be mitigated through improved cell and catalyst design.

10 SYNTHETIC FUELS↗

Highly Loaded Sulfur Cathode, Coated Separator and Gel Electrolyte for High Rate Li-Sulfur Batteries

As one of DOE Battery 500 Seedling projects, Cornell University and EIC Labs investigated and developed i) highly loaded sulfur cathodes (> 3 mg/cm 2 ), ii) hybrid separators, and iii) gel ceramic electrolytes (GCE) to mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries. Scalable nanomanufacturing processes such as air-controlled electrospray (ACES) and gas-assisted electrospinning (GAES) have been utilized to develop directly deposited electrodes and polymer/ceramic hybrid separators. First, in the development of highly loaded cathodes, alternating layers of sulfur impregnated mesoporous carbon and graphene were fabricated via ACES and the resulting layered cathodes and coated separators exhibit higher capacity and capacity retention (about 1,000 mAh/g capacity with less than 0.02% fade/cycles) than single layer cathode or cathode prepared by conventional slurry cast. Alternating layer approach via ACES has been applied to high loading systems (3 - 5 mg S/cm 2 ), demonstrating the potential to increase sulfur utilization and capacity retention. We have also incorporated iron oxides (Fe 3 O 4 ) into S/mesoporous carbon/graphene cathodes to enhance sulfur utilization and mitigation of polysulfide shuttling. and the effect of Fe 3 O 4 in mesoporous carbon and Gr is highly pronounced at high C rates of 1C and 2C cycling performance. To further improve the cathodes at high rates, graphene nanoribbons (GNR) which can promote ion transport were incorporated in the cathode, resulting in 550 mAh/g at 5C/5C rates. Hybrid Li-ion/Li-S cathodes has also been explored to better engage unreacted polysulfides during charge/discharge. S/LFP hybrid cathodes offer higher sulfur utilization and enhanced rate capability, as well as higher areal loading. This study suggests inclusion of iron phosphide (Fe2P) which can chemically interact with polysulfides can further enhance sulfur utilization and mitigation of soluble polysulfides at high rates. Secondly, in the development of hybrid separators, we first employed graphene coating on the commercial polyolefin separators, which exhibits higher capability, better capacity retention and enhanced rate capability. To improve the rate capability with enhanced safety features such as thermal stability and nonflammability, we developed polymer/ceramic hybrids based on thermally stable polyimide (PI) and room temperature curable ceramic precursors such as organopolysilazane (OPSZ) or polysilsesquioxanes (PSSQ), which exhibit no shrinkages up to 300 ºC and non-flammability. To improve mechanical properties and electrochemical stability, polybenzimidazole (PBI) and alumina have been incorporated in polymer/ceramic hybrid separator, replacing PI and OPSZ/PSSQ, respectively. Finally, the gel ceramic electrolyte (GCE) based on ceramic cross linkers have been applied to make Li-S cells even safer and also to mitigate the polysulfide shuttling further. The resulting gel ceramic electrolyte offers improved capacity retention and rate capability, and also effectively mitigates polysulfide shuttling which was also confirmed by modeling. Inclusion of high ion conducting additives into GCE together with polymer/ceramic hybrid separators exhibit the higher ionic conductivity than liquid electrolyte with commercial polyolefin separator. We demonstrated that the developed highly loaded sulfur cathodes, polymer/ceramic hybrid separators and gel ceramic electrolyte can effectively mitigate the low rate capability, shuttling effect and limited cycle life in high performance Li-Sulfur batteries with improved safety.

25 ENERGY STORAGE↗

Cabibbo-Kobayashi-Maskawa unitarity deficit reduction via finite nuclear size

We revisit the extraction of the |𝑉 𝑢⁢𝑑 | Cabibbo-Kobayashi-Maskawa (CKM) matrix element from the superallowed transition decay rate of 26⁢𝑚 Al → 26 Mg, focusing on finite nuclear size effects. The decay rate dependence on the 26⁢𝑚 Al charge radius is found to be four times higher than previously believed, necessitating precise determination. However, for a short-lived isotope of an odd 𝑍 element such as 26⁢𝑚 Al , radius extraction relies on challenging many-body atomic calculations. We performed the needed calculations, finding an excellent agreement with previous ones, which used a different methodology. This sets a new standard for the reliability of isotope shift factor calculations in many-electron systems. The ℱ⁡𝑡 value obtained from our analysis is lower by 2.2𝜎 than the corresponding value in the previous critical survey, resulting in an increase in |𝑉 𝑢⁢𝑑 | 2 by 0.9𝜎. Adopting |𝑉 𝑢⁢𝑑 | from this decay alone reduces the CKM unitarity deficit by one standard deviation, irrespective of the choice of |𝑉 𝑢⁢𝑠 |.

beta-decay↗

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>

03 NATURAL GAS↗

IEA PVPS Task 13 Techno-Economic Study of Bifacial Photovoltaic Systems on Single Axis Trackers

The International Energy Agency PVPS Task 13 has assembled an international team of photovoltaic (PV) researchers from government labs, academia, and industry to study the specific application of bifacial PV modules deployed on tracking systems. This configuration is of particular interest as it has been identified as the PV system design with the lowest Levelized Cost of Electricity (LCOE) for over 90% of the world [1]. As such, much research, development, and commercial activity are focused on further optimizing this system design for different regions and markets, including field deployment and advanced modeling activities. Despite these efforts, many challenges remain to overcome with this system design. This conference paper will report on several areas the team is working on as part of this project. The first part of this study focuses on extensive interviews with PV tracker companies (we have identified 35) and customers worldwide to identify emerging technology trends, design diversity, market environments, and the reliability and performance of these systems. We will provide a market summary of technologies such as advanced tracking algorithms, methods for dealing with topography within the PV plant, different system configurations and layouts, backside irradiance optimization from albedo enhancement, and ground sculpting. We will also review dual-use applications of tracked bifacial systems, such as Agrivoltaics and Building-Integrated PV. These interviews are underway now, and we will be able to report our initial findings at the conference. The second part of the study focuses on summarizing performance monitoring and evaluation methods, with particular attention to capacity and acceptance testing for such systems. The third part of the study reviews performance modeling and yield assessment methods for these tracked bifacial PV systems. The final part of the study covers reliability and operations, and maintenance data from these systems.

albedo↗

A Magnetized Electron Source For Ion Beam Cooling

A number of electron-ion collider facilities for nuclear physics research are under consid- eration in the United States. At Brookhaven National Lab (BNL), the eRHIC (electron Relativistic Heavy Ion Collider) facility would augment the existing ion/proton facility with an electron accelerator. Thomas Jefferson National Accelerator Facility (JLab) plans to use the existing CEBAF machine and add an ion/proton accelerator, as part of the Jefferson Lab Electron-Ion Collider (JLEIC). All such facilities require cooling of the ion beams in order to reach the luminosity goals. Different methods of cooling the ions using an electron beam are envisaged. BNL is pursuing coherent electron cooling and non-magnetized, bunched-beam cooling, while JLab is considering magnetized cooling. In addition to electron cooling, magnetized beams are of interest for other applica- tions, such as flat beam klystrons and novel means for producing bright beams for micro- undulators and compact X-ray sources. For example, flat beams generated from a mag- netized injector, in conjunction with low emittance, enable RF sources with frequencies above 100 GHz. While the market for high-performance injectors for electron cooling is limited, the market for high-frequency RF sources and compact X-ray systems is con- siderable. Thus, the design methodologies developed in this project have a wide range of applicability. In Phase I of this SBIR project, Xelera Research LLC performed simulations and calcu- lations to develop a prototype design for a magnetized electron injector that can be used as a source for cooling an ion beam. We developed general design methodologies and tech- niques that are applicable not only to specific machine designs but to other applications requiring magnetized injectors as well. In this Phase II SBIR project, Xelera Research LLC, in collaboration with a team at JLab, designed, built, and tested a thermionic elec- tron source for driving a magnetized electron cooler in a future electron-ion collider project. This device was delivered to JLab in July 2019 and achieved first beam in December 2019.

43 PARTICLE ACCELERATORS↗