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At least 1,207 records · Page 67

INTERFUEL: FAST - Fueling Center / EVSE Inventory Reporting Update [Slides]

This presentation presents an overview of coming changes to how federal agencies with motor vehicles will submit required information about fueling centers and electric vehicle supply equipment (EVSE) inventory through the Federal Automotive Statistical Tool (FAST). The presentation provides background on the process, a re-cap of how the information is currently submitted, and describes the new approach for organizations to submit the required information this year. This presentation is intended for delivery via WebEx/GoToMeeting at the August 11, 2021 meeting of the DOE-sponsored INTERFUEL working group. FAST is a web-based information management tool developed by INL and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

99 GENERAL AND MISCELLANEOUS↗

USAID Colombia Young Leaders Workforce Training Program Action Plans: Early Adopters Work to Accelerate Electric Vehicle Transitions in Boyacá, Colombia

As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, Empresa de Energía de Boyacá (EBSA) participants leveraged their training and professional experience to develop an electric mobility and transition action plan for their organization. This case study provides and overview of the technical assistance that USAID-NREL provided to EBSA to inform their fleet transition decision making process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Development of a Pre-Combustion CO 2 Capture Process Using High-Temperature PBI Hollow-Fiber Membranes

The overall objective of this project was to evaluate the advantages of transformational polybenzimidazole (PBI) polymer hollow-fiber membrane (HFM)-based, carbon dioxide (CO 2 ) capture and purification technology at bench-scale using an actual coal-derived syngas stream from a coal gasification facility. The project was carried out over two budget periods. The technical objectives in Budget Period 1 (BP1) included preparing HFs and modules and upgrading the available skid for field testing. The technical objectives for BP2 were to field-test the skid unit with actual coal-derived syngas from an oxygen-blown gasifier to obtain performance data, update the Techno-Economic Analysis (TEA) that would assist with future process scale-up, and provide information on the design of a small pilot-scale test unit. The goal was to advance the PBI-HFM CO 2 capture and gas separation system for pre-combustion applications beyond second-generation economic performance predictions and make progress toward meeting overall fossil energy performance goals of CO 2 capture with 95% CO 2 purity at a cost of electricity (COE) 30% less than baseline capture approaches. The research program was designed with progressive technical tasks leading to both dynamic and steady-state testing of the PBI-HFM skid with actual coal-derived syngas. The work plan was to: (1) fabricate sufficient Generation-2 (GEN-2) fibers for module fabrication; (2) upgrade the fiber skid to accommodate large fiber modules for bench-scale field testing; (3) conduct dynamic and steady-state testing with coal-derived syngas from an oxygen-blown gasifier and obtain system performance data; (4) perform a TEA and environmental, health, and safety (EH&S) assessment; (5) update the State-Point Data Table, Technology Gap Analysis (TGA), and Technology Maturation Plan (TMP); (6) uninstall and return the test skid to the Recipient’s facilities; and (7) submit a Final Report that describes the results and analysis of the project research effort.

03 NATURAL GAS↗

Enabling Real-time Scattering Data Analysis with Scalable Optimization [Slides]

Diffraction experiments produce datasets with rich multidimensional physics information such as microstructure, equations of state, crystal structure, elastoplastic properties, and other key inputs to LANL mission-essential multiphysics models. This information is typically extracted through a process called Rietveld refinement, which involves selecting appropriate models of the instrument, crystal structure, and microstructure, identifying suitable starting values, and then fitting often hundreds of model parameters using a sequence of empirical parameter turnon/off sequences within a non-global gradient-based optimization. Extensive user expertise is required to properly setup a refinement, identify appropriate models, and select initial parameter values close to truth, such that the refinement will yield parameter values that are optimally predictive. This is a very tedious manual process performed far after the beamline campaign has ended. As facilities have become capable of generating larger volumes of data, the limitation in throughput due to Rietveld refinement has led to a dramatic increase in unanalyzed data as opposed to an intended increase in new science. In our FY22 TED, we demonstrated an integrated toolset providing near real-time automated Rietveld analysis. If this toolset can be optimized to provide automated Rietveld analysis in real-time, this could alleviate the bottleneck in unanalyzed diffraction data, aid in decision-making during experiments, and increase efficiency of the facility.

74 ATOMIC AND MOLECULAR PHYSICS↗

Probing photochemical kinetics and mechanisms using photoNMR

Nuclear magnetic resonance spectroscopy (NMR) is a form of spectroscopy that yields detailed mechanistic information about chemical structures, reactions, and processes. Photochemistry has widespread use across many industries and holds excellent utility for additive manufacturing (AM) processes. Here, we use photoNMR to investigate three photochemical processes spanning AM relevant timescales. We first investigate the photodecomposition of a photobase generator on the slow timescale, then the photoactivation of a ruthenium catalyst on the intermediate timescale, and finally the radical polymerization of an acrylate system on the fast timescale. In doing so, we gain fundamental insights to mission relevant photochemistries and develop a new spectroscopic capability at SNL.

36 MATERIALS SCIENCE↗

Quick Talk: Resilient Communities, Maryland

Groundswell, Inc., in partnership with the Maryland Energy Administration (MEA), Ayika Solutions, the National Renewable Energy Lab (NREL), and the Baltimore Office of Sustainability, is advancing a vision for resilient, community-centered energy systems in Maryland. This effort aligns with Groundswell's commitment to a clean energy economy that equitably benefits all communities, closing gaps in representation, wages, and access to wealth generation, savings, and local jobs within a diverse energy supply chain. Project Vision and Objectives The project emphasizes "energy resilience," defined as a community’s capacity to anticipate, adapt to, and swiftly recover from power disruptions through inclusive planning and technical solutions. The approach centers on Resilience Hubs—designated community facilities equipped to support residents before, during, and after power-related disruptions. These hubs offer emergency resources, coordinate communications, and deliver essential services while reducing carbon emissions, ultimately enhancing residents' quality of life. Additionally, Resilience Hubs foster social connections, support disaster preparedness, and provide spaces for community programming and everyday use. The goals of Resilient Communities Maryland include: Developing a replicable framework for community energy resilience, applicable beyond Maryland. Defining community-led indicators of social impact and resilience. Establishing equitable decision-making processes in project design and implementation. Informing MEA of practical, community-based resilience strategies to shape future state initiatives. Approach Groundswell and its partners prioritize collaborative engagement with local stakeholders, ensuring that solutions are responsive to each community's unique needs. By integrating feedback from residents, local organizations, and government entities, the team has developed a holistic model for resilience that balances immediate benefits, such as improved emergency response, with long-term gains in social equity and environmental sustainability. Key Outcomes This initiative has produced valuable resources and insights, including: A Community Energy Resilience Framework: Designed to guide other communities in establishing energy resilience strategies tailored to their specific needs. Case Studies: Documenting best practices and lessons learned from pilot projects to serve as models for future resilience efforts. Community-Driven Impact Metrics: Highlighting the positive social impacts that resilience initiatives can bring, such as improved social connectedness and local decision-making power. Recommendations for MEA: Offering evidence-based insights to inform policies and funding opportunities that support resilient energy infrastructure in vulnerable communities. Next Steps Groundswell's final report will detail findings, including the potential for scaling resilience hubs across Maryland and other regions, with a focus on equitable access and community-driven outcomes. This project underscores the importance of aligning energy resilience with social equity, reinforcing community agency, and building systems that withstand and recover from future challenges effectively and sustainably.

14 SOLAR ENERGY↗

Targeted Rare Earth Element Extraction from Mine Drainage Treatment Solids Informed by Advanced Characterization

In support of a clean energy transition in the U.S., National Energy Technology Laboratory (NETL) has collaborated with staff at Hedin Environmental and students at the University of Pittsburgh to characterize critical mineral content and recovery potential from acid mine drainage treatment solids (AMD solids). AMD solids in Appalachia are an unconventional feedstock of rare earth elements (REEs), with potential of suppling 1,102 tons REE/year. To inform recovery efforts, select AMD solids were examined using synchrotron microprobe analysis in conjunction with USGS-developed geochemical modeling to indicate likely phases hosting critical minerals (REE, Co, Ni, etc.) and associated metals . More than 100 AMD solids were collected from 94 passive AMD treatment systems in Pennsylvania, where limestone aggregates are used for acidity neutralization. As pH increases, dissolved metals and critical minerals in AMD are attenuated as surface coatings on limestone. The collected AMD solids contained up to 2000 mg/kg REE, up to 13,000 mg/kg transition metals (Co, Ni, Zn) and up to 440 mg/kg Li. Regardless of the diverse chemical compositions from AMD solids (Al-rich, Mn-rich, or Al,Fe,Mn-rich), REEs were mostly associated with Al and Mn (hydr)oxides, while select heavy REEs (e.g., Gd, Dy) were co-localized with Fe (hydr)oxides. Co and Ni have different distribution zones, while both co-localized with Mn (hydr)oxides. Based on this characterization, NETL developed a patent-pending innovative step-leaching protocol, “Targeted Rare Earth Extraction (TREE)” to effectively recover up to 90% REE and 60% Co in separate steps. In addition, select post-TREE solid residuals (purified Al oxides, or Mn oxides) can be further developed into functional materials (e.g., lithium and CO2 sorbents) needed for green energy transition and carbon management. This characterization-informed approach as well as TREE processing from AMD solids can be used for other legacy wastes (e.g., coal ash, oil and gas drill cutting, mine tailings), and offers an opportunity to transform waste streams into environmental and economic assets that meet U.S. Department of Energy and U.S. Environmental Protection Agency goals.

characterization and extraction of rare earth elem↗

Harnessing Heterologous Bacterial Two-Component Systems as Biosensors to Address Challenges in Fermentation Scale-Up

Scaling up bacterial fermentation from bench to industrial scale often results in unpredictable performance losses, possibly in part due to changes in microenvironmental conditions such as pH. To investigate this, we developed a suite of pH-sensitive biosensors from bacterial two-component systems (TCSs) that provide a dynamic, fluorescent readout in response to extracellular pH changes. TCSs consist of a periplasmic sensor histidine kinase (HK) that, in response to an extracellular stimulus, autophosphorylates intracellularly and subsequently transfers the phosphate to a cognate response regulator (RR) that modulates transcription of target genes. We utilized three pH-responsive TCSs (referred to here as CVJ1, CVJ30, and CVJ79) and linked their output to GFP. This was achieved by placing the RR promoter upstream of GFP or by constructing a chimeric RR composed of the native receiver domain and the DNA-binding domain of another well-characterized RR with a defined promoter. All components - HK, RR (native or chimeric), and GFP under its corresponding promoter - were cloned into a broad-host-range plasmid. Sensors were validated in Escherichia coli and Pseudomonas putida, including the muconic acid-producing strain P. putida TL207. All three biosensors successfully reported pH, with fluorescence (normalized to optical density) correlating strongly with media pH. Among the native sensors, CVJ79 showed the most robust performance while CVJ1 also performed best in its native form; CVJ30 exhibited improved functionality as a chimera, suggesting that modular RR design can enhance compatibility in some heterologous hosts. Further, CVJ79 was activated by alkaline conditions, while CVJ30 responded to acidic environments. Notably, CVJ1 was induced by high pH in wild-type E. coli and P. putida, but low pH in TL207. The observed differences in sensor activation between strains - particularly the divergent response of CVJ1 - suggest that host-specific regulatory pathways may influence how cells perceive and adapt to pH stress. Moving forward, these biosensors can be used to guide the rational design of more robust strains, optimize process conditions in real time, and inform strategies to minimize physiological heterogeneity during scale-up. Integrating these tools into high-throughput screening and bioreactors will be a key step toward improving predictability and performance in industrial bioprocesses.

09 BIOMASS FUELS↗

A consensus mathematical model of vaccine-induced antibody dynamics for multiple vaccine platforms and pathogens

Introduction: Vaccine platforms used in successful, licensed vaccines have varied among pathogens. However, antibody level is still the main clinical correlate of protection in most approved vaccines. Decisions as to the best vaccine platform to pursue for a given pathogen may be informed through improved understanding of the process of antibody generation and its temporal dynamics, as well as the relationship between these processes and the type of vaccine. Methods: We have analyzed the dynamics of antibody generation for different vaccine platforms against diverse pathogens, and developed a consensus mathematical model that captures antibody dynamics across these diverse systems. Initially, the model was fitted to a rich dataset of antibody and immune cell concentrations in a SARS-CoV-2 vaccine experiment. We then used concepts from machine learning, such as transfer learning, to apply the same model to a variety of systems, involving different pathogens, vaccine platforms, and booster dose use/timing, fixing most parameter values relating to the dynamics of the immune system. Results: The model includes B cell proliferation and differentiation, as well as the generation of plasma cells, which secrete large amounts of antibody, and memory B cells. Overall, the model describes antibody generation in all systems tested well and shows that the main differences across platforms are related to the dynamics of antigen presentation. Discussion: This model can be used to predict antibody generation in pairs of vaccine platform/pathogen, allowing for the use of in silico results to narrow down experimental burden in vaccine development.

59 BASIC BIOLOGICAL SCIENCES↗

State-Selective Double Photoionization of Atomic Carbon and Neon

Double photoionization (DPI) allows for a sensitive and direct probe of electron correlation, which governs the structure of all matter. For atoms, much of the work in theory and experiment that informs our fullest understanding of this process has been conducted on helium, and efforts continue to explore many-electron targets with the same level of detail to understand the angular distributions of the ejected electrons in full dimensionality. Expanding on previous results, we consider here the double photoionization of two 2p valence electrons of atomic carbon and neon and explore the possible continuum states that are connected by dipole selection rules to the coupling of the outgoing electrons in 3P, 1D, and 1S initial states of the target atoms. Carbon and neon share these possible symmetries for the coupling of their valence electrons. Results are presented for the energy-sharing single differential cross section (SDCS) and triple differential cross section (TDCS), further elucidating the impact of the initial state symmetry in determining the angular distributions that are impacted by the correlation that drives the DPI process.

Yip, Frank L. (ORCID:000000025409495X)↗

A Multi-Dimensional Benefit Assessment of Automated Mobility Platforms (AMP) for Large Facilities: Mobility, Energy, Equity, and Facility Management & Design

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability - both of which are important metrics often overlooked during the engineering design process. Therefore, to evaluate systems and inform critical near- and long-term decisions more effectively, a holistic evaluation framework is proposed focused on four key areas: (1) mobility, with emphasis on travel time and accessibility within an airport, (2) environment, focused on energy consumption and greenhouse gas (GHG) emissions associated with intra-airport mobility, (3) equity, specifically to the PRM community, but with an eye to the whole of society, and (4) built environment, or the fundamental changes in building design enabled by different mobility systems for larger and more flexible, functional, and energy-efficient structures. Below, AMPs are defined, and each metric is discussed further, all with a focus on airport mobility.

ADVANCED PROPULSION SYSTEMS↗

Source apportionment of VOCs, IVOCs and SVOCs by positive matrix factorization in suburban Livermore, California

Abstract. Gas- and particle-phase molecular markers provide highly specific information about the sources and atmospheric processes that contribute to air pollution. In urban areas, major sources of pollution are changing as regulation selectively mitigates some pollution sources and climate change impacts the surrounding environment. In this study, a comprehensive thermal desorption aerosol gas chromatograph (cTAG) was used to measure volatile, intermediate-volatility and semivolatile molecular markers every other hour over a 10 d period from 11 to 21 April 2018 in suburban Livermore, California. Source apportionment via positive matrix factorization (PMF) was performed to identify major sources of pollution. The PMF analysis identified 13 components, including emissions from gasoline, consumer products, biomass burning, secondary oxidation, aged regional transport and several factors associated with single compounds or specific events with unique compositions. The gasoline factor had a distinct morning peak in concentration but lacked a corresponding evening peak, suggesting commute-related traffic emissions are dominated by cold starts in residential areas. More monoterpene and monoterpenoid mass was assigned to consumer product emissions than biogenic sources, underscoring the increasing importance of volatile chemical products to urban emissions. Daytime isoprene concentrations were controlled by biogenic sunlight- and temperature-dependent processes, mediated by strong midday mixing, but gasoline was found to be the dominant and likely only source of isoprene at night. Biomass burning markers indicated residential wood burning activity remained an important pollution source even in the springtime. This study demonstrates that specific high-time-resolution molecular marker measurements across a wide range of volatility enable more comprehensive pollution source profiles than a narrower volatility range would allow.

54 ENVIRONMENTAL SCIENCES↗

GENESPACE tracks regions of interest and gene copy number variation across multiple genomes

The development of multiple chromosome-scale reference genome sequences in many taxonomic groups has yielded a high-resolution view of the patterns and processes of molecular evolution. Nonetheless, leveraging information across multiple genomes remains a significant challenge in nearly all eukaryotic systems. These challenges range from studying the evolution of chromosome structure, to finding candidate genes for quantitative trait loci, to testing hypotheses about speciation and adaptation. Here, we present GENESPACE, which addresses these challenges by integrating conserved gene order and orthology to define the expected physical position of all genes across multiple genomes. We demonstrate this utility by dissecting presence–absence, copy-number, and structural variation at three levels of biological organization: spanning 300 million years of vertebrate sex chromosome evolution, across the diversity of the Poaceae (grass) plant family, and among 26 maize cultivars. The methods to build and visualize syntenic orthology in the GENESPACE R package offer a significant addition to existing gene family and synteny programs, especially in polyploid, outbred, and other complex genomes.

59 BASIC BIOLOGICAL SCIENCES↗

Machine Learning Approaches for Nuclear Material Accounting Data from Irradiation and Reprocessing

We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.

Drescher, Adam↗

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗

Thermal energy storage apparatus, controllers and thermal energy storage control methods

Thermal energy storage apparatus, controllers and thermal energy storage control methods are described. According to one aspect, a thermal energy storage apparatus controller includes processing circuitry configured to access first information which is indicative of surpluses and deficiencies of electrical energy upon an electrical power system at a plurality of moments in time, access second information which is indicative of temperature of a thermal energy storage medium at a plurality of moments in time, and use the first and second information to control an amount of electrical energy which is utilized by a heating element to heat the thermal energy storage medium at a plurality of moments in time.

Hammerstrom, Donald J.↗

Leak Detection and Sensor Importance Within a Solvent Extraction Process Abstract

In anticipation of the Special Nuclear Material test bed (Beartooth), Idaho National Laboratory has developed a smaller, multi-sensor system for analyzing the solvent extraction process. These systems will allow for research into nuclear fuel processing operations. The multi-sensor system consists of a row of centrifugal contactors and allows for measurement sources that are not traditionally used in the solvent extraction process to be explored including temperature, vibration, acoustics, pH, color, flow, and motor current. Currently, the solvent extraction process is very labor intensive and requires vigilant operators to identify the occurrence of leaks, which can be common during startup or after any change to the system. This study aims to locate leaks using non-traditional measurement sources then to identify which signals were of greatest importance in making this classification using Local Interpretable Model-agnostic Explanations. These results can be used to help solvent extraction process operators detect leaks and to inform future test beds designers to which sensors contain relevant, actionable information in this scenario.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗