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At least 37 records · Page 2

New Particle Formation and Growth in the Houston Atmosphere During TRACER (Final Report)

From 2020-2025, researchers from UC Irvine, UC Riverside, and Colorado State University collaborated on a Department of Energy-funded project to understand how airborne particles form and grow in urban atmospheres, conducting an intensive field campaign in Houston, Texas during summer 2022. Using advanced instruments to measure gas-phase chemicals, particle composition, and a specialized chamber to study particle growth, the team discovered that sulfur-containing compounds from industrial and power plant emissions are the dominant driver of new particle formation in Houston, with particles typically forming locally in the city and growing as air moves away in the urban plume. The research revealed an important methodological insight: measurements from fixed ground stations can be misleading when interpreting how particles actually evolve as air masses move, which has significant implications for how scientists worldwide interpret atmospheric observations. These findings improve understanding of urban air quality and help reduce uncertainties in climate models, since these particles play critical roles in cloud formation and Earth's radiation balance, while also providing detailed information about ultrafine particle composition relevant to public health. The project trained three doctoral students, developed enhanced computer models for urban particle formation, and made all data publicly available through the DOE Atmospheric Radiation Measurement data archive for use by the broader scientific community.

54 ENVIRONMENTAL SCIENCES

Insights into the Oxidation Mechanism of Vivianite to Metavivianite from First-Principles Calculations

Vivianite, a hydrous ferrous iron-phosphate mineral (Fe 3 (PO 4 ) 2 ·8H 2 O), readily oxidizes in contact with air yielding the less hydrous mixed-valent iron-phosphate mineral metavivianite. This topotactic transformation nominally occurs by oxidative dehydrogenation in which outgoing electrons from the iron sublattice are charge compensated by hydrolysis of structural water. However, the details of this internal charge balancing mechanism that allows the structure to remain electrostatically stable remain unknown. Here, in this study, we use density functional theory (DFT) calculations and ab initio thermodynamics (AIT) to evaluate the energetics of this process in terms of hydrogen release as a function of environmental variables such as partial pressure and temperature. The results show a thermodynamic driving force for vivianite phase transformation as oxidation progresses that is triggered by its rigid structure that has a limited accommodation for hydrogen vacancies. In contrast, metavivianite has a more flexible lattice and hydrogen bond network that stabilizes these hydrogen defects. Metavivianite is shown to be a stable intermediate for 66% residual Fe 2+ down to 33% Fe 2+ , below which other phases/structures such as santabarbarite should be more thermodynamically favorable. Our study provides a basis for experimental tests of our mechanistic findings and helps fill a basic knowledge gap about the solid-state process that defines how vivianite interacts with its surrounding environment.

Sassi, Michel [Pacific Northwest National Laborato

Hydrogen from Carbonaceous Waste Material - Hydrogen Fuel Cells Prize Phase 2 Voucher: Cooperative Research and Development (Final Report)

NLR conducted a conceptual design study for scaling up biomass conversion technology from Green Fortress Engineering (GFE). GFE has proprietary technology where cellulosic biomass is thermally converted to a tar-free syngas. A ceramic membrane separation unit (MSU) previously developed with NLR can extract high-purity hydrogen from the syngas. The energy content of the retentate stream is sufficient to power the process with a gas-powered genset. Design details including mass and energy balances, process and instrumentation diagrams (P&ID), and major equipment schedules were delivered.

08 HYDROGEN

Traceable and Scalable Food Balance Sheets from Agricultural Commodity Supply and Utilization Accounts (2010–2022)

Abstract The Food Balance Sheets (FBS), compiled by the Food and Agriculture Organization (FAO), serve as a cornerstone dataset for studies on agricultural development, food security, and dietary health, providing a broad overview of global and regional food systems. However, its limited transparency and scalability hinder its application in empirical analysis and multisector dynamic modeling. Here, we present a traceable Food Balance Sheets (T-FBS) dataset, developed from detailed Supply Utilization Accounts (SUA) using a novel Primary Commodity equivalent (PCe) aggregation approach. This framework enables the aggregation of commodity flows along supply chains while ensuring consistency and balance across multiple dimensions. The T-FBS dataset includes 57 PCe commodities across 195 regions for the period 2010–2022, consolidated from over 500 SUA products. While T-FBS closely aligns with FAO-FBS at aggregate levels for dietary energy and macronutrients, it identifies key uncertainties in other elements (e.g., feed, trade, stocks). By enhancing methodological transparency, traceability, and scalability, T-FBS strengthens the robustness of food system studies and fosters future research and collaboration within the open-source community.

agriculture

Control Boundary Analysis for Liquid-Fueled Molten Salt Reactors

The US Nuclear Regulatory Commission (NRC) will likely require license applicants for liquid-fueled molten salt reactors (MSRs) with circulating fuel to submit a nuclear material control and accounting (MC&A) plan or provide a detailed MC&A program description for the facility. In liquid-fueled MSRs with special nuclear material (SNM) in bulk form (i.e., not in discrete items) and with rapidly changing quantities due to fuel transmutation and depletion, a novel MC&A approach is needed because traditional nuclear material accounting methods with material balance evaluations will not be sufficient. This report details the continued efforts carried out at Oak Ridge National Laboratory (ORNL) during FY 2025 to develop a distinct MC&A approach suitable specifically for domestic safeguards of the first-of-a-kind MSRs. These efforts are built on previous ORNL efforts reported in ORNL/SPR-2023/3181 and ORNL/SPR-2024/3555.

22 GENERAL STUDIES OF NUCLEAR REACTORS

A Rhenium Bis -tetramethylphenanthroline Catalyst for CO 2 Reduction to Formate

Catalytic CO 2 reduction reactions featuring high selectivity toward formate are relatively rare. In some homogeneous molecular CO 2 -reducing electrocatalysis, using triethylamine (TEA) and isopropanol (IPA) as additives improves catalytic performance in producing formate. In this paper, we investigate whether the rhenium(I) bis-diimine dicarbonyl complexes, cis-[Re(N^N) 2 (CO) 2 ] + , where N^N is 2,2’-bipyridine ([1] + ) or 3,4,7,8-tetramethyl-1,10-phenanthroline ([2] + ), are capable of electrocatalytically reducing CO 2 to formate in acetonitrile containing TEA and IPA. Catalyst [1] + was ineffective at CO 2 reduction, yielding formate quantities comparable to those produced in experiments without the catalyst. Catalyst [2] + , however, is a promising electrocatalyst for the CO 2 reduction reaction in the presence of TEA and IPA, with formate being produced in millimolar concentrations (10.5 mM), as detected by 1 H NMR spectroscopy after 6 h electrolysis (formate Faradaic efficiency = 11%, with the major balance going to H 2 ). Upon more detailed examination, [2] + exhibited a turnover frequency (TOF) of 12 s –1 for formate, comparable to other leading molecular catalysts that competently execute this reduction. Combinations of spectroscopy, electrochemistry, and theory were used to better understand the mechanism of CO 2 reduction by [2] + . Fourier transform infrared spectroelectrochemical (FTIR-SEC) data provided no evidence for CO ligand dissociation or substitution upon one- and two-electron reduction of [2] + , suggesting that a mechanism distinct from one that is metal-hydride-based is operative in catalysis. Computational studies guide mechanistic investigations toward the proposed formation of a hydrophenanthroline-based intermediate responsible for hydride transfer to CO 2 and electrocatalytic formate production from [2] + .

Beverages

TRANSP integrated modeling code for interpretive and predictive analysis of tokamak plasmas

This paper provides a comprehensive review of the TRANSP code, a sophisticated tool for interpretive and predictive analysis of tokamak plasmas, detailing its major capabilities and features. It describes the equations for particle, power, and momentum balance analysis, as well as the poloidal field diffusion equations. The paper outlines the spatial and time grids used in TRANSP and details the equilibrium assumptions and solvers. Various models for heating and current drive and radiation, including updates to the NUBEAM model, are discussed. The handling of large-scale events such as sawtooth crashes and pellet injections is examined, along with the predictive capabilities for advancing plasma profiles. The integration of TRANSP with the ITER Integrated Modeling and Analysis Suite (IMAS) is highlighted, demonstrating enhanced data access and analysis capabilities. Additionally, the paper discusses best practices and continuous integration techniques to enhance TRANSP's robustness. The suite of TRANSP tools, designed for efficient data analysis and simulation, further supports the optimization of tokamak operations and coupling with other tokamak codes. Continuous development and support ensure that TRANSP remains a major code for the analysis of experimental data for controlled thermonuclear fusion, maintaining its critical role in supporting the optimization of tokamak operations and advancing fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Hybrid Dynamic Modeling of Smart Inverter

This letter proposes a novel hybrid method for assessing grid-connected three-phase converter interfaced resources (CIR) dynamics with the IEEE standard 1547-2018 grid support functions (GSFs), which blends physics and data-driven techniques. First, the letter derives an analytical model of a CIR to represent the internal physics and data-driven model (DDM) using a system identification algorithm to represent the rest of the dynamics, including the GSF. The derived hybrid model combines the analytical model of CIR and DDM, which balances accuracy and flexibility and is compared with the detailed switched model. Furthermore, the efficacy of the proposed approach to represent the advanced CIR dynamics is substantiated by power hardware-in-the-loop experiment data where real measurements from a commercial CIR are used to cross-validate the proposed approach. Furthermore, the results indicate that despite simple, the hybrid model accurately reproduces the dynamics of the detailed CIR model with an acceptable accuracy.

Data-driven model

How Inverter-Based Resources (IBRs) Affect Protection Relay Elements

This presentation starts with the details of IEEE 2800-2022 requirements of IBR for balanced and unbalanced faults. Then, it shows how to design a droop based GFM control to be IEEE 2800-2022 compliant. An performance evaluation is carried out to see if three OEM GFM inverters 2800-2022 compliant or not. And finally we show how IEEE 2800-2022 complaint and non-compliant GFM inverter will impact the transmission line protection elements, such as directional element and FID. Finally, recommendations are made if the GFM is not IEEE 2800-2022 compliant to disable the protection elements that rely on reliable and regulated negative sequence current.

24 POWER TRANSMISSION AND DISTRIBUTION

Convection-Permitting Ensembles of an Isolated Mountain Thunderstorm during RELAMPAGO/CACTI

Abstract The north–south-oriented Sierras de Córdoba (SDC) ridge in central Argentina is noted for initiating thunderstorms that may grow into intense mesoscale convective systems (MCSs). It also initiates more isolated, shorter-lived cells under weaker synoptic forcing. These cells are less impactful than MCSs but may be difficult to predict in convective-scale numerical weather prediction (NWP) due to their strong sensitivities to subgrid and partially resolved processes. To study the mechanisms and predictability of such cells, convection-permitting ensemble simulations were conducted of an isolated, diurnally forced SDC thunderstorm during Cloud, Aerosol, and Complex Terrain Interactions (CACTI)/Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO). The rich observational data facilitated detailed ensemble verification, where dry biases in the surface energy balance and soil moisture were identified. These biases promoted rapid removal of convective inhibition and an early onset of precipitating cells over the SDC that were shallower and weaker than the observed cell. Correction, and then overcorrection, of the soil moisture bias in two successive ensembles was required to rectify the surface energy balance and improve the representation of the SDC cell. Nevertheless, substantial ensemble variability in convective precipitation was found, with some members producing more widespread convection than observed and others producing no deep convection at all. This variability was largely explained by a combination of thermodynamic and dynamic mechanisms, dominated by a positive sensitivity of convective precipitation to preconvective moist instability over the ridge. Secondary sensitivities were found to low-level upward mass flux and midlevel cross-barrier winds, the latter of which caused gravity waves with elevated downdrafts that tended to suppress incipient clouds.

Lopez, Andres [Department of Atmospheric and Ocean

A Bottom-Up Cost Estimation Tool for Nuclear Microreactors

The rising interest in nuclear microreactors has highlighted the need for comprehensive technoeconomic assessments. However, the scarcity of publicly available designs and cost data has posed significant challenges. To address this issue, the Microreactor Optimization Using Simulation and Economics (MOUSE) tool is developed. MOUSE is a tool that integrates nuclear microreactor design with reactor economics. The design calculations encompass core simulations using the OpenMC Monte Carlo Particle Transport Code [romano2015], along with simplified balance of plant calculations. On the economic side, MOUSE provides detailed bottom-up cost estimates, calculating both the total capital cost and the levelized cost of energy for first-of-a-kind and nth-of-a-kind microreactors. The cost estimation correlations are developed using data from the MARVEL project and additional literature sources. MOUSE has released as an open-source tool on GitHub (MOUSE Tool). By combining design calculations with cost equations, MOUSE enables users to evaluate the impact of various technological consideration, advanced moderators, design changes, material/fuel changes, and geometry modifications—as well as economic parameters like interest rates and construction duration. This comprehensive framework can guide stakeholders towards technological solutions that enhance microreactor competitiveness. Additionally, powered by the WATTS toolkit [romano2022], MOUSE supports optimization studies, parametric analyses, and uncertainty calculations/propagation. Currently, preconceptual designs of three microreactor types are included in MOUSE: a liquid metal thermal microreactor (LTMR), gas cooled TRISO-fueled microreactor (GCMR) and heat-pipe TRISO fueled microreactor (HPMR). To showcase its ability, MOUSE was used to conduct detailed bottom-up cost estimates for the first of a kind (FOAK) and Nth of a kind (NOAK) of the following microreactors • A 20MWt LTMR that is built on the ongoing MARVEL demonstration at Idaho National Laboratory (INL) • A 15 MWt GCMR that was designed to be more representative of the typical commercial microreactor • A 7 MWt HPMR that was built on previous work (Choi 2024) The The reader should note that these three designs and corresponding cost estimates are examples to demonstrate the MOUSE capability. The designs are pre-conceptual, the reactor designs were not optimized, and the cost estimates were developed with incomplete information. Additionally, stakeholders might be interested in a variety of designs that may differ from the examples provided in this report. The MOUSE tool can also be used to study how design choices affect economics. To demonstrate its capability, MOUSE was used conduct parametric studies such as examining the economic impact of the reflector's material and thickness, the moderator's booster material and dimensions, fuel composition and enrichment, core size, and power level. Several insights were gained from these parametric studies.

Hanna, Botros

Solid oxide electrolysis cell and stack testing best practices

Solid oxide electrolyzer (SOE) technology is an emerging method for hydrogen production, noted for its superior electrical efficiency. Despite the significant progress made in recent years, the broad development of SOE technology is often constrained by the necessary and extensive "skill of the craft" required to successfully test simple single cell test articles. This may be linked to the dearth of practical and pragmatic guidance within the literature for safe, reliable, and performant test equipment and test procedures. Researchers at the Idaho National Laboratory (INL) have been actively testing SOEs ranging from button cells to stacks up to 500 kW, in collaboration with industry and other national laboratories. Based on operational experience, INL has developed system design procedures that ensure safe and reliable operation of SOE systems with the level of support required for each test. This paper presents key aspects of SOE stack and system testing, including safe design procedures, balance of plant components design, and specific implementations at INL. Practical design details of reactants, heat, and power management are presented along with lessons learned from the SOE test facility operations at INL.

08 HYDROGEN

Poincaré beams from a free electron laser

Poincaré beams are light beams that have spatially inhomogeneous polarization structure that spans a finite portion of the Poincaré sphere. This feature bestows the beams with intriguing topological properties and has led to a surge in research on their fundamental characteristics, their controlled generation and on emerging applications. Here we present an experimental demonstration of a Poincaré beam generated in the extreme ultraviolet (16.7 nm) at the FERMI free electron laser (FEL). The ‘star’ type Poincaré beam is generated by exploiting the phase and intensity structure intrinsic to FEL radiation without relying on optical elements. Here, we controlled the spatial polarization distribution through a precise overlap and power balance between two FEL pulses, each with different transverse phase distributions and orthogonal circular polarizations. The spatial polarization structure was mapped in detail and shows extensive coverage of the Poincaré sphere, in agreement with analytic predictions. This method of in situ Poincaré beam production in FELs enables straightforward flexibility in the orientation and balance of polarization states, and can readily be extended to other vector beams and to shorter wavelengths enabling novel science applications in modern light sources.

Morgan, Jenny [SLAC National Accelerator Laborator

Spatially and Temporally Detailed Water and Carbon Footprints of U.S. Electricity Generation and Use

Electricity generation in the United States entails significant water usage and greenhouse gas emissions. However, accurately estimating these impacts is complex due to the intricate nature of the electric grid and the dynamic electricity mix. Existing methods to estimate the environmental consequences of electricity use often generalize across large regions, neglecting spatial and temporal variations in water usage and emissions. Consequently, electric grid dynamics, such as temporal fluctuations in renewable energy resources, are often overlooked in efforts to mitigate environmental impacts. The U.S. Department of Energy (DOE) has initiated the development of resilient energyshed management systems, requiring detailed information on the local electricity mix and its environmental impacts. This study supports DOE's goal by incorporating geographic and temporal variations in the electricity mix of the local electric grid to better understand the environmental impacts of electricity end users. We offer hourly estimates of the U.S. electricity mix, detailing fuel types, water withdrawal intensity, and water consumption intensity for each grid balancing authority through our publicly accessible tool, the Water Integrated Mapping of Power and Carbon Tracker (Water IMPACT). While our primary focus is on evaluating water intensity factors, our dataset and programming scripts for historical and real-time analysis also include evaluations of carbon dioxide (equivalence) intensity within the same modeling framework. This integrated approach offers a comprehensive understanding of the environmental footprint associated with electricity generation and use, enabling informed decision-making to effectively reduce Scope 2 water usage and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

Impact of super-Gaussian electron distributions on plasma K-shell emission

Electron distributions in laser-produced plasmas will be driven toward a super-Gaussian distribution due to inverse bremsstrahlung absorption [Langdon, Phys. Rev. Lett. 44, 575 (1980)]. Both theoretical and experimental evidence suggest that fundamental plasma properties are altered by the super-Gaussian distribution. Here, this paper examines how the super-Gaussian distribution affects the ionization balance and K-shell emission of atomic plasmas, utilizing approximate formulas and detailed collisional-radiative simulations. While the impact on plasma ionization is small, K-shell spectra can be significantly modified. Based on these findings, we demonstrate that K-shell spectroscopy can be used to infer super-Gaussian or other similar nonequilibrium electron distributions.

Atomic spectra

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost

A novel approach to increase accuracy in remotely sensed evapotranspiration through basin water balance and flux tower constraints

Remote sensing-derived evapotranspiration (RSET) products capture the spatiotemporal variations of evapotranspiration (ET) from field to basin scales with unprecedented details. However, their accuracy varies across RSET estimation methods and diverse hydroclimate regions. While ET modeling efforts to account for biophysical processes and controlling parameters have made good progress in recent years, a parallel approach of integrating in-situ ET with RSET could reduce biases in RSET products. Basin water balance ET (WBET) and flux tower ET are widely applied to evaluate RSET accuracy, yet such ET measurements are rarely used for RSET bias corrections, especially for large area applications. To address this issue, we propose a novel approach: the water balance equivalence (WABE) method, which generates spatially continuous WBET for correcting biases in RSET products. The WABE method computes synthetic WBET by integrating observed WBET and flux tower-derived FLUXCOM ET, which fills the spatial gaps of observed WBET and generates a spatially continuous WBET dataset. Synthetic WBET (2002–2015 annual average) of eight-digit hydrologic unit code (HUC8) basins across the conterminous United States (CONUS), constituting 44 % (887 out of 2035 basins) of CONUS basins, was determined within 2.0 % (RMSE = 12 %) of observed WBET at CONUS and between 1–12 % (RMSE = 3–33 %) across 18 regions in CONUS. With WABE-based bias corrections, the overall annual bias of RSET decreased from 10 % (RMSE = 34 %) to 6 % (RMSE = 26 %) across 37 flux tower sites. The WABE method offers a new approach for RSET accuracy improvement and shows great promise for large area implementations with a potential to yield substantial benefits for building accurate basin water budgets and water management decisions.

Khand, Kul

CatTestHub: A benchmarking database of experimental heterogeneous catalysis for evaluating advanced materials

The ability to quantitatively compare newly evolving catalytic materials and technologies is hindered by the widespread availability of catalytic data collected in a consistent manner. While certain catalytic chemistries have been widely studied across decades of scientific research, quantitative comparisons based on literature information is hindered by variability in reaction conditions, types of reported data, and reporting procedures. Here, we present CatTestHub, an open-access database dedicated to benchmarking experimental heterogeneous catalysis data. Combining systematically reported catalytic activity data for selected probe chemistries, with relevant material characterization and reactor configuration information, the database provides a collection of catalytic benchmarks for distinct classes of active site functionality. Through key choices in data access, availability, and traceability, CatTestHub seeks to balance the fundamental information needs of chemical catalysis and the FAIR data design principles. Details of the database architecture and the means through which to navigate it are presented, highlighting examples of catalytic insights readily drawn from the available benchmarking data. In its current iteration, CatTestHub spans over 250 unique experimental data points, collected over 24 solid catalysts, that facilitated the turnover of 3 distinct catalytic chemistries. Here, a roadmap is presented through which to expand the open-access platform that serves as a community wide benchmark, primarily through continuous addition of kinetic information on select catalytic systems by members of the heterogeneous catalysis community at large.

Benchmark