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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuously monitoring fence-line sensors

The dependable reporting of methane (CH 4 ) emissions from point sources, such as fugitive leaks from oil and gas infrastructure, is important for profit maximization (retaining more hydrocarbons), evaluating climate impacts, assessing CH 4 fees for regulatory programs, and validating CH 4 intensity in differentiated gas programs. Currently, there are disagreements between emissions reported by different quantification techniques for the same sources. It has been suggested that downwind CH 4 quantification methods using CH 4 measurements on the fence line of production facilities could be used to generate emission estimates from oil and gas operations at the site level, but it is currently unclear how accurate the quantified emissions are. To investigate the accuracy of downwind methods, this study uses fence-line simulated data collected during controlled-release experiments as input for a non-standard closed-path eddy covariance (EC), the Gaussian plume inverse model (GPIM), and the backward Lagrangian stochastic (bLs) model in a range of atmospheric conditions. This study's EC attempt was unsuccessful due to data collection and instrumentation issues, resulting in invalid results characterized by underestimated emissions, large negative fluxes, and cospectra/ogives that deviated from their ideal shapes. Consequently, the EC results could not be compared with the GPIM and bLS model. The bLs model demonstrated the highest accuracy for single-release single-point emissions, though it exhibited greater uncertainty than GPIM under multi-release conditions. Across the GPIM and bLs model, the most reliable quantification was achieved with 15 min averaging and a narrow 5° wind sector range. Although EC was limited in this context, future studies should consider employing a standard EC system and further optimizing GPIM and bLs approaches – particularly for complex multi-source scenarios – to enhance quantification accuracy and reduce uncertainty.

03 NATURAL GAS↗
DOE OSTI2025

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Revival and Technology Transfer of 90SrTiO3 Production for Heat Source Applications

Demand for radioisotope power systems (RPS) appears to be on the rise, and it is unlikely that this new demand can be met by plutonium-238. As a result, new heat source designs are under development. One such design is Z1. Z1 is a strontium-90 demonstration heat source developed by Zeno Power Systems in collaboration with the University of Dayton Research Institute and the Pacific Northwest National Laboratory. SrTiO3 was chosen as the fuel form for Z1. SrTiO3 was used to produce dozens of terrestrial RPS decades ago. While this indicates the technology is proven, the skill and experience necessary to effectively produce SrTiO3 has been lost. Recapturing SrTiO3 production technology therefore became necessary. Development started with non-radioactive surrogate experiments using natural strontium. This work showed that the old Oak Ridge flowsheets for SrTiO3 production are quite robust, but some critical pieces of the technology are left out of the old documentation. Specifically, particle sizes of the reagents are critical to producing a phase pure SrTiO3. If the reagent particles are not the right size, then a significant Sr3Ti2O7 phase impurity is observed. This phase impurity was proven to be the result of an incomplete reaction between the strontium and titanium precursors. This technology was transferred to Pacific Northwest National Laboratory where the technology was adapted for use in a hot cell. With the adaptations complete, this technology was used to produce the fuel for Z1 late last year. This represents the first new heat source design produced in the U.S. in over 40 years.

90Sr, strontium titanate, SrTi03, RTG, Radioisotop↗
DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗
DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗
DOE OSTI2026

First constraints on causal sources of primordial gravitational waves from BICEP/Keck, SPTpol, SPT-3G, Planck and WMAP $B$-mode data

Non-inflationary sources of gravitational waves in the early Universe generically predict causality-limited tensor power spectra at low frequencies. We report the first-ever constraints on such sources based on cosmic microwave background (CMB) $B$-mode polarization measurements. Using data from BICEP/Keck, SPTpol, SPT-3G, Planck, and WMAP, we constrain the amplitude of an early causal tensor (ECT) power spectrum parameterized by $r_{ect}$, the ratio of causal tensor power to total scalar power at $k~=~0.01$ Mpc$^{-1}$, and obtain a 95% CL upper limit of $r_{ect}<$ 0.0077. Since $r_{ect}$ can easily be related to the parameters of a given theory, our bound robustly constrains a broad class of well-motivated gravitational wave sources in the early universe, including first-order cosmological phase transitions, enhanced small-scale density perturbations, and various topological defects. Finally, we translate our limit into a bound on the present-day energy density in gravitational waves at ultra-low frequencies otherwise inaccessible to traditional gravitational wave detection strategies, including pulsar timing arrays, interferometers, and resonant cavities.

Zebrowski, Jessica A. [Fermilab; Chicago U., KICP]↗
DOE OSTI2025

The HIBEAM instrument at the European spallation source

The European spallation source (ESS) will be the world’s brightest neutron source and will open a new intensity frontier in particle physics. The HIBEAM collaboration aims to exploit the unique potential of the ESS with a dedicated ESS instrument for particle physics which offers world-leading capability in a number of areas. The HIBEAM program includes the first search in thirty years for free neutrons converting to antineutrons and searches for sterile neutrons, ultralight axion dark matter and nonzero neutron electric charge. This paper outlines the capabilities, design, infrastructure, and scientific potential of the HIBEAM program, including its dedicated beamline, neutron optical system, magnetic shielding and control, and detectors for neutrons and antineutrons. Additionally, we discuss the long-term scientific exploitation of HIBEAM, which may include measurements of the neutron electric dipole moment and precision studies of neutron decays.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

An Open Source Perovskite Solar Cell Curve Tracer

When developing systems for perovskite solar cells (PSCs), it is important to have a testing platform that closely resembles your deployed systems. While developing a 1 U CubeSat, the Big Red Sat-1 at the University of Nebraska-Lincoln, we found a lack of passive curve tracing instrumentation, which we needed for our mission. To that end, we developed a benchtop passive curve tracer that leverages the Ossila Solar Simulator as an AM1.5 light source. This device utilizes a ladder of switched resistors and a precision voltage and current measurement to achieve the curve tracing. It also integrates a common-anode multiplexer to switch through multipixel PSCs. Finally, the solar cell holder is separate from the main measurement system, so various substrates sizes and pixel counts can be supported. This system is tested using various PSCs. It has been open sourced to enable reuse in future systems that may benefit from the lower power consumption and flight heritage.

14 SOLAR ENERGY↗
DOE OSTI2025

EGS Collab Experiment 2: Continuous Active Source Seismic Monitoring (CASSM)

The dataset contains continuous active-source seismic monitoring (CASSM) data collected during EGS Collab Experiment 2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to investigate enhanced geothermal systems through high-pressure fluid injections at depths of 1200-1500 meters. The seismic monitoring system included 16 three-component piezoelectric accelerometers and 24 hydrophones installed in boreholes around the injection zones, recording signals from piezoelectric seismic sources. Data were acquired using both continuous and triggered recording systems, with sampling rates of up to 100 kHz. The raw data are organized by timestamps and stored in .dat format, with accompanying log files. Calibration certificates for selected accelerometers are provided to aid in correcting sensor responses, though users are advised to consider possible effects of enclosures and installation on sensor performance. Users are strongly advised to consult the accompanying report, which outlines the experimental setup, data acquisition, sensor specifications, and recording systems.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Development of electron source feedback for enhanced X-ray beam stability at NSLS-II

Future synchrotron light sources are being designed to deliver significantly higher brightness and coherence, enabling faster scanning and more advanced imaging techniques. However, realizing these capabilities requires improved X-ray beam stability, as vibrations directly limit measurement accuracy and image quality. At the NSLS-II Hard X-ray Nanoprobe (HXN), a local mechanical feedback system mitigates low-frequency motion but provides only limited suppression of dominant vibrations at 27 Hz and 120 Hz. To address this limitation, this work explores the use of the electron beam itself as the actuator for feedback by integrating X-ray beam position monitor signals into the fast orbit feedback system through a dedicated electrometer. Experimental results show that this approach effectively suppresses the dominant vibration peaks and enhances stability at the focusing point. Benchmark ptychography measurements further confirm that electron-beam-based feedback reduces background fluctuations and mitigates vibration-induced artifacts under fast-scanning conditions. These results establish the feasibility of using the electron beam as a feedback actuator for next-generation synchrotron applications and provide an experimental assessment of its potential and limitations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advanced defrosting techniques in air source heat pumps: A review of vapor injection, thermal energy storage, and experimental frost accumulation data

Electrification is a critical step for reducing greenhouse gas emissions from heating. Air source heat pumps (ASHPs) are a promising alternative to fossil fuel-based systems due to their high coefficients of performance (COP), dual heating and cooling capability, and lower carbon footprint. However, for ASHPs to achieve widespread adoption, they must operate reliably across all climates, including cold regions. Additionally, defrosting techniques should be energy efficient and minimally disruptive to indoor comfort. Vapor injection (VI) technology can address the high-pressure and high-temperature lift challenges encountered in low ambient conditions. More recently, in addition to enhancing heating performance, VI has also been shown to improve the speed and efficiency of reverse cycle defrosting. Likewise, thermal energy storage (TES) has steadily gained attention for its ability to serve as an auxiliary heat source during both normal operation and defrosting. This review analyzes the benefits and limitations of VI- and TES-assisted defrosting approaches. While both technologies show strong potential individually, no studies to date have explored their combined use in ASHP systems. Additionally, to support continued development of defrosting strategies, both in modeling and experimental work, it is critical to establish frost accumulation data under a range of operating conditions. By compiling the available data from the literature, this paper also highlights the limited availability of such experimental data and the wide variation in frosting and defrosting durations and termination criteria, which are often influenced by system design and test setups.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Effect of a transparent water-cooled cathode on the neutron production rate in the glow discharge-type fusion neutron source

In glow discharge-type deuterium–deuterium fusion neutron sources, fusion reactions occurring on the cathode surface contribute significantly to the neutron production rate (NPR); therefore, cathode design plays a crucial role in enhancing NPR. Although the NPR generally increases with discharge current, deuterium desorption caused by cathode heating tends to stagnate it in the high-current regime. Water cooling has been shown to mitigate this stagnation for nontransparent cathodes, but its effectiveness for transparent cathodes has not been experimentally clarified. Here, in this study, a transparent cathode with active water cooling and a spherical geometry was designed and fabricated using stainless steel tubing. Neutron production experiments were conducted with and without water cooling: with water cooling, applied voltages of 20–40 kV were investigated, while without water cooling, the applied voltage was limited to 25 kV. The results showed that the NPR increased continuously with discharge current without stagnation when water cooling was applied. A maximum NPR of (1.8 ± 0.02) × 10 6 n/s was achieved at 40 kV and 50 mA. Compared with our previously reported disk cathode and nontransparent water-cooled cathode of the same diameter, the transparent water-cooled cathode exhibited a significantly enhanced NPR. These findings indicate that combining cathode transparency with active cooling is an effective strategy for improving neutron production in glow discharge-type fusion neutron sources.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Commissioning a time-gated camera for fast neutron beamline spatial-energy characterization at LANSCE-WNR spallation source

An energy-resolved fast neutron beam imaging diagnostic has been successfully commissioned at the Weapons Neutron Research (WNR) spallation source within the Los Alamos Neutron Science Center (LANSCE) facility. This diagnostic replaces the existing analog phosphor image plates, which integrate across all neutron energies, as well as other particles, with a near-real-time energy-sensitive imaging capability. The system uses a fast plastic scintillator coupled with an intensified CCD camera. Specifically, the Teledyne Pi-MAX4 camera is coupled with either a 4 mm thick Eljen (EJ) 204 or 228 plastic scintillator. These scintillators are most sensitive to the fast neutrons (0.8-800 MeV) directly from the spallation source rather than low energy background radiation. Experimentally, these plastic scintillators were shown to have sufficiently fast decay to differentiate the bright gamma flash from the spallation neutrons. The spatial resolution is dominated by neutron beam divergence, with minimal additional contributions from scatter and light divergence. The system successfully resolved changes in neutron beam characteristics caused by intentional proton steering variations. Additionally, simulations of scintillator light yield as a function of thickness conducted using PHITS (with Scinful-QMD package) found that increasing scintillator thickness from 4 mm to 6 or 8 mm could potentially increase brightness ~ 3x. This may be explored if there is a need to reduce image acquisition time from several minutes to under one minute.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Nearby Sites Show Similar Upwind Sources and Differing Semivolatile Concentrations in Coastal Aerosol Particles

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized aerosol composition using measurements at two sites within 3 km (Scripps Pier and Mt. Soledad) from 15 February 2023 to 14 February 2024. Comparing the two sites shows the strong influence of upwind sources that results in similar monthly compositions at both sites. The seasonal changes in chemical mass concentrations were largely driven by the upwind source regions, with coastal northwesterly back-trajectories occurring 63−65% of the year and bringing submicrometer mass concentrations that were lower than the EPCAPE average for all trajectories at each site. In contrast, refractory black carbon (rBC) and nonrefractory (NR)-organics and nitrate mass concentrations exceeded EPCAPE average concentrations for back-trajectories from urban areas such as Los Angeles-Long Beach. For hourly measurements, NR-organics and non-sea-salt (NSS)-sulfate mass concentrations at Mt. Soledad were correlated strongly (r = 0.73−0.82) to those measured at Scripps Pier, but NR-nitrate was correlated only moderately (r = 0.63). The explanation for the lower correlation of NR-nitrate is both emissions between the sites and semivolatility, with semivolatility accounting for site-to-site changes in daily averages of +0.01 μg m −3 per percentage site-to-site difference in relative humidity and −0.07 μg m −3 per degree Celsius site-to-site difference in temperature. On average, comparing Scripps Pier to Mt. Soledad, NR-nitrate was higher by 29% because of relative humidity and lower by −26% because of temperature. NR-nitrate and rBC mass concentrations at Scripps Pier for nighttime were 13−15% higher than those for daytime because land breezes brought higher inland concentrations. Concentrations of rBC were 52% higher at Mt. Soledad than those measured at Scripps Pier, accompanied by increases in tracers for brake wear because of traffic on the steep roads within 10 m of that site. The implications are that these nearby sites had comparable monthly concentrations of measured components due to their similar backtrajectories, but hourly and daily concentration differences supported quantification of the meteorological effects from relative humidity and temperature on semivolatile NR-nitrate as well as minor differences from land−sea breezes and local emissions.

Aerosols↗
DOE OSTI2025

Demagnetization analysis of an 18 GHz electron cyclotron resonance ion source permanent magnet hexapole

An upgrade of ECR2 at the Argonne Tandem Linac Accelerator System is under way, focusing on increasing the intensity capabilities of the facility. ECR2 is a room temperature electron cyclotron resonance ion source, and the upgrade has strict requirements to retain radial access to the plasma chamber and keep the ion source operating without the use of superconducting magnets. The upgrade design with respect to the magnet arrangement and magnetization vectors has recently been presented [R. C. Vondrasek, J. McLain, and R. H. Scott, J. Phys.: Conf. Ser. 2743 , 012044 (2024)] using the same magnetic material as the current ECR2 hexapole. A thorough exploration of the demagnetization potential of this hexapole was carried out, and the risk of demagnetization was deemed too high, despite the magnetic performance meeting the requirements for the upgrade. Additional permanent magnet materials are considered with their respective performance evaluated. Magnet strength and demagnetization resistance are investigated and optimized with the final room temperature design demonstrating a high temperature transient demagnetization resistance and a radial magnetic field of 1.18 T at the plasma chamber wall. Finally, the simulations of this hexapole suggest that it will be sufficient to optimize intensity with a 14.5 GHz driving frequency and will allow 18 GHz operation, while keeping a high safety margin for maintaining magnet performance.

Argonne Tandem Linac Accelerator System↗
DOE OSTI2025

A multi-scale cognitive interaction model of instrument operations at the Linac Coherent Light Source

The Linac Coherent Light Source (LCLS) is the world’s first x-ray free electron laser. It is a scientific user facility operated by the SLAC National Accelerator Laboratory, at Stanford, for the U.S. Department of Energy. As beam time at LCLS is extremely valuable and limited, experimental efficiency—getting the most high quality data in the least time—is critical. Our overall project employs cognitive engineering methodologies with the goal of improving experimental efficiency and increasing scientific productivity at LCLS by refining experimental interfaces and workflows, simplifying tasks, reducing errors, and improving operator safety and stress. Here, in this study, we describe a multi-agent, multi-scale computational cognitive interaction model of instrument operations at LCLS. Our model simulates the aspects of human cognition at multiple cognitive and temporal scales, ranging from seconds to hours, and among agents playing multiple roles, including instrument operator, real time data analyst, and experiment manager. The model can roughly predict impacts stemming from proposed changes to operational interfaces and workflows. Example results demonstrate the model’s potential in guiding modifications to improve operational efficiency. We discuss the implications of our effort for cognitive engineering in complex experimental settings and outline future directions for research. The model is open source, and the videos of the supplementary material provide extensive detail.

47 OTHER INSTRUMENTATION↗