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At least 199 records · Page 11

Erratum: “Initial characterization of electron temperature and density profiles in PEGASUS spherical tokamak discharges driven solely by local helicity injection” [Phys. Plasmas 28, 102504 (2021)]

Here, this article describes errata in 'Initial characterization of electron temperature and density profiles in PEGASUS spherical tokamak discharges driven solely by local helicity injection,' Phys. Plasmas 28, 102504 (2021) that correct reported electron temperature values and their implications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Interpreting AI for fusion: An application to plasma profile analysis for tearing mode stability

Artificial intelligence models have demonstrated strong predictive capabilities for various instabilities in fusion devices such as Tokamaks, including tearing modes (TM), edge localized modes, and disruptive events, but their opaque nature raises concerns about safety and trustworthiness when applied to fusion power plants. Here, we present a physics-based interpretation framework using a TM prediction model as a demonstration that is validated through a dedicated DIII-D TM avoidance experiment. By applying Shapley analysis, we identify how profiles such as rotation, temperature, and density contribute to the model's prediction of TM stability. Our analysis shows that in our experimental scenario, core electron temperature and rotation peaking play the primary role in TM stability, while density changes have smaller effects on stability. We show that off-axis ion temperature stabilizes TMs, suggesting that off-axis neutral beam heating can further stabilize this scenario. This work presents a generalizable ML-based event prediction methodology, from training to physics-driven interpretation, bridging the gap between physics understanding and opaque ML models.

Farre-Kaga, Hiro J. [Princeton Univ., NJ (United S↗

Deriving effective electrode–ion interactions from free-energy profiles at electrochemical interfaces

Understanding ion adsorption at electrified metal–electrolyte interfaces is essential for accurate modeling of electrochemical systems. Here, in this study, we systematically investigate the free energy profiles of Na + , Cl − , and F − ions at the Au(111)–water interface using enhanced sampling molecular dynamics with both classical force fields and machine-learned interatomic potentials (MLIPs). Our classical metadynamics results reveal a strong dependence of predicted ion adsorption on the Lennard-Jones parameters, highlighting that—without due care—standard mixing rules can lead to qualitatively incorrect descriptions of ion–metal interactions. We present a systematic methodology for tuning the cross term LJ parameters to control adsorption energetics in agreement with more accurate models. As a surrogate for an ab initio model, we employed the recently released Universal Models for Atoms MLIP, which validates classical trends and displays strong specific adsorption for chloride, weak adsorption for fluoride, and no specific adsorption for sodium, in agreement with experimental and theoretical expectations. By integrating molecular-level adsorption free energies into continuum models of the electric double layer, we show that specific ion adsorption substantially alters the interfacial ion population, the potential of zero charge, and the differential capacitance of the system. Our results underscore the critical importance of force field parameterization and advanced interatomic potentials for the predictive modeling of ion-specific effects at electrified interfaces and provide a robust framework for bridging molecular simulations and continuum electrochemical models.

Roncoroni, Fabrice [Lawrence Berkeley National Lab↗

Neoclassical transport and profile prediction in transport barriers

Strong gradient regions in tokamaks, such as the pedestal or internal transport barriers, are regions of reduced turbulence where neoclassical transport can play a dominant role. However, standard neoclassical transport theory assumes that the gradient length scales of density, temperature, and potential are of the order of the system size. In the pedestal, gradient length scales are much shorter and are measured to be of the order of the ion poloidal gyroradius. We present an extension of neoclassical theory that is applicable in transport barriers of large aspect ratio tokamaks. We show that particle and momentum transport are connected in such a way that a source of parallel momentum can drive a significant neoclassical ion particle flux. In strong gradient regions, density, electric potential, mean parallel flow, and ion temperature are shown to no longer be flux functions. Instead, they have a small but important poloidally varying piece that modifies the transport equations to lowest order. This introduces a nonlinearity in the transport problem through the coupling with quasineutrality that yields multiple co-existing solutions when solving for the plasma profiles. The different solutions could be connected to low and high transport states and jumps between solutions could provide a new neoclassical explanation for H-L back-transitions.

Trinczek, Silvia [Princeton Plasma Physics Laborat↗

Motivations for early high-profile FRIB experiments

This white paper is the result of a collaboration by many of those that attended a workshop at the facility for rare isotope beams (FRIB), organized by the FRIB Theory Alliance (FRIB-TA), on ‘Theoretical Justifications and Motivations for Early High-Profile FRIB Experiments’. It covers a wide range of topics related to the science that will be explored at FRIB. After a brief introduction, the sections address: section 2: Overview of theoretical methods, section 3: Experimental capabilities, section 4: Structure, section 5: Near-threshold Physics, section 6: Reaction mechanisms, section 7: Nuclear equations of state, section 8: Nuclear astrophysics, section 9: Fundamental symmetries, and section 10: Experimental design and uncertainty quantification.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Plasma confinement state classification in fusion power plants: Profile reflectometer and ensemble diagnostics

As Fusion Pilot Plants (FPPs) are increasingly viewed as within reach, many engineering challenges remain. Not many diagnostics are expected to be available in a reactor environment. Survivability, maintainability, and limited port space substantially restrict the number of FPP-relevant diagnostics. One remaining challenge is developing tools and devices to extract plasma state information necessary for controlling an FPP from a limited subset of diagnostics. This work is part of an overarching project to address this challenge. The specific diagnostic subset to be used in FPPs is still under debate. We take the approach of developing machine-learning-based tools for different significant plasma state parameters, using already known FPP-viable diagnostics. Previously we developed a plasma confinement mode classifier utilizing the Electron Cyclotron Emission (ECE) diagnostic. Here, we expand on this by developing a Profile Reflectometer (PR) based classifier with 97% test accuracy, and an ensemble model that combines the ECE and PR models into a single model, achieving 99% test accuracy.

Clark, Randall [Univ. of California, San Diego, CA↗

Comparison of horizontal wind speed and direction measurements from dual-Doppler radar and profiling lidars

Dual-Doppler radar is a relatively new technology in the wind energy community and thus not yet studied vastly. This paper aims to compare horizontal wind speed and direction data retrieved from dual-Doppler radar and profiling lidars within the American WAKE experimeNt (AWAKEN) to investigate the influence of measurement height, wind direction and speed on the comparison. The 10-min averaged data show a better agreement of the measurements for higher altitudes, especially at faster wind speeds. For the wind direction, two sectors of larger differences in the measurements were detected: around 270° transient winds occur with a higher frequency than in other sectors. To explain the different measurement values in the wind direction sector around 90°, further studies, e.g. on the influence of atmospheric stability, are necessary.

17 WIND ENERGY↗

Testing hadronic-model predictions of depth of maximum of air-shower profiles and ground-particle signals using hybrid data of the Pierre Auger Observatory

We test the predictions of hadronic interaction models regarding the depth of maximum of air-shower profiles, X max , and ground-particle signals in water-Cherenkov detectors at 1000 m from the shower core, S ( 1000 ) , using the data from the fluorescence and surface detectors of the Pierre Auger Observatory. The test consists of fitting the measured two-dimensional ( S ( 1000 ) , X max ) distributions using templates for simulated air showers produced with hadronic interaction models pos-, et--04, 2.3d and leaving the scales of predicted X max and the signals from hadronic component at ground as free-fit parameters. The method relies on the assumption that the mass composition remains the same at all zenith angles, while the longitudinal shower development and attenuation of ground signal depend on the mass composition in a correlated way. The analysis was applied to 2239 events detected by both the fluorescence and surface detectors of the Pierre Auger Observatory with energies between 10 18.5 eV to 10 19.0 eV and zenith angles below 60°. We found, that within the assumptions of the method, the best description of the data is achieved if the predictions of the hadronic interaction models are shifted to deeper X max values and larger hadronic signals at all zenith angles. Given the magnitude of the shifts and the data sample size, the statistical significance of the improvement of data description using the modifications considered in the paper is larger than 5 σ even for any linear combination of experimental systematic uncertainties. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗

A Novel Low-Profile High-Efficiency Three-Phase Matrix Transformer

High step-down isolated DC-DC conversion from an 800 V DC bus to low-voltage, high-current outputs is required in automotive auxiliary converters and data center power supplies. In such applications, conventional transformer-based converters require large turns ratios, which increase winding resistance, leakage inductance, and magnetic height. This paper proposes a novel low-profile three-phase matrix transformer that realizes a large effective voltage ratio through flux division among multiple secondary legs, without increasing the physical turns count of each winding. As a result, the proposed structure reduces copper usage and transformer height while preserving the voltage conversion capability of a conventional three-phase transformer. Finite element analysis shows that the proposed design reduces magnetic height by 27%, ferrite volume by 34%, and copper volume by 28%. Circuit-level simulations of an 800 V/12 V,3 kW CLLLC dual-active-bridge converter further show that the lower winding resistance reduces total system loss by 91% and increases DC-DC efficiency from 82.6% to 97.6% at 3 kW output.

Inoue, Shuntaro [ORNL] (ORCID:0000000262637627)↗

Intestinal microbiome profile of the brown rock sea cucumber ( Holothuria glaberrima ) using ITS and 16S rDNA amplicons from direct mechanical, enzymatic, and chemical metagenomic extraction

Using direct mechanical, enzymatic, and chemical extraction methods, the intestinal microbiome of the marine invertebrate Holothuria glaberrima was obtained. ITS and 16S rDNA regions were sequenced to enrich and investigate the prokaryotic and fungal diversity profiles from different anatomical regions within the sea cucumber’s intestinal biology.

16S↗

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE↗

Coupling of high-resolution mass spectrometer and photosynthesis system for comprehensive leaf volatile metabolite profiling

Background Leaf-level biogenic volatile organic compounds (BVOCs) emissions represent a major source of organic gases in the atmosphere, influencing both climate and air quality. These emissions are strongly driven by environmental perturbations, which affect individual plant- to ecosystem-level processes. Uncovering all the BVOCs and understanding how their emissions respond to altered environmental conditions provide critical insights into vegetation-driven changes in atmospheric chemistry. We developed a tandem instrumentation setup that integrates a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) with parts-per-trillion detection limits and a photosynthetic infrared gas exchange system for the untargeted survey of all the BVOCs. This novel system enables simultaneous, real-time monitoring of BVOC emissions and photosynthetic parameters at the leaf level, offering new opportunities to disentangle the physiological and environmental drivers of VOC release. Furthermore, we established the VOC Analysis and Processing Optimization Resource (VAPOR), an open-access software tool designed for rapid data post-processing and the analysis of the variability of hundreds of BVOCs. We assessed the performance of the tandem system under varying background conditions, using standard gas mixtures and a range of environmental factors. Results Blank emissions were substantially lower for major BVOCs (e.g., isoprene) compared to those observed in plant emissions. Despite this, the observation of background-level VOCs highlights the importance of routinely acquiring and accounting for blank measurements in analyses using the coupled instrumentation. Introduction of known VOC concentrations to the system demonstrated a linear response across different compounds with varying molecular compositions, indicating minimal gas loss regardless of chemical moieties within the coupled instrumentation. We applied the optimized system to investigate the physiological mechanisms driving BVOC emissions across different genotypes of poplar and pennycress. The high mass resolution capabilities of the PTR-ToF-MS, coupled with comprehensive VAPOR-driven data analysis, enabled the identification of several important BVOCs, including methanol and methanethiol; these BVOCs displayed substantial variation across pennycress genotypes and showed concentrations ~ 100–350% higher than the blank. Moreover, isoprene emissions varied significantly among poplar genotypes grown in different potting media. Conclusions Tandem instrumentation offers a powerful tool for profiling volatile molecular markers and elucidating their genetic and environmental underpinnings. This approach enhances our ability to predict BVOC emissions in response to genotype by environmental interactions and contributes to a deeper understanding of vegetation responses to environmental changes.

Biogenic volatile organic compounds↗

MAPS Wind Profile Data

This dataset includes 40km vertical wind profiles from late 2023 through 9/30/2024 for Oklahoma, Kansas, and the Northeastern US. The data are in text format. Key for interpreting data is included in this package. Additionally, a descriptor accompanies each data file.

54 ENVIRONMENTAL SCIENCES↗

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Public Data Set: Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in G.M. Bodner et al., ‘Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection,’ Physics of Plasmas 28, 102504 (2021) and its erratum in Physics of Plasmas 31, 129904 (2024).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Public Data Set: Erratum: “Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection” [Phys. Plasmas 28, 102504 (2021)]

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in G.M. Bodner et al., ‘Erratum: “Initial Characterization of Electron Temperature and Density Profiles in PEGASUS Spherical Tokamak Discharges Driven Solely by Local Helicity Injection” [Phys. Plasmas 28, 102504 (2021)],’ Physics of Plasmas 31, 129904 (2024).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Ionization Profile Monitors for the IOTA Proton Beam

Ionization profile monitors (IPMs) are widely used in accelerators for non-destructive and fast diagnostics of high energy particle beams. Two such monitors - one vertical and one horizontal - are being developed for installation in the IOTA storage ring at Fermilab. They will be used for turn-by-turn (microseconds scale) measurements of the 70 MeV/c IOTA proton beam sizes. In this paper we present the IPMs design (largely following the FNAL Booster IPMs which employ no external guiding magnetic fields), their mechanical, vacuum, and electric subsystems and DAQ, and discuss anticipated effects on the beams circulating in IOTA.

43 PARTICLE ACCELERATORS↗

Low Energy Muon Beam Diagnostics - Scintillating Fiber Profile Monitor (SFPM)

The MeV Test Area (MTA) houses the 400 MeV H^− Beam at the end of the Linac and a secondary beamline of muons and pions created from hitting a Tungsten target. The MTA is in the Irradiation Test Area (ITA), where experiments involve studying the effects of radiation on materials in the MTA beam. There is a need for a retractable detector to monitor the secondary beam s intensity and coarse profile. The SFPM was chosen when considering factors like ability to measure low rates and handle high intensities. The plan was to test different scintillating fibers & Silicon Photomultiplier (SiPM) models to figure out which combination gives the best signals, and gain familiarity with the detector assembly, operation, and data acquisition software before using with final detectors in beamline. The SiPM circuit has been tested with a LED pulser successfully. The immediate steps that follow will be to set the SiPM up on the monitor with three different types of optical fibers, use the Caen software to configure the best mode of data acquisition, and proceed with an offline source test using Strontium-90. Once the most efficient measurement method is clear, they will be ready for use in the beamline.

Leith, Justin↗