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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of electrolyte solutions on carbon dioxide fixation in single chamber Al–CO 2 battery

Governments and research & development (R&D) organizations are actively initiating various programs and research strategies for CO 2 capture, its utilization, and integration with long duration energy storage from renewable sources worldwide. In line with the carbon capture goals, here we report a novel electrochemical Al-CO 2 battery cell, that can simultaneously capture CO 2 and convert it into value-added products, in addition to long-duration energy generation and storage. Here, this innovative approach employs cost-effective Al metal as an anode and an in-house synthesized Ni–Fe based bimetallic double hydroxide catalyst as the cathode, with meticulously optimized compositions and morphologies. We explore the impact of different aqueous electrolyte solutions compositions on the cell performance, demonstrating up to 10 h of stable long duration energy storage with a stable voltage profile. The cell exhibits low polarization even at high current densities of up to 12 mA cm -2 and maintains stable cycling over 500 h. Through Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, X-ray Diffraction and X-ray photoelectron spectroscopy (XPS) analysis, we determined that the discharge product is either NaAlCO 3 (OH) 2 or KAlCO 3 (OH) 2 , distinct from the Al 2 (CO 3 ) 3 typically reported in conventional Al–CO 2 batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A Demonstration System for Geological Thermal Energy Storage of Concentrating Solar Thermal

Energy storage is increasingly necessary as variable energy technologies are deployed. Seasonal energy storage can shift energy generation from the summer to the winter, but these technologies must have extremely large energy capacities and low costs. Geological Thermal Energy Storage (GeoTES) is proposed as a solution for long-term energy storage [1]. Excess thermal energy can be stored in permeable reservoirs such as aquifers and depleted hydrocarbon reservoirs for several months. The energy capacity cost of GeoTES is very low which makes it suitable for both daily- and seasonal storage of Concentrating Solar Thermal (CST) energy, thus enabling CST to provide value to electricity markets and thermal energy off-takers. A CST-GeoTES demonstration system has been funded by the U.S. Department of Energy, Solar Energy Technology Office. In this article, we will describe this demonstration system and progress that has been made in its development. The demonstration system will comprise a 2 MWth parabolic trough with an 8m aperture developed by Gossamer Space Frames, seven wells, and a 100 kWe power cycle. The demonstration system will be deployed in Kern County, California by Premier Resource Management. A techno-economic model for CST-GeoTES systems has also been developed [3] and is applied to the demonstration system and its planned future expansion. The model integrates the output of specialist models of each subsystem, which enables the performance and cost of both the subsurface and surface systems to be captured. Off-design models enable the performance to be evaluated at each hour of the year, before being aggregated to evaluate the economic potential of CST-GeoTES. Initial analysis indicates that CST-GeoTES can provide long duration energy storage capabilities with low marginal costs of energy capacity - leading to a low value of Levelized Cost of Storage (LCOS) compared to alternative technologies, see Figure 2. In this article, we investigate the cost and performance of the specific demonstration site being developed by PRM and explore a range of operational profiles that can deliver different value streams, such as daily and seasonal storage, capacity, and resiliancy.

14 SOLAR ENERGY↗
DOE OSTI2026

Estimation of Fission Product Transport Parameters for Cesium in the AGR-3/4 TRISO Fuel Experiment

A one-dimensional (1D) finite-element model of fission product transport in the AGR-3/4 experiment has been developed using the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and implemented in the fuel performance code, BISON. The model resolves capsule-specific geometries, materials, and temperature histories and simulates radial migration of fission products from the fuel compact through the inner ring, outer ring, and into the sink ring. Model parameters governing diffusion and sorption were estimated for key fission products – cesium (Cs), and europium (Eu) – by simultaneously fitting modeled isotopic concentration profiles and total ring inventories to a post-irradiation experimental measurement. These data include gamma scanning, liquid scintillation for Sr-90, radial deconsolidation leach-burn-leach analysis, tomographic reconstructions, and destructive physical sampling. A mortar-based interfacial sorption framework was implemented to enforce physically consistent mass transfer and flux conservation across gas gaps. Two classes of parameter sets were derived: a least-squares best-fit, and a safety-oriented conservative-fit, what applies strong penalties for underprediction of sink inventories. Across all twelve capsules, the model successfully reproduces the dominant radial transport trends for Cs, Sr, with decreasing concentrations from the compact outward through successive rings. Cs behavior is captured most consistently, while strontium predictions reveal systematic trade-offs between compact accuracy and conservative sink-ring bounding. The results demonstrate that sink ring weighted calibration provides conservative, safety relevant bounds on low temperature fission product transport, but at the cost of underpredicting compact inventories for Sr isotopes. These discrepancies highlight the need for additional physics, including fast-slow diffusion model, incorporating trapping mechanism in the transport behavior. Overall, this work establishes a robust, capsule-specific modeling framework for AGR-3/4 fission product transport and provides a defensible basis for parameter selection in source-term and fuel performance analyses for high temperature gas-cooled reactors.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗
DOE OSTI2026

On FIRE mode in KSTAR

We report on the status of Fast Ion Regulated Enhancement (FIRE) mode experiments in the Korea Superconducting Tokamak Advanced Research. This regime is being developed for high-performance, steady-state operation which features a stationary ion internal transport barrier, enabling a central ion temperature approaching 10 keV to be sustained for up to 50 s, without the need for delicate profile control and with no significant impurity accumulation. As its key novelty lies in the significant contribution of fast ions that stabilize core turbulence, the regime has been named FIRE mode. To achieve this regime, neutral beam injection is applied at moderate power levels near the L–H power threshold, while maintaining low plasma density to avoid the L–H transition. The scenario is typically established in diverted magnetic configurations. The core features of FIRE mode were investigated through power balance analysis and fluctuation measurements, revealing a clear transport bifurcation in the ion channel. At the plasma edge, FIRE mode occasionally exhibits I-mode characteristics, particularly in unfavorable magnetic null configurations with q 95 ∼ 4, including the presence of weakly coherent modes. In terms of MHD activity, sawtooth oscillations are observed but appear to be stabilized during the high-performance phase. Fast ion-driven Alfvénic eigenmodes (AEs), indicated by strong frequency chirping near 200 kHz, are also observed. Additionally, lower-frequency MHD activities, distinct from the fast ion-driven AEs, are present and have some influence on plasma performance. The enhancement of core confinement is primarily attributed to fast ion effects, which were evaluated with respect to dilution, alpha stabilization, and resonant interactions with turbulence using gyrokinetic analyses. Among these, the dilution effect was found to be the most dominant. The characteristics of FIRE mode were compared with those of other hot ion plasma scenarios, such as supershot and hot ion mode. While they share many similarities, FIRE mode is distinguished by the accessibility to conditions with T i ≈ T e , presence of I-mode edge features, and its long-duration sustainment. Predictive simulations of FIRE mode were performed using integrated transport modeling with TRIASSIC, employing the TGLF anomalous transport model. These simulations confirmed the critical role of fast ions in achieving this regime. The future prospect of FIRE mode for application in fusion reactors is discussed, with an emphasis on possibly extending the regime to higher density operation.

FIRE mode↗
DOE OSTI2025

Electric Grid Simulator For Human Factor Research

The developed code simulates real-time monitor and control for west area of IEEE 118-bus system. The 24-hour load profile for each bus is derived by scaling the system’s rated load in the PSSE sav file according to the California Independent System Operator’s Day-ahead load forecast for May 1, 2024. This simulator performs several critical functions: (1) Calculating time-series power flow every 4 seconds; (2) Updating and dispatching AGC signals every minute; (3) Conducting N-1 contingency analysis every 5 minutes. Additionally, the simulator can trip lines and subsequently update and dispatch AGC signals, running power flow analysis after each tripping event.

Huang, Jianqiao [Idaho National Laboratory (INL), ↗
DOE OSTI2026

Effect of Sample Mass, Confinement, and Preheating Time on the Thermal Response of LLM‐105: Experiments and Kinetic Analysis

Various small-scale experiments were performed to provide data for developing a model to predict the thermal response of LLM-105 over a wide range of conditions. The thermal decomposition of LLM-105 was studied as a function of sample mass, confinement of volatile products, and preheating time in both isothermal and ramped heating experiments. The thermal decomposition of LLM-105 is a two-step process, as shown by the two exothermic peaks in the heat flow profiles, which were fitted to two nth-order autocatalytic reaction models with a similar activation energy of ∼289 kJ/mol. The magnitude and shape of these peaks varied with sample mass and confinement. Increasing sample mass enhanced the second exotherm with respect to the first one, while increasing the level of confinement promoted a transition from a sublimation-dominated regime towards thermal decomposition. The effect of LLM-105 particle size on the rate of weight loss was evident for open-pan experiments, where bigger particles sublimed at lower temperatures than smaller particles. Thermal response and solid residue composition of LLM-105 samples were analyzed following preheating for different durations. Longer preheating times caused a shift of the second exotherm to lower temperatures and a decrease in the reaction enthalpy, confirming that LLM-105 decay is a consecutive reaction mechanism, probably autocatalytic. In conclusion, the kinetic model derived from ramped experiments was validated against the measured LLM-105 fraction remaining and the enthalpy remaining of the solid residue as a function of preheating times and showed good agreement.

Chemistry - Chemical explosives↗
DOE OSTI2026

Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part II. Bright Galaxy Survey and Emission-Line Galaxies

We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT temperature maps, we detect the kSZ signal at high significance, reaching signal-to-noise ratios of up to $\sim$9 for BGS and $\sim$7.5 for ELGs in optimal stellar-mass selections. Together with the LRG measurements presented in Paper I, these constitute the most significant kSZ detections from any spectroscopic survey to date. We perform the analysis in both real and harmonic space, obtaining consistent results. By splitting both tracers into stellar-mass bins, we study the scaling of the kSZ amplitude with galaxy properties. Combining the kSZ measurements with ACT Data Release 6 (DR6) CMB lensing maps enables a joint calibration of the galaxy-halo connection and the gas fractions of host halos. For the BGS galaxies, we observe low gas fractions around the virial radius relative to standard expectations, likely attributable to active galactic nuclei (AGN) activity. We find some evidence for higher-mass halos retaining a larger fraction of their baryons, consistent with more efficient feedback in lower-mass systems. For the ELG sample, dominated by blue, star-forming galaxies, we provide the first detection of the gas distribution in ELG host halos. The ELGs appear to exhibit relatively high gas fractions, which points to the possibility of weaker feedback (due to e.g. low AGN and supernova feedback activity) at their mass scale. Finally, we present generalized Navarro-Frenk-White (GNFW) fits to the harmonic-space measurements, providing a compact parametrization of gas profiles for forward modeling in large-scale structure analyses.

Hadzhiyska, B. [Cambridge U.; Cambridge U., Inst. ↗
DOE OSTI2026

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗
DOE OSTI2025

EVs@Scale High Power Charging Pillar

Slide deck assesses a portfolio of EVs, EVSEs, and Fleets that are expected to utilize High Power Charging (>200kW) to understand charging rates, grid impacts, and asset utilization. Provide DOE, project partners, stakeholders, and the public with analysis on the capability of HPC performance of today's charging infrastructure.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Evaluation of the Planetary Boundary Layer Height From ERA5 Reanalysis With MOSAiC Observations Over the Arctic Ocean

The planetary boundary layer height (PBLH) is a crucial indicator reflecting the region of the atmosphere characterized by continuous turbulence. Here, we use radiosonde and surface meteorological observations (4–7 times per day, year-round measurements) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition to derive the PBLH (PBLH MOSAiC ), and further evaluate the PBLH from the ERA5 reanalysis (PBLH ERA5 ). Comparisons between PBLH MOSAiC and PBLH ERA5 from different perspectives reveal that: (a) The overestimation of PBLH ERA5 when the sea ice concentration is >90% is significant with the centered root mean squared error reaching up to 201 m; (b) The difference between the two products is notably pronounced in cold seasons, while it is comparatively diminished in warm seasons; (c) In neutral boundary layers, differences in PBLH ERA5 are larger compared with stable and convective boundary layers. In addition, the analysis of error sources indicates that the bias of PBLH ERA5 is sensitive to the bias of vertical thermal structure and wind speed profiles in ERA5 data sets in all conditions. Finally, we find a Random Forest model effectively reduces the bias of PBLH ERA5 with the index of agreement reaching up to 0.71 in the test data set, while a multiple linear regression demonstrates comparable performance to the Random Forest model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data & Code from Phoenix CPPP Phase 2 Analysis

This data and code package supports the analysis presented in “Beyond Surface Cooling: Comprehensive Field Assessment of Reflective Pavement Thermal Performance in Phoenix, Arizona” and provides fully reproducible workflows for evaluating the thermal performance of cool pavement treatments in a hot urban environment. The dataset integrates multi-modal field measurements collected across residential and nonresidential settings, including mobile air temperature traverses, stationary air temperature monitoring, residential mean radiant temperature (MRT) measurements, subsurface temperature profiles, and controlled testbed observations. The data package contains raw and processed datasets in comma-separated value (CSV) format, accompanying metadata files describing site characteristics and measurement protocols, and R scripts (.R files) used for data cleaning, time synchronization, spatial and temporal matching, quality control filtering, statistical comparison, and figure generation. All analyses were conducted using R (version ≥ 4.2.0) with commonly available packages (e.g., tidyverse, lubridate, data.table, ggplot2). No proprietary software is required to reproduce results. Field campaigns were designed to quantify the effects of high-reflectance pavement coatings on surface temperature, near-surface air temperature, subsurface heat propagation, and radiative heat exposure. Temporal alignment procedures include standardized timestamp conversion and nearest-neighbor matching of high-frequency sensor measurements to stop-based metadata within defined tolerance windows to ensure comparability across instruments. The workflows generate summary statistics, treatment–control contrasts, depth-dependent thermal gradients, and time-series visualizations used in the associated publication. By integrating mobile, stationary, radiative, and subsurface measurements within a unified and transparent processing framework, this package enables comprehensive evaluation of cool pavement performance across multiple thermal exposure pathways and supports reuse in future urban heat mitigation and climate resilience studies.

AIR TEMPERATURE↗
DOE OSTI2024

Optimizing Deep Geothermal Drilling for Energy Sustainability in the Appalachian Basin

This study investigates the geological and geomechanical characteristics of the MIP 1S geothermal well in the Appalachian Basin to optimize drilling and address the wellbore stability issues encountered. Data from well logs, sidewall core analysis, and injection tests were used to derive elastic and rock strength properties, as well as stress and pore pressure profiles. A robust 1D-geomechanical model was developed and validated, correlating strongly with wellbore instability observations. This revealed significant wellbore breakout, widening the diameter from 12 ¼ inches to over 16 inches. Advanced technologies like Cerebro Force™ In-Bit Sensing were used to monitor drilling performance with high accuracy. This technology tracks critical metrics such as bit acceleration, vibration in the x, y, and z directions, Gyro RPM, stick-slip indicators, and bending on the bit. Cerebro Force™ readings identified hole drag caused by poor hole conditions, including friction between the drill string and wellbore walls and the presence of cuttings or debris. This led to higher torque and weight on bit (WOB) readings at the surface compared to downhole measurements, affecting drilling efficiency and wellbore stability. Optimal drilling parameters for future deep geothermal wells were determined based on these findings.

Environmental Sciences & Ecology↗
DOE OSTI2024

MHD stability trends and improved performance of LHD inward-shifted configurations: The role of the neutral beam current drive and thermal plasma density

The aim of the present study is to analyze the effect of the neutral beam current drive (NBCD), thermal plasma density, and NBI operational regime on the stability of pressure gradient-driven modes (PGDM) and Alfvén eigenmodes (AE) in LHD inward-shifted configurations. The stabilization of n/m = 1/2 PGDM (n toroidal mode and m poloidal mode) is observed in the discharge 167 800 during the co-NBCD phase. The iota profile evolution measured by motional stark effect diagnostic may indicate the iota profile up-shift caused by the co-NBCD can induce a non-resonant transition of the rational surface 1/2 before the mode stabilization. The evolution of the iota profile and continuum gaps in the discharge 167 805 during the ctr-NBCD phase leads to the stabilization of the AE, caused by the narrowing of the continuum gap as the iota profile down-shift. Opposite stability trends are identified for PGDM and AE stability with respect to the thermal plasma density. A larger thermal plasma density (larger thermal β) further enhances PGDM although the continuum gaps are narrower leading to configurations with stable AEs. The linear stability of AEs is analyzed using the gyro-fluid FAR3d code to reproduce the AE stability trends observed in the experiments with respect to the NBCD and thermal plasma density. The analysis of hypothetical scenarios dedicated to study different NBI operational regimes with respect to EP energy, and β and radial density profiles indicate off-axis NBI operation shows a higher EP β threshold to destabilize AEs compared to on-axis configuration. This is explained by the presence of a TAE gap in the inner plasma region, easily destabilized by an on-axis NBI injection. The control of the NBCD and thermal plasma in the discharge 167 800 shows a transitory stabilization of PGDM and AEs, as well as an improved discharge performance identified by an increment of the neutron fluxes.

Varela, Jacobo↗
DOE OSTI2026

Gear Test Assembly - Experimental Testing and Analysis of Gears and Bearings - FY2026

The Gear Test Assembly (GTA) is an experimental test apparatus built and installed in the Mechanisms and Engineering Test Loop (METL) at Argonne National Laboratory (ANL). While designed to accommodate a variety of components intended for use in advanced compact in-vessel transfer machine, the focus of GTA been the testing of large radial spur gears. The performance of the components used in GTA motivates the choices made in the design, components, and material choices for the forthcoming METL test articles; the Gripper Test Assembly (GrTA), and the Bearing Test Assembly (BTA). To date, GTA has completed nine experimental testing campaigns and achieved over 21 million revolutions under prototypic sodium fast reactor loads and operating conditions. This report provides an overview and results for the two most recent experiments Campaign #8 and Campaign #9. `Campaign #8 was the first campaign to make use of a set of nickel alloy radial spur gears, made from Hastelloy C-22HS, and combined with heat-treated tapered roller bearings. The bearings and torque profile used allowed Campaign #8 to be directly compared with Campaign #1 where Inconel 718 gears were used instead. Campaign #8 attained 1,058,880 shaft revolutions within 23% of the 1,314,855 revolutions achieved in Campaign #1. These results demonstrate that the heat-treated tapered roller bearings show consistent increased lifetimes, approximately three times longer than for non heat-treated taper rollers, and that the particular material of the gear does not play a substantial role in performance. Similar to Campaign #7 where bearing failure resulted in fragmentation and transport of bearing material into the gear teeth led to tooth damage in the Inconel gears, a similar process led to the damage of the Hastelloy gears. Subsequent NDE analysis showed that the damage was only limited to the tooth surface and does not extend into the gear interiors. Based on the NDE reports, the Hastelloy gears can be reconditioned and put back into service for future campaigns as was done for the Inconel gears. Reconditioned Inconel 718 gears damaged in Campaign #7 were returned to service in Campaign #9 and paired with non heat-treated tapered roller bearings. In Campaign #9 a novel set of operating conditions were implemented whereby the gears and bearings were cycled between hot, submerged refueling conditions where fuel handling operations occurred and cold, dry, and inert conditions where the sodium was drained and the vessel was allowed to cool simulating long, ex-vessel storage of the fuel handling machine. A total of eight of these operating cycles were achieved before a bearing failure occurred after the accumulation of 475,692 shaft revolutions were achieved. During Campaign #9, one of the drive motors was damaged and over the course of a 240 day standby period, the entire GTA drive system was upgraded from a 480VAC system to a 240VAC system that provided the opportunity to consolidate wall-space in the METL facility and provide more space for additional test articles being installed in the coming year. The over 475,000 shaft revolutions achieved in Campaign #9 eclipses the previous record for lifetime of non heat-treated tapered roller bearings held by Campaign #3 of 392,000 shaft revolutions. Further analysis and future campaigns hope to shed light on the cause of this approximately 17% increase in lifetime.

42 ENGINEERING↗
DOE OSTI2025

Monitoring the long-term performance of organic redox flow battery by a distribution of relaxation time analysis

Organic redox flow batteries hold great promise as an energy storage technology, but their intricate chemistry makes them vulnerable to various degradation mechanisms. Monitoring this degradation is essential for identifying the limiting processes within the cells. Electrochemical impedance spectroscopy (EIS) offers a straightforward, in-situ method for measuring the total resistance of an operating cell. However, to pinpoint the limiting processes during long-term cycling, EIS data must be complemented by other techniques. Distribution of relaxation time (DRT) analysis is particularly effective for differentiating resistance components. Here, in this study, we perform a comprehensive analysis of resistance evolution and the separation of anode and cathode contributions during long-term cycling of a full cell employing 7,8-dihydroxyphenazine-2-sulfonic acid (DHPS) as the anolyte. Separate analyses of the DHPS anolyte and ferri-/ferrocyanide catholyte were conducted using a symmetric cell setup. The relaxation times derived from symmetric cells facilitate the identification of peaks in the DRT profiles from the full cell. Importantly, the DRT profiles indicate a correlation between the evolution of charge transfer resistance and the chemical degradation of DHPS. The methodologies and results outlined in this study offer significant insights for developing diagnostic tools applicable to other types of redox flow batteries.

Distribution of relaxation time↗
DOE OSTI2026

Plasma confinement state classification via FPP relevant microwave diagnostics

We present a parsimonious and robust machine learning approach for identifying plasma confinement states in fusion power plants (FPPs) where reliable identification of the low-confinement and high-confinement regimes is critical for safe and efficient operation. Unlike research-oriented devices, FPPs must operate with a severely constrained set of diagnostics. To address this challenge, we demonstrate that a minimalist model, using only electron cyclotron emission (ECE) signals, can achieve accurate and reliable state classification. ECE provides electron temperature profiles without the engineering or survivability issues of in-vessel probes, making it a primary candidate for FPP-relevant diagnostics. Our framework employs ECE as input, extracts features using radial basis functions, and applies a gradient boosting classifier, achieving a test accuracy of 96% (correct predictions). Robustness analysis and feature importance analyzes confirm the approach’s reliability. These results demonstrate that state-of-the-art performance is attainable from a restricted diagnostic set, paving the way for minimalist yet resilient plasma control architectures for FPPs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗