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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

VitriEdge: Repairable & Durable Vitrimer Coatings for Wind Turbine Blade Leading Edges

The primary goal of this Level 1b incubator project was to explore the use of vitrimer coatings for repair of leading-edge erosion on end-of-life wind turbine blade surfaces, beyond coating strength of adhesion which has previously been demonstrated in the Level 1a project. Uniform vitrimer coatings (thickness: 400 µm) were applied to two end-of-life wind turbine blades for flexural, fatigue, and laminate tensile testing where the addition of the coating did not produce any statistical variation in tensile properties with minor drops in flexural strength for some laminate formulations. However, a <2% variation in storage modulus was measured for laminate structures (i.e., blade samples with vitrimer coatings) across 100,000 flexural cycles and upon laminate tensile failure, the vitrimer coatings displayed no visible signs of delamination. In addition, three methods to heal vitrimer coating damage was displayed: oven heating, addition of hot water, and a forced convection heat gun. All three heating and healing mechanisms demonstrated significant healing with scratch depths decreasing between 79-91% at healing times ranging between 1-min and 10-minutes. Finally, a water jet machine was used to simulate rain erosion for both the blade surfaces and vitrimer-coated blade surfaces where the diameter and depth of the damage was recorded as a function of exposure time, water pressure, height of exposure, and angle of exposure. Of interest, while the vitrimer coating did not significantly lessen the damage experienced during rain erosion, the addition of vitrimer composite coatings(5 wt.% mica addition) did result in a crack-resistant, durable coating capable of self-healing behavior and in all cases the angle of rain exposure was the most critical parameter explored. It is crucial to continue exploring this space where vitrimer coatings are of interest for both their self-healing properties and potential use as reversible adhesives.

17 WIND ENERGY↗
DOE OSTI2020

Highly-Active and Contaminant-Tolerant Cathodes for Durable Solid Oxide Fuel Cells (Final Report)

The objective of this project is to investigate the fundamental degradation methods occurring in solid oxide fuel cell (SOFC) cathodes when exposed to chromium and carbon dioxide contamination and to rationally design alkaline earth-based catalysts to increase stability and tolerance to contaminate poisoning. With a mechanistic and fundamental understanding of the degradation methods, advanced catalytic surface modifications can be applied to reduce degradation. The specific technical objectives are: (1) To identify/develop new catalysts (alkaline-earth based-) that are compatible chemically with the state-of-the-art cathode materials at high temperatures required for fabrication and with contaminates commonly encountered under operating conditions; (2) To improve the infiltration process for optimal control of the thickness, composition, and uniformity of the catalyst coatings; (3) To evaluate the electro-catalytic activity toward ORR of the chemically-stable materials when exposed to different types of contaminants using electrical conductivity relaxation measurements on bar samples and performance evaluation of catalyst-infiltrated cathodes; (4) To unravel the contamination-tolerant mechanisms of the new catalyst coatings under realistic environmental conditions (with different types of contaminants) using powerful in situ and in operando characterization techniques performed on model cells with thin-film/pattern electrodes, as guided by modeling and simulation; (5) To establish scientific basis for rational design of new catalysts of high tolerance to contaminants; (6) To validate the long term stability of modified LSCF cathodes in commercially available cells/stacks under ROC. Alkaline earth-based catalysts have been systematically explored and tested under various contamination conditions. BaCoO 3-δ (BCO) was shown to produce the best catalytic activity enhancement as well as stability in a variety of contaminating conditions, including CO 2 and chromium. The microstructural evolution was investigated with SEM, EDS, and Raman spectroscopy, showing the BCO catalyst prevents the formation of insulating SrCrO 4 by forming electrically conductive BaCrO 4 . Electrochemical relaxation measurements determined the BCO catalyst coatings increased the surface diffusion coefficient but did not significantly affect the diffusion coefficient and determined an optimum surface modification layer of 100 nm. A novel Ba 0.9 Co 0.7 Fe 0.2 Nb 0.1 O x (BCFN) catalyst was also shown to have excellent stability in chromium containing atmospheres. A novel surface sol-gel (SSG) surface modification, which offers superior thickness and compositional control, was applied to SOFCs to produce BaO catalyst coatings. SSG BaO coatings were shown to produce conformal coatings on the electrode surface, greatly increasing stability in chromium containing atmospheres. An atomic level mechanistic approach was applied to investigate the stability of PrBa 0.8 Ca 0.2 Co2O 5+δ (PBCC) with respect to a variety of common contaminants, demonstrating thermodynamically its superior stability in CO2 containing atmospheres. Finally, the best catalyst coatings demonstrated in this project, BCO and PBCC, were applied to full cells which demonstrated superior stability for over 300 hours in CO 2 and Cr atmospheres.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Highly-Active and Contaminant-Tolerant Cathodes for Durable Solid Oxide Fuel Cells

The objective of this project is to investigate the fundamental degradation methods occurring in solid oxide fuel cell (SOFC) cathodes when exposed to chromium and carbon dioxide contamination and to rationally design alkaline earth-based catalysts to increase stability and tolerance to contaminate poisoning. With a mechanistic and fundamental understanding of the degradation methods, advanced catalytic surface modifications can be applied to reduce degradation. The specific technical objectives are: (1) To identify/develop new catalysts (alkaline-earth based-) that are compatible chemically with the state-of-the-art cathode materials at high temperatures required for fabrication and with contaminates commonly encountered under operating conditions; (2) To improve the infiltration process for optimal control of the thickness, composition, and uniformity of the catalyst coatings; (3) To evaluate the electro-catalytic activity toward ORR of the chemically-stable materials when exposed to different types of contaminants using electrical conductivity relaxation measurements on bar samples and performance evaluation of catalyst-infiltrated cathodes; (4) To unravel the contamination-tolerant mechanisms of the new catalyst coatings under realistic environmental conditions (with different types of contaminants) using powerful in situ and in operando characterization techniques performed on model cells with thin-film/pattern electrodes, as guided by modeling and simulation; (5) To establish scientific basis for rational design of new catalysts of high tolerance to contaminants; (6) To validate the long term stability of modified LSCF cathodes in commercially available cells/stacks under ROC. Alkaline earth-based catalysts have been systematically explored and tested under various contamination conditions. BaCoO 3-δ (BCO) was shown to produce the best catalytic activity enhancement as well as stability in a variety of contaminating conditions, including CO 2 and chromium. The microstructural evolution was investigated with SEM, EDS, and Raman spectroscopy, showing the BCO catalyst prevents the formation of insulating SrCrO 4 by forming electrically conductive BaCrO 4 . Electrochemical relaxation measurements determined the BCO catalyst coatings increased the surface diffusion coefficient but did not significantly affect the diffusion coefficient and determined an optimum surface modification layer of 100 nm. A novel Ba 0.9 Co 0.7 Fe 0.2 Nb 0.1 O x (BCFN) catalyst was also shown to have excellent stability in chromium containing atmospheres. A novel surface sol-gel (SSG) surface modification, which offers superior thickness and compositional control, was applied to SOFCs to produce BaO catalyst coatings. SSG BaO coatings were shown to produce conformal coatings on the electrode surface, greatly4 increasing stability in chromium containing atmospheres. An atomic level mechanistic approach was applied to investigate the stability of PrBa 0.8 Ca 0.2 Co 2 O 5+δ (PBCC) with respect to a variety of common contaminants, demonstrating thermodynamically its superior stability in CO 2 containing atmospheres. Finally, the best catalyst coatings demonstrated in this project, BCO and PBCC, were applied to full cells which demonstrated superior stability for over 300 hours in CO 2 and Cr atmospheres.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Highly-Active and Contaminant-Tolerant Cathodes for Durable Solid Oxide Fuel Cells

The objective of this project is to investigate the fundamental degradation methods occurring in solid oxide fuel cell (SOFC) cathodes when exposed to chromium and carbon dioxide contamination and to rationally design alkaline earth-based catalysts to increase stability and tolerance to contaminate poisoning. With a mechanistic and fundamental understanding of the degradation methods, advanced catalytic surface modifications can be applied to reduce degradation. The specific technical objectives are: (1) To identify/develop new catalysts (alkaline-earth based-) that are compatible chemically with the state-of-the-art cathode materials at high temperatures required for fabrication and with contaminates commonly encountered under operating conditions; (2) To improve the infiltration process for optimal control of the thickness, composition, and uniformity of the catalyst coatings; (3) To evaluate the electro-catalytic activity toward ORR of the chemically-stable materials when exposed to different types of contaminants using electrical conductivity relaxation measurements on bar samples and performance evaluation of catalyst-infiltrated cathodes; (4) To unravel the contamination-tolerant mechanisms of the new catalyst coatings under realistic environmental conditions (with different types of contaminants) using powerful in situ and in operando characterization techniques performed on model cells with thin-film/pattern electrodes, as guided by modeling and simulation; (5) To establish scientific basis for rational design of new catalysts of high tolerance to contaminants; (6) To validate the long term stability of modified LSCF cathodes in commercially available cells/stacks under ROC. Alkaline earth-based catalysts have been systematically explored and tested under various contamination conditions. BaCoO 3-δ (BCO) was shown to produce the best catalytic activity enhancement as well as stability in a variety of contaminating conditions, including CO 2 and chromium. The microstructural evolution was investigated with SEM, EDS, and Raman spectroscopy, showing the BCO catalyst prevents the formation of insulating SrCrO 4 by forming electrically conductive BaCrO 4 . Electrochemical relaxation measurements determined the BCO catalyst coatings increased the surface diffusion coefficient but did not significantly affect the diffusion coefficient and determined an optimum surface modification layer of 100 nm. A novel Ba 0.9 Co 0.7 Fe 0.2 Nb 0.1 O x (BCFN) catalyst was also shown to have excellent stability in chromium containing atmospheres. A novel surface sol-gel (SSG) surface modification, which offers superior thickness and compositional control, was applied to SOFCs to produce BaO catalyst coatings. SSG BaO coatings were shown to produce conformal coatings on the electrode surface, greatly 4 increasing stability in chromium containing atmospheres. An atomic level mechanistic approach was applied to investigate the stability of PrBa 0.8 Ca 0.2 Co 2 O 5+δ (PBCC) with respect to a variety of common contaminants, demonstrating thermodynamically its superior stability in CO 2 containing atmospheres. Finally, the best catalyst coatings demonstrated in this project, BCO and PBCC, were applied to full cells which demonstrated superior stability for over 300 hours in CO 2 and Cr atmospheres

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

First operation of a multi-channel Q-Pix prototype: measuring transverse electron diffusion in a gas time projection chamber

We report measurements of the transverse diffusion of electrons in P-10 gas (90% Ar, 10% CH 4 ) in a laboratory-scale time projection chamber (TPC) utilizing a novel pixelated signal capture and digitization technique known as Q-Pix. The Q-Pix method incorporates a precision switched integrating transimpedance amplifier whose output is compared to a threshold voltage. Upon reaching the threshold, a comparator sends a 'reset' signal, initiating a discharge of the integrating capacitor. The time difference between successive resets is inversely proportional to the average current at the pixel in that time interval, and the number of resets is directly proportional to the total collected charge. We developed a 16-channel Q-Pix prototype fabricated from commercial off-the-shelf components and coupled them to 16 concentric annular anode electrodes to measure the spatial extent of the electron swarm that reaches the anode after drifting through the uniform field of the TPC. The swarm is produced at a gold photocathode using pulsed UV light. The measured transverse diffusion agrees with simulations in PyBoltz across a range of operating pressures (200–1500 Torr). These results demonstrate that a Q-Pix readout can successfully reconstruct the ionization topology in a TPC.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

From Deposition to Encapsulation: Roll-to-roll manufacturing of organic light emitting devices for lighting (Final Report)

Organic light emitting devices (OLEDs) are promising solid state light sources due to their high efficiency, high color quality and flexible form factors. The key to enable low cost OLED lighting, is to rapidly fabricate thin film organic layers on a continuous flexible roll, called R2R processing. This project aims to investigate the feasibility of mass production of OLED lighting using the R2R process, from deposition to encapsulation. A high efficiency white OLED is fabricated on 10 cm-wide substrate rolls in a pilot R2R tool comprising of two different organic deposition: vacuum thermal evaporation (VTE) and organic vapor phase deposition (OVPD). A high quality encapsulation process to package OLEDs is demonstrated using an atomic layer deposition tool integrated to the R2R system without air exposure. The method to achieve ultrahigh deposition rates required by R2R processing is demonstrated by OVPD. Uniform organic semiconductor thin films grown by OVPD at rates as high as 50 Å/s are achieved. A comprehensive numerical model that is capable of simulating complex, multilayer WOLED structures is developed to provide an alternative to experimental iterations of OLED design and tests. A cost estimate on the R2R production of WOLEDs for lighting is developed. Assuming a WOLED luminance of 10 klm/m 2 , the cost of a WOLED light engine is anticipated to be $\$ 12.5$ /klm. With incremental reduction in material and driver costs and improved luminance, the cost of WOLED lighting can be reduced to $\$ 6.3$ /klm in the near term. These findings suggest OLED lighting can be volume manufactured by R2R vapor deposition methods with much reduced costs compared to current batch processing methods, potentially positioning WOLEDs for use in numerous premium lighting applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Spatial and temporal evaluations of the liquid argon purity in ProtoDUNE-SP

Liquid argon time projection chambers (LArTPCs) rely on highly pure argon to ensure that ionization electrons produced by charged particles reach readout arrays. ProtoDUNE Single-Phase (ProtoDUNE-SP) was an approximately 700-ton liquid argon detector intended to prototype the Deep Underground Neutrino Experiment (DUNE) Far Detector Horizontal Drift module. It contains two drift volumes bisected by the cathode plane assembly, which is biased to create an almost uniform electric field in both volumes. The DUNE Far Detector modules must have robust cryogenic systems capable of filtering argon and supplying the TPC with clean liquid. This paper will explore comparisons of the argon purity measured by the purity monitors with those measured using muons in the TPC from October 2018 to November 2018. A new method is introduced to measure the liquid argon purity in the TPC using muons crossing both drift volumes of ProtoDUNE-SP. For extended periods on the timescale of weeks, the drift electron lifetime was measured to be above 30 ms using both systems. A particular focus will be placed on the measured purity of argon as a function of position in the detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2023

Energy resolution of the LZ detector for high-energy electronic recoils

The LUX-ZEPLIN (LZ) detector is a dual-phase liquid xenon time projection chamber (TPC) installed at the Sanford Underground Research Facility (Lead, South Dakota) at a depth of 1478 meters. Although the main objective of LZ is the direct detection of dark matter, its low background environment allows for the search of other rare processes, such as the neutrinoless double beta decay of xenon isotopes 134 Xe and 136 Xe with the respective Q-values of 826 keV and 2458 keV. The sensitivity of the detector to these decays is directly determined by the energy resolution, which, in turn, is degraded by non-uniformities in detector response. In this work, we present a novel method to correct, in the data, the non-uniformity of the light collected by an array of photosensors in a scintillation detector. This method is based on the knowledge of the light response functions of individual photosensors. With these techniques, we report, at a very early phase of the detector operations, a state-of-the-art energy resolution (σ/μ) of (0.67 ± 0.01)% at 2614 keV for the fiducial volume of 5.6 tonnes of liquid xenon.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Hydraulic Response to Thermal Stimulation Efforts at Raft River Based on Stepped Rate Injection Testing

The injection well stimulation project at the Raft River geothermal field tests the effect of long-term cold water injection and high pressure injection on well injectivity, improvements to which could reduce operating costs. The primary data for analysis and interpretation of the injection test are step-rate flow tests run before each new phase of the injection. These tests were analyzed using a combination of standard pump-test analytical solution methods and methods developed expressly for the observed conditions. The stepped rate injection tests, combined with long-term flow and pressure response data suggest that the well is located within a fractured formation of low transmissivity but high storativity. These calculated parameters appeared to increase with pressure during the first injection test and the higher values were reproduced during the second stepped rate test. Calculated transmissivity and storativity are on the order of 4E-5 m cm 2 and 1E-4 m Pa -1 , respectively. The apparent pressure dependence of fitted hydraulic parameters may reflect near-well fracture compliance that increased the effective radius of the wellbore during the first test. While the type curve fit analysis also suggests that the reservoir behaves as a uniformly fractured reservoir with a radial flow regime, the hydraulic parameters indicate that condition may exist only a very limited distance (<10 m) from the well. Longer-term pressure response suggests that flow in the system effectively reaches steady state in a period of less than a day, which may reflect pressure stabilization resulting from pressure-dependent permeability or a region of much higher permeability located with a few meters of the well. The transmissivity estimates obtained from this analysis, converted to approximate fracture density and aperture, provide useful constraints on the distance to which the thermal front may migrate from the well during the cold water injection phase of the stimulation project. We estimate that the cooling front will migrate less than a tenth of a kilometer over an approximately one-year injection period. Here, the effects of that cooling, however, may be substantial, because increases in permeability have maximum effect nearest the well.

cold water injection↗
DOE OSTI2026

Challenging conventional assumptions in PV: a high-throughput open-air approach to low-cost perovskite module production

Perovskite solar modules (PSMs) offer a promising pathway to low-cost photovoltaics, yet their commercialization is challenged by manufacturing scalability, device uniformity, additive costs, interlayer complexity, and module stability. This study introduces a comprehensive technoeconomic analysis of single junction PSM's and projections for tandem perovskite-Si modules that integrate all materials and manufacturing steps, module performances, projected lifetimes, and manufacturing costs across scales. Here, we highlight an open-air manufacturing approach to fabricate all active layers of serially interconnected PSMs, including electrodes and charge transport layers, enabling high-throughput production without inert or vacuum environments. The analysis reveals two orders of magnitude throughput enhancement and cost reductions of 24% in all-open-air production, escalating to over 60% at 1 GW factory capacity compared to conventional methods. Levelized cost of energy (LCOE) projections for utility-scale installations over 30 years, accounting for module replacement and recycling, demonstrate the potential to achieve the 2030 US target of $0.03 per kWh with realistic 7–11-year PSM lifetimes, outperforming incumbent silicon-based modules. Neither four terminal (4T) nor two terminal (2T) tandem-Si PSMs improve over single junction perovskite or silicon LCOE regardless of higher efficiencies at any modeled lifetime. Addressing PSM technical challenges with a cost-modeling framework guides commercialization efforts and provides a convincing pathway for challenging incumbent Si-based PV.

14 SOLAR ENERGY↗
DOE OSTI2021

Single-Site Metal Organic Complexes on Oxide Supports for Selective Alkane Functionalization

High levels of reaction selectivity for heterogeneous catalysis are generally difficult to achieve with traditional metal nanoparticle catalysts, due to the variety of metal binding sites available. In this project, we have developed a metal-ligand coordination strategy to form transition metal single-sites on high surface area supports as heterogeneous single-site catalysts. Metal centers can be atomically dispersed in the binding pockets of organic ligands on oxide supports. The systems have to be carefully designed so that tendencies for metal cluster formation or binding to surface defect sites are overcome by the attractive coordination environment provided by the organic ligand. This was confirmed by a comprehensive set of characterization methods, including XAS, XPS, XRD, TEM, and CO adsorption. Design and tuning of metal-support and support-ligand interactions were crucial for high structural uniformity. We demonstrate that supported metal-ligand SSCs are effective, recyclable catalysts for alkene hydrosilylation reactions. Compared with commercial homogeneous catalysts, they exhibit improved yield and selectivity, less metal aggregation and side reactions, and stronger tolerance with functionalized substrates. These results give some preliminary indication that coordination with organic ligands can improve activity and selectivity in metal/oxide heterogeneous catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Fast-RF-Shimming: Accelerate RF shimming in 7T MRI using deep learning

Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical diagnostics and advanced research. However, the jump to higher fields introduces complications, particularly transmit radiofrequency (RF) field ($B^{+}_{1}$) inhomogeneities, manifesting as uneven flip angles and image intensity irregularities. These artifacts can degrade image quality and impede broader clinical adoption. Traditional RF shimming methods, such as Magnitude Least Squares (MLS) optimization, effectively mitigate $B^{+}_{1}$ inhomogeneity, but remain time-consuming. Recent machine learning approaches, including RF Shim Prediction by Iteratively Projected Ridge Regression and other deep learning architectures, suggest alternative pathways. Although these approaches show promise, challenges such as extensive training periods, limited network complexity, and practical data requirements persist. In this paper, we introduce a holistic learning-based framework called Fast-RF-Shimming, which achieves a 5000 ​× ​speed-up compared to the traditional MLS method. In the initial phase, we employ random-initialized Adaptive Moment Estimation (Adam) to derive the desired reference shimming weights from multi-channel $B^{+}_{1}$ fields. Next, we train a Residual Network (ResNet) to map $B^{+}_{1}$ fields directly to the ultimate RF shimming outputs, incorporating the confidence parameter into its loss function. Finally, we design Non-uniformity Field Detector (NFD), an optional post-processing step, to ensure the extreme non-uniform outcomes are identified. Comparative evaluations with standard MLS optimization underscore notable gains in both processing speed and predictive accuracy, which indicates that our technique shows a promising solution for addressing persistent inhomogeneity challenges.

Deep learning↗
DOE OSTI2021

Calorimetric classification of track-like signatures in liquid argon TPCs using MicroBooNE data

The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Advanced sorbents for modular oxygen production for REMS gasifiers

Under a DOE funded effort, Thermosolv LLC has been developing a sorbent-based oxygen production technology for gasification and oxy-combustion applications. The sorbents utilize oxygen-storage properties of certain perovskites to (1) selectively adsorb oxygen at moderate temperature from compressed air and (2) release the adsorbed oxygen into a vacuum or a sweep gas such as CO2 and/or steam. Through cyclic operations of multiple sorbent beds such a process can be made continuous. Pressure drop across the sorbent bed and other similar design considerations dictate that the sorbent be in the form of a high surface-area-to-volume pellet and yet still possess sufficient crush strength and integrity. Process efficiency is determined by the sorption and desorption kinetics and sorbent capacity. Typical process involves cycle times in the order of 100 seconds, a time too short to fully utilize the full volume of the sorbent and the sorption capacity of the sorbent pellets. As a part of this project, Thermosolv LLC undertook the development of oxygen sorbents as a high-surface area supported sorbent on a light-weight inert support to (1) reduce the cost, (2) increase the productivity, and (3) reduce the overall weight of the reactor. Using a previously developed perovskite (LSCF 1991) with its well-characterized performance, composite sorbent pellets each consisting of an inert core coated by a thin layer of the functional perovskite material were produced. Several low-density, inexpensive inert solids supports in the 1/8”-1/4” size were selected to keep the pressure drop across the sorbent bed in the acceptable range. A number of commercial technologies including spray coating, dip coating, incipient impregnation of porous substrate followed by thermal annealing at various temperatures and duration were employed and tested to produce robust composite supported sorbent pellets. A sense of optimum coating thickness was developed by testing sorbent pellets of various increasing diameter pellets. LSCF-1991extrudates ranging in size from 1/32” to 3/16” were tested in a TGA and in a fixed-bed pressure swing test set-up for sorption/desorption cycles of interest. The data show that for the operational conditions of interest the coating thickness for a supported sorbent pellet needs to be approximately 1/32” (about 0.8 mm). Subsequent work thereby concentrated on developing composite pellets of various substrates, shapes and sizes with coating layer of about this size range. Candidate support materials were chosen based on cost, inertness, mechanical strength, thermal expansion and chemical stability with sorbent material, and in a size range to give an acceptable pressure drop in fixed-bad reactor configurations. Coating application methods used for application of the sorbent onto the support included precipitation, spray coating and dip coating from sorbent slurries and sol gels. For all coated supports where we could successfully apply a uniform coating of desired thickness with an acceptable handling performance in terms of exfoliation, TGA-based cyclic sorption/desorption testing was performed to determine cycling capacity of oxygen. Among nearly twenty different support materials tested, best adhesion performance was obtained from stainless saddle supports. In the bench-scale fixed-bad tests stainless steel saddle support composite pellets with a coating thickness in the 0.6 mm or so range, the composite sorbent pellet performance approached up to 95% of that of the 2 mm parent material pellets. In a parallel approach to reducing the cost of the sorbent, alternate sorbent formulations replacing/reducing the amount of cobalt in the LSCF family were also investigated. Successful formulations that could match the performance of LSCF 1991 were identified based on TGA cyclic tests as LSCF 1919 and LSF 1910. In the range of operational envelop of cycle times and other relevant process operating conditions, the reduced Co formulations showed comparable performance in the bench-scale fixed-bad cyclic operations. As a part of this project, we also attempted substitution of La and Sr with Ca and Ba, and Co with Mn, Ni and Cu with little success, but the overall project goal of reducing sorbent cost in terms of raw material and manufacturing expenses was successful.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

D–MOPH–25: diverse MOF–molecule pairs for Henry’s constants prediction

Computational methods like grand-canonical Monte Carlo simulations and machine learning (ML) have accelerated metal–organic frameworks (MOF) exploration but are typically limited to a narrow range of adsorbates due to data availability and force field constraints. In this study, we introduce a dataset of diverse MOF–molecule pairs for Henry’s constant prediction, D–MOPH–25, which systematically explores a diverse chemical space by combining 113 molecular adsorbates with over 5000 MOF structures through an active learning process. D–MOPH–25 constitutes the most diverse adsorbate dataset used in any ML study of molecular adsorption in MOFs to date. Our workflow builds a benchmark for predicting Henry’s constants at 300 K, leveraging conformal prediction for uncertainty quantification. Assessment through Shannon entropy and uniform manifold approximation and projection confirms the comprehensiveness of D–MOPH–25 while highlighting the importance of robust classification to filter out unphysical data points in regression tasks. Although future enhancements in model architecture and sampling criteria could improve predictive performance, our dataset already spans the target space using only 2.31% of total possibilities. This comprehensive dataset facilitates assessment of model generalizability across adsorbate species and can establish a foundation for high-throughput MOF screening and ML-driven separation processes.

active learning↗
DOE OSTI2021

Lower-hybrid drift waves and their interaction with plasmas in a 3D symmetric reconnection simulation with zero guide field

We investigate lower-hybrid drift waves (LHDW) in symmetric magnetic reconnection with zero guide field using three-dimensional particle-in-cell simulations. The long-wavelength mode with kρiρe∼1 develops in the bifurcated electron current layer around the X-line within the width of the electron meandering motion from the mid-plane, where ρi(e) is the ion (electron) gyroradius. The short-wavelength mode with kρe∼1 develops in the separatrix region downstream of the electron outflow jet, producing electron vortices in the background flow frame. Electrons follow the E × B drift with corrections from the diamagnetic drift and are heated inside the vortices with diverging electric fields. In the vortices, ions have comparable E × B and inertia drifts, which together mostly cancel the diamagnetic drift. Toward the center of diverging field vortices, ions are decelerated, leading to a decrease in the perpendicular temperature, while the loss of low-energy ions results in an increase in the parallel temperature. Parallel electric fields exist as a combination of the LHDW wave field projected to the magnetic field direction and the penetration of whistler waves that are mainly outside of the LHDW layer. The magnetic flux tube is twisted in the vortices. The twist may potentially lead to slippage reconnection, as indicated by the non-uniform parallel potential variation across field lines, while the periodic variations of the twisting directions are a limiting factor.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Identifying Vehicle Signals in Continuous Seismic Data Using Unsupervised Machine-Learning Techniques

Seismic sensors deployed near roadways effectively capture ground vibrations generated by passing vehicles. Although both traditional and machine‐learning algorithms have been utilized for analyzing such signals, independent validation of detected vehicle events remains limited. We applied two unsupervised machine‐learning algorithms, uniform manifold approximation and projection for dimension reduction, and hierarchical density‐based spatial clustering of applications with noise, to continuous seismic data collected along a road on the main campus of Oak Ridge National Laboratory. The algorithms identified seven distinct cluster labels across the entire dataset. By comparing these cluster labels with precipitation records from a nearby weather station and image‐derived labels from a local camera system, we identified one cluster associated with rainfall and another with vehicle activity. Our algorithms identified a greater number of vehicle‐related labels compared to the camera‐derived labels because seismic data are unaffected by poor lighting conditions. The arrival times of the newly detected vehicle signals corresponded well with the road’s speed limit, supporting our findings. Our algorithm outperformed the short‐term average/long‐term average method and k‐means clustering. Our results suggest that seismic data, when analyzed with machine‐learning algorithms, can complement existing vehicle monitoring systems, particularly under challenging environmental conditions.

Chai, Chengping [Oak Ridge National Laboratory (OR↗