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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 667 records · Page 37

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Storage

This paper presents a prototype methodology to assess the possible transition of Class II carbon dioxide-enhanced oil recovery (CO2-EOR) wells to Class VI wells. The focus is on wellbore construction materials—casing, cement, tubing, and the packer—and includes comprehensive workflows to evaluate these materials, with primary emphasis on compliance with Environmental Protection Agency (EPA) Class VI well construction and conversion guidelines. These workflows systematically assess material properties and performance criteria to ensure regulatory compliance and optimize long-term wellbore integrity and functionality. Utilizing Python scripts and JavaScript Object Notation (JSON) representations, the study automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on workflow criteria. By emphasizing critical factors such as casing integrity, cementing techniques, tubing compatibility, and packer selection, the methodology helps well owners and operators prioritize wells for potential reuse as CO2 injection wells. Given limitations in digitized data, manual user verification is required in some sections. Future improvements include integrating non-digitized data through web scraping and machine learning techniques. This research serves as a practical guide for stakeholders, supporting environmental compliance and sustainable well operations.

geologic carbon sequestration↗

Adaptive Cybersecurity for Distributed Energy Resources (AdCyDER): Online Reinforcement Learning with Stackelberg-Optimized Defenses — Pipeline Architecture, Evaluation Methodology, and Findings from a Synthetic-Data Evaluation

This report documents the design and evaluation of an integrated online-learning pipeline developed within the AdCyDER project for Distributed Energy Resource (DER) cybersecurity. The pipeline couples a Reinforcement Learning (RL) attack classifier — which produces an attack-type probability distribution — with a Stackelberg game-theoretic (GT) defense selector that consumes those distributions alongside SME-encoded priors over (defense, attack) effectiveness pairings and perdefense costs to choose grid-health-preserving defenses. The objective is not attack classification per se but production of distributions that drive effective defense selection through the Stackelberg layer, learned from delayed grid-health feedback rather than labeled attack data. AdCyDER as a whole is broader than the work presented here; this report covers the specific RL/GT loop integration and its evaluation. We present the integrated pipeline (SCADA telemetry with Fronius inverter physics, Suricata IDS, time-windowed aggregation, per-facility LSTM classifier, Stackelberg optimizer, OpenC2 actuators), an experimental campaign of 28 eight-hour iterations across three baseline modes, and a pipeline-ordered diagnostic protocol. The protocol identifies two distinct failure modes within the loop: paired supervised ceilings on the same features establish that the deployed online RL classifier (macro F1 ≈ 0.07) sits at least 4.7× below a same-architecture supervised LSTM (≈ 0.34) and 10–11× below a linear feature-signal ceiling (≈ 0.70–0.79 depending on per-facility isolation), localizing the dominant failure to the training procedure; and the reward signal driving online updates carries weak directional coupling with classifier correctness in the methodology-expected direction (multi-lens convergent: top-decile P(true) records produce more frequent state changes and slightly larger improvements, top-vs-bot Cohen’s 𝑑 ≈ −0.19), but at effect magnitudes too small to drive gradient-based learning at the campaign sample size. The original learning hypothesis is not supported by the data. The primary contributions are the diagnostic methodology — proposed as a transferable falsification protocol for online RL/GT defense pipelines learning from delayed environmental reward — and the open, reproducible experimental infrastructure. We outline reward reformulation as the highest-priority aspirational next step given the underpowered-but-aligned Q6 reading, with hardware-in-the-loop evaluation as the broadest scope-expansion option.

Blakely, Benjamin [Argonne National Laboratory (AN↗

Operation of a Modular 3D-Pixelated Liquid Argon Time-Projection Chamber in a Neutrino Beam

The 2x2 Demonstrator, a prototype for the Deep Underground Neutrino Experiment (DUNE) liquid argon (LAr) Near Detector, was exposed to the Neutrinos from the Main Injector (NuMI) neutrino beam at Fermi National Accelerator Laboratory (Fermilab). This detector is a prototype of a new modular design for a liquid argon time-projection chamber (LArTPC), comprising a two-by-two array of four modules, each further segmented into two optically isolated LArTPCs. The 2x2 Demonstrator features a number of pioneering technologies, including a low-profile resistive field shell to establish drift fields, native 3D ionization pixelated imaging, and a high-coverage dielectric light readout system. The 2.4-tonne active mass detector is flanked upstream and downstream by supplemental solid-scintillator tracking planes, repurposed from the MINERvA experiment, which track ionizing particles exiting the argon volume. The antineutrino beam data collected by the detector over a 4.5 day period in 2024 include over 30,000 neutrino interactions in the LAr active volume—the first neutrino interactions reported by a DUNE detector prototype. During its physics-quality run, the 2x2 Demonstrator operated at a nominal drift field of 500 V/cm and maintained good LAr purity, with a stable electron lifetime of approximately 1.25 ms. This paper describes the detector and supporting systems, summarizes the installation and commissioning, and presents the initial validation of collected NuMI beam and off-beam self-triggers. In addition, it highlights observed interactions in the detector volume, including candidate muon antineutrino events.

47 OTHER INSTRUMENTATION↗

The DUNE Science Program

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy for the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the previous European Strategy for Particle Physics. The construction of DUNE Phase I is well underway. DUNE Phase II consists of a third and fourth far detector module, an upgraded near detector complex, and an enhanced > 2 MW beam. The fourth FD module is conceived as a 'Module of Opportunity', aimed at supporting the core DUNE science program while also expanding the physics opportunities with more advanced technologies. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Neutrinos and cosmic messengers', 'BSM physics' and 'Dark matter and dark sector' streams focuses on the physics program of DUNE. Additional inputs related to DUNE detector technologies and R&D, DUNE software and computing, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The DUNE Phase II Detectors

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy for the implementation of this leading-edge, large-scale science project. The 2023 report of the US Particle Physics Project Prioritization Panel (P5) reaffirmed this vision and strongly endorsed DUNE Phase I and Phase II, as did the previous European Strategy for Particle Physics. The construction of DUNE Phase I is well underway. DUNE Phase II consists of a third and fourth far detector module, an upgraded near detector complex, and an enhanced > 2 MW beam. The fourth FD module is conceived as a 'Module of Opportunity', aimed at supporting the core DUNE science program while also expanding the physics opportunities with more advanced technologies. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Detector instrumentation' stream focuses on technologies and R&D for the DUNE Phase II detectors. Additional inputs related to the DUNE science program, DUNE software and computing, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DUNE Software and Computing Research and Development

The international collaboration designing and constructing the Deep Underground Neutrino Experiment (DUNE) at the Long-Baseline Neutrino Facility (LBNF) has developed a two-phase strategy toward the implementation of this leading-edge, large-scale science project. The ambitious physics program of Phase I and Phase II of DUNE is dependent upon deployment and utilization of significant computing resources, and successful research and development of software (both infrastructure and algorithmic) in order to achieve these scientific goals. This submission discusses the computing resources projections, infrastructure support, and software development needed for DUNE during the coming decades as an input to the European Strategy for Particle Physics Update for 2026. The DUNE collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This submission to the 'Computing' stream focuses on DUNE software and computing. Additional inputs related to the DUNE science program, DUNE detector technologies and R&D, and European contributions to Fermilab accelerator upgrades and facilities for the DUNE experiment, are also being submitted to other streams.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

European Contributions to Fermilab Accelerator Upgrades and Facilities for the DUNE Experiment

The Proton Improvement Plan (PIP-II) to the FNAL accelerator chain and the Long-Baseline Neutrino Facility (LBNF) will provide the world's most intense neutrino beam to the Deep Underground Neutrino Experiment (DUNE) enabling a wide-ranging physics program. This document outlines the significant contributions made by European national laboratories and institutes towards realizing the first phase of the project with a 1.2 MW neutrino beam. Construction of this first phase is well underway. For DUNE Phase II, this will be closely followed by an upgrade of the beam power to > 2 MW, for which the European groups again have a key role and which will require the continued support of the European community for machine aspects of neutrino physics. Beyond the neutrino beam aspects, LBNF is also responsible for providing unique infrastructure to install and operate the DUNE neutrino detectors at FNAL and at the Sanford Underground Research Facility (SURF). The cryostats for the first two Liquid Argon Time Projection Chamber detector modules at SURF, a contribution of CERN to LBNF, are central to the success of the ongoing execution of DUNE Phase I. Likewise, successful and timely procurement of cryostats for two additional detector modules at SURF will be critical to the success of DUNE Phase II and the overall physics program. The DUNE Collaboration is submitting four main contributions to the 2026 Update of the European Strategy for Particle Physics process. This paper is being submitted to the 'Accelerator technologies' and 'Projects and Large Experiments' streams. Additional inputs related to the DUNE science program, DUNE detector technologies and R&D, and DUNE software and computing, are also being submitted to other streams.

43 PARTICLE ACCELERATORS↗

Multi-channel, multi-template event reconstruction for SuperCDMS data using machine learning

SuperCDMS SNOLAB uses kilogram-scale germanium and silicon detectors to search for dark matter. Each detector has Transition Edge Sensors (TESs) patterned on the top and bottom faces of a large crystal substrate, with the TESs electrically grouped into six phonon readout channels per face. Noise correlations are expected among a detector's readout channels, in part because the channels and their readout electronics are located in close proximity to one another. Moreover, owing to the large size of the detectors, energy deposits can produce vastly different phonon propagation patterns depending on their location in the substrate, resulting in a strong position dependence in the readout-channel pulse shapes. Both of these effects can degrade the energy resolution and consequently diminish the dark matter search sensitivity of the experiment if not accounted for properly. We present a new algorithm for pulse reconstruction, mathematically formulated to take into account correlated noise and pulse shape variations. This new algorithm fits N readout channels with a superposition of M pulse templates simultaneously - hence termed the N$\times$M filter. We describe a method to derive the pulse templates using principal component analysis (PCA) and to extract energy and position information using a gradient boosted decision tree (GBDT). We show that these new N$\times$M and GBDT analysis tools can reduce the impact from correlated noise sources while improving the reconstructed energy resolution for simulated mono-energetic events by more than a factor of three and for the 71Ge K-shell electron-capture peak recoils measured in a previous version of SuperCDMS called CDMSlite to $<$ 50 eV from the previously published value of $\sim$100 eV. These results lay the groundwork for position reconstruction in SuperCDMS with the N$\times$M outputs.

Albakry, M. F. [British Columbia U.; TRIUMF]↗

Measurements of differential charged-current cross sections on argon for electron neutrinos with final-state protons in MicroBooNE

This work presents single-differential electron-neutrino charged-current cross sections on argon measured using the MicroBooNE detector at the Fermi National Accelerator Laboratory. The analysis uses data recorded when the Neutrinos at the Main Injector beam was operating in both neutrino and antineutrino modes, with exposures of $2 \times 10^{20}$ and $5 \times 10^{20}$ protons on target, respectively. A selection algorithm targeting electron-neutrino charged-current interactions with at least one proton, one electron, and no pions in the final topology is used to measure differential cross sections as a function of outgoing electron energy, total visible energy, and opening angle between the electron and the most energetic proton. The interaction rate as a function of proton multiplicity is also reported. The total cross section is measured as [4.1 $\pm$ 0.4 (stat.) $\pm$ 1.2 (syst.)]$ $$\times 10^{-39} \mathrm{cm}^{2}/ \mathrm{nucleon}$. The unfolded cross-section measurements are compared to predictions from neutrino event generators commonly employed in the field. Good agreement is seen across all variables within uncertainties.

Abratenko, P. [Tufts U. (main)]↗

Probing Nuclear Effects with Transverse Kinematic Imbalance in Muon-neutrino Induced Charged-Current $π^0$ Production on Argon with the MicroBooNE Detector

Neutrino-nucleus cross-section measurements are needed to improve interaction modeling and to enable precision neutrino oscillation measurements in upcoming experiments such as the Deep Underground Neutrino Experiment (DUNE), Hyper-Kamiokande, and the Short-Baseline Neutrino program. Baryon-resonance neutrino interactions constitute a dominant contribution near the peak of the DUNE neutrino energy spectrum. We present the first measurement of muon neutrino charged-current resonance-like interactions on argon using transverse kinematic imbalance variables with the MicroBooNE detector. These observables are highly sensitive to the modeling of final-state interactions. This measurement probes kinematic imbalances using the reconstructed momenta of the muon, leading proton, and neutral pion. A comprehensive characterization of the $π^0$-proton final state is presented; however, none of the models considered are able to simultaneously reproduce all measured observables.

Abratenko, P. [Tufts U. (main)]↗

First Measurement of Sub-GeV $ν_μ$ Charged-Current Coherent Pion Production on Argon in MicroBooNE

We report a measurement of the charged-current coherent pion production cross section on argon using the MicroBooNE liquid argon time projection chamber exposed to the Booster Neutrino Beam at Fermilab. The measurement uses the MicroBooNE data set corresponding to $1.26 \times 10^{21}$ protons on target with a mean neutrino energy of $0.8$~GeV. The flux-averaged cross section is measured to be $(9.1 \pm 1.2_{\text{stat}} \pm 1.2_\text{syst}) \times 10^{-40}\,\text{cm}^2/\text{Ar}$. This result represents the first measurement of charged-current coherent pion production on argon at sub-GeV neutrino energies. Due to its clean two-body kinematics, where the neutrino interacts coherently with the entire nucleus producing a forward muon and pion with no nuclear breakup, this process provides a useful tool for constraining neutrino flux uncertainties in current and future oscillation experiments such as DUNE.

Abratenko, P. [Tufts U.] (ORCID:0000000169455941)↗

Characterizing the energy resolution of the MicroBooNE LArTPC at the MeV scale using monoenergetic features of $^{208}$Tl decays

A detailed understanding of the capabilities and fidelity of low-energy reconstruction is crucial for taking advantage of MeV-scale neutrino physics opportunities in liquid argon time projection chambers (LArTPCs). This study presents a measurement of the resolution of reconstructed energy in the MicroBooNE LArTPC at $\approx 1.5$ MeV. The characterization is performed using monoenergetic signals generated by $2.614$ MeV $γ$-rays from $^{208}$Tl decays undergoing pair production in the detector. The resolution is found to be ($7.52 \pm 0.78 \text{(stat)} \pm 0.92 \text{(syst)}$)%. This value is consistent with the MicroBooNE simulation prediction of ($9.70 \pm 0.65 \text{(stat)}$)% at the $1.6 σ$ level. This study represents the first ever measurement of LArTPC energy resolution at the MeV scale and provides a pathway for monoenergetic energy calibrations in future experiments using LArTPC detectors.

Abratenko, P. [Tufts U.]↗

Ion Pair Uptake in Ion Gel Devices Based on Organic Mixed Ionic–Electronic Conductors

Abstract In organic mixed ionic–electronic conductors (OMIECs), it is critical to understand the motion of ions in the electrolyte and OMIEC. Generally, the focus is on the movement of net charge during gating, and the motion of neutral anion–cation pairs is seldom considered. Uptake of mobile ion pairs by the semiconductor before electrochemical gating (passive uptake) can be advantageous as this can improve device speed, and both ions can participate in charge compensation during gating. Here, such passive ion pair uptake in high‐speed solid‐state devices is demonstrated using an ion gel electrolyte. This is compared to a polymerized ionic liquid (PIL) electrolyte to understand how ion pair uptake affects device characteristics. Using X‐ray photoelectron spectroscopy, the passive uptake of ion pairs from the ion gel into the OMIEC is detected, whereas no uptake is observed with a PIL electrolyte. This is corroborated by X‐ray scattering, which reveals morphological changes to the OMIEC from the uptake of ion pairs. With in situ Raman, a reorganization of both anions and cations is then observed during gating. Finally, the speed and retention of OMIEC‐based neuromorphic devices are tuned by controlling the freedom of charge motion in the electrolyte.

Quill, Tyler J.↗

Double Doping of Semiconducting Polymers Using Ion-Exchange with a Dianion

The interactions between counterions and electronic carriers in electrically doped semiconducting polymers are important for delocalization of charge carriers, electronic conductivity, and thermal stability. The introduction of a dianions in semiconducting polymers leads to double doping where there is one counterion for two charge carriers. Double doping minimizes structural distortions, but changes the electrostatic interactions between the carriers and counterions. Polymeric ionic liquids (PIL) with croconate dianions are helpful to investigate the role of the counterion in p-type semiconducting polymers. PILs prevent diffusion of the cation into the semiconducting polymers during ion exchange. The redox-active croconate dianions undergo ion exchange with doped semiconducting polymers depending on their ionization energy. Croconate dianions are found to reduce doped films of poly(3-hexyl thiophene), but undergo ion exchange with a polythiophene with tetraethylene glycol side chains, P(g 4 2T-T), that has a lower ionization energy. The croconate dianion maintains crystalline order in P(g 4 2T-T) and leads to a lower activation energy for the electrical conductivity than PF 6 – counterions. The control of the doping level with croconate allows optimization of the thermoelectric performance of the semiconducting polymer. Finally, the thermal stability of the doped films of P(g 4 2T-T) is found to depend strongly on the nature of the counterion.

36 MATERIALS SCIENCE↗

Rare earth element potential in coal and coal ash in the U.S. Gulf Coast

United States heavy reliance on imports of critical minerals (CMs), including rare earth elements (REEs), underscores the importance of development of domestic sources. The study objective was to quantify CM and REE concentrations in coal and coal ash in the US Gulf Coast region. CM and REE concentrations were measured for 118 samples from outcrops and 14 mines in the Gulf Coast. Results show that total REE + Yttrium (REY) concentrations (dry coal basis) are comparable to those of the upper continental crust (UCC) with localized hot spots, such as the Texas Gibbons Creek mine (REY ≤ ~ 2860 ppm). When normalized to UCC REY concentration (169 ppm, dry coal basis), REY to UCC ratios for Gulf Coast coal samples range from 0.1 to 17 (median ratio 0.6). REE extractability from lignites is high (median: 63%–93%) using environmentally benign weak acid. In addition to raw coal, coal ash from power plants could also serve as an REE source with a median ratio of REY in ash relative to coal of 4; however, extractability from coal ash is generally much lower (≤ 5% using the same weak acid as in coal). The median basket price for extracted REY as oxides from coal, assuming 70% extractability, is $\$3.2$ per tonne of coal and $\$186$ billion based on 58 billion metric tonnes of dry coal in the Gulf Coast. REEs important for magnets (Pr + Nd + Tb + Dy) account for ~ 80% of the total value. The corresponding median basket price for extracted REY as oxides from coal ash, assuming ~ 30% extractability, is ~$\$4.4$ per tonne of ash and $\$1.2$ billion based on 258 million tonnes of ash. REE production from coal would likely require co-products, such as activated carbon or humic acids, to attain economic viability. Production of REEs from coal ash could offset remediation costs related to potential water contamination. This reconnaissance study shows the potential for REE production from coal and coal ash in the Gulf Coast; however, carbon coproducts and/or societal benefits would likely be required for socioeconomic viability.

01 COAL, LIGNITE, AND PEAT↗

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗

The impact of infill percentage and layer height in small-scale material extrusion on porosity and tensile properties

We report material extrusion additive manufacturing is prone to introducing porosity within the structure due to the layer-by-layer construction using elliptical beads of material. This open porosity ultimately plays a role in determining the mechanical properties of printed parts. The shape, size, and amount of porosity within a printed part is influenced by a variety of factors, including nozzle diameter, infill percentage, layer height, raster orientation, and print speed. While several studies have investigated these and other parameters’ effects on mechanical performance and porosity, better understanding the interconnected relationships is crucial in balancing the various input parameters to achieve maximum strength. This work initially examined the influence of key print parameters (infill percentage and layer height) on the internal porosity of a printed Acrylonitrile Butadiene Styrene (ABS) part. Then, the print parameters and internal porosity were statistically correlated to final mechanical properties. Porosity was further classified as either open or closed to differentiate between connected voids in the mesostructure from isolated voids within the material itself. Mechanical performance increased with an increasing density and infill percentage, displaying a 224 % increase in elastic modulus and a 150 % increase in ultimate tensile strength. The contribution of layer height was found to be conditional upon the infill percentage.

3D Printing↗