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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 235 records · Page 13

Geologic hydrogen: From natural occurrences to anthropogenic generation – A review of fundamentals, potential, challenges and prospects

Growing demand for hydrogen is exposing the environmental and economic limits of reforming-based and carbon-managed supply chains, while the scale-up of electrolytic capacity remains capital-constrained. Geologic hydrogen, defined as molecular H₂ generated and stored within the Earth's crust offers a complementary, potentially lower-cost resource, yet exploration is still ad hoc. This review (1) revisits a global inventory of confirmed hydrogen seeps and subsurface occurrences; (2) analyzes the controlling reactions, migration pathways, and trapping conditions governing these occurrences; (3) proposes a process-based geologic hydrogen system concept analogous to, yet distinct from, the petroleum system; and (4) evaluates potential geologic hydrogen systems within the United States as a representative case study. Here, we contrast natural systems powered by serpentinization, mantle degassing or radiolysis with anthropogenic systems that stimulate the same reactions or convert in-situ hydrocarbons. Stable hydrogen accumulations require generation rates that outpace combined physical, chemical and microbial losses; the Bourakébougou field (Mali) exemplifies a self-recharging, free-gas reservoir sustained by meteoric-water serpentinization beneath an efficient caprock. Prospective geologic hydrogen resources are likely to occur in regions where iron-rich lithologies, deep-seated faults, and low-permeability sealing formations coexist. Applying this principle, we highlight three promising hydrogen play types in U.S. geological terrains: ophiolite belts (Appalachian and Californian regions), the Midcontinent Rift and the Lake Superior banded‑iron formations. Multiphysics numerical models and positive-unlabeled machine-learning workflows help to accelerate play screening and de-risk future production; yet, reaction kinetics, stimulation strategies, and full techno-economic and life-cycle assessments remain pivotal knowledge gaps.

Anthropogenic hydrogen generation↗

Accessing Transient Isomers in the Photoreaction of Metastable‐State Photoacid

The photoreaction of a metastable‐state photoacid (mPAH) generally involves multiple isomers with various connected pathways of photoinduced structural changes during a single reaction cycle. However, only a limited number of isomers have been identified experimentally so far owing to the inherent complexity in combination with the presence of various competing electronic and vibrational processes, as well as the constantly varying interactions between mPAH isomers and solvent molecules. Here, in this work, an optical spectroscopic study on a benzimidazole‐based mPAH, a novel photoacid using benzimidazole as the structural moiety with the active proton, is reported. Through measurements of linear absorption and steady‐state fluorescence in neat solvents and binary mixtures, a pronounced effect of neat water and its binary mixture with glycerol is discovered on the photoreaction of this benzimidazole‐mPAH, manifested by the remarkably distinct spectral responses to irradiation from that observed for an organic solution under identical conditions. Measurements of time‐ and frequency‐resolved fluorescence emission further enable to access transient isomers and the associated spectral characteristics from other competing electronic excited‐state relaxation processes. Spectral deconvolution analysis and time‐dependent density functional theory calculations are applied to separate distinct spectral components and access their potential origin.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ Characterization of Surface Recombination in p-Si/SiO x Based Photoelectrochemical Cells

Time-resolved infrared (TRIR) and electrochemical impedance spectroscopy (EIS) were utilized to quantify surface states present at silicon oxide (SiO x ) protected crystalline p-Si electrolyte interfaces. The primary goal was to identify p-Si/SiO x photoelectrodes with both low surface recombination rates and efficient multi-electron transfer to an acceptor present in the external electrolyte. Three SiO x layers were investigated: native oxide (nOx), chemical oxide (cOx), and rapid thermal annealed (RTA) thermal oxide (tOx). Comparative study with [Ru(bpy) 3 ](PF 6 ) 2 as the electron acceptor indicated that tOx was most optimal with a small effective recombination rate, multi-electron transfer capability, and photovoltage of 500 ± 50 mV. A secondary goal was to analyze the surface recombination rates with the Shockley–Read–Hall (SRH) kinetic model. Two surface states were identified from this analysis, one closer to the CB edge (V t,1 ) and the other near the midgap (V t,2 ). EIS and SRH analyses revealed that a forming gas (5% H 2 /N 2 ) anneal (FGA) decreased surface recombination for tOx and nOx through a lower density of surface states. In the case of tOx, the infrared data indicated that V t,2 was completely removed. Here, the energetic positions of the band edges were correlated with the surface state density; low densities corresponded to more favorable potentials for inversion layer formation, which is expected to be most optimal for photocatalysis. Collectively this study indicates that the free carrier dynamics provided by TRIR represent a powerful in situ probe of the band edge and the surface state energetics in silicon based photoelectrochemical cells.

Electrochemical Impedance Spectroscopy↗

Probing Quantum Anomalous Hall States in Twisted Bilayer WSe 2 via Attractive Polaron Spectroscopy

Moiré superlattices in semiconductors exhibit a rich variety of interaction-induced topological states, including quantum anomalous Hall (QAH) effects. A recent study hinted that twisted WSe 2 homobilayer (tWSe 2 ) could host a QAH state but lacked direct evidence of ferromagnetism, a key hallmark of this phase. Here, we report the first direct evidence of QAH states in tWSe 2 with spontaneous ferromagnetism. Specifically, we employ polarization-resolved attractive polaron spectroscopy on a dual-gated, 2° tWSe 2 and observe direct signatures of spontaneous time-reversal symmetry breaking at hole filling 𝜈 = 1. Together with a Chern number (𝐶) measurement via Streda formula analysis, we identify this magnetized state as a topological state, characterized by 𝐶 = 1. Furthermore, we demonstrate that these topological and magnetic properties are tunable via a finite displacement field, between a QAH ferromagnetic state and an antiferromagnetic state. Our findings position tWSe 2 as a highly versatile, stable, and optically addressable platform for investigating topological order and strong correlations in two-dimensional landscapes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

eLog analysis for accelerators: status and future outlook

This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory. We evaluate contemporary tools and methodologies for information retrieval with Retrieval Augmented Generation (RAGs), focusing on operational insights and integration with existing accelerator control systems. The study addresses challenges and proposes solutions for state-of-the-art eLog analysis through practical implementations, demonstrating applications and limitations. We present a framework for enhancing accelerator facility operations through improved information accessibility and knowledge management, which could potentially lead to more efficient operations.

Accelerator Physics↗

eLog Analysis for Accelerators: Status and Future Outlook

This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory. We evaluate contemporary tools and methodologies for information retrieval with Retrieval Augmented Generation (RAGs), focusing on operational insights and integration with existing accelerator control systems. The study addresses challenges and proposes solutions for state-of-the-art eLog analysis through practical implementations, demonstrating applications and limitations. We present a framework for enhancing accelerator facility operations through improved information accessibility and knowledge management, which could potentially lead to more efficient operations.

Hellert, Thorsten [LBNL, ALS]↗

eLog analysis for accelerators: status and future outlook

This work demonstrates electronic logbook (eLog) systems leveraging modern AI-driven information retrieval capabilities at the accelerator facilities of Fermilab, Jefferson Lab, Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory. We evaluate contemporary tools and methodologies for information retrieval with Retrieval Augmented Generation (RAGs), focusing on operational insights and integration with existing accelerator control systems. The study addresses challenges and proposes solutions for state-of-the-art eLog analysis through practical implementations, demonstrating applications and limitations. We present a framework for enhancing accelerator facility operations through improved information accessibility and knowledge management, which could potentially lead to more efficient operations.

Sulc, A. [LBL, Berkeley]↗

LSAFE: a Lightweight Static Analysis Framework for binary Executables

Static analysis is a widely used technique for analyzing various aspects of programs. However, as programs become more complex, static analysis tools require larger resources, such as CPU time and memory, to perform the same tasks. Moreover, the source code of programs may not always be accessible, requiring static analysis to be performed on the binary executable code directly. To overcome these challenges, we propose a lightweight static analysis framework called LSAFE, which constructs control flow graphs (CFGs) and data dependency graphs (DDGs) of target programs with optimized performance in terms of CPU and memory usage. We evaluated the proposed framework using both Spec benchmark programs and real-world industrial applications, and found that it outperformed Angr, an existing state-of-the-art static analysis tool. Additionally, we demonstrate a case study that utilizes the CFG generated by LSAFE to detect memory leaks.

Qu, Guangzhi↗

Decision-making based on Markov decision process in integrated artificial reasoning framework—Part I: Theory

This paper presents a decision-making framework based on an integrated artificial reasoning framework and Markov decision process (MDP). The integrated artificial reasoning framework provides a physics-based approach that converts system information into state transition models, and the analysis result will be represented by the transition probabilities that can be used with an MDP to find a traceable and explainable optimal pathway. A dynamic Bayesian network (DBN) is well suited for representing the structure of an MDP. The causality information among process variables (or among subsystems) is mathematically represented in a DBN by the conditional probabilities of the node’s states provided different probabilities of the parent node’s states. To define node states in a physically understandable manner, we used multilevel flow modeling (MFM). An MFM follows the fundamental energy and mass conservation laws and supports the selection of process variables that represent the system of interest so that causal relations among process variables are properly captured. An MFM-based DBN supports developing state transition models in an MDP to capture the effect of process variables of system having physical relations. The operators of the target system can capture stochastic system dynamics as multiple subsystem state transitions based on their physical relations and uncertainties coming from component degradation or random failures. We analyzed a simplified exemplary system to illustrate an optimal operational policy using the suggested approach.

Markov decision process↗

Transient Triplet Metallopnictinidenes M–Pn (M = Pd II , Pt II ; Pn = P, As, Sb): Characterization and Dimerization

Nitrenes (R–N) have been subject to a large body of experimental and theoretical studies. The fundamental reactivity of this important class of transient intermediates has been attributed to their electronic structures, particularly the accessibility of triplet vs singlet states. In contrast, electronic structure trends along the heavier pnictinidene analogues (R–Pn; Pn = P–Bi) are much less systematically explored. We here report the synthesis of a series of metallodipnictenes, {M–Pn=Pn–M} (M = Pd II , Pt II ; Pn = P, As, Sb, Bi) and the characterization of the transient metallopnictinidene intermediates, {M–Pn} for Pn = P, As, Sb. Structural, spectroscopic, and computational analysis revealed spin triplet ground states for the metallopnictinidenes with characteristic electronic structure trends along the series. In comparison to the nitrene, the heavier pnictinidenes exhibit lower-lying ground state SOMOs and singlet excited states, thus suggesting increased electrophilic reactivity. Furthermore, the splitting of the triplet magnetic microstates is beyond the phosphinidenes {M–P} dominated by heavy pnictogen atom induced spin–orbit coupling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Search for bottom-type vectorlike quark pair production in dileptonic and fully hadronic final states in proton-proton collisions at s = 13 TeV

A search is described for the production of a pair of bottom-type vectorlike quarks ( B VLQs) with mass greater than 1000 GeV. Each B VLQ decays into a b quark and a Higgs boson, a b quark and a Z boson, or a t quark and a W boson. This analysis considers both fully hadronic final states and those containing a charged lepton pair from a Z boson decay. The products of the H → b b boson decay and of the hadronic Z or W boson decays can be resolved as two distinct jets or merged into a single jet, so the final states are classified by the number of reconstructed jets. The analysis uses data corresponding to an integrated luminosity of 138 fb - 1 collected in proton-proton collisions at s = 13 TeV with the CMS detector at the LHC from 2016 to 2018. No excess over the expected background is observed. Lower limits are set on the B VLQ mass at the 95% confidence level. These depend on the B VLQ branching fractions and are 1570 and 1540 GeV for 100% B → b H and 100% B → b Z , respectively. In most cases, the mass limits obtained exceed previous limits by at least 100 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Super-resolution model for overlapping peak detection and improved spatial resolution in high-energy diffraction microscopy

Reconstruction quality in Far-field High-Energy Diffraction Microscopy (FF-HEDM) is limited by the spatial resolution of area detectors and the frequent occurrence of overlapping diffraction spots. To address these challenges, we developed a super-resolution (SR) framework using convolutional neural networks (CNNs) to recreate 2D diffraction peaks at up to ×8 resolution from raw detector data. A specialized simulation tool was created to generate synthetic training datasets with varying degrees of peak overlap. Integrated into the Microstructural Imaging using Diffraction Analysis Software (MIDAS), the SR model improves the spatial accuracy and precision of 3D grain reconstruction by an order of magnitude. This approach provides a robust solution for investigation of complex micromechanical states and material classes where the analysis is limited by the presence of overlapping peaks. Furthermore, the methodology developed here can potentially be extended to other techniques that require sub-pixel accuracy for high-fidelity data analysis.

High-energy diffraction microscopy↗

Influence of Peripheral Substituents on Fe(II) Spin State in Complexes with Tridentate Schiff‐Base Ligands

Abstract Six Fe(II) complexes with substituted 6‐((quinoline‐8‐ylimino)methyl)phenolates (R 2 qsal) were synthesized. X‐ray crystal structure determination for [Fe(R 2 qsal) 2 ], where R=F ( 1 ), Cl ( 2 ), Br ( 3 ), I ( 4 ), CF 3 /H ( 5 ), or CN/H ( 6 ), revealed mononuclear complexes that crystallize either solvent‐free in case of 1 , 5 , and 6 or as CH 2 Cl 2 solvates in the case of 2 , 3 , and 4 . Complexes 1 – 4 , which contain π‐donating substituents, exhibit only high‐spin (HS) state, as shown by crystal structure analysis and magnetic measurements. In contrast, complexes 5 and 6 , which contain electron‐withdrawing substituents, exist in the low‐spin (LS) state at lower temperatures but exhibit crossover to the HS state above 300 K. Electronic structure calculations show a good correlation between the relative energies of the LS and HS states and the experimentally observed behavior.

Gakiya‐Teruya, Miguel↗

The impact of regional resources and technology availability on carbon dioxide removal potential in the United States

To achieve net zero carbon emissions by mid-century, the United States may need to rely on carbon dioxide removal (CDR) to offset emissions from difficult-to-decarbonize sectors and/or shortfalls in near-term mitigation efforts. CDR can be delivered using many approaches with different requirements for land, water, geologic carbon storage capacity, energy, and other resources. The availability of these resources varies by region in the U.S. suggesting that CDR deployment will be uneven across the country. Using the global change analysis model for the United States (GCAM-USA), we modeled six classes of CDR and explored their potential using four scenarios: a scenario where all the CDR pathways are available (Full Portfolio), a scenario with restricted carbon capture and storage (Low CCS), a scenario where the availability of bio-based CDR options is limited (Low Bio), and a scenario with constraints on enhanced rock weathering (ERW) capabilities (Low ERW). We find that by employing a diverse set of CDR approaches, the U.S. could remove between 1 and 1.9 GtCO 2 /yr by midcentury. In the Full Portfolio scenario, direct air carbon capture and storage (DACCS) predominates, delivering approximately 50% of CO 2 removal, with bioenergy with carbon capture and storage contributing 25%, and ERW delivering 11.5%. Texas and the agricultural Midwest lead in CDR deployment due to their abundant agricultural land and geological storage availability. In the Low CCS scenario, reliance on DACCS decreases, easing pressure on energy systems but increasing pressure on the land. In all cases CDR deployment was found to drive important impacts on energy, land, or materials supply chains (to supply ERW, for example) and these effects were generally more pronounced when fewer CDR technologies were available.

54 ENVIRONMENTAL SCIENCES↗

Techno-economic analysis of synthetic fuel production from existing nuclear power plants across the United States

Abstract Low carbon synfuel can reduce dependence on fossil fuels like diesel and jet fuel, and, with large-scale cost-effective production, contribute to global transportation sector decarbonization, Simultaneously, nuclear power plants are struggling economically due to falling wholesale electricity prices. Converting existing nuclear plants for synfuel production could preserve these low-carbon assets and enable large-scale synfuel production, yet no comprehensive technoeconomic analysis exists. This study evaluates the potential of integrating synthetic fuel production with five US nuclear plants, considering electricity and fuel markets and carbon dioxide source access. Such integration could enhance nuclear plant profitability by up to $792 million and offer a 10% return on investment over 20 years. The hydrogen production tax credit from the 2022 Inflation Reduction Act is crucial, comprising 75% of revenues on average. Carbon feedstock transportation has the highest cost at 35%, followed closely by synfuel production capital costs. Incentive policies are thus key for the decarbonization of the transportation sector and the economic importance of the geographic location of Integrated Energy Systems.

Garrouste, Marisol (ORCID:0000000168388644)↗

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗

Neutrino-Argon Cross Sections in MicroBooNE: Measurements Spanning Multiple Interaction Channels, Final States, and Neutrino Fluxes

Neutrinos are one of the most elusive particles in the Standard Model of particle physics due to their tiny interaction cross section, which makes them challenging to detect and study. There are three known flavors of neutrinos, and any given neutrino probabilistically oscillates between them as a function of the particle's energy and propagation distance. Experimental characterization of these oscillations elucidates fundamental properties of the neutrino and the Standard Model. Meeting the precision goals of ongoing and future oscillation measurements requires detailed modeling of the way neutrinos interact with nuclear matter. Precision modeling of these interactions is a challenging theoretical problem, rich with intricate physics effects to explore, and requires input from equally precise measurements of neutrino-nucleus interaction cross sections spanning a broad range of scattering channels. To fill this need, there is an ongoing multi-experiment effort to measure these cross sections across energies, interaction channels, and nuclear targets. This thesis describes three analyses reporting neutrino-argon cross section measurements with data from the MicroBooNE liquid argon time projection chamber detector. These span multiple interaction channels, final state topologies, and neutrino fluxes. The first analysis is a set of inclusive charged current muon neutrino cross section measurements for final states with and without protons, which provides a unique view of the hadronic final state produced in these interactions. Second is a set of cross section measurements for neutral current neutral pion production, which provides a vital dataset on this under-characterized channel. Third is significant progress on measuring neutrinos produced by kaons decaying at rest, which represents a unique opportunity to measure cross sections with a mono-energetic flux of neutrinos. These measurements are accompanied by a modeling study in the GiBUU theory framework, which probes the sensitivity of the muon neutrino and pion production measurements to the modeling of nucleon-nucleon final state interactions in neutrino-nucleus scattering.

Bogart, Benjamin [Michigan U.]↗

Developing Lanthanide-Nitrate Cluster Chemistry toward Rare Earth Separations

Nitrate-decorated hexamers with a [Ln 6 (μ 6 -O)(μ 3 –OH) 8 ] 8+ core have been reported for nearly every lanthanide ion and are used as precursors for the assembly of functional metal–organic frameworks. Yet, few studies have examined the correlation between the solution and solid-state species, and the formation of mixed-metal clusters. Toward this end, a series of homo- and heterometal lanthanide nitrate hexamers was prepared via pH adjustment of aqueous lanthanide nitrate solutions. Examination of the homometallic europium solutions using Small Angle X-ray Scattering and nESI-MS showed that lower order complexes dominate lanthanide speciation in nitrate media. Yet, powder X-ray diffraction data of the precipitated phase confirmed the formation of [Ln 6 (μ 6 -O)(μ 3 -OH) 8 (NO 3 ) 6 (H 2 O) 12 ]·2(NO 3 )·n(H 2 O), Ln 6 , for Ln = Eu and Tb. For heterometal systems, analysis of the solid-state product by ICP–MS showed the selective incorporation of the heavier rare earths into Ln 6 . Selectivity was quantified by calculating an average separation factor, which is defined as the ratio of recovery factors of both metals. Further examination of the luminescence behavior of mixed metal [Tb 6–x Eu x (μ 6 -O)(μ 3 -OH) 8 (NO 3 ) 6 (H 2 O) 12 ]·2(NO 3 )·n(H 2 O), with x = 1.1–3.6, showed that the relative intensities of the peaks at 489 nm (terbium, 5 D 4 → 7 F 6 ) and 690 nm (europium, 5 D 0 → 7 F 4 ) trend with the percent incorporation of europium and terbium into the cluster.

anions↗