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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Opto-twistronic Hall effect in a three-dimensional spiral lattice

Studies of moire systems have elucidated the exquisite effect of quantum geometry on the electronic bands and their properties, leading to the discovery of new correlated phases. However, most experimental studies have been confined to a few layers in the 2D limit. The extension of twistronics to its 3D limit, where the twist is extended into the third dimension between adjacent layers, remains underexplored due to the challenges in precisely stacking layers. Here, in this study, we focus on 3D twistronics on a platform of self-assembled spiral superlattice of multilayered WS 2 . Our findings reveal an opto-twistronic Hall effect in the spiral superlattice. This mesoscopic response is an experimental manifestation of the noncommutative geometry that arises when translational symmetry is replaced by a non-symmorphic screw operation. We also discover signatures of altered laws of optical excitation, manifested as an unconventional photon momentum-lattice interaction owing to moire of moire modulations in the 3D twistronic system. Crucially, our findings mark the initial identification of higher-order quantum geometrical tensors in light-matter interactions. This breakthrough opens new avenues for designing quantum materials-based optical lattices with large nonlinearities, paving the way for the development of advanced quantum nanophotonic devices.

Ji, Zhurun↗
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Advancing Detector R&D for High-Pressure Gaseous Argon TPCs in Precision Neutrino Physics

High-pressure gaseous argon time projection chambers (HPgTPCs) represent an emerging detector paradigm for neutrino physics, combining increased target density with the intrinsic tracking and low thresholds of gaseous detectors. This approach enables detailed reconstruction of exclusive final states, improved particle identification, and sensitivity to low-energy and rare processes — capabilities that are increasingly central to precision oscillation measurements and searches for beyond-the-Standard-Model signatures. This abstract presents an overview of ongoing detector R&D toward high-pressure gaseous argon TPC operation, with emphasis on micro-pattern gas detector (MPGD) charge amplification in argon-based mixtures. We report experimental characterization of triple-GEM structures at pressures relevant for neutrino applications, including studies of multiplication factor scaling, stability, and operational voltage envelopes across gas admixtures. Measurements performed at the TOAD and GORG test stands at Fermilab help define viable amplification and electronics noise regimes in conditions where higher density imposes stricter constraints on signal formation. These results provide essential input to the optimization of high-pressure gaseous argon detectors for future neutrino experiments, including near-detector concepts such as ND-GAr in DUNE Phase II near detector upgrade. More broadly, this program shows how dedicated detector R&D can expand the precision frontier in neutrino physics by enabling complementary reconstruction capabilities beyond conventional detectors.

McConnell, Brenna [Indiana U.] (ORCID:000900041138↗
DOE OSTI2025

Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. II. Statistical Properties from the First Data Release

We present the identification of changing-look active galactic nuclei (CL-AGNs) from the Dark Energy Spectroscopic Instrument First Data Release and Sloan Digital Sky Survey Data Release 16 at z ≤ 0.9. To confirm the CL-AGNs, we utilize spectral flux calibration assessment via an [O III ]-based calibration, pseudophotometry examination, and visual inspection. This rigorous selection process allows us to compile a statistical catalog of 561 CL-AGNs, encompassing 527 Hβ, 149 Hα, and 129 Mg II CL behaviors. In this sample, we find (1) a 283:278 ratio of turn-on to turn-off CL-AGNs. (2) The median Eddington ratio for CL-AGNs in the dim state is approximately λ Edd ∼ 0.01. (3) A strong correlation between the change in the luminosity of the broad emission lines (BELs) and variation in the continuum luminosity, with Mg II and Hβ displaying similar responses during CL phases. (4) The Baldwin–Phillips–Terlevich diagram for CL-AGNs shows no statistical difference from the general AGN catalog. (5) Five CL-AGNs are associated with asymmetrical mid-infrared flares, possibly linked to tidal disruption events. Given the large CL-AGN sample and the stochastic sampling of spectra, we propose that some CL phenomena are inherently due to typical AGN variability during low accretion rates, particularly for CL phenomenon only occurring on one BEL. Finally, we introduce a monotonically dimming CL phase for objects characterized by a gradual decline over decades in the light curve and the complete disappearance of entire BELs in faint spectra, indicative of a real transition in the accretion disk.

accretion↗
DOE OSTI2025

Changing-look Active Galactic Nuclei from the Dark Energy Spectroscopic Instrument. II. Statistical Properties from the First Data Release

We present the identification of changing-look active galactic nuclei (CL-AGNs) from the Dark Energy Spectroscopic Instrument First Data Release and Sloan Digital Sky Survey Data Release 16 at z≤ 0.9. To confirm the CL-AGNs, we utilize spectral flux calibration assessment via an [O iii]-based calibration, pseudophotometry examination, and visual inspection. This rigorous selection process allows us to compile a statistical catalog of 561 CL-AGNs, encompassing 527 Hβ, 149 Hα, and 129 Mg ii CL behaviors. In this sample, we find (1) a 283:278 ratio of turn-on to turn-off CL-AGNs. (2) The median Eddington ratio for CL-AGNs in the dim state is approximately λ$_{Edd}$ ∼ 0.01. (3) A strong correlation between the change in the luminosity of the broad emission lines (BELs) and variation in the continuum luminosity, with Mg ii and Hβ displaying similar responses during CL phases. (4) The Baldwin–Phillips–Terlevich diagram for CL-AGNs shows no statistical difference from the general AGN catalog. (5) Five CL-AGNs are associated with asymmetrical mid-infrared flares, possibly linked to tidal disruption events. Given the large CL-AGN sample and the stochastic sampling of spectra, we propose that some CL phenomena are inherently due to typical AGN variability during low accretion rates, particularly for CL phenomenon only occurring on one BEL. Finally, we introduce a monotonically dimming CL phase for objects characterized by a gradual decline over decades in the light curve and the complete disappearance of entire BELs in faint spectra, indicative of a real transition in the accretion disk.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Leveraging machine learning to enhance aerosol classification using Single-Particle Mass Spectrometry

Advancing automated classification of atmospheric aerosols from Single-Particle Mass Spectrometry (SPMS) data remains challenging due to overlapping ion signatures, compositional diversity, and limited labeled data. This study evaluates supervised and semi-supervised learning frameworks to enhance aerosol identification by jointly leveraging labeled and unlabeled spectra. Four models were compared: a supervised Support Vector Machine (SVM), a self-training SVM, a stacked autoencoder classifier, and a stacked autoencoder trained using a temporal-ensembling Mean Teacher approach. All models achieved high and stable accuracies (90.0 %–91.1 %), surpassing previous results on the same dataset (87 %) and matching the performance of state-of-the-art deep learning methods. Despite small global metric differences (≤ 1 %), semi-supervised variants yielded up to 5 %–10 % improvements for compositionally rare particle types – such as soot (0.77 % of spectra, F1-score: 0.93–0.97) and hazelnut pollen (0.98 % of spectra, F1-score: 0.97–1.00) – equating to roughly ∼ 187 additional correctly classified spectra. These gains are scientifically significant, as such rare particles exert disproportionate influence on radiative absorption and ice nucleation processes; their improved detection reduces modeled uncertainties in aerosol absorption optical depth and mixed-phase cloud ice nucleation rates. The models' residual misclassifications (≈ 9 %) largely arise from true spectral overlap among chemically adjacent species (e.g., Na- vs. K-feldspar, coated vs. uncoated feldspars), reflecting physical compositional continuity rather than algorithmic error. Collectively, these findings demonstrate that leveraging unlabeled data to learn robust spectral representations and refine classification enhances both fidelity and interpretability, bridging data-driven analysis with aerosol–climate process understanding.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Heat load measurements for the PIP-II pHB650 cryomodule

This study presents a brief overview of the 1st and 2nd phases and an in-depth analysis of the 3rd phase heat load testing performed on the pHB650 (prototype High Beta 650 MHz) cryomodule at PIP2IT (PIP-II Injector Test Facility), with a focus on both the results and the methodological advancements that have improved testing efficiency and accuracy. A key challenge identified in the testing campaign is the higher-than-expected heat loads observed in the first PIP-II (Proton Improvement Plan II) prototype cryomodules (pSSR1 and pHB650) tested at PIP2IT. Elevated heat loads are concerning given the fixed capacity of the PIP-II cryoplant that is currently being installed at Fermilab. However, understanding the sources of these elevated heat loads offers a critical opportunity to implement effective heat load mitigations on upcoming PIP-II cryomodules to stay within the available capacity of the PIP-II cryoplant. The study includes a summary of test results, descriptions of measurement procedures, and key observations on parameters directly and indirectly related to heat load measurements. Direct observations include measured heat loads and the effectiveness of JT heat exchanger under varying conditions, while indirect observation analyze factors such as the temperature distribution on the two-phase pipe and relief piping under varying conditions. Thermal acoustic oscillations (TAO) were identified during testing, which was mitigated by replacing the original G10 stem with a stainless steel stem equipped with wipers for the cryomodule cooldown valve. A major innovation during pHB650 Phase 3 testing was the development of an automated Python script to streamline data acquisition, analysis, and reporting of heat load results. This script automatically retrieved data from ACNET (Accelerator Control Network), performed heat load calculations, and generated detailed reports featuring plots and tables. This advancement significantly reduced manual labor and enhanced the thoroughness of data analysis compared to earlier campaigns. The heat load test reports were promptly uploaded to the electronic logbook shortly after each test, enabling rapid feedback and collaboration between the SRF and cryogenic teams. The heat load measurements included various components: HTTS (high-temperature thermal shield), LTTS (low-temperature thermal shield), 2K isothermal and non-isothermal heat loads. Results were recorded both within the cryomodule and between the bayonet can supply and return. Measurements were conducted under different operating conditions such as "standard", "linac", and "simulated dynamic". Additionally, HTTS and LTTS heat loads were calculated in real time, allowing for the tracking of thermal stability and identification of changes during testing, both in steady-state and transient conditions. The results of this testing campaign not only provide valuable insights into the performance of the pHB650 cryomodule but also highlight best practices and lessons learned that will inform future cryomodule testing at PIP2IT. These include adopting automated tools for data analysis, refining real-time measurement capabilities, and emphasizing detailed pre-test planning. The framework established in this campaign aims to set an improved standard for cryomodule testing and heat load reporting in future cryomodule test campaigns.

Porwisiak, D. [Fermilab; Wroclaw Tech. U.]↗
DOE OSTI2024

Measurement report: The Fifth International Workshop on Ice Nucleation phase 1 (FIN-01): intercomparison of single-particle mass spectrometers

Knowledge of the chemical composition and mixing state of aerosols at a single-particle level is critical for gaining insights into atmospheric processes. One common tool to make these measurements is single-particle mass spectrometry. There remains a need to compare the performance of different single-particle mass spectrometers (SPMSs). An intercomparison of SPMSs was conducted at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) chamber at the Karlsruhe Institute of Technology (KIT) in November 2014, as part of the first phase of the Fifth International Workshop on Ice Nucleation (FIN-01). In this paper we compare size distributions and mass spectra of atmospherically relevant particle types measured by five SPMSs. These include different minerals, desert and soil dusts, soot, bioaerosol (Snomax; protein granule), secondary organic aerosol (SOA), and SOA-coated mineral particles. Most SPMSs reported similar vacuum aerodynamic diameter (d va ) within typical instrumental ranges from ~100–200 nm (lower limit) to ~2–3 µm (upper limit). In general, all SPMSs exhibited a wide dynamic range (up to ~10 3 ) and high signal-to-noise ratio (up to ~10 4 ) in mass spectra. Common spectral features with small diversities in mass spectra were found with high average Pearson's correlation coefficients, i.e., for average positive spectra r avg-pos =0.74 ± 0.12 and average negative spectra r avg-neg =0.67 ± 0.22. We found that instrument-specific detection efficiency (DE) was more dependent on particle size than particle type, and particle identification favored the use of bipolar, rather than monopolar, instruments. Particle classification from “blind experiments” showed that all instruments differentiated SOA, soot, and soil dust and detected subtle changes in the particle internal mixing but had difficulties differentiating among specific mineral types and dusts. This study helps to further understand the capabilities and limitations of the single-particle mass spectrometry technique in general and the specific performance of the instrument in characterizing atmospheric aerosol particles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Interpretable machine learning models classify minerals via spectroscopy

Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.

Machine learning↗
DOE OSTI2025

Detection of a Space Capsule Entering Earth’s Atmosphere with Distributed Acoustic Sensing (DAS)

On 24 September 2023, the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer sample return capsule (SRC) entered Earth’s atmosphere after successfully collecting samples from an asteroid. The known trajectory and timing of this return provided a rare opportunity to strategically instrument sites to record geophysical signals produced by the capsule because it travelled at hypersonic speeds through the atmosphere. For this work, we deployed two distributed acoustic sensing (DAS) interrogators to sample over 12 km of surface-draped fiber-optic cables, as well as six collocated seismometer-infrasound sensor pairs, spread across two sites near Eureka, Nevada. This campaign-style rapid deployment is the first reported recording of an SRC re-entry with any distributed fiber-optic sensing technology. The DAS interrogators recorded an impulsive arrival with an extended coda which had features that were similar to recordings from both the seismometers and infrasound sensors. While the signal-to-noise ratio of the DAS data was lower than the seismic-infrasound data, the extremely dense spacing of fiber-optic sensors allowed for more phases to be clearly distinguished and the visualization of the continuous transformation of the wavefront as it impacted the ground. Unexpectedly, the DAS recordings contain less low-frequency content than is present in both the seismic and infrasound data. The deployment conditions strongly affected the recorded DAS data; in particular, we observed that fiber selection and placement exert strong controls on data quality.

58 GEOSCIENCES↗
DOE OSTI2025

Analysis of the linear and nonlinear stability of Alfven eigenmodes and fish-bones in JET DT discharges: mode identification and shear flows generation

The plasma in future nuclear fusion reactors will be heated by neutral beam injectors (NBIs) and high frequency electromagnetic waves as well as fusion born alpha particles. Energetic particles (EPs), with energies up to two orders of magnitude larger than the thermal plasma, can trigger EP driven modes and induce harmful EP losses, reducing the plasma heating efficiency and the economical viability of the reactor. The present study is dedicated to analyze the Alfven Eigenmode (AE) activity in JET D–T discharges, the closest experiment to reactor-like operation performed until now. There, EP driven modes are induced by the combined effect of tangential NBIs and ion cyclotron resonance heating (ICRH) driven EP. Linear and nonlinear simulations are performed with the gyro-fluid FAR3d code to analyze the AE activity observed in the discharge 99896. The linear simulations reproduce the unstable n = 3 to 5 toroidal AEs (TAE) at the inner plasma region observed in the experiment, triggered by highly energetic passing deuterium populations injected by the tangential NBIs, further accelerated by the effect of the ICRH up to 1 MeV. In addition, fish-bones triggered by energetic trapped hydrogen induced by the ICRH are also reproduced. On the other hand, the alpha particles density is too small to destabilize AEs in the experiment. Nonetheless, increasing artificially the alpha density by one order of magnitude, an n = 1 beta induced AE can be destabilized in the inner plasma region. Nonlinear simulations indicate the generation of zonal structures during the AE/fish-bone saturation phase. TAE and fish-bones causes a rather weak increase of the passing D and trapped H EP (around 2%), respectively. Shear flows and zonal currents are generated during the saturation of TAE and fish-bones. Nonlinear simulations performed for D–T and pure deuterium thermal plasma indicate AE/fish-bone activity is weaker and shear flows are less intense in the pure deuterium case, trends consistent with the experimental observations that also indicates a deterioration of the thermal plasma confinement. Therefore, both numerical studies and experimental evidence indicate the generation of shear flows by AE/fish-bones could be connected with an improvement of the thermal plasma confinement.

AE↗
DOE OSTI2024

Fast Oxygen Redox Kinetics Induced by CoO 6 Octahedron With π –Interaction in P2–Type Sodium Oxides

Enhancing the kinetics of lattice oxygen redox (LOR) in P2-type layered sodium oxide cathodes is crucial for the advancement of sodium-ion batteries (SIBs) with superior energy and power densities. Electronic structure regulation stands out as a highly effective approach to address the inherent limitations of P2-type layered oxides with LOR, including sluggish kinetics, phase transitions, voltage hysteresis, and local structural distortion. In this work, a strategy involving the introduction of CoO 6 octahedra with π-interaction into Na 0.6 Li 0.1 Fe 0.3–x Co x Mn 0.6 O 2 (x = 0, 0.15, 0.3) cathodes to facilitate Na-ion transport is proposed. Furthermore, the impact of FeO 6 octahedra with σ-interaction in P2-type cathodes on electrochemical performance is comprehensively investigated. Through multimodal in-situ and ex-situ characterization techniques, it is revealed that Co–O with π-interaction effectively mitigates P2-OP4 phase transitions by strengthening Na–O, reduces voltage hysteresis, and stabilizes the local structure. Consequently, Na 0.6 Li 0.1 Co 0.3 Mn 0.6 O 2 demonstrates enhanced Na-ion diffusion kinetics, leading to improved rate performance and a reversible capacity of 55 mAh g –1 at 10 C, significantly outperforming cathodes with Fe–O σ-interaction. Moreover, when coupled with hard carbon, the full cell achieves a remarkable energy density of 395 Wh kg –1 (on cathode) at 0.1 C, with a capacity retention of 75% over 100 cycles at 1 C.

25 ENERGY STORAGE↗
DOE OSTI2025

Intrinsic Kinetics of Polyethylene Terephthalate Pyrolysis via Micropyrolysis and Multivariate Chromatographic Analysis

This study provides an in-depth investigation of the primary decomposition of polyethylene terephthalate (PET) via pyrolysis, employing an experimental-analytic workflow that integrates design of experiments (DoE), micropyrolysis coupled with comprehensive two-dimensional gas chromatography (GC×GC), and multivariate data analysis to verify intrinsic kinetic conditions and elucidate evolving product distributions for mapping key reaction pathways. Peaks that could not be identified using commercial spectral libraries were assigned using Mass Frontier simulations, enabling the identification of divinyl terephthalate, ethyl vinyl terephthalate, and 2-(benzoyloxy)ethyl vinyl terephthalate. A polar×polar (non-orthogonal) column set tailored for the detection of carboxylic acids enhanced the quantification of benzoic acid, 4-vinylbenzoic acid, 4-ethylbenzoic acid, and methylbenzoic acid by up to 6-fold relative to an orthogonal column combination (non-polar×mid-polar). Moreover, pyrolysis variables were systematically evaluated using a Box- Behnken design (BBD), encompassing pyrolysis temperature (500−600 °C), sample weight (50−150 μg), and carrier gas flow rate (100−300 mL min −1 ). Among these, pyrolysis temperature was the only statistically significant factor influencing product yields, ranging from 58.78 to 84.26 wt %. In contrast, neither the sample weight nor the carrier gas flow rate had a significant effect on product yields within the evaluated experimental space. At 600 °C, the major pyrolysis products were benzoic acid (up to 20.20 ± 1.46 wt %) and CO 2 (up to 21.28 ± 1.46 wt %), which can be produced through decarboxylation reactions. These findings underscore the critical importance of selecting appropriate analytical columns for the accurate quantification of heteroatomcontaining products such as carboxylic acids, which may otherwise be underestimated or undetected due to their reactivity with the stationary phase of non-polar and mid-polar columns, as well as other GC components. They also highlight the importance of selecting pyrolysis conditions for investigating the primary decomposition of PET under an isothermal kinetically limited regime.

aromatic compounds↗
DOE OSTI2025

Sulfur Species in Zinc-Rich Condylar Zones of a Rat Temporomandibular Joint

We performed synchrotron-based micro-X-ray absorption near-edge spectroscopy (µ-XANES) coupled with micro-X-ray fluorescence (µ-XRF) for the identification of elements that included biometal zinc (Zn) and nonmetal sulfur (S) (and its species) in the condylar zones of a rat temporomandibular joint (TMJ). Zone-specific spatial localization of biometal Zn and nonmetal S from a materials viewpoint when correlated with hypoxia inducible factor-1α (HIF-1α) (a surrogate for tissue oxygenation) can provide insights into Zn-specific redox pathways at the vulnerable subchondral interface. Histologic localization of Zn, HIF-1α, and sulfur-rich proteoglycans (PGs) were mapped using an optical microscope. The µ-XRF maps coupled with site-specific micro-X-ray diffraction (µ-XRD) patterns were used to underline Zn-incorporated biological apatite in the subchondral bone and the bone of a rat TMJ condyle. Results demonstrated an association between Zn, PG, and HIF-1α histologic maps with µ-XRF, µ-XANES, and µ-XRD data and provided insights into plausible biological S species in Zn-enriched zones of a rat TMJ condyle. Spatially localized Zn and S underscore their roles in cell and tissue functions in a zone-specific manner. Elemental Zn with organic and inorganic S species at the cartilage-bone interface and the biomineral phase of Zn-enriched biological apatite from subchondral bone to condylar bone were ascertained using µ-XRF-XANES and µ-XRF-XRD. The coupled µ-XRF-XANES in situ complemented with µ-XRF-XRD in situ and immunohistochemistry provided valuable biological insights into zone-specific biological pathways in rat TMJ condyles. Based on these data, we present a workflow to reliably map and correlate S species within Zn-enriched regions of cartilage, bone, and their interface. We suggest the use of this correlative and complementary microspectroscopic spatial information for zone-specific localization of biometal Zn and nonmetal S to gain insights into plausible microanatomy-specific oxidative stress in the TMJ.

apatites↗
DOE OSTI2025

Enhancing quantum memory lifetime with measurement-free local error correction and reinforcement learning

Reliable quantum computation requires systematic identification and correction of errors that occur and accumulate in quantum hardware. To diagnose and correct such errors, standard quantum error-correcting protocols utilize global error information across the system obtained by mid-circuit readout of ancillary qubits. We investigate circuit-level error-correcting protocols that are measurement-free and based on local error information. Such a local error correction (LEC) circuit consists of faulty multi-qubit gates to perform both syndrome extraction and ancilla-controlled error removal. We develop and implement a reinforcement learning framework that takes a fixed set of faulty gates as inputs and outputs an optimized LEC circuit. To evaluate this approach, we quantitatively characterize an extension of logical qubit lifetime by a noisy LEC circuit. For the two-dimensional (2D) classical Ising model and four-dimensional toric code, our optimized LEC circuit performs better at extending a memory lifetime compared with a conventional LEC circuit based on Toom's rule in a subthreshold gate error regime. We further show that such circuits can be used to reduce the rate of mid-circuit readouts to preserve a 2D toric code memory. Lastly, we discuss the application of the LEC protocol on dissipative preparation of quantum states with topological phases.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Molecular Mass Growth Processes to Polycyclic Aromatic Hydrocarbons through Radical–Radical Reactions Exploiting Photoionization Reflectron Time-of-Flight Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) represent critical building blocks in molecular mass growth processes to carbonaceous nanoparticles, referred to as interstellar and circumstellar grains along with soot particles in astrophysical environments and combustion systems, respectively. Recent advancements on elucidating elementary steps to PAHs have utilized reactions of aromatic radicals, resonantly stabilized free radicals, and aliphatic radicals with closed shell hydrocarbons. However, the role of radical–radical reactions (RRRs) leading to PAHs has remained largely unexplored on the molecular level due to preceding experimental challenges in producing sufficiently high number densities of radical reactants for isomer-selective detection of products from bimolecular and termolecular reactions. This Account offers the latest developments in our knowledge on the mechanisms and pathways to PAHs via RRRs probed in a chemical microreactor at temperatures as high as 1600 K. Product preservation in a molecular beam coupled with synchrotron vacuum ultraviolet photoionization reflectron time-of-flight mass spectrometry and photoelectron photoion coincidence spectroscopy enabled isomer-selective detection of PAHs of up to three rings by their photoionization efficiency curves, which were fit with a linear combination of reference curves for identification. Experiments were combined with computational fluid dynamics modeling of the physicochemical processes in the microreactor, as well as high-level electronic structure calculations to reveal the reaction pathways of each system. Six distinct reaction mechanisms were discovered in this work: propargyl addition─benzannulation (PABA), methyl addition─ring expansion (MARE), cyclopentadienyl addition─naphthylization (CPAN), fulvenallenyl addition─cyclization─aromatization (FACA), benzyl addition─aromatization (BAA), and phenyl addition─pentacyclization (PAP). By systematically varying the number of carbon atoms in the radical reactants, molecular mass growth processes involving reactions between radicals with odd numbers of carbon atoms access aromatics carrying one, two, or three six-membered rings, whereas reactions between even- and odd-carbon-numbered radicals produce aromatics combining five- and six-membered rings. Our investigations reveal unconventional cycloadditions on excited state triplet surfaces, additions of radicals to low spin density carbon-centered radicals, spiroaromatic and fulvene-type intermediates, and highly strained bicyclic reaction intermediates, challenging current perceptions of PAH molecular mass growth processes. All of the listed mechanisms, except for FACA, feature endoergic reactions or barriers which lie above the separated reactants and therefore might be central to circumstellar environments of carbon-rich stars and planetary nebulae as their descendants, but they play no role in the gas phase of cold molecular clouds where temperatures as low as 10 K dominate. Altogether, this work provides detailed reaction mechanisms of PAH growth processes, advancing our knowledge of the chemistry of carbonaceous matter in the universe.

Addition reactions↗
DOE OSTI2025

X-ray Diffraction Studies of Single-Crystal Materials for Broad Battery Applications

Single-crystal materials have attracted growing interest in battery research due to their well-defined crystallographic orientation, absence of grain boundaries, and enhanced mechanical and electrochemical stability. This Review provides a comprehensive overview of recent advances in the synthesis, structural evolution, and performance optimization of single-crystal electrodes and solid electrolytes. Particular focus is placed on the application of advanced X-ray diffraction (XRD) techniques, including operando synchrotron diffraction, reciprocal space mapping, and Bragg coherent diffraction imaging, which have enabled in-depth investigations of lattice strain, cation disorder, phase transitions, and defect formation. Representative case studies across Ni-rich layered oxides, spinel-type cathodes, and garnet-based electrolytes are examined to highlight the structural features unique to single crystals. Additionally, the synergistic integration of XRD with machine learning, tomography, and spectroscopy is discussed as a powerful direction for real-time analysis and predictive modeling. Furthermore, these insights provide critical guidance for the rational design of high-performance single-crystal materials in lithium, sodium, and solid-state battery systems.

25 ENERGY STORAGE↗
DOE OSTI2024

A new hybrid gadolinium nanoparticles-loaded polymeric material for neutron detection in rare event searches

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often feature a dedicated neutron detector surrounding the active target volume. In the context of the development of DarkSide-20k detector at INFN Gran Sasso National Laboratory (LNGS), several R&D projects were conceived and developed for the creation of a new hybrid material rich in both hydrogen and gadolinium nuclei to be employed as an essential element of the neutron detector. Thanks to its very high cross-section for neutron capture, gadolinium is one of the most widely used elements in neutron detectors, while the hydrogen-rich material is instrumental in efficiently moderating the neutrons. In this paper results from one of the R&Ds are presented. In this effort the new hybrid material was obtained as a poly(methyl methacrylate) (PMMA) matrix, loaded with gadolinium oxide in the form of nanoparticles. We describe its realization, including all phases of design, purification, construction, characterization, and determination of mechanical properties of the new material.

Dark Matter detectors (WIMPs, axions, etc.)↗