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DOE OSTI2025

High-energy $η^{(')}π$ photoproduction and the nature of exotic waves

The observation of hybrid mesons in photoproduction experiments can provide essential insight into the inner workings of quantum chromodynamics in the strong coupling regime. In particular, the study of final $η^{(')}π$ states is of great interest due to the presence of the lowest lying hybrid candidate with manifestly exotic quantum numbers, the $π_1$(1600). In this work, a double-vector exchange model with Reggeized $ρ$ and $ω$ trajectories is developed to describe the photoproduction of $η^{(')}π$ in the high-mass region. Results are presented for the differential cross sections and forward-backward asymmetries in the energy region of interest to the GlueX experiment. The model contains no free parameters, and reproduces the magnitude and t-dependence of existing CLAS data at $E_γ$ = 5 GeV. The model predicts a stronger asymmetry in the $η'π$ channel than in the $ηπ$ channel, consistent with what has previously been observed in pion beam experiments. This suggests that the sizeable production of exotic odd waves in $η'π$ is not necessarily related to the presence of gluon-rich environments. Confirmation of these predicted asymmetries from forthcoming GlueX data would enable further predictions of the low-energy spectrum.

Montaña, Glòria [Thomas Jefferson National Acceler↗

DOE OSTI2025

Improved signal stability in inductively coupled plasma–atomic emission spectrometry through use of tandem spray chambers and surfactant addition

A search for causes of intermittent mid-term (about two hours) instability in emission signals from an inductively coupled plasma led to adoption of a tandem spray-chamber arrangement and subsequently to use of a surfactant (Triton X-100) to mitigate the remaining and newly found instabilities. Through a series of investigations, abrupt signal excursions in the tandem setup were traced to droplet coagulation and drainage inside the glass tube that connected the two spray chambers. However, the signal shifts were not the result of sample-solution release directly but rather to the influence of the underlying factors on plasma behavior. Experiments tailored to the study included not only examination of temporal signal behavior but also collection of long-term videos and measurement of radiofrequency characteristics of the plasma. The addition of a surfactant, Triton X-100, for signal-stability improvement is applicable not only to systems that employ tandem spray chambers but also to conventional single Scott-type chamber arrangements. Further, use of the surfactant was unsuccessful in overcoming “acid effects”, either of the steady-state or transient nature, and did not alter plasma background or analyte signals significantly.

Inductively coupled plasma–atomic emission spectro↗

DOE OSTI2026

Double Quantum Dots with Quenched Charging Energy in PbTe Nanowires

Here, we investigate double quantum dots defined by electrostatic gating in semiconductor PbTe nanowire devices. We perform transport measurements to obtain charge stability diagrams distinguished by negligible separation between paired triple points and by the spin degeneracy of all transport resonances at zero magnetic field. We show a 4-fold splitting of high-bias stability diagram triangles in an applied magnetic field to illustrate the lifting of this spin degeneracy. We also identify patterns of narrow transport resonances in these high-bias triangles and discuss their possible physical origins. Our results represent a step toward the realization of PbTe-based spin qubits.

PbTe nanowire↗

DOE OSTI2025

Intrinsically Bifunctional and Tunable Tungsten Carbide Catalysts Enable Efficient PVC-Compatible Polyolefin Hydrocracking

Hydrocracking is a promising route for the chemical recycling of polyolefins (PO), converting them into short hydrocarbons over bifunctional catalysts with metal sites for hydrogenation and dehydrogenation, and Brønsted acid sites (BAS) for isomerization and C–C bond cleavage. However, PO feedstocks containing polyvinyl chloride (PVC) can release chlorine (Cl) under reaction conditions, deactivating conventional noble metal/zeolite catalysts. Moreover, the lack of site intimacy and the presence of micropores within conventional catalysts create challenges around the transport of high-molecular-weight, sterically encumbered polymer intermediates. Here, in this study, we report tungsten carbides (W x C) as a novel type of bifunctional catalysts that address these challenges. W/W 2 C phases on W x C offer “metal” sites, and −OH on WO x species introduces BAS in close proximity. The “metal”:BAS ratio can be tuned through carburization temperature, leading to a volcano-shaped activity trend reflecting the requirement for metal–BAS balance. Kinetic data demonstrate that each PO chain undergoes sequential cleavage, while trends in cracking ideality and selectivity follow those in short-alkane hydrocracking. On the per-BAS basis, W x C is more efficient than conventional bifunctional catalysts by more than an order of magnitude, due to enhanced polymer transport. They maintain or show increased activity with 10 wt % PVC in the substrate. This work establishes transition-metal carbides as earth-abundant bifunctional catalysts with unique site proximity and heteroatom compatibility. These features, along with the broad structure space for rational tuning, make them promising options to tackle specific challenges that polymer feedstocks present in hydrocracking.

Nwachukwu, Uchenna C. [Univ. of Akron, OH (United ↗

DOE OSTI2025

Similarities in Meteorological Composites Among Different Atmospheric River Detection Tools During Landfall Over Western Coastal North America

Many atmospheric river detection tools (ARDTs) have been developed over the past few decades to identify atmospheric rivers (ARs). Different ARDTs have been observed to capture a variety of frequencies, shapes, and sizes of ARs. Due to this, questions have arisen about the underlying phenomena associated with the detected ARs: do all ARDTs detect the same meteorological phenomena? In this paper, we assess eight ARDTs and investigate the underlying synoptic scale phenomena during landfalling ARs along the west coast of North America. We find that during landfalling AR events, prevalent low-pressure and high-pressure systems converge and enhance moisture influx toward the landfalling site. We identify that all eight ARDTs identify AR conditions associated with baroclinic waves, with the region of intense integrated vapor transport (IVT) located downstream of the upper level (500 hPa) trough. The magnitude of IVT is enhanced by the strength of the pressure gradients in the confluence region. Although the ARDTs assessed agree on the general phenomena, there are however subtle differences in each ARDT per the clustering analysis we performed. We conclude that the eight ARDTs identify similar underpinning synoptic scale meteorological phenomena.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Recommendations for Comprehensive and Independent Evaluation of Machine Learning‐Based Earth System Models

Abstract Machine learning (ML) is a revolutionary technology with demonstrable applications across multiple disciplines. Within the Earth science community, ML has been most visible for weather forecasting, producing forecasts that rival modern physics‐based models. Given the importance of deepening our understanding and improving predictions of the Earth system on all time scales, efforts are now underway to develop Earth‐system models (ESMs) capable of representing all components of the coupled Earth system (or their aggregated behavior) and their response to external changes over long timescales. Building trust in ESMs is a much more difficult problem than for weather forecast models, not least because the model must represent the alternate (e.g., future or paleoclimatic) coupled states of the system for which there are no direct observations. Given that the physical principles that enable predictions about the response of the Earth system are often not explicitly coded in these ML‐based models, demonstrating the credibility of ML‐based ESMs thus requires us to build evidence of their consistency with the physical system. To this end, this paper puts forward five recommendations to enhance comprehensive, standardized, and independent evaluation of ML‐based ESMs to strengthen their credibility and promote their wider use.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Compound Mesoscale Convective Systems and Low‐Pressure Systems in Tropical Monsoon Regions: Assessing Their Meteorology and Precipitation

Mesoscale convective systems (MCS) and low-pressure systems (LPS) are both strongly associated with precipitation across the regions where they occur, particularly within global monsoon systems; however, their co-occurrence and its relationship to precipitation have not been systematically examined. Here, we use LPS and MCS trackers to detect compound MCS and LPS events in five monsoon regions and assess the association of this co-occurrence with anomalies of winds, precipitation, and other atmospheric variables. Additionally, we investigate the spatial distribution of precipitating MCS and LPS events. Our results show that most (∼60%) MCS and LPS co-occurrences are located in the lower latitudes, where they contribute up to 40% of annual precipitation. We find that compound events generally produce more extreme precipitation than MCS-only or LPS-only events. Furthermore, our assessment of the synoptic and mesoscale composites reveals that the underlying dynamics of compound events exhibit anomalously positive convective available potential energy and an anomalously low-pressure within the location of the event. In terms of the synoptic environment of the features, the compound MCS and LPS events are associated with inverted troughs in three out of five monsoon locations assessed.

Environmental sciences↗

DOE OSTI2025

The effect of residential solar on energy insecurity among low- to moderate-income households

Each year, millions of Americans experience energy insecurity, or the inability to afford enough energy to meet their basic needs. Here, this study evaluates whether residential rooftop solar can serve as a preventative solution to energy insecurity among low- to moderate-income households. Using a national, matched sample of solar and non-solar households based on detailed and address-specific data, we find that solar leads to large, robust and salient reductions in five indicators of energy insecurity. Moreover, the benefits of solar ‘spill over’ to improve a household’s ability to pay other energy bills. The results suggest that rooftop solar may be an effective tool for policymakers who seek to reduce energy insecurity.

14 SOLAR ENERGY↗

DOE OSTI2025

Molecular orbital symmetry-driven trimer formation in Kagome correlated electron materials

Correlated electron materials with molecular orbital states extending over transition metal clusters can host multiferroicity, spin frustration, and unconventional insulating phases. However, the fundamental criteria that govern cluster formation and stability remain unclear. Here, we identify a symmetry, correlation, and electron-filling-driven criteria that stabilize triangular metal trimers in materials displaying transition metal Kagome patterns. Using density functional theory and chemical bonding analysis, we show that trimer formation emerges when 6–8 electrons occupy molecular orbitals derived from transition metal d-states, achieving near-complete filling of bonding states while avoiding antibonding occupation, and correlations are of intermediate strength. This principle explains the stability of Nb 3 X 8 (X = Cl, Br, I), and more broadly, our findings offer a general design rule to obtain quantum materials with quantum states extended across transition metal clusters.

Kumari, Varsha [Indiana Univ., Bloomington, IN (Un↗

DOE OSTI2025

Readout electronics for low occupancy High-Pressure Gas TPCs

High-Pressure Gas Time Projection Chambers (HPgTPCs) have benefits such as low energy thresholds, magnetisability, and 4π acceptance, making them ideal for neutrino experiments such as DUNE. We present the design of an FPGA-based solution optimised for Gaseous Argon Near Detector (ND-GAr), which is part of the Phase-II more capable near detector for DUNE. These electronics reduce the cost significantly compared to using collider readout electronics, which are typically designed for much higher occupancy and therefore, for example, need much larger numbers of FPGAs and power per channel. We demonstrate the performance of our electronics with the Teststand for an Overpressurised Argon Detector (TOAD) at Fermilab in the US at a range of pressures and gas mixtures up to 4.5 barA, reading out ∼10 000 channels from a Multi-Wire Proportional Chamber (MWPC). The operation took place between April and July of 2024. We measure the noise characteristics of the system to be sufficiently low, and we identify sources of noise that can be further mitigated in the next iteration. We also note that the cooling scheme used in the test requires improvement before full-scale deployment. Despite these necessary improvements, we show that the system can fulfil the needs of a HPgTPC for a fraction of the price of collider readout electronics.

Data acquisition concepts↗

DOE OSTI2025

Controlling magnetism and transport at perovskite cobaltite interfaces via strain-tuned oxygen vacancy ordering

Complex oxides such as perovskite cobaltites exhibit rich phenomena at interfaces due to the complex interplay between their structural, defect, electronic, and magnetic degrees of freedom. Here, we study this interplay here in the ferromagnetic metallic cobaltite La 1−𝑥 ⁢Sr 𝑥⁢ CoO 3−𝛿 , using specific substrates to vary both the heteroepitaxial strain (compressive vs tensile) and growth orientation ((001) vs (110)). Transmission electron microscopy, electron energy-loss spectroscopy, high-resolution X-ray diffraction, magnetometry, polarized neutron reflectometry, and electronic magnetotransport measurements are applied. Lattice mismatch and growth orientation are found to enable the precise control of interfacial oxygen vacancy ordering in La 1−𝑥⁢ Sr 𝑥 ⁢CoO 3−𝛿 , thus dictating strain relaxation and oxygen vacancy depth profiles, in turn controlling thickness-dependent magnetic and electronic properties. In particular, compressive strain and (110) orientations minimize deleterious magnetic/electronic dead layer effects, leading to the optimization of interfacial magnetism and transport. Strain and orientation tuning of oxygen vacancy ordering are thus established as powerful means to control physical properties at cobaltite-based interfaces, relevant to several fields.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Analyzing and Exploring Training Recipes for Large-Scale Transformer-Based Weather Prediction

Abstract The rapid rise of deep learning (DL) in numerical weather prediction (NWP) has led to a proliferation of models which forecast atmospheric variables with comparable or superior skill than traditional physics-based NWP. However, among these leading DL models, there is a wide variance in both the training settings and architecture used. Further, the lack of thorough ablation studies makes it hard to discern which components are most critical to success. In this work, we show that it is possible to attain high forecast skill even with relatively off-the-shelf architectures, simple training procedures, and moderate compute budgets. Specifically, we train a minimally modified Swin Transformer V2 (SwinV2) on ERA5 data and find that it attains superior skill in terms of mean-square errors of deterministic forecasts when compared against the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS). Almost all DL–NWP systems share a core set of hyperparameters and design decisions. To aid and expedite future DL–NWP research, we present an in-depth, systematic exploration of different loss functions, model sizes and depths, patch sizes, and multistep training objectives. We also examine the model performance with metrics beyond the typical accuracy (ACC) and RMSE and investigate how the performance scales with model size. Through our open-source code, scoring pipelines, and models, we share our findings on key aspects of the training pipeline. These ablations reduce the necessity for expensive hyperparameter tuning and lower the barrier to entry for future DL–NWP research. Significance Statement This study investigates the potential of using large-scale transformer-based models for weather prediction, showing that it is possible to achieve high forecast accuracy with simpler, off-the-shelf architectures. By training a minimally modified SwinV2 transformer on ERA5 data, we show that the model achieves competitive forecast skill in terms of mean-square error for key variables, outperforming the European Centre for Medium-Range Weather Forecasts’ Integrated Forecasting System (IFS) at all lead times. Our findings suggest that effective training strategies, such as multistep fine-tuning and channel-weighted losses, significantly enhance the model’s performance. However, we also highlight that these improvements come with trade-offs in other areas, such as ensemble spread and high-frequency spatial detail. This work highlights the promise of deep learning in improving weather forecasts, which could lead to better preparedness and response to weather events, ultimately benefiting society by providing more reliable weather predictions.

Willard, Jared D. [Lawrence Berkeley National Labo↗

DOE OSTI2025

Soil biogeochemical properties and metrics of tree-mycorrhizal dominance for a 25-Ha forest in South Central Indiana, USA.

This data package contains a dataset used in the papers “Seeing the forest for all the trees: Mycorrhizal-associated nutrient economies are modulated by stem density and the synchrony between overstory and understory communities” and “Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry”. Four csv files are included along with a dataset. The dataset features chemical soil properties for a single sampling campaign within the 25 Ha Lilly-Dickey Woods Smithsonian Forest Global Earth Observatory (ForestGEO) plot in South Central Indiana, USA (ldw_dat_raw.csv). Also included are separate files focused on pH (pH_data.csv), carbon and nitrogen (CN_data.csv), and nitrification rates (Nitrification_data.csv). These variables are commonly associated with the tree-mycorrhizal dominance of forest stands. In these data subsets, each soil variable was matched to a 10 meter radius neighborhood wherein metrics of tree-mycorrhizal dominance (basal area, stem count, importance value, etc.) were calculated. Models between these soil variables and dominance metrics were used to investigate how different assessments of mycorrhizal associated nutrient economies (MANE) capture these relationships. This research was performed as a part of the Smithsonian ForestGEO project. This data package can be used to explore spatial variability in soil chemistry within a mature hardwood forest, or it can be combined with the included tree data, other fine-scale spatial information, or other tree inventory data for the site to evaluate how soil chemistry varies with tree community composition or edaphic or topographic properties.

Craig, Matthew [ORNL] (ORCID:0000000288907920)↗

DOE OSTI2025

AmeriFlux US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops)

This is the AmeriFlux version of the carbon flux data for the site US-VT1 Vermillion Tributary Paired Cropland – Site 1 (Corn/Soy; No Cover Crops). Site Description - US-VT1 is located on flat, actively managed farmland operated by working farmers, following a conventional no-till corn–soybean rotation in the U.S. Midwest. US-VT1 is one of two paired working farm sites on the same property; both are managed using similar conventional practices, with the key difference being that the paired site (US-VT2) incorporates cover crops into its rotation. This paired design enables direct site-to-site comparisons to assess the impacts of cover cropping on carbon, water, and energy fluxes.