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Fermi-surface driven frustrations in charge ordered kagome metal LuNb 6 ⁢Sn 6

The charge density wave (CDW), a translational symmetry breaking electronic liquid, plays a pivotal role in correlated quantum materials, such as high-𝑇 𝑐 superconductors and topological semimetals. Recently, CDWs that possibly intertwine with superconductivity and magnetism are observed in various kagome metals. However, the nature of CDWs and the role of the Fermi-surface (FS) topology in these materials remain an unresolved challenge. In this paper, we reveal the formation of CDWs in the newly discovered kagome metal LuNb 6 ⁢Sn 6 . Here, we observe a ‘‘yield sign’’-like hollow triangular diffuse scattering pattern and nearly complete softening of a flat optical phonon band near 𝐐 𝐻 = (1/3,1/3,1/2). The scattering intensity of the diffuse scattering displays divergent behavior as decreasing temperature until 𝑇 CDW = 70 K, where a competing CDW at 𝑄 CDW = (1/3,1/3,1/3) emerges. Combined with scanning tunneling microscopy/spectroscopy and first-principles calculations, our observations support a Fermi-surface driven frustration that suppresses the leading CDW instability at 𝐐 𝐻 . This frustration is relieved by the emergence of a subleading CDW at 𝑄 CDW . These results provide insights into the interplay between the Fermi surface, strong electron-phonon coupling, and charge density wave formation in quantum materials.

Yang, F. Z. [Oak Ridge National Laboratory (ORNL),

Modelling of cracking during beam oscillation laser welding of a creep-resistant nickel alloy

During high power laser welding of Inconel 740H, horizontal solidification cracks form at locations between approximately 70–80% of the weld depth. With the integration of circular beam oscillation, the laser energy density distribution and underlying thermo-mechanical conditions were altered. By coupling three-dimensional heat transfer, fluid flow, and stress modelling tools, the role that circular beam oscillation plays in the formation of the strain rates and stresses driving this cracking phenomenon was identified. While the addition of a circular oscillation pattern appeared to lower the stress levels along the solidification front, it did not eliminate the appearance of horizontal cracking. Only when the beam amplitudes reached 1.6 mm did solidification cracking disappear, but the weld depths were also significantly reduced.

Gao, Mingze

Partners in root nodule symbiosis respond uniquely to heavy metal stresses in a host genotype-dependent manner

Abstract The mutualistic symbiosis between legume roots and soil rhizobia culminates in the formation of root nodules, where nitrogen is fixed. Root nodule symbiosis is inhibited by heavy metal stress. In this study, we investigated the relative responses of the symbiotic partners to a non-essential heavy metal cadmium (Cd) and an essential heavy metal zinc (Zn) stress and identified patterns in gene expression. We performed dual transcriptomics in nodules, using theMedicago truncatula-Sinorhizobium melilotisymbiotic system. Phenotypes were measured in the wild-typeMedicago truncatulaand a mutant in anABCtransporter gene (Mtabcg36), which showed compromised nodule formation in control conditions and further after heavy metal treatment. We observed that the rhizobia were particularly sensitive to Zn in mutant nodules. The greatest degree of differential gene expression in the host plant were observed under Cd and Zn treatments in wild-type nodules. Most Cd-regulated host genes were also differentially regulated by Zn, revealing little discernment between an essential and a non-essential ion under increased exposure. Furthermore, the host response to both the stresses affected auxin and iron homeostasis genes in a host genotype-dependent manner. Our results suggested impaired cadmium export from the mutant nodules. These results have potential implications in agricultural management systems and bioremediation strategies.

Science & Technology - Other Topics

Mechanism of Vapor-Phase Infiltration of Organometallic Hf in Poly(Methyl Methacrylate) for Hybrid Resist Applications

Inorganic–organic hybrid thin films synthesized by vapor-phase infiltration (VPI) of metal oxides into organic photoresists, such as poly(methyl methacrylate) (PMMA), have recently demonstrated their utility in extreme ultraviolet lithography, critical for angstrom-era semiconductor device miniaturization. Hafnium oxide infiltration has been reported recently for this purpose, but its detailed VPI mechanism has remained largely unexplored. In this study, we investigated the VPI characteristics and mechanisms of tetrakis(dimethylamido)hafnium (TDMAHf)─the hafnium precursor predominantly used for VPI in the field─into PMMA and examined its impact on electron-beam lithography (EBL) exposure behavior. VPI was performed at temperatures ranging from 85 to 150 °C, with chemical interactions characterized using infrared reflection-absorption spectroscopy, and resist patterning performance was evaluated through EBL dose-sensitivity assessments. The results indicate that TDMAHf forms a reversible adduct with PMMA at temperatures up to 120 °C, whereas at 150 °C, covalent bond formation occurs, most likely via dealkylation that leads to acetate formation. EBL studies reveal that resist sensitivity is influenced by both infiltration temperature and developer selection, with aqueous isopropyl alcohol development demonstrating enhanced sensitivity compared to organic solvent-based development. The optimized infiltration protocol at 120 °C ensures a uniform inorganic distribution without compromising resist dissolution. These findings not only help refine hybrid resist patterning performance but also offer insights potentially applicable to the VPI of other homoleptic metal-amide organometallic VPI precursors that include TDMA ligands.

36 MATERIALS SCIENCE

Dislocation half-loop control for optimal V-defect density in GaN-based light emitting diodes

V-defects are morphological defects that typically form on threading dislocations during epitaxial growth of $(0001)$-oriented GaN layers. A V-defect is a hexagonal pyramid-shaped depression with six {$10\bar{1}1$}-oriented sidewalls. These semipolar sidewalls have a lower polarization barrier than the polarization barriers present between the polar c-plane quantum wells and quantum barriers and can laterally inject carriers directly into quantum wells in GaN-based light emitting diodes (LEDs). This is especially important, as the high polarization field in c-plane GaN is a significant factor in the high forward voltage of GaN LEDs. The optimal V-defect density for efficient lateral carrier injection in a GaN LED (∼10 9 cm −2 ) is typically an order of magnitude higher than the threading dislocation density of GaN grown on patterned sapphire substrates (∼10 8 cm −2 ). Pure-edge dislocation loops have been known to exist in GaN, and their formation into large V-defects via low-temperature growth with high Si-doping has recently been studied. Here, in this work, we develop a method for pure-edge threading dislocation half-loop formation and density control via disilane flow, growth temperature, and thickness of the half-loop generation layer. We also develop a method of forming the threading dislocation half-loops into V-defects of comparable size to those originating from substrate threading dislocations.

Crystallographic defects

Large-Scale Visualization of 3D Unstructured Groundwater Model Using Cave Automated Virtual Environment

The immersive three-dimensional (3D) virtual reality (VR) visualization of groundwater models allows us to deepen our understanding of aquifer systems and provide better solutions to present groundwater-related problems, such as groundwater recharge, water quality, and sustainability. Visualization assists in accurately developing groundwater models and revealing important subsurface features, including faulting, folding, and unconformity. However, assessing model accuracy poses challenges due to the complexity of geology and groundwater systems. This research demonstrates a workflow to visualize and analyze raw 3D unstructured groundwater model data using an immersive Cave Automated Virtual Environment (CAVE). To visualize the unstructured groundwater model data, the raw dataset is converted into interactive CAVE-compatible formats utilizing a set of tools: ParaView, Blender, and Unity. This enables researchers to immerse themselves in the data, identifying influential patterns and relationships. e resulting insights can inform the development of sophisticated machine-learning models for groundwater level prediction. The CAVE’s immersive capabilities allow intuitive exploration from various perspectives, providing a more holistic understanding of the factors affecting groundwater levels. These insights are crucial to improve predictive models. The CAVE results also facilitate collaborative analysis and have potential applications in training and education. is research demonstrates the value of immersive VR tools such as the CAVE for unraveling intricacies within high-dimensional scientific data to drive real-world forecasting and modeling applications.

54 ENVIRONMENTAL SCIENCES

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES

Understanding the effect of friction stir processing on electrical steel: Microstructural changes and mechanical transformations

Raising Si beyond 3.5 wt% reduces core loss but embrittles electrical steels, constraining processing and application. Here we assess friction stir processing (FSP) as a solid‑state route to enable Fe–4.0 wt% Si with improved mechanical performance. Temperature‑controlled FSP with a PcBN tool produced a defect‑free processed zone. SEM/EBSD revealed dynamic recrystallization and grain refinement from an average 110 μm in the base material to ∼20 μm in the processed region, with ∼ 80% of grains < 40 μm and a reduction in high‑angle boundary fraction to ∼65% (vs >85% in the base). Comparative mechanical property analysis shows a moderate increase in yield strength in FSP samples relative to the base material, with a significant improvement in ductility (∼35–50%). Post‑fracture EBSD identified 60° twin boundaries in the base while sub-grain formation with elevated KAM in the FSP sample. Fractography revealed a shift from quasi‑cleavage in the Base-faceted planes with river patterns, steps, and occasional secondary cracks—to ductile micro void coalescence after FSP. Following FSP, the material retains soft‑magnetic behavior, with modest shifts in saturation magnetization consistent with grain refinement and stored strain, accompanied by a clear gain in formability. These results indicate that FSP provides a viable route to deploy higher‑Si electrical steels with concurrent gains in strength and ductility.

Electrical steel

Adsorption Hysteresis Under Control: Tuning Host–Guest Interactions via a Genetic Algorithm

Mesoporous adsorbent materials offer a large volumetric capacity; however, cyclic adsorption/desorption processes in these systems often suffer from hysteresis and may require a significant pressure swing to access this capacity. To mitigate hysteresis, a proposed strategy is to include nucleation sites on the walls of the mesoporous material to facilitate droplet and bubble formation, lowering the free energy barriers to the respective phase transitions. It is unclear, however, what combination of adsorbate− adsorbent interactions and spatial patterning would be beneficial for a given application, considering that improvements to some sorption properties may come at the expense of other attributes. To understand these interconnected observables, we examine two model systems, planar-slit and cylindrical pores with tunable interaction sites, using GPU-accelerated transition matrix Monte Carlo simulations. The simulations provide a free energy map of the pressure−adsorption space in a matter of minutes, which we use to track adsorption isotherm characteristics as a function of adsorbent properties. We then leverage the rapid acquisition of simulation data to construct a genetic algorithm to iteratively modify interaction sites of the slit-pore wall to minimize the hysteresis of this system without sacrificing uptake. We find that the adsorption branch of the isotherm is easily modulated via the average host−guest interaction strength, but desorption is only adjustable if there is a suitable bubble nucleation site. Within the context of a slit-pore system, we identify relative interaction strengths and patch sizes required to gain control over both branches of the hysteresis loop.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Analysis of biofilm assembly by large area automated AFM

Biofilms are complex microbial communities critical in medical, industrial, and environmental contexts. Understanding their assembly, structure, genetic regulation, interspecies interactions, and environmental responses is key to developing effective control and mitigation strategies. While atomic force microscopy (AFM) offers critically important high-resolution insights on structural and functional properties at the cellular and even sub-cellular level, its limited scan range and labor-intensive nature restricts the ability to link these smaller scale features to the functional macroscale organization of the films. We begin to address this limitation by introducing an automated large area AFM approach capable of capturing high-resolution images over millimeter-scale areas, aided by machine learning for seamless image stitching, cell detection, and classification. Large area AFM is shown to provide a very detailed view of spatial heterogeneity and cellular morphology during the early stages of biofilm formation which were previously obscured. Using this approach, we examined the organization of Pantoea sp. YR343 on PFOTS-treated glass surfaces. Our findings reveal a preferred cellular orientation among surface-attached cells, forming a distinctive honeycomb pattern. Detailed mapping of flagella interactions suggests that flagellar coordination plays a role in biofilm assembly beyond initial attachment. Additionally, we use large-area AFM to characterize surface modifications on silicon substrates, observing a significant reduction in bacterial density. This highlights the potential of this method for studying surface modifications to better understand and control bacterial adhesion and biofilm formation.

59 BASIC BIOLOGICAL SCIENCES

Extrusion‐Based Printing of Nanostructured Fatty Acid Gels Incorporated in Hydrogels

Soft materials with unique nanostructures such as lamellar, hexagonal, and cubic morphologies can replicate complex structures that have potential in various fields, including biomedical and industrial applications. However, a key challenge in advancing the broader applications of 3D printing for these nanostructured soft materials is insufficient mechanical properties that hinder their printability and compromise structural stability in the final product. In this study, the suitability of a fatty acid‐based lamellar gel is evaluated for direct extrusion‐based 3D printing. Here, the lamellar gel with varying water content is integrated with a photocurable hydrogel to preserve the shape and stability of the final prints. Complex 2D and 3D design patterns are used to assess extrusion behavior, structural stability, and print precision under varying pressures. Small‐angle X‐ray Scattering (SAXS) measurements reveal the formation of lamellar nanostructures and confirm their retention after photocuring in various gels. Rheological analysis confirms that these gels exhibit key properties suitable for extrusion‐based 3D printing, such as shear‐thinning behavior. Additionally, tensile testing is conducted to evaluate the mechanical properties across cured print samples. This study underscores the potential of nanostructured gels as a robust and versatile platform, facilitating the development of materials engineered for various applications.

36 MATERIALS SCIENCE

Experimental Report: Multi-Instrument Comparison of AAF Condensation Particle Counters

Condensation particle counters (CPCs), also known as condensation nucleus counters (CNCs) are sophisticated instruments designed to measure the concentration of aerosol particles in the atmosphere. These devices are pivotal in environmental monitoring, industrial applications, and scientific research, particularly in atmospheric studies. CPCs are vital for understanding the role of aerosols in climate systems. Aerosols influence cloud formation, radiative forcing, and atmospheric chemistry. By providing accurate measurements of particle concentrations and distributions, CPCs contribute to models that predict atmospheric impact and weather patterns (Mei et al. 2021). CPCs operate by enlarging submicron particles, including those as small as a few nanometers, to sizes detectable by optical methods. This report delves into the mechanisms, importance, and contributions of CPCs to atmospheric research at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF), highlighting their role in advancing air quality assessment, pollution control, and atmospheric studies.

54 ENVIRONMENTAL SCIENCES

A traffic accident dataset for Chattanooga, Tennessee

This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].

97 MATHEMATICS AND COMPUTING

Preserving the Josephson Coupling of Twisted Cuprate Junctions via Tailored Silicon Nitride Circuits Boards

Controlled fabrication of twisted van der Waals heterostructures is essential to unlock the full potential of moiré materials. However, achieving reproducibility remains a major challenge, particularly for air-sensitive materials such as Bi 2 Sr 2 CaCu 2 O 8 + δ (BSCCO), where it is crucial to preserve the intrinsic and delicate superconducting properties of the interface throughout the entire fabrication process. Here, a dry, inert and cryogenic assembly method is presented that combines silicon nitride nanomembranes (NMBs) with pre-patterned electrodes and the cryogenic stacking technique (CST) to fabricate high-quality twisted BSCCO Josephson junctions (JJs). This protocol prevents thermal and chemical degradation during both interface formation and electrical contact integration. It is also found that asymmetric membrane designs, such as a double cantilever, effectively suppress vibration-induced disorder due to wire bonding, resulting in sharp and hysteretic current–voltage characteristics. The junctions exhibit a twist-angle-dependent Josephson coupling with magnitudes comparable to the highest-performing devices reported to date, but achieved through a straightforward and versatile contact method, offering a scalable and adaptable platform for future applications. These findings highlight the importance of both interface and contact engineering in addressing reproducibility in superconducting van der Waals heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area: Preprint

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs drilled in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated including a single, double, and multi-lateral design. The subsurface within area is characterized by deep, hot (> 200degreesC) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lies within a target depth of 6 km where temperatures are estimated to approach 300degreesC. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down technoeconomic analysis model. The results show that the performance and cost optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60degreesC/km. By injecting 20 degreesC-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth can be achieved, resulting in an LCOE and LCOH of $136/MWh and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal

Data readiness pipeline patterns for scientific AI at scale: Insights from climate, fusion, life sciences, and materials

This article examines how data readiness for AI principles apply to large scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, life sciences, and materials—to identify common preprocessing patterns and domain‐specific constraints. We introduce a two‐dimensional readiness model that combines canonical preprocessing patterns with a five‐level operational readiness scale, both tailored to high‐performance computing (HPC) environments. This construct helps outline key challenges in transforming large‐scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross‐domain support for scalable and reproducible AI for science. Finally, we evaluate this maturity matrix in the context of case studies including ClimaX (climate), AFLOW (materials), OpenFold (proteomics), and DIII‐D fusion disruption‐prediction workflows, from which we distill lessons learned and provide recommendations to guide practitioners in developing robust AI‐readiness pipelines. Finally, we discuss remaining cross‐cutting challenges that persist across scientific domains.

97 MATHEMATICS AND COMPUTING

Decadal-Scale Hydrothermal Alteration of Basalt: Implications for Long-Term Reactivity in Subsurface Technologies

Global demands to secure critical mineral supply chains and managing water resources require innovative resource management strategies. Subsurface basalt reservoirs offer a dual-purpose application, where CO2 enhanced critical metal recovery can be coupled with water remediation strategies for the extraction of economically important and environmentally relevant elements. This study utilizes static batch experiments conducted on Columbia River Basalt Group samples to evaluate long-term fluid–rock interactions relevant to coupled subsurface applications. Samples were reacted under elevated temperature and pressure conditions, for 296 and 4,061 days, providing a unique dataset to assess geochemical evolution, element partitioning, and aqueous chemistry over decadal timescales. The alteration was dominated by silicate, aluminosilicate, and oxide phases. Progressive hydrothermal alteration increased the cation exchange capacity through the formation of secondary minerals (e.g. clays and zeolites), influencing solute retention, ion exchange behavior, and aqueous chemistry. Grain-scale and bulk analyses revealed selective cation release and retention patterns, establishing a mechanistic baseline for predicting element mobility. These geochemical constraints inform the prospective use of CO2-enhanced metal recovery for critical resources (e.g. Co, Ni, Mn, Mg, Ti, Fe) and associated water-quality impacts, providing a foundation for the design and management of engineered fluid–rock systems in basalt reservoirs.

Gibson, Marie N.

Hydrogenation of calcite and change in chemical bonding at high pressure: Diamond formation above 100GPa

Synchrotron X-ray diffraction (XRD) and Raman spectroscopy in laser heated diamond anvil cells and first principles molecular dynamics (FPMD) calculations have been used to investigate the reactivity of calcite and molecular hydrogen (H 2 ) at high pressures up to 120 GPa. We find that hydrogen reacts with calcite starting below 0.5 GPa at room temperature forming chemical bonds with carbon and oxygen. This results in the unit cell volume expansion; the hydrogenation level is much higher for powdered samples. Single-crystal XRD measurements at 8–24 GPa reveal the presence of previously reported III, IIIb, and VI calcite phases; some crystallites show up to 4% expansion, which is consistent with the incorporation of ≤ 1 hydrogen atom per formula unit. At 40–102 GPa XRD patterns of hydrogenated calcite demonstrate broadened features consistent with the calcite VI structure with incorporated hydrogen atoms. Above 80 GPa, the C–O stretching mode of calcite splits suggesting a change in the coordination of C–O bonds. Laser heating at 110 GPa results in the formation of C–C bonds manifested in the crystallization of diamond recorded by in situ XRD at 300 K and 110 GPa and by Raman spectroscopy on recovered samples commenced with C 13 calcite. We explored several theoretical models, which show that incorporation of atomic hydrogen results in local distortions of CO 3 groups, formation of corner-shared C–O polyhedra, and chemical bonding of H to C and O, which leads to the lattice expansion and vibrational features consistent with the experiments. In conclusion, the experimental and theoretical results support recent reports on tetrahedral C coordination in high-pressure carbonate glasses and suggest a possible source of the origin of ultradeep diamonds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH