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133 records · Page 7

Monitoring Depolymerization in Mesopores Using Dynamic Properties of Polymeric Melt Accessed via Dielectric Spectroscopy

Traditional design principles for heterogeneous catalysis guide the use of catalytic particles with mesosized (∼2–50 nm) pores to increase the number of surface-active sites by way of an increased surface area. However, the entry of long-chain polymers into such pores may be significantly limited by the size and entanglement of polymers in the melt state, thereby decreasing the number of accessible sites. Assessment of catalyst performance from traditional reactor-based studies averages over intrapore reaction events as well as reactions on the surface of a particle, resulting in an inability to distinguish between differences in site accessibility and activity. Techniques that assess the intrapore performance can inform the design of future heterogeneous catalysts for polymer upcycling. In this work, we demonstrate the use of broadband dielectric spectroscopy to monitor depolymerization of a polymer melt within mesopores via changes in the segmental relaxation time scale of amorphous polymer chains. In particular, we highlight the use of an anodic aluminum oxide (AAO) membrane as a readily available model for catalyst pores with a well-characterized pore morphology. The decrease in the segmental relaxation (α-relaxation) time of the melt with increasing chain scission emerges as a measure of the extent of polymer deconstruction inside mesopores. To demonstrate the utility of this technique, we demonstrate the decomposition of two commercial poly(propylene carbonate) polymers with different decomposition rates within mesopores. As the polymers depolymerize, their segmental relaxation time decreases as the molecular weight decreases (as predicted by the Fox–Flory equation). The BDS-measured change in segmental relaxation time mirrors the expected trend based on change in molecular weight measured by size exclusion chromatography.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Single particle – MC-ICP-MS for isotopic analysis of uranium particles

Single particle – multi-collector – inductively coupled plasma – mass spectrometry (SP-MC-ICP-MS) was employed to measure a suspension of 1 µm U3O8 particles (∼1.3 pg total U/particle) to determine their individual isotopic compositions of 234U/238U, 235U/238U, and 236U/238U. The effects of different detector combinations for 235U and 238U, including secondary electron multipliers (SEM) and Faraday detectors (1011 and 1013 Ω amplifiers), were explored for accuracy and precision optimization on the observed 235U/238U. The minor isotopic ratios (i.e., 234U/238U and 236U/238U) were analyzed such that the 234U and 236U were monitored on SEM detectors and the 238U was monitored on a Faraday (1011 Ω) detector. Various integration times (5, 10, 25, and 50 ms) were investigated in all detector configurations to gain a better understanding of their impact on sensitivity, accuracy, and precision. For 235U/238U ratios of 1 µm U3O8 particles, a dual Faraday detector measurement with 1011 Ω was the optimal choice; measurement of 1021 particles yielded an average 235U/238U ratio of 0.00170 (14), a −1.8% relative difference (% RD) from the reference value. The minor isotopic compositions were determined to be 0.0000070 (14) and 0.0000758 (48) for the 234U/238U and 236U/238U, respectively. These measurements correspond to <8% and <1% RD from their reference value for the 234U/238U and 236U/238U, respectively. SP-MC-ICP-MS was also able to provide insight into measurement sensitivity. In these individual particles, merely 15 and 165 atto-grams (ag) of 234U and 236U were present (calculated). Initial limits of detection for SP-MC-ICP-MS were determined to be ∼1.0 ag (when measured via SEM detectors). This valuable approach is applicable to areas including nuclear forensics, nuclear safeguards, and geochemical analysis, which require high-precision measurements of uranium within micron-sized particles.

Manard, Benjamin [ORNL] (ORCID:0000000207400627)

From Pollutant Removal to Renewable Energy: MoS2-Enhanced P25-Graphene Photocatalysts for Malathion Degradation and H2 Evolution

The widespread presence of pesticides—especially malathion—in aquatic environments presents a major obstacle to conventional remediation strategies, while the ongoing global energy crisis underscores the urgency of developing renewable energy sources such as hydrogen. In this context, photocatalytic water splitting emerges as a promising approach, though its practical application remains limited by poor charge carrier dynamics and insufficient visible-light utilization. Herein, we report the design and evaluation of a series of TiO2-based ternary nanocomposites comprising commercial P25 TiO2, reduced graphene oxide (rGO), and molybdenum disulfide (MoS2), with MoS2 loadings ranging from 1% to 10% by weight. The photocatalysts were fabricated via a two-step method: hydrothermal integration of rGO into P25 followed by solution-phase self-assembly of exfoliated MoS2 nanosheets. The composites were systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), UV-Vis diffuse reflectance spectroscopy (DRS), and photoluminescence (PL) spectroscopy. Photocatalytic activity was assessed through two key applications: the degradation of malathion (20 mg/L) under simulated solar irradiation and hydrogen evolution from water in the presence of sacrificial agents. Quantification was performed using UV-Vis spectroscopy, gas chromatography–mass spectrometry (GC-MS), and thermal conductivity detection (GC-TCD). Results showed that the integration of rGO significantly enhanced surface area and charge mobility, while MoS2 served as an effective co-catalyst, promoting interfacial charge separation and acting as an active site for hydrogen evolution. Nearly complete malathion degradation (~100%) was achieved within two hours, and hydrogen production reached up to 6000 µmol g−1 h−1 under optimal MoS2 loading. Notably, photocatalytic performance declined with higher MoS2 content due to recombination effects. Overall, this work demonstrates the synergistic enhancement provided by rGO and MoS2 in a stable P25-based system and underscores the viability of such ternary nanocomposites for addressing both environmental remediation and sustainable energy conversion challenges.

Chemistry

Divergent trait controls on soluble sugars and starch underlie global strategies of tree carbohydrate storage

Nonstructural carbohydrate (NSC) stores buffer tree metabolism, osmotic regulation, and defense, thereby mediating tolerance and survival under climate extremes. Yet, the functional and evolutionary determinants of interspecific variation in NSC remain elusive, limiting understanding and prediction of forest carbon allocation and mortality under global change. Here, we present a cross-species synthesis of NSC concentrations across multiple organs for 281 woody species from 102 mixed forest communities worldwide, where we quantified species-specific deviations from community means to disentangle intrinsic trait effects from environmental and methodological variation. We found phylogenetic signals in NSC deviations, with coniferous gymnosperms and evergreen species consistently maintaining lower stem soluble sugars and starch concentrations than co-occurring angiosperms and deciduous species, respectively. A global pattern emerged where greater stomatal sensitivity to leaf water potential was associated with declines in the relative concentrations of both sugars and starch. In contrast, xylem hydraulic safety traits showed weak and organ-dependent relationships with NSC concentrations. Sugars increased with photosynthetic capacity and declined with wood density, whereas starch showed the reverse pattern, which aligned with the distinct functional-metabolic roles of sugars and starch. By integrating trait-based ecology with a community-centered framework, our study provides global evidence that stomatal regulation, photosynthetic capacity, specific leaf area, and wood density jointly govern interspecific NSC variation, through contrasting effects on sugars and starch. These are among the most broadly measured traits globally, thus the emergent carbohydrate–trait relationships can have broad applications toward understanding and predicting forest growth and survival under climate change.

tropic system

SUDA: A SUrface Dust Analyser for Compositional Mapping of the Galilean Moon Europa

Abstract The Surface Dust Analyser (SUDA) is a mass spectrometer onboard the Europa Clipper mission for investigating the surface composition of the Galilean moon Europa. Atmosphereless planetary moons such as the Galilean satellites are wrapped into a ballistic dust exosphere populated by tiny samples from the moon’s surface produced by impacts of fast micrometeoroids. SUDA will measure the composition of such surface ejecta during close flybys of Europa to obtain key chemical signatures for revealing the satellite’s composition such as organic molecules and salts, history, and geological evolution. Because of their ballistic orbits, detected ejecta can be traced back to the surface with a spatial resolution roughly equal to the instantaneous altitude of the spacecraft. SUDA is a Time-Of-Flight (TOF), reflectron-type impact mass spectrometer, optimized for a high mass resolution which only weakly depends on the impact location. The instrument will measure the mass, speed, charge, elemental, molecular, and isotopic composition of impacting grains. The instrument’s small size of$268 ~\mathrm {mm} \times 250 ~\mathrm {mm} \times 171$ 268 mm × 250 mm × 171 $~\mathrm {mm}$ mm , radiation-hard design, and rather large sensitive area of 220 cm 2 matches well the challenging demands of the Clipper mission.

Astronomy & Astrophysics

Utilities Perspective on Protection Challenges with High IBR Penetration

Utilities have seen rapid increase in Solar, Wind, and Battery Energy Storage Resources that interconnect to their electric system through Inverters. Inverter-Based Resources (IBRs) have fault current characteristics that are unlike the fault current response of traditional rotating-machine-based generators, which is well known and repeatable. IBR’s non-traditional fault current behavior is due to the IBR control scheme, which is configured to provide a clean AC output but also protect the inverter’s sensitive power electronics devices from damage, one source of which is overcurrent. This results in low fault current magnitude, low or no negative sequence current injection, the variability of sequence component currents, the variability of voltage with respect to current angles, and the lack of inertia. The control scheme also results in a fault current response that can vary between manufactures and between models of the same manufacturer. High penetration of IBRs can adversely affect the protection schemes applied in areas with high penetration of IBRs. With the proliferation of IBRs, utilities are finding out that conventional protection schemes are not adequately equipped to protect the electric systems. This is mainly because the existing protection elements and practices have been designed based on the fault current response of conventional rotating machines. In several cases, the available literature does not provide any clear solution for the issues when the protection scheme does not operate properly near IBRs. This presentation identifies various protection challenges due to IBRs that industry is facing, from the utility perspective. Instead of facing on one issue, we are looking broadly on all the challenges that system protection has experienced with high penetration of IBRs. Based on the IBR response from various utilities during real fault events and gathering perspective from different utility SMEs via questionnaire, the presentation summarizes on gathered data and internal experiences.

24 POWER TRANSMISSION AND DISTRIBUTION

Paleotribological models using preserved fossil tissue properties reveal functional significance of Eurasian mammoth dental evolution

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.

Dental wear

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Highly Ordered Eutectic Mesostructures via Template‐Directed Solidification within Thermally Engineered Templates

Template-directed self-assembly of solidifying eutectics results in emergence of unique microstructures due to diffusion constraints and thermal gradients imposed by the template. Here, the importance of selecting the template material based on its conductivity to control heat transfer between the template and the solidifying eutectic, and thus the thermal gradients near the solidification front, is demonstrated. Simulations elucidate the relationship between the thermal properties of the eutectic and template and the resultant microstructure. The overarching finding is that templates with low thermal conductivities are generally advantageous for forming highly organized microstructures. When electrochemically porosified silicon pillars (thermal conductivity < 0.3 Wm −1 K −1 ) are used as the template into which an AgCl-KCl eutectic is solidified, 99% of the unit cells in the solidified structure exhibit the same pattern. In contrast, when higher thermal conductivity crystalline silicon pillars (≈100 Wm −1 K −1 ) are utilized, the expected pattern is only present in 50% of the unit cells. The thermally engineered template results in mesostructures with tunable optical properties and reflectances nearly identical to the simulated reflectances of perfect structures, indicating highly ordered patterns are formed over large areas. This work highlights the importance of controlling heat flows in template-directed self-assembly of eutectics.

36 MATERIALS SCIENCE

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science

Improving creep resistance of Al-0.27Zr-0.08Sn (wt%) via cold swaging while maintaining high electrical conductivity

This study investigates the effect of mechanical cold work (0, 50, and 90% cross-sectional area reduction via swaging) on the creep properties of cast aluminum alloys with high electrical conductivity including high-purity Al (HP-Al), Al-0.15Zr (Al-Zr), and Al-0.27Zr-0.08Sn (Al-Zr-Sn, wt%). The Al-Zr alloy is strengthened by Zr in solid solution while the Al-Zr-Sn alloy is additionally strengthened by Al3Zr nanoprecipitates (8 nm diameter). After 90% cold swaging, the alloys exhibit grains elongated along the swaging direction with their widths ranging between 8 and 152 μm perpendicular to the swaging direction. Creep testing at 200 °C shows that the minimum creep rate of all 90% swaged alloys shows high sensitivity to stress, which can be modeled via a threshold stress σth. Increasing swaging magnitude from 0 to 50 to 90% in Al-Zr-Sn improves the creep resistance without reducing electrical conductivity. The formation of subgrains, increased dislocation density, and columnar grain structure in swaged alloys all enhance creep resistance. HP-Al swaged to 90% exhibits much lower creep resistance (σth = 18 MPa) due to subgrain coarsening and the absence of precipitates compared to Al-Zr (σth = 40 MPa) and Al-Zr-Sn (σth = 40 MPa), which maintain stable subgrain structures and benefit from solid solution strengthening and Al3Zr nanoprecipitates, respectively. Although Al3Zr precipitates are known to stabilize the deformed microstructure by pinning grain-boundaries, this work demonstrates that Zr in solid solution alone can effectively stabilize the deformed microstructure resulting in enhanced creep resistance. This effect of Zr solute on stabilizing grain boundaries for creep performance was not previously well-defined in the literature. Despite similar creep performances of Al-Zr and Al-Zr-Sn, the latter shows 70% higher room-temperature microhardness and slightly improved electrical conductivity (56%IACS (International Annealed Copper Standard) vs. 57%IACS, respectively). This work provides new insights into creep mechanisms of cold-worked Al–Zr alloys that will guide the design of heat-resistant Al conductors for high-demand applications.

Coello ramirez, Ismael [Northwestern University,]

Electronic structure of the kagome compound CaTi 3⁢ Bi 4 using high-field torque magnetometry and density functional theory

Here, we report systematic torque magnetometry measurements to investigate the electronic properties of the newly discovered kagome compound CaTi 3 ⁢Bi 4 . Electrical transport, magnetic susceptibility, and thermal measurements reveal no evidence of a magnetic ground state in this material. Torque data obtained in magnetic fields up to 41.5 T exhibit clear de Haas–van Alphen (dHvA) oscillations, with nine distinct frequencies ranging from 13 to 6164 T. Angular-dependent dHvA measurements show that, with the exception of the lowest frequency (13 T), all observed frequencies nearly follow a 1/cos ⁡𝜃 dependence, where 𝜃 is the angle between the crystallographic 𝑐 axis and the magnetic field direction. This behavior is characteristic of quasi-two-dimensional Fermi-surface sheets with nearly circular cross sections. To further elucidate the electronic structure, we performed density functional theory (DFT) calculations of the band structure and Fermi surface. The calculated bands reveal the presence of multiple Dirac points (DP), flat bands (FB), and van Hove singularities (VHS) near the Fermi level. The resulting Fermi surface consists of several quasi-two-dimensional cylindrical sheets, consistent with the experimentally observed 1/cos⁡ 𝜃 dependence. Notably, the theoretical dHvA frequencies, derived from extremal Fermi-surface cross-sectional areas, agree well with the experimental values and reproduce their angular dependence. Remarkably, all experimentally observed frequencies are captured by the DFT predictions. Pressure-dependent calculations up to 10 GPa show that the electronic features—DP, FB, and VHS—evolve systematically with pressure. In particular, the VHS shifts closer to the Fermi level, demonstrating that pressure acts as an effective tuning parameter in this material. These combined experimental and theoretical results provide a comprehensive understanding of the electronic structure of CaTi 3 ⁢Bi 4 and demonstrate how pressure can be used to tune its key electronic features, offering valuable guidance for exploring related kagome materials.

Shtefiienko, Kyryl [West Texas A & M University, C

Characterization of lateral amorphous selenium photodetectors for low-photon and VUV detection at cryogenic temperatures

The performance of amorphous selenium (a-Se) as a cryogenic photodetector material is evaluated through a series of experiments using laterally structured devices operated in a custom optical test stand. These studies investigate the response of a-Se detectors to low-photon fluxes at high electric fields near avalanche conditions, the linearity of the photoconductive response over a wide dynamic range and the direct detection of narrowband 130 nm vacuum ultraviolet (VUV) illumination. At 87 K, matched-filter analysis shows reliable single-shot detection with efficiencies ≥80% and area under the curve (AUC) ≥ 0.85 using as few as ∼ 6800 incident 401 nm photons, corresponding to ∼ 3400 photons within field-active regions after accounting for geometric constraints. Measurements are performed at cryogenic temperatures using calibrated photon fluxes derived from a silicon photomultiplier reference and a characterized optical filter stack. Additional experiments using a tellurium-doped a-Se (a-SeTe) device explore the material's behavior under identical test conditions and demonstrate that avalanche is achievable in a-SeTe at cryogenic temperatures. The results demonstrate reproducible low-noise operation, VUV sensitivity and field-dependent gain behavior in a lateral a-Se architecture, representing the first reported observation of avalanche multiplication in laterally structured a-Se and a-SeTe devices at cryogenic temperatures. These findings support the potential integration of laterally structured a-Se devices into next-generation pixelated liquid-argon time projection chambers (TPCs) requiring scalable, high-field-compatible photon detection systems.

Amorphous selenium

Dark Energy Survey year 6 results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology

Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample M ag L im++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the BALROG synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 ± 0.08, 2.76 ± 0.21, 4.09 ± 0.15, 4.42 ± 0.16, 4.90 ± 0.29, 4.83 ± 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger BALROG area and reweighting to better match the data properties. Here, the cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the BALROG -derived estimates, we observe shifts of 1.37σ in S 8 and -0.84σ in Ω m (with cosmic shear included: -0.61σ in S 8 and -0.71σ in Ω m ), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.

Cosmological parameters

Electrostatic‐Attraction‐Driven Self‐Assembled Graphene‐Disordered Rocksalt Composite Cathode for Lithium‐Ion Batteries

Disordered rocksalt cathodes hold promise for achieving high-capacity lithium-ion batteries while using low-cost, earth-abundant elements. However, their electrochemical performance remains critically limited by their poor electronic conductivity. Conventional strategies such as high-energy ball milling with excess carbon additives can improve conductivity but remain challenging to scale and often produce defects and increase surface area, thereby accelerating capacity degradation. Herein, we report an alternative approach of electrostatic-attraction-driven self-assembly to fabricate Li 1.2 Mn 0.6 Ti 0.2 O 1.8 F 0.2 (LMTOF) particles uniformly wrapped with electronically conductive graphene sheets without associated materials degradation. The graphene-wrapped LMTOF demonstrates significantly improved cycling stability (89% capacity retention after 100 cycles) and superior rate capability compared with an LMTOF-carbon composite electrode fabricated using the conventional high-energy ball-milling process. Post-cycling analysis reveals reduced oxygen evolution, suppressed unwanted side reactions, and improved structural integrity for the graphene-LMTOF composite. This work highlights the advantages of solution-based carbon wrapping and offers a scalable strategy to prepare high-performance DRX cathodes for lithium-ion batteries.

carbon composite

The SRG/eROSITA All-Sky Survey: Optical identification and properties of galaxy clusters and groups in the western galactic hemisphere

The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western Galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster findereROMaPPer, we measured individual photometric properties (redshiftz λ , richnessλ, optical center, and BCG position) for 12000 eRASS1 clusters over a sky area of 13 116 deg 2 , augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample isz= 0.31, with 10% of the clusters atz> 0.72. The photometric redshifts have an accuracy ofδz/(1 +z) ≲ 0.005 for 0.05 specand velocity dispersionσ) were measured a posteriori for a subsample of 3210 and 1499 eRASS1 clusters, respectively, using an extensive compilation of spectroscopic redshifts of galaxies from the literature. We infer that the primary eRASS1 sample has a purity of 86% and optical completeness >95% forz> 0.05. For these and further quality assessments of the eRASS1 identified catalog, we applied our identification method to a collection of galaxy cluster catalogs in the literature, as well as blindly on the full Legacy Surveys covering 24069 deg 2 . Using a combination of these cluster samples, we investigated the velocity dispersion-richness relation, finding that it scales with richness as log(λ norm ) = 2.401 × log(σ) − 5.074 with an intrinsic scatter ofδ in = 0.10 ± 0.01 dex. The primary product of our work is the identified eRASS1 cluster catalog with high purity and a well-defined X-ray selection process, opening the path for precise cosmological analyses presented in companion papers.

Astronomy & Astrophysics

The MuFusE large-volume diamond anvil cell for exploring muon-catalyzed fusion at higher pressures and temperatures

A new large-volume diamond anvil cell (DAC) has been developed for the Muon-catalyzed Fusion (μCF) Experiment (MuFusE), enabling the compression and heating of deuterium–tritium (d–t) mixtures to pressures and temperatures needed to advance μCF research. The MuFusE DAC achieves the large sample volumes necessary for high-precision fusion measurements while integrating cryogenic loading, all-metal sealing, and flexible bellows to maintain a secure environment during cell compression. Combined with remote pneumatic actuation and secondary containment, the DAC safely managed a 25 Ci tritium inventory while providing a clear optical path for in situ measurements of sample pressure and composition via laser spectroscopy. Utilizing 5 mm diameter diamond anvils oriented in the path of a high-intensity muon beam, the apparatus achieved a stable sample volume of 19.2 mm 3 at liquid density, pressures up to 933 MPa and temperatures up to 400 K—benchmarks that significantly exceed previously reported limits for static d–t targets.

Kalow, J. D. [Acceleron Fusion, Inc., Cambridge, M

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY