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At least 199 records · Page 11

Resonant inelastic X-ray scattering tools to count 5 $f$ electrons of actinides and probe bond covalency

The actinides possess a complex electronic structure, making their chemical and physical properties among the least understood in the periodic table. Advanced spectroscopic tools, able to obtain deep insights into the electronic structure and binding properties of the actinides, are highly desirable. Here, we introduce two sensitive spectroscopic tools: one determines the number of localized 5f electrons on an actinide atom, and another assesses the covalent character of actinide-ligand bonding. Both tools are based on the multiplet structure present in actinide M 4 edge core-to-core resonant inelastic X-ray scattering (CC-RIXS) maps. The spectral intensity of different many-body final-state multiplets directly depends on the local many-electron ground-state symmetry including the local 5 f spin configuration. By comparing U M 4 edge CC-RIXS data for 21 U, Np, Pu and Am compounds, we demonstrate the ability to compare the number of localized 5 f electrons and bond covalency across the actinide series.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Thermal Radiation Transport with Tensor Trains

We present a novel tensor network algorithm to solve the time-dependent, gray thermal radiation transport equation. The method invokes a tensor train (TT) decomposition for the specific intensity. The efficiency of this approach is dictated by the rank of the decomposition. When the solution is “low rank,” the memory footprint of the specific intensity solution vector may be significantly compressed. The algorithm, following a step-then-truncate approach of a traditional discrete ordinates method, operates directly on the compressed state vector, thereby enabling large speedups for low-rank solutions. To achieve these speedups, we rely on a recently developed rounding approach based on the Gram-SVD. We detail how familiar S N algorithms for (gray) thermal transport can be mapped to this TT framework and present several numerical examples testing both the optically thick and thin regimes. The TT framework finds low-rank structure and supplies up to ≃60× speedups and ≃1000× compressions for problems demanding large angle counts, thereby enabling previously intractable SN calculations and supplying a promising avenue to mitigate ray effects.

79 ASTRONOMY AND ASTROPHYSICS↗

Recoil imaging for dark matter, neutrinos, and physics beyond the Standard Model

Recoil imaging entails the detection of spatially resolved ionization tracks generated by particle interactions. This is a highly sought-after capability in many classes of detector, with broad applications across particle and astroparticle physics. However, at low energies, where ionization signatures are small in size, recoil imaging only seems to be a practical goal for micro-pattern gas detectors. This white paper outlines the physics case for recoil imaging, and puts forward a decadal plan to advance towards the directional detection of low-energy recoils with sensitivity and resolution close to fundamental performance limits. The science case covered includes: the discovery of dark matter into the neutrino fog, directional detection of sub-MeV solar neutrinos, the precision study of coherent-elastic neutrino-nucleus scattering, the detection of solar axions, the measurement of the Migdal effect, X-ray polarimetry, and several other applied physics goals. We also outline the R&D programs necessary to test concepts that are crucial to advance detector performance towards their fundamental limit: single primary electron sensitivity with full 3D spatial resolution at the $\sim$100 micron-scale. These advancements include: the use of negative ion drift, electron counting with high-definition electronic readout, time projection chambers with optical readout, and the possibility for nuclear recoil tracking in high-density gases such as argon. We also discuss the readout and electronics systems needed to scale-up such detectors to the ton-scale and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

ITeM: Independent temporal motifs to summarize and compare temporal networks

We report networks are a fundamental and flexible way of representing various complex systems. Many domains such as communication, citation, procurement, biology, social media, and transportation can be modeled as a set of entities and their relationships. Temporal networks are a specialization of general networks where every relationship occurs at a discrete time. The temporal evolution of such networks is as important to understand as the structure of the entities and relationships. We present the Independent Temporal Motif (ITeM) to characterize temporal graphs from different domains. ITeMs can be used to model the structure and the evolution of the graph. In contrast to existing work, ITeMs are edge-disjoint directed motifs that measure the temporal evolution of ordered edges within the motif. For a given temporal graph, we produce a feature vector of ITeM frequencies and the time it takes to form the ITeM instances. We apply this distribution to measure the similarity of temporal graphs. We show that ITeM has higher accuracy than other motif frequency-based approaches. We define various ITeM-based metrics that reveal salient properties of a temporal network. We also present importance sampling as a method to efficiently estimate the ITeM counts. We present a distributed implementation of the ITeM discovery algorithm using Apache Spark and GraphFrame. We evaluate our approach on both synthetic and real temporal networks.

97 MATHEMATICS AND COMPUTING↗

The Entropic Braiding Index ( eBI ): A Robust Metric to Account for the Diversity of Channel Scales in Multi‐Thread Rivers

Abstract The Braiding Index ( BI ), defined as the average count of intercepted channels per cross‐section, is a widely used metric for characterizing multi‐thread river systems. However, it does not account for the diversity of channels (e.g., in terms of water discharge) within different cross‐sections, omitting important information related to system complexity. Here we present a modification of BI, the Entropic Braiding Index ( eBI ), which augments the information content in BI by using Shannon Entropy to encode the diversity of channels in each cross section. eBI is interpreted as the number of “effective channels” per cross‐section, allowing a direct comparison with the traditional BI . We demonstrate the potential of the ratio BI/eBI to quantify channel disparity, differentiate types of multi‐thread systems (braided vs. anastomosed), and assess the effect of discharge variability, such as seasonal flooding, on river cross‐section stability.

54 ENVIRONMENTAL SCIENCES↗

Conservation laws and effective hadronization models

Hadronization models based on local string-breaking dynamics are typically Markovian by construction, yet the physical ensemble of final states is shaped by global constraints that couple the entire fragmentation trajectory. Recasting hadronization as a conditioned stochastic diffusion process provides a precise mathematical resolution to this tension. In particular, this language reveals explicitly that constraints stemming from conservation laws induce non-Markovian correlations between otherwise independent fragmentation steps, and that these correlations can be absorbed exactly into a renormalization of the local dynamics through a Doob $h$-transform. We develop this formalism for a $q\bar{q}$ string in the chiral limit, where the longitudinal-transverse factorization of the Lund kernel becomes exact, enabling systematic power counting and clean ultraviolet (UV)/infrared (IR) separation. The dynamics organize naturally into a tower of effective theories distinguished by the remaining string mass, spanning a UV fixed point with scale-invariant transport coefficients, an intermediate regime where transverse phase space induces controlled running, and an IR boundary layer where non-local effects enter at leading order. The tower exhibits genuine Wilsonian structure, including $β$-functions, anomalous dimensions, and systematic matching conditions. The resulting framework achieves a clean factorization of universal microscopic fragmentation dynamics from infrared constraint effects, and opens new directions for both the theoretical analysis and practical simulation of hadronization.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

Low energy neutron light output characterization of EJ301D and deuterated stilbene with a comparison of light output characterization methods

The neutron-induced light yield of a 2.54 cm diameter by 2.54 cm long right circular cylinder of EJ301D and a (5.08 cm)3 custom made cube of deuterated trans-stilbene-d12 (d-stilbene) were measured over incident neutron energies from 300 keV to 2.2 MeV and 200 keV to 2.4 MeV, respectively. The measurements were performed using a time-of-flight experiment with a Cf-252 source and an approximately 1.5 m flight path. We compare three light output spectrum full energy deposition edge estimation methods: (1) simulating the neutron energy spectrum edge and fitting it to the light output spectrum, (2) using the inflection point of the light output spectrum edge (derivative method, a.k.a. Kornilov’s method), and (3) using an empirical model fit to the edge of the light output spectrum. Both the derivative and equation fit methods do not account for physical processes such as multiple neutron scattering in the detectors. They instead rely on assumptions about the linear shape continuum shape of the light output spectrum and the direct correlation between the location of the spectrum’s inflection point and maximum energy deposition. These assumptions were found to introduce bias into those methods when tested against simulated spectra with known edge locations. When tested against measured spectra the derivative method was found to differ from the simulation fit by greater than 30% at low energies with large discontinuities for adjacent data points above 800 keV incident neutron energy. The empirical equation fitting method was found to also exhibit bias of a similar magnitude, but with significantly more continuous behavior, especially with the lower count data of the smaller volumed EJ301D scintillator. Experimental light output yield for this neutron energy range is reported using the simulated spectrum fitting method because it includes physics neglected by the other methods, and did not exhibit the bias observed in the other methods

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data from: Land-based climate solutions for the United States

Meeting end-of-century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature-based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature-based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the U.S. that illustrates the benefits of combining approaches. We assign a portion of non-forested former cropland to bioenergy sufficient to meet projected mid-century transportation needs, with the remainder assigned to nature-based solutions such as reforestation. Bottom-up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost-effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of reforestation. Results show a conservative end-of-century mitigation capacity of 110 (57 – 178) Gt CO2e for the U.S., ~50% higher than existing estimates that prioritize nature-based or bioenergy solutions separately. Further research is needed to shrink uncertainties but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

09 BIOMASS FUELS↗

LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty

Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.

Environmental sciences↗

Land‐based climate solutions for the United States

Abstract Meeting end‐of‐century global warming targets requires aggressive action on multiple fronts. Recent reports note the futility of addressing mitigation goals without fully engaging the agricultural sector, yet no available assessments combine both nature‐based solutions (reforestation, grassland and wetland protection, and agricultural practice change) and cellulosic bioenergy for a single geographic region. Collectively, these solutions might offer a suite of climate, biodiversity, and other benefits greater than either alone. Nature‐based solutions are largely constrained by the duration of carbon accrual in soils and forest biomass; each of these carbon pools will eventually saturate. Bioenergy solutions can last indefinitely but carry significant environmental risk if carelessly deployed. We detail a simplified scenario for the United States that illustrates the benefits of combining approaches. We assign a portion of non‐forested former cropland to bioenergy sufficient to meet projected mid‐century transportation needs, with the remainder assigned to nature‐based solutions such as reforestation. Bottom‐up mitigation potentials for the aggregate contributions of crop, grazing, forest, and bioenergy lands are assessed by including in a Monte Carlo model conservative ranges for cost‐effective local mitigation capacities, together with ranges for (a) areal extents that avoid double counting and include realistic adoption rates and (b) the projected duration of different carbon sinks. The projected duration illustrates the net effect of eventually saturating soil carbon pools in the case of most strategies, and additionally saturating biomass carbon pools in the case of forest management. Results show a conservative end‐of‐century mitigation capacity of 110 (57–178) Gt CO 2 e for the U.S., ~50% higher than existing estimates that prioritize nature‐based or bioenergy solutions separately. Further research is needed to shrink uncertainties, but there is sufficient confidence in the general magnitude and direction of a combined approach to plan for deployment now.

54 ENVIRONMENTAL SCIENCES↗

Prompt Gamma Analysis of ARIES Materials and Updates to the 2015 Calibration Equations

Prompt gamma (PG) analysis is a nondestructive, nuclear, elemental analysis technique that uses charged particle reactions to interrogate a sample, and elements present in the sample matrix are identified through the characteristic gamma-rays emitted from the product nuclei in alpha-p and alpha-n nuclear reactions. This technique has been applied to plutonium oxide packaged in over 4,000 individual 3013 containers, and the concentrations of certain light elements were determined from the integrated peak areas based on a calibration that was published previously. This report provides the results for a new population of 3013 containers packaged with oxide materials produced by the conversion of metal by Advanced Recovery and Integrated Extraction System (ARIES) project using the direct metal oxidation (DMO) process and muffle furnaces. New PG and analytical chemistry data collected since 2015 were added to the existing calibration data sets to refine the calibration parameters. Calibration equations were also developed for determining beryllium and fluorine at low concentrations in high-purity ARIES product oxides. The new fluorine calibration provides an order of magnitude greater sensitivity and results in an additional 1,408 containers in the original population identified as having fluorine as an impurity. Additionally, equations for calculating the lower limits of detection (LLDs) as a function of the actual counting time (live time) were obtained using WLS regression technique for samples in the calibration data set. This resulted in changes to the LLDs published previously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Applications and Deployment of Neutron Scatter Cameras in Nuclear Safeguards Scenarios

Neutron scatter cameras (NSCs) are a type of directionally sensitive neutron detector that rely on two consecutive neutron scattering events to localize a source of neutrons. NSCs can be used to locate, image, and identify unknown neutron sources or verify the geometry and identity of known sources. Much technical progress has been made in improving NSC designs, but little literature exists exploring the full range of practical application of neutron scatter cameras. This paper seeks to identify scenarios related to nuclear security and non-proliferation where deployment of NSCs may be useful. These situations could include: limited searches for sources during cargo screening, counting nuclear warheads for treaty verification, verification of special nuclear material during inspections, imaging nuclear contamination, imaging nuclear reactor cores, searching for lost sources, and matching neutron images in shipper/receiver or inventory management scenarios. These scenarios are examined with respect to existing NSC designs and proposed designs in terms of usefulness and practicality of deployment when compared to currently used detection systems.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Skipper-CCDs: Current applications and future

This work briefly discusses the potential applications of the Skipper-CCD technology in astronomy and reviews its current use in dark matter and neutrino experiments. An overview of the ongoing efforts to build multi-kilogram experiments with these sensors is given, in the context of the Oscura experiment. First results from the characterization of Oscura sensors from the first 200 mm wafer-fabrication run with a new vendor are presented. The overall yield of the electron counting capability of these sensors is 71%. In conclusion, a noise of 0.087 e - RMS, with 1225 samples/pix, and a dark current of (0.031±0.013) e - /pix/day at 140 K were measured.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Improved Neutron Lifetime Measurement with UCN$\tau$

In this work, we report an improved measurement of the free neutron lifetime $\tau_n$ using the UCN$\tau$ apparatus at the Los Alamos Neutron Science Center. We count a total of approximately 38×10 6 surviving ultracold neutrons (UCNs) after storing in UCN$\tau$’s magnetogravitational trap over two data acquisition campaigns in 2017 and 2018. We extract $\tau$ n from three blinded, independent analyses by both pairing long and short storage time runs to find a set of replicate $\tau$ n measurements and by performing a global likelihood fit to all data while self-consistently incorporating the β-decay lifetime. Both techniques achieve consistent results and find a value $\tau$ n =877.75±0.28 stat +0.22/–0.16 syst s. With this sensitivity, neutron lifetime experiments now directly address the impact of recent refinements in our understanding of the standard model for neutron decay.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Influence of irrigation approaches and spatial geolocation on tritium speciation, uptake and depuration

Pine needles and tree cores from a tritium (T) contaminated phytoremediation forest at the Savannah River Site (SRS in Aiken, SC) Mixed Waste Management Facility (MWMF) were measured for total T and T speciation and compared to other locations at the SRS and the surrounding area. Tree core ages ranged from 9 to 14 years old, covering over half of the ~20-year on-going remediation efforts, while pine needles represent more recent time periods of 1-to-2-year increments. Remedial irrigation efforts at the MWMF are found to directly influence the pine needle T concentrations. The T content in the MWMF samples is higher than non-irrigated needle samples from other locations around the SRS. Furthermore, the different forms of organic bound T are preferentially stored in tree core tissue, compared to pine needles where tritiated water dominates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

On the Prospect of Chemically Transferable Coarse-Grained Electronic Models for Soft Materials

Electronic coarse-graining (ECG) methods predict quantum-mechanical electronic properties directly from coarse-grained (CG) molecular configurations, enabling electronic predictions at mesoscale length scales. Here, we present a diagnostic assessment of the feasibility of chemically transferable ECG models across a broad polymer-relevant chemical space using all-atom, united-atom, and Martini-scale representations. While high-resolution ECG models achieve near-quantitative accuracy, we show that chemically transferable ECG at the Martini resolution fails because the CG force field does not sample the same configurational distribution of local molecular structure as that underlying the DFT-parameterized ECG model. We demonstrate that our proposed Element-Count-Label (ECL) representation, which augments Martini beads with explicit stoichiometric data, significantly improves chemical generalization across diverse polymer chemistries. However, we find that even with improved chemical resolution, the model cannot recover electronic property distributions that are absent from the configurational space sampled by the CG force field. These results demonstrate that chemically transferable ECG requires future Martini-like force fields to explicitly preserve quantum chemistry–compatible local molecular structure in addition to thermodynamic and structural fidelity.

Kidder, Katherine M [Department of Chemistry; Univ↗

GLIDR promotes the progression of glioma by regulating the miR-4677-3p/MAGI2 axis

Gliomas are the most common and fatal primary brain tumors. Growing evidence suggests that long non-coding RNAs (lncRNAs) constitute novel and potential therapeutic targets for glioma. However, the biological role of glioblastoma down-regulated RNA (GLIDR) in glioma remains largely elusive. In the current study, we used quantitative real-time polymerase chain reaction (qRT-PCR) to detect GLIDR expression in glioma cells. Cell counting kit 8 (CCK-8) assay, colony formation assay, JC-1 staining, and flow cytometry were used to evaluate the role of GLIDR in proliferation and apoptosis of glioma cells. Western blotting was performed to assess the effect of GLIDR on the level of apoptosis-related proteins. In addition, bioinformatics prediction, RNA immunoprecipitation (RIP), RNA pull-down, and luciferase reporter gene assays were used to study the regulatory mechanisms of GLIDR in glioma. GLIDR was found to be highly expressed in glioma cells and silencing of GLIDR inhibited cell proliferation and promoted apoptosis. Functionally, GLIDR bound to miR-4677-3p that directly targeted membrane-associated guanylate kinase, WW, and PDZ domain-containing protein 2 (MAGI2). Our data showed that GLIDR affects the proliferation and apoptosis of glioma cells by targeting miR-4677-3p to regulate the expression of MAGI2. In conclusion, our study determined the oncogenic role of GLIDR in glioma, which may provide a new perspective for the treatment of glioma.

60 APPLIED LIFE SCIENCES↗