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At least 109 records · Page 6

Statistical perspective on embrittling potency for intergranular fracture

Embrittling potency is a thermodynamic metric that assesses the influence of solute segregation to a grain boundary (GB) on intergranular fracture. Historically, authors of studies have reported embrittling potency as a single scalar value, assuming a single segregation site of importance at a GB and a particular cleavage plane. However, the topography of intergranular fracture surfaces is not generally known a priori. Accordingly, we, in this study, present a statistical ensemble approach to compute embrittling potency, where many free surface (FS) permutations are systematically considered to model fracture of a GB. The result is a statistical description of the thermodynamics of GB embrittlement. As a specific example, embrittling potency distributions are presented for Cr segregation to sites at two Ni $\langle 111 \rangle$ symmetric tilt GBs using atomistic simulations. We show that the average embrittling potency for a particular GB site, considering an ensemble of FS permutations, is not equal to the embrittling potency computed using the lowest energy pair of FSs. A mean GB embrittlement is proposed, considering both the likelihood of formation of a particular FS and the probability of solute occupancy at each GB site, to compare the relative embrittling behavior of two distinct GBs.

36 MATERIALS SCIENCE↗

Excitation spectrum and low-temperature magnetism in the disordered defect-fluorite Ho2⁢Zr2⁢O7

In this work, we report on the thermomagnetic characterization and crystalline-electric field (CEF) energy scheme of the disordered defect-fluorite Ho2⁢Zr2⁢O7. This structural phase is distinguished by the coexistence of magnetic frustration and extensive disorder, with Ho3+ and Zr4+ sharing randomly the same 4⁢𝑎 site with even 50% occupancy, and an average 1/8 oxygen vacancy per unit cell. AC magnetic susceptibility measurements performed on powder samples down to 0.5 K revealed signs of slowing spin dynamics without glassy behavior, including a frequency dependent peak at ∼1K. Yet, no evidence for long-range magnetic order is found down to 200 mK in the specific heat. Inelastic neutron scattering measurements show a weak, low-lying CEF excitation around 2 meV, accompanied by a broad level centered at 60 meV. To fit our observations, we propose an approach to account for structural disorder in the crystal-field splitting of the non-Kramers Ho3+. Our model provides an explanation to the broadening of the high-energy, single-ion excitations and suggests that the zirconate ground-state wavefunction has zero magnetic moment. Through the breaking of local symmetry, structural disorder enables the magnetic response observed in Ho2⁢Zr2⁢O7, allowing the mixing of low-lying states at finite temperatures. Finally, we show that this scenario is in good agreement with the bulk properties reported in this work.

Gardner, Jason [ORNL] (ORCID:0000000278234072)↗

Protecting building occupants against the inhalation of outdoor-origin aerosols

During normal operations, buildings can protect their occupants from outdoor airborne particle hazards of all types, including airborne pollutants. A long-term international research effort has advanced our knowledge of building protection physics. Recently we have developed an operationally efficient, regional-scale methodology - Regional Shelter Analysis - to account for both building protection effects and the typical distribution of people in and among buildings. To provide input to this capability, we estimate here the degree of protection afforded by the currently existing US building stock. Here, we first assemble and summarize the published literature relevant to indoor particle losses including (a) deposition to indoor surfaces, (b) losses that occur when particles penetrate through the building envelope, and (c) heating, ventilation and air conditioning (HVAC) system filtration efficiencies as well as general building operating conditions. Building protection against inhaling particulate hazards varies strongly, by orders of magnitude, according to particle size, airborne particle loss rate, and to a lesser extent building use (occupancy). Protection increases modestly as particle size increases from 0.1 to 1 μm and significantly as particle size increases from 1 to 10 μm. Model results are placed in context with previously reported measurements. Suggestions for future work, including enhanced validation datasets are provided.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Nonlocal Coulomb interaction and spin-freezing crossover as a route to valence-skipping charge order

Abstract Multiorbital systems away from global half-filling host intriguing physical properties promoted by Hund’s coupling. Despite increasing awareness of this regime dubbed Hund’s metal, effect of nonlocal interaction is still elusive. Here we study a three-orbital model with 1/3 filling (two electrons per site) including the intersite Coulomb interaction ( V ). Using the G W plus extended dynamical mean-field theory, the valence-skipping charge order transition is shown to be driven by V . Most interestingly, the instability to this transition is significantly enhanced in the spin-freezing crossover regime, thereby lowering the critical V to the formation of charge order. This behavior is found to be closely related to the population profile of the atomic multiplet states in the spin-freezing regime. In this regime, maximum spin states are dominant in each total charge subspace with substantial amount of one- and three-electron occupations, which leads to almost equal population of one- and the maximum spin three-electron state. Our finding unveils another feature of the Hund’s metal and has potential implications for the broad range of multiorbital systems as well as the recently discovered charge order in iron pnictides.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Kondo effect in ferromagnetic quantum critical CeRh 6 ⁢Ge 4

The mechanism of a pressure-induced quantum critical point in the heavy fermion ferromagnet CeRh 6 ⁢Ge 4 has attracted interest, as ferromagnetic quantum criticality in a clean itinerant Ce compound is typically avoided. The localized versus itinerant character of the 4⁢𝑓 electrons is a key aspect for understanding this behavior. We investigated the electronic structure of the 4⁢𝑓 shell in CeRh 6 ⁢Ge 4 using core-level photoelectron and x-ray absorption spectroscopy, demonstrating the hybridization of Ce 4⁢𝑓 with the conduction electrons. Linearly polarized x-ray absorption reveals a temperature-dependent linear dichroism consistent with the crystal-electric-field sequence as inferred from the static susceptibility. This dichroism cannot be described by an ionic full-multiplet model alone, but is reproduced by including the Kondo effect within a single-impurity Anderson model in the noncrossing approximation. The Kondo effect mixes higher-lying crystal-field states into a resulting multiorbital ground state with 4⁢𝑓 occupancy, 𝑛 𝑓 ∼ 0.9. Deviations at low temperatures between the measured linear dichroism and calculated dichroism suggest an orbital-dependent Kondo effect. A scenario in which there is a multiorbital ground state and orbital-dependent Kondo hybridization should be a starting point for a model of pressure-induced criticality in CeRh 6 ⁢Ge 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spatio-Temporal Anomaly Detection with Graph Networks for Data Quality Monitoring of the Hadron Calorimeter

The Compact Muon Solenoid (CMS) experiment is a general-purpose detector for high-energy collision at the Large Hadron Collider (LHC) at CERN. It employs an online data quality monitoring (DQM) system to promptly spot and diagnose particle data acquisition problems to avoid data quality loss. In this study, we present a semi-supervised spatio-temporal anomaly detection (AD) monitoring system for the physics particle reading channels of the Hadron Calorimeter (HCAL) of the CMS using three-dimensional digi-occupancy map data of the DQM. We propose the GraphSTAD system, which employs convolutional and graph neural networks to learn local spatial characteristics induced by particles traversing the detector and the global behavior owing to shared backend circuit connections and housing boxes of the channels, respectively. Recurrent neural networks capture the temporal evolution of the extracted spatial features. We validate the accuracy of the proposed AD system in capturing diverse channel fault types using the LHC collision data sets. The GraphSTAD system achieves production-level accuracy and is being integrated into the CMS core production system for real-time monitoring of the HCAL. We provide a quantitative performance comparison with alternative benchmark models to demonstrate the promising leverage of the presented system.

43 PARTICLE ACCELERATORS↗

Unexpected Hydride: Ce 4 B 2 C 2 H 2.42 , a Stuffed Variant of the Nd 2 BC Structure Type

Ce 4 B 2 C 2 H 2.42 was grown as large crystals from a cerium/copper eutectic flux. The structure was characterized by single-crystal X-ray and neutron diffraction and was found to be a stuffed variant of Nd 2 BC with the addition of two interstitial hydrogen positions. The tetrahedral hydrogen position is fully occupied, while the octahedral position has an occupancy of 42(3)%. Initial synthesis was due to hydrogen contamination of the cerium metal but has been successfully repeated using anthracene as a carbon and hydrogen source. Density of states calculations suggest that the incorporation of hydrogen stabilizes the compound with respect to the nonhydrided model. Magnetic susceptibility data show a complex magnetic ordering at 7.7 K that originates from the localized electron on the Ce 3+ in the structure. The trivalent state is also supported by X-ray photoelectron spectroscopy measurements. Heat capacity and electrical resistivity data show that the phase transition is broad in temperature, which may be due to structural disorder. Furthermore, the large low temperature value of C/T also indicates possible heavy fermion behavior.

36 MATERIALS SCIENCE↗

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Manganese and Vanadium Co-Exposure Induces Severe Neurotoxicity in the Olfactory System: Relevance to Metal-Induced Parkinsonism

Chronic environmental exposure to toxic heavy metals, which often occurs as a mixture through occupational and industrial sources, has been implicated in various neurological disorders, including Parkinsonism. Vanadium pentoxide (V 2 O 5 ) typically presents along with manganese (Mn), especially in welding rods and high-capacity batteries, including electric vehicle batteries; however, the neurotoxic effects of vanadium (V) and Mn co-exposure are largely unknown. In this study, we investigated the neurotoxic impact of MnCl 2 , V 2 O 5 , and MnCl 2 -V 2 O 5 co-exposure in an animal model. C57BL/6 mice were intranasally administered either de-ionized water (vehicle), MnCl 2 (252 µg) alone, V 2 O 5 (182 µg) alone, or a mixture of MnCl 2 (252 µg) and V 2 O 5 (182 µg) three times a week for up to one month. Following exposure, we performed behavioral, neurochemical, and histological studies. Our results revealed dramatic decreases in olfactory bulb (OB) weight and levels of tyrosine hydroxylase, dopamine, and 3,4-dihydroxyphenylacetic acid in the treatment groups compared to the control group, with the Mn/V co-treatment group producing the most significant changes. Interestingly, increased levels of α-synuclein expression were observed in the substantia nigra (SN) of treated animals. Additionally, treatment groups exhibited locomotor deficits and olfactory dysfunction, with the co-treatment group producing the most severe deficits. The treatment groups exhibited increased levels of the oxidative stress marker 4-hydroxynonenal in the striatum and SN, as well as the upregulation of the pro-apoptotic protein PKCδ and accumulation of glomerular astroglia in the OB. The co-exposure of animals to Mn/V resulted in higher levels of these metals compared to other treatment groups. Taken together, our results suggest that co-exposure to Mn/V can adversely affect the olfactory and nigral systems. These results highlight the possible role of environmental metal mixtures in the etiology of Parkinsonism.

59 BASIC BIOLOGICAL SCIENCES↗

Delivery-Risk-Aware Flexibility Scheduling and Dispatch for Aggregated Flexible Loads

Flexible loads like smart thermostats and water heaters can shift energy consumption and provide flexibility to the grid. However, this flexibility is dependent on occupant behavior and can lead to delivery risk, which causes utilities and grid operations to consider them as unreliable for purposes of grid operation. To date, they have not been well integrated into wholesale electricity markets or ancillary service offerings. With proper consideration of uncertainty and risk, these resources can be one of the most cost-effective sources of flexibility. This work uses stochastic optimization to quantify and bid flexibility from a fleet of flexible resources while considering their delivery risk.

DER↗

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗

Eu 5 Al 3 Sb 6 : Al 4 Tetrahedra Embedded in a Rock-Salt-Like Structure

The new Eu 5 Al 3 Sb 6 phase has been successfully synthesized as a pure phase through Sn flux methods yielding large, high-quality crystals. This structure type features disordered Al clusters that appear in the form of dual tetrahedra. It crystallizes in the monoclinic C2/m space group exhibiting a rock-salt-like Eu–Sb framework with [Al 4 ] tetrahedra replacing some of the cationic Eu atoms (space group: C2/m, a = 8.151(1) Å, b = 14.181(2) Å, c = 8.145(1) Å, β = 109.577(2)°). The structure models the [Al 4 ] as dual tetrahedra with the Al atom sites 37.5% occupied along with Eu present on the central site at 8% occupancy and the remainder of the site being vacant. The presence of the [Al 4 ] cluster is further supported by HRTEM. Electronic structure calculations show that this material is a semimetal with observed band crossings close to the Fermi level. Strong Al–Sb antibonding interactions were found from COHP calculations close to the Fermi level and provide the rationale for the deficiency of the Al cluster. Mössbauer spectroscopy on Eu-151 and Sb-121 provides oxidation states of 2+ and 3– along with the local environment. Magnetic susceptibility measurements can be described well with a Curie–Weiss law where an effective moment of 7.80 μB/mol Eu is obtained, consistent with Eu 2+ , and show canted antiferromagnetic behavior below 10 K. Temperature dependent resistivity shows a Kondo-like low-temperature upturn caused by enhanced scattering of the itinerant electrons with the 4f orbitals of Eu.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine learning study of magnetism in uranium-based compounds

Actinide and lanthanide-based materials display exotic properties that originate from the presence of itinerant or localized f electrons and include unconventional superconductivity and magnetism, hidden order, and heavy-fermion behavior. Due to the strongly correlated nature of the 5f electrons, magnetic properties of these compounds depend sensitively on applied magnetic field and pressure, as well as on chemical doping. However, precise connection between the structure and magnetism in actinide-based materials is currently unclear. In this investigation, we established such structure-property links by assembling and mining two datasets that aggregate, respectively, the results of high-throughput density functional theory simulations and experimental measurements for the families of uranium- and neptunium-based binary compounds. Various regression algorithms were utilized to identify correlations among accessible attributes (features or descriptors) of the material systems and predict their cation magnetic moments and general forms of magnetic ordering. Descriptors representing compound structural parameters and cation f-subshell occupation numbers were identified as most important for accurate predictions. The best machine learning model developed employs the random forest regression algorithm. It can predict both spin and orbit moment size with root-mean-square error of 0.17 μ B and 0.19 μ B , respectively. Lastly, the random forest classification algorithm is used to predict the ordering (paramagnetic, ferromagnetic, and antiferromagnetic) of such systems with 76% accuracy.

36 MATERIALS SCIENCE↗

Unveiling the Finite Temperature Physics of Hydrogen Chains via Auxiliary Field Quantum Monte Carlo

The ability to accurately predict the finite temperature properties and phase diagrams of realistic quantum solids is central to uncovering new phases and engineering materials with novel properties ripe for device applications. Nonetheless, there remain comparatively few many-body techniques capable of elucidating the finite temperature physics of solids from first principles. Here, we take a significant step toward developing such a technique by generalizing our previous, exact fully ab initio finite temperature Auxiliary Field Quantum Monte Carlo (FT-AFQMC) method to model periodic solids and employing it to uncover the finite temperature physics of periodic hydrogen chains. Our chains’ unit cells consist of 10 hydrogen atoms modeled in a minimal basis, and we sample 5 k-points from the first Brillouin zone to arrive at a supercell consisting of 50 orbitals and 50 electrons. Based upon our calculations of these chains’ many-body energies, free energies, entropies, heat capacities, double and natural occupancies, and charge and spin correlation functions, we outline their metal–insulator and magnetic ordering as a function of both H–H bond distance and temperature. At low temperatures approaching the ground state, we observe both metal–insulator and ferromagnetic–antiferromagnetic crossovers at bond lengths between 0.5 and 0.75 Å. We then demonstrate how this low-temperature ordering evolves into a metallic phase with decreasing magnetic order at higher temperatures. In order to contextualize our results, we compare the features we observe to those previously seen in one-dimensional, half-filled Hubbard models at finite temperature and in ground state hydrogen chains. Interestingly, we identify signatures of the Pomeranchuk effect in hydrogen chains for the first time and show that spin and charge excitations that typically arise at distinct temperatures in the Hubbard model are indistinguishably coupled in these systems. Beyond qualitatively revealing the many-body phase behavior of hydrogen chains in a numerically exact manner without invoking the phaseless approximation, our efforts shed light on the further theoretical developments that will be required to construct the phase diagrams of the more complex transition metal, lanthanide, and actinide solids of longstanding interest to physicists.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

2000-2001 California Statewide Household Travel Survey

The 2000-2001 California Statewide Household Travel Survey, conducted under the auspices of the California Department of Transportation, was conducted between October 2000 and December 2001 among households located in each of California's 58 counties. The purpose of the study was to update the statewide database of household socioeconomic and travel information and helped to refine travel estimates, models, and forecasts throughout California. The survey was an essential element in determining statewide and regional travel patterns. A total of 17,040 households participated in the survey, contributing household socioeconomic and travel data. Travel variables collected include trip times, mode, activity at location, origin and destination, and vehicle occupancy, among other travel-related data from 134,173 trips. Residents completed diary records of their daily travel over a 24-hour (weekday) or 48-hour period (Friday/Saturday or Sunday/Monday pair).

1Hz data↗

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DC Arc Incident Energy in Photovoltaic Systems: Methods for Evaluation

Renewable energy systems continue to be one of the fastest growing segments of the energy industry. This article focuses on the understanding of how photovoltaic (PV) technology behaves under dc arc conditions. Emphasis is placed on the electrical safety aspect of dc arc-flash incident energy (IE) evaluation. Because of the fast proliferation of PV systems and lack of formal equivalent calculation guidelines, such as IEEE 1584 for ac systems, it has been necessary to rely on different equations and models presented by various researchers over the last few years. This article discusses the behavior of PV systems under arc conditions and presents the results of the available methods to estimate the dc arc-flash IE. It provides a comparative analysis of a proposed arc-flash IE calculation method against different laboratory tests, including those performed for this article at the National Renewable Energy Laboratory (NREL). Detailed explanations are provided regarding the effect of the PV module current-voltage (I-V) and power-voltage (P-V) curves under arcing conditions. Examples of the application of the proposed calculation method to the test measurements are included.

arc discharges↗