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At least 307 records · Page 17

Multiprobe cosmology from the abundance of SPT clusters and DES galaxy clustering and weak lensing

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3 × 2 ⁢pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining Λ cold dark matter (Λ ⁢CDM) parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure Ω m = 0.300 ± 0.017 and 𝜎 8 = 0.797 ± 0.026. Compared to constraints from Planck primary cosmic microwave background (CMB) anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 (1.2⁢𝜎) for the two-parameter difference. We further obtain 𝑆 8 ≡𝜎 8 ⁢(Ω m /0.3) 0.5 = 0.796 ± 0.013 which is lower than the Planck measurement at the 1.6⁢𝜎 level. The combined SPT cluster, DES 3 ×2 ⁢pt, and Planck datasets mildly prefer a nonzero positive neutrino mass, with a 95% upper limit ∑ 𝑚 𝜈 < 0.25 eV on the sum of neutrino masses. Assuming a 𝑤⁢CDM model, we constrain the dark energy equation of state parameter 𝑤 = −1.1⁢5$^{+0.23}_{−0.17}$ and when combining with Planck primary CMB anisotropies, we recover 𝑤 = −1.2⁢0$^{+0.15}_{−0.09}$, a 1.7⁢𝜎 difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology and our analysis paves the way for upcoming joint analyses of next-generation datasets.

79 ASTRONOMY AND ASTROPHYSICS↗

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Continuity of reaction kinetics across the pressure and materials gaps in CO oxidation on FeO–Pt interfaces

Translating atomic-scale insights from surface science studies of model catalysts to practical powder catalysts remains a persistent challenge in heterogeneous catalysis. Here, in this study, we demonstrate mechanistic continuity across the pressure and materials gaps during CO oxidation at the FeO-Pt interface using in situ microscopy, spectroscopy and computational modelling. Under reaction conditions, coordinatively unsaturated Fe (Fe cus ) sites at the interface enable selective O 2 activation on CO-saturated surfaces, circumventing the CO-poisoning limitation of platinum-group metals. We identify parallel reaction pathways involving the *O 2 -*CO intermediate. Remarkably, activation energies remain consistent at 12-15 kJ mol −1 (0.12-0.16 eV) from ultrahigh vacuum to atmospheric pressures and from FeO/Pt(111) model catalysts to FeO/Pt powder catalysts, validating mechanistic insights derived from surface science studies. Our findings show an example of bridging the long-standing divide between model and practical catalyst systems, establishing an effective approach to capture catalytic behaviours under operational conditions and advancing mechanism-driven catalyst design.

03 NATURAL GAS↗

Coordinating the electric vehicle transition and electricity grid decarbonization in the U.S. is not essential to achieving substantial long-term carbon dioxide emissions reductions

Abstract How quickly the US can decarbonize light-duty vehicle (LDV) transportation depends on the rates of change of electric vehicle (EV) sales, stock turnover, and grid decarbonization. We build a stock turnover model to assess how sensitive achieving 2050 LDV decarbonization targets is to these rates. We estimate carbon dioxide (CO 2 ) reductions of 70%–85% by 2050, including emissions from vehicles and upstream electricity generation, provided that new vehicle sales transition to 100% EVs and substantial grid decarbonization are accomplished by 2050. This result is robust to continuation of long-term trends of increasing vehicle longevity, and to whether the timing of EV sales growth and grid decarbonization are coordinated. If the two key goals are met, the annual contribution of EV electricity use to CO 2 emissions will be small over the entire period.

Leard, Benjamin↗

A Machine Learning Approach for Hourly Traffic Prediction Used in EV-Charging Sites

Reliable forecasting of hourly traffic volumes on highways is critical for planning and operating electric-vehicle charging infrastructure without overloading the grid. In this work, we develop and evaluate a station-specific machine-learning approach based on NeuralProphet, enhanced with conditional seasonality to better distinguish weekday, weekend, and holiday patterns. For each station, the model automatically retrieves the same calendar day from the prior years as an AR-Net initialization, fits trend and Fourier-based seasonality components, and then applies short-term auto-regressive corrections. We train and test on 2021 and 2022 TMAS data, respectively, and validate performance over the whole year. We chose to demonstrate how the model performs on a typical weekday (3/15/2022), weekend (3/27/2022), and a special holiday (12/25/2022). Our results yield MAPE of 7.4%, 23.6%, and 32.0%, respectively. Over the entire year 2022, the overall MAPE was 17%. This demonstrates that station-specific models with conditional seasonality can achieve accurate, scalable hourly forecasts for EV-charging load planning.

99 - GENERAL AND MISCELLANEOUS↗

Multimode two-dimensional vibronic spectroscopy. I. Orientational response and polarization-selectivity

Two-dimensional Electronic–Vibrational (2D EV) spectroscopy and two-dimensional Vibrational–Electronic (2D VE) spectroscopy are among the newest additions to the coherent multidimensional spectroscopy toolbox, and they are directly sensitive to vibronic couplings. In this first of two papers, the complete orientational response functions are developed for a model system consisting of two coupled anharmonic oscillators and two electronic states in order to simulate polarization-selective 2D EV and 2D VE spectra with arbitrary combinations of linearly polarized electric fields. Here, we propose analytical methods to isolate desired signals within complicated spectra and to extract the relative orientation between vibrational and vibronic dipole moments of the model system using combinations of polarization-selective 2D EV and 2D VE spectral features. Time-dependent peak amplitudes of coherence peaks are also discussed as means for isolating desired signals within the time-domain. This paper serves as a field guide for using polarization-selective 2D EV and 2D VE spectroscopies to map coupled vibronic coordinates on the molecular frame.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning Models for Binary Molecular Classification using VUV Absorption Spectra

Machine learning methods were combined with differential absorption spectroscopy measurements in the vacuum-ultraviolet region (5.167 – 9.920 eV) in order to develop predictive capabilities for inferring molecular structure from the spectra. Several types of species were analyzed and, for modeling purposes, were defined using a single classification: (1) alkane, (2) conjugation with oxygen (e.g. diacetyl, ethyl vinyl ether), (3) non-conjugated alkene (e.g. 1-butene, 1,4-cyclohexadiene), (4) oxygen-containing (e.g. 1-butanol, tetrahydrofuran), or (5) cyclic (e.g. cyclopentane, cyclohexanone). The latter molecular classification excluded cyclic ethers. Several modeling methods were employed in the analysis of 102 absorption spectra, 24 of which were measured for the first time. The primary objective was to identify suitable methods that enable accurate predictions of molecular structure classifications with minimized statistical uncertainties. Rather than identifying a single, unifying method to reliably predict molecular structure contributions to VUV absorption spectra, coordination is required among a particular method, the type of molecular structure detail (e.g. conjugation), and absorption region of interest. The latter is accomplished using a binning approach, wherein absorption regions of ~0.5 eV were utilized rather than the entire ~4.8 eV range. Photon energy binning enabled analysis of region-specific predictions of accuracy, precision, and recall. The outcome from the binning approach is that, rather than utilizing the entire spectrum, optimal determination of molecular structure using machine learning methods depends on the absorption region. Furthermore, the present work provides separate machine learning models for each molecular classification, which enables the identification of multi-functional species relevant to atmospheric chemistry and combustion chemistry, where isomer-resolved speciation is critical to understanding complex reaction networks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-modular capacitive wireless power transfer circuit and related techniques

A high performance kilowatt-scale large air-gap multi-modular capacitive wireless power transfer (WPT) system is provided for electric vehicle (EV) charging. In one particular implementation, the multi-modular system achieves high power transfer while maintaining fringing electric fields within prescribed safety limits. The fringing fields are reduced using near-field phased-array field-focusing techniques, wherein the adjacent modules of the multi-modular system are out-phased with respect to one another. The inter-module interactions in this multi-modular system can be modeled, and an approach to eliminate these interactions in a practical EV charging environment is provided. To illustrate one example implementation, a prototype 1.2-kW 6.78-MHz 12-cm air-gap multi-modular capacitive WPT system comprising two 600-W modules is provided. This prototype system achieves 21.2 kW/m2 power transfer density and a peak efficiency of 89.8%. This multi-modular system also achieves a fringing field reduction of 50% compared to its individual modules.

Afridi, Khurram K.↗

Vehicle Electrification Impacts on Energy Consumption for Different Connected-Autonomous Vehicle Scenario Runs

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Neutron detector response modeling in NOvA

Neutrons can present a significant challenge for neutrino experiments in which energy reconstruction is critical. With the ability to escape detection completely and with a weak correlation between their kinetic energy and any eventual energy deposition, it is difficult to fully account for neutrons produced in neutrino interactions. This in turn leads to significant model dependence when evaluating neutron-related systematic uncertainties. The NOvA experiment is a long-baseline neutrino oscillation experiment with a high-statistics sample of antineutrino data collected by its near detector. We report an excess relative to data of simulated neutron candidates with low energy depositions when using standard Geant4 physics lists. The simulation excess is traced to an overabundance of secondary photons produced from interactions of neutrons with kinetic energy greater than \SI{20}{\mega\eV}. Improved agreement with data is obtained by applying the data-driven neutron-on-carbon \menate model for neutrons between \SI{20}{\mega\eV} and ${\sim}$\SI{100}{\mega\eV}. With \menate, the residual oversimulation is more uniform across the calorimetric neutron energy spectrum, suggesting possible overproduction of primary neutrons by the GENIE neutrino interaction generator. These results motivate the adoption of \menate-supplemented Geant4 simulation as the nominal simulation in the production of future \nova simulation.

Abubakar, S.↗

Preliminary searches for spin-dependent interactions using sidebands of nuclear spin-precession signals

Various theories beyond the Standard Model predict new particles with masses in the sub-eV range with very weak couplings to ordinary matter. A new P-odd and T-odd interaction between polarized and unpolarized nucleons proportional to s⃗⋅r̂ is one such possibility, where r⃗=rr̂ is the spatial vector connecting the nucleons, and s⃗ is the spin of the polarized nucleon. Such an interaction involving a scalar coupling gsN at one vertex and a pseudoscalar coupling gpn at the polarized nucleon vertex can be induced by the exchange of spin-0 pseudoscalar bosons. We describe a new technique to search for interactions of this form and present the first measurements of this type. We show that future improvements to this technique can improve the laboratory upper bound on the product gsNgpn by two orders of magnitude for interaction ranges at the 100 micron scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Step in Understanding the Hubble Tension

As cosmological data have improved, tensions have arisen. One such tension is the difference between the locally measured Hubble constant H 0 and the value inferred from the cosmic microwave background (CMB). Interacting radiation has been suggested as a solution, but studies show that conventional models are precluded by high-ℓ CMB polarization data. It seems at least plausible that a solution may be provided by related models that distinguish between high- and low-ℓ multipoles. When interactions of strongly-coupled radiation are mediated by a force-carrier that becomes non-relativistic, the dark radiation undergoes a "step" in which its relative energy density increases as the mediator deposits its entropy into the lighter species. If this transition occurs while CMB-observable modes are inside the horizon, high- and low-ℓ peaks are impacted differently, corresponding to modes that enter the horizon before or after the step. Here, these dynamics are naturally packaged into the simplest supersymmetric theory, the Wess-Zumino model, with the mass of the scalar mediator near the eV-scale. We investigate the cosmological signatures of such "Wess-Zumino Dark Radiation" (WZDR) and find that it provides an improved fit to the CMB alone, favoring larger values of H 0 . If supernovae measurements from the SH0ES collaboration are also included in the analysis, the inferred value of H 0 is yet larger, but the preference for dark radiation and the location of the transition is left nearly unchanged. Utilizing a standardized set of measures, we compare to other models and find that WZDR is among the most successful at addressing the H 0 tension and the best of those with a Lagrangian formulation.

79 ASTRONOMY AND ASTROPHYSICS↗

First Measurement of Z Opacity Sample Evolution near Solar Interior Conditions Using Time-Resolved Spectroscopy

Opacity model differences with Fe opacity measurements at high temperature (T>1⁢8⁢0 eV ) and high electron density (𝑛 𝑒 >3×10 22 cm −3 ) at nearly solar interior conditions have remained unresolved [Bailey et al., Nature 517, 56 (2015) and Nagayama et al., Phys. Rev. Lett. 122, 235001 (2019)]. Systematic errors from temporal gradients are one hypothesis for the discrepancy. Past data recorded on x-ray film provided spectral measurements over a time determined by the 2.8-ns backlighter duration. Here, we present the first measurements of opacity sample temporal evolution using novel hCMOS ultrafast x-ray camera technology. The measured conditions, measured backlighter time history, and modeled opacities are used to show that temporal gradients do not resolve the model-data discrepancy. The methods demonstrated provide potential advantages, including opacities at more extreme conditions, spectral line shift measurements, and improved measurements at other facilities.

atomic spectra↗

Effect of dilute Rh on oxygen dissociation, spillover, and the oxidation of Cu across many orders of magnitude pressure

Knowledge of how trace amounts of more reactive metals influence the oxidation rate and mechanism of Cu surfaces is essential for developing strategies to optimize the performance of Cu-based catalysts. We find that the addition of 1% Rh to Cu(111) increases the initial O 2 dissociation rate by approximately 9-fold. CO poisoning experiments reveal that single Rh atoms activate O 2 and facilitate the spillover of atomic oxygen to Cu sites. Scanning tunneling microscopy (STM) and in situ X-ray photoelectron spectroscopy (XPS) support this mechanism, showing enhanced surface oxygen near Rh atoms. Here, a density functional theory (DFT)-based model demonstrates that Rh binds the O 2 precursor 0.15 eV more strongly than Cu(111) and lowers the O 2 dissociation barrier by 0.02 eV. Both single-crystal and nanoparticle experiments show that at low oxygen pressures, Rh enhances Cu oxidation, whereas at higher pressures, it inhibits deeper oxidation, as evidenced by in situ ultraviolet-visible (UV-vis) spectra.

36 MATERIALS SCIENCE↗

Operational optimization for multi-functional charging station with electric and hydrogen-powered vehicles

The rapid adoption of electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs), combined with global efforts to reduce carbon emissions, has accelerated the development of EV charging and hydrogen refueling stations. In response to this demand, this paper introduces the concept of Multi-Functional Charging Station (MFCS) that integrates power generation, EV charging, battery swapping, and hydrogen refueling. A comprehensive operational model is developed for the MFCS that couples electricity and hydrogen conversion and storage technologies to enhance infrastructure utilization and improve overall system efficiency. The model also considers multiple revenue streams, including participation in energy and ancillary markets. To validate the effectiveness of the proposed model and evaluate its performance, a series of numerical experiments are conducted with different charger numbers, different electricity purchase limits, and different charger allocations. Numerical results demonstrate that shared charger configurations can lead to 8.11 % improvement in operational profit by improving resource utilization and reducing the number of depleted batteries at the end of operations compared to allocated charger setups. By varying the number of chargers, sensitivity analysis identifies diminishing marginal returns beyond about 45 chargers, suggesting it as an optimal sizing point under current settings. The integration of electricity and hydrogen conversion is also explored under scenarios with limited external electricity purchases. In conclusion, these findings indicate that optimizing charger allocation and energy management can significantly enhance station productivity and profitability, ultimately supporting the broader adoption of electrified and hydrogen-based transportation solutions.

Charging station↗

Work Function Engineering of 2D Materials: The Role of Polar Edge Reconstructions

2D materials have attracted tremendous interest as functional materials because of their diverse and tunable properties, especially at their edges. A material’s work function is a critical parameter in many electronic devices; however, a fundamental understanding and a path toward large alterations of the work function in 2D materials still remain elusive. Here in this paper, we report the first evidence for anisotropy of the work function in 2D MoS 2 from first-principles calculations. We also demonstrate large work-function tunability (in the range of 3.45–6.29 eV) choosing the 2H phase of MoS 2 as a model system by sampling various edge configurations. We furthermore reveal the origin of this work function anisotropy and tunability by extending the existing work function relation to the local dipole moment at surfaces of 3D materials to those at edges in 2D materials. We then use machine-learning approaches to correlate work function with edge structures. These results pave the way for intrinsic edge engineering for electronic and catalytic applications.

36 MATERIALS SCIENCE↗

Self-interacting dark scalar spikes around black holes via relativistic Bondi accretion

For this work, we consider the spike mass density profile in a dark halo by self-consistently solving the relativistic Bondi accretion of dark matter onto a non-spining black hole of mass M. We assume that the dominant component of the dark matter in the halo is a Standard model gauge-singlet scalar. Its mass m ≃ 10 -5 eV and quartic self-coupling λ ≲ 10 19 are constrained to be compatible with the properties of galactic dark halos. In the hydrodynamic limit, we find that the accretion rate is bounded from below, M min = 96πG 2 M 2 m 4 /λ$\hbar$ 3 . Therefore, for M = 10 6 M ⊙ we have M min ≃ 1.41 x 10 -9 M ⊙ yr -1 , which is subdominant compared to the Eddington accretion of baryons. The spike density profile ρ0(r) within the self-gravitating regime cannot be fitted well by a single-power law but a double-power one. Despite that, we can fit ρ 0 (r) piecewise and find that ρ 0 (r) ∝ r -1.20 near the sound horizon, ρ 0 (r) ∝ r -1.00 towards the Bondi radius and ρ 0 (r) ∝ r -1.08 for the region in between. This contrasts with more cuspy ρ 0 (r) ∝ r -1.75 for dark matter with Coulomb-like self-interaction.

79 ASTRONOMY AND ASTROPHYSICS↗

Improvement of SCALE-XSPROC Multigroup Cross Section Processing Based on the CENTRM Pointwise Slowing Down Calculation

The SCALE-XSProc multigroup (MG) cross section processing procedure based on the CENTRM pointwise slowing down calculation is the primary procedure to process problem-dependent self-shielded MG cross sections and scattering matrices for neutron transport calculations.This procedure supports various cell-based geometries including slab, 1-D cylindrical, 1-D spherical and 2-D rectangular configurations and doubly heterogeneous particulate fuels. Recently, this procedure has been significantly improved to be applied to any advanced reactor analysis covering thermal and fast reactor systems, and to be comparable to continuous energy (CE) Monte Carlo calculations. Some reactivity bias and reaction rate differences have been observed compared with CE Monte Carlo calculations, and several areas for improvement have been identified in the SCALE-XSProc MG cross section processing: (1) resonance self-shielding calculations within the unresolved resonance range, (2) 10 eV thermal cut-off energy for the free gas model, (3) on-the-fly adjustments to the thermal scattering matrix, (4) normalization of the pointwise neutron flux, and (5) fine MG energy structure. This procedure ensures very accurate MG cross section processing for high-fidelity deterministic reactor physics analysis for various advanced reactor systems.

Kim, Kang Seog↗