Analysis of Urban Freight Flows and Retail Goods Movement Using GPS Trajectory and Land Use Data
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Sahin, Olcay↗
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Search in diphoton and dielectron final states for displaced production of Higgs or Z bosons with the ATLAS detector in s = 13 TeV p p collisions
A search is presented for displaced production of Higgs bosons or Z bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes H → γ γ and Z → ee . The analysis uses the full Run 2 dataset of proton-proton collisions delivered by the LHC at an energy of $\sqrt{s}$ = 13 TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb -1 . Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced Higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a Z boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for Higgsino pair production, up to a $\bar{χ}^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\bar{χ}^0_1$ to Higgs (Z) bosons for a $\bar{χ}^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Reversible Electron-Beam Patterning of Colloidal Nanoparticles at Fluid Interfaces
The directed self-assembly of colloidal nanoparticles (NPs) using external fields guides the formation of sophisticated hierarchical materials but becomes less effective with decreasing particle size. As an alternative, electron-beam-driven assembly offers a potential avenue for targeted nanoscale manipulation, yet remains poorly controlled due to the variety and complexity of beam interaction mechanisms. Here, we investigate the beam–particle interaction of silica NPs pinned to the fluid–vacuum interface of ionic liquid droplets. In these experiments, scanning electron microscopy of the droplet surface resolves NP trajectories over space and time while simultaneously driving their reorganization. With this platform, we demonstrate the ability to direct particle transport and create transient, reversible colloidal patterns on the droplet surface. By tuning the beam voltage, we achieve precise control over both the strength and sign of the beam–particle interaction, with low voltages repelling particles and high voltages attracting them. This response stems from the formation of well-defined solvent flow fields generated from trace radiolysis of the ionic liquid, as determined through statistical analysis of single-particle trajectories under varying solvent composition. Altogether, electron-beam-guided assembly introduces a versatile strategy for nanoscale colloidal manipulation, offering new possibilities for the design of dynamic, reconfigurable systems with applications in adaptive photonics and catalysis.
36 MATERIALS SCIENCE↗
Multiscale Reactive Model for 1,3,5-Triamino-2,4,6-trinitrobenzene Inferred by Reactive MD Simulations and Unsupervised Learning
When high-energy-density materials are subjected to thermal or mechanical insults at extreme conditions (shock loading), a coupled response between the thermo-mechanical and chemical behaviors is systematically induced. Herein we develop a reaction model for the fast chemistry of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) at the mesoscopic scale, where the chemical behavior is determined by underlying microscopic reactive simulations. The slow carbon cluster formation is not discussed in the present work. All-atom reactive molecular dynamics (MD) simulations are performed with the ReaxFF potential, and a reduced-order chemical kinetics model for TATB is fitted to isothermal and adiabatic simulations of single crystal chemical decomposition. Unsupervised machine learning techniques based on non-negative matrix factorization are applied to MD trajectories to model the decomposition kinetics of TATB in terms of a four-component model. The associated heats of reaction are fit to the temperature evolution from adiabatic decomposition trajectories. Using a chemical species analysis, we show that non-negative matrix factorization captures the main chemical decomposition steps of TATB and provides an accurate estimation of their evolution with temperature. The final analytical formulation, coupled to a diffusion term, is incorporated into a continuum formalism, and simulation results are compared one-to-one against MD simulations of 1D reaction propagation along different crystallographic directions and with different initial temperatures. A good agreement is found for both the temporal and spatial evolution of the temperature field.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Machine learning for collective variable discovery and enhanced sampling in biomolecular simulation
Classical molecular dynamics simulates the time evolution of molecular systems through the phase space spanned by the positions and velocities of the constituent atoms. Molecular-level thermodynamic, kinetic, and structural data extracted from the resulting trajectories provide valuable information for the understanding, engineering, and design of biological and molecular materials. The cost of simulating many-body atomic systems makes simulations of large molecules prohibitively expensive, and the high-dimensionality of the resulting trajectories presents a challenge for analysis. Driven by advances in algorithms, hardware, and data availability, there has been a flare of interest in recent years in the applications of machine learning – especially deep learning – to molecular simulation. Furthermore, these techniques have demonstrated great power and flexibility in both extracting mechanistic understanding of the important nonlinear collective variables governing the dynamics of a molecular system, and in furnishing good low-dimensional system representations with which to perform enhanced sampling or develop long-timescale dynamical models. It is the purpose of this article to introduce the key machine learning approaches, describe how they are married with statistical mechanical theory into domain-specific tools, and detail applications of these approaches in understanding and accelerating biomolecular simulation.
74 ATOMIC AND MOLECULAR PHYSICS↗
How does vertical wind shear influence entrainment in squall lines?
The influence of vertical wind shear on updraft entrainment in squall lines is not well understood. To address this knowledge gap, a suite of high-resolution idealized numerical model simulations of squall lines were run in various vertical wind shear (hereafter “shear”) environments to study the effects of shear on entrainment in deep convective updrafts. Low-level horizontal mass flux into the leading edge of the cold pool was strongest in the simulations with the strongest low-level shear. These simulations consequently displayed wider updrafts, less entrainment-driven dilution, and larger buoyancy than the simulations with comparatively weak low-level shear. An analysis of vertical accelerations along trajectories that passed through updrafts showed larger net accelerations from buoyancy in the simulations with stronger low-level shear, which demonstrates how less entrainment-driven dilution equated to stronger updrafts. Additionally, the effects of upper-level shear on entrainment and updraft vertical velocities were generally less pronounced than the effects of low-level shear. We argue that in addition to the outflow boundary-shear interactions and their effect on updraft tilt established by previous authors, decreased entrainment-driven dilution is yet another beneficial effect of strong low-level shear on squall line updraft intensity.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Nonlinear Tune-Shift Measurements in the Integrable Optics Test Accelerator
The first experimental run of Fermilab’s Integrable Optics Test Accelerator (IOTA) ring aimed at testing the concept of nonlinear integrable beam optics. In this report we present the preliminary results of the studies of a nonlinear focusing system with two invariants of motion realized with the special elliptic-potential magnet. The key measurement of this experiment was the horizontal and vertical betatron tune shift as a function of transverse amplitude. A vertical kicker strength was varied to change the betatron amplitude for several values of the nonlinear magnet strength. The turn-by-turn positions of the 100 MeV electron beam at twenty-one beam position monitors around the ring were captured and used for the analysis of phase-space trajectories.
43 PARTICLE ACCELERATORS↗
Spatiotemporal Analyses of Groundwater and Shoreline Cr(VI) Concentrations in the 100 Areas at Hanford
Cleanup efforts have been ongoing since the late 1990s to remediate contaminated waste sites and groundwater in the 100 Areas at the U.S. Department of Energy (DOE) Hanford Site. One of the primary contaminants of concern is hexavalent chromium (Cr(VI)), which was used as a corrosion inhibitor in cooling water for nuclear reactors that formerly operated along the shoreline of the Columbia River. Cleanup efforts have included 1) removal, treatment (as needed), and disposal of contaminated sediments; 2) in situ redox manipulation as a permeable reactive barrier; 3) pump-and-treat; 4) soil flushing; and 5) monitored natural attenuation. DOE’s annual groundwater monitoring reports document the significant reductions in Cr(VI) plume areas that have occurred over the past 10 years or more as a result of these cleanup efforts. The Record of Decision for the 100-HR-3 operable unit specified a cleanup level (CUL) for Cr(VI) in groundwater of 48 µg/L to protect human receptors, and a surface water CUL of 10 µg/L to protect aquatic organisms in the Columbia River. The Record of Decision did not specify point-of-compliance locations for the surface water CUL. Data for 2019 from the six groundwater operable units (OUs) in the 100 Areas indicate that the 48 μg/L groundwater CUL has been achieved in 100% of the wells in the 100-BC and 100-NR OUs, and in 89- 97% of the wells in the other OUs (100-KR, 100-HR-D, 100-HR-H, 100-FR). Data for 2019 indicate that 100% of the aquifer tubes monitored for Cr(VI) in the 100 Areas have concentrations below the 48 μg/L groundwater CUL. However, the 10 μg/L standard has not yet been consistently achieved for both inland groundwater monitoring wells and shoreline aquifer tubes. This report describes a series of data analyses performed to identify consistent relationships, if any, between inland well and shoreline Cr(VI) concentrations within the 100 Areas. To this end, select monitoring data for Cr(VI) measured in groundwater and aquifer tubes at the 100 Areas were analyzed for a 10-year period—2010 to 2019. Relationships between inland groundwater plumes and surface-water points of discharge in and along the Columbia River were examined through several analyses that included inland well and aquifer tube concentrations as a function of distance from the shoreline, evaluation of cumulative probability plots, trend analysis, correlation analysis, cluster analysis, and identification of plume trajectories for each of the 100 Areas. The analyses did not identify consistent relationships between inland groundwater Cr(VI) concentrations and shoreline concentrations within the 100 Areas due to several confounding factors influencing groundwater flow directions and Cr(VI) concentrations. The proximity of groundwater Cr(VI) plumes to the river, and the highly dynamic nature of the river, influence the transport behavior of the plumes and create challenges for quantifying attenuation of Cr(VI) between the inland monitoring wells and shoreline concentrations. Other factors contributing to temporal and spatial Cr(VI) concentrations, as supported by some of the data analyses, include the presence of vadose zone sources, variable sorption behavior, and complexities associated with Cr(VI) mass transfer between the upper and lower aquifers and their interactions with the river. Hence, monitoring to assess compliance with target CULs will need to be determined for each area individually since several factors influence Cr(VI) concentrations in the 100 Areas.
54 ENVIRONMENTAL SCIENCES↗
Determining Optimal Running Conditions for TinyTPC Detector
Liquid argon time projection chambers, (LArTPCs), are particle detectors used to collect ionization charge information from particle trajectories, facilitating detailed particle track analysis. They are currently used as particle detectors in major physics projects such as the deep underground neutrino experiment (DUNE), to detect and study the nature of the elusive neutrino particle. TinyTPC is a small scale LArTPC featuring a pixelated readout system (LArPix) that we will use to study liquid argon doping. We expect this doping to enhance the resolution of LAr detectors, especially for low energy particles below 10 MeV which would expand the capabilities of currently running experiments. Housed within a cryostat filled with liquid argon, the TinyTPC will rely on a high and a low voltage system to collect data. In preparation for deployment we found and resolved issues in the HV and LV systems and we determined optimal running conditions in a test vessel. This presentation will go over the detector commissioning process that enabled data taking with the TinyTPC.
Gonzalez, Rebecca↗
Techno-Economic Evaluation of Electrified Vehicle Options in Drayage Fleets
The electrification of drayage fleets offers potential economic and operational benefits, but the financial viability of electrified vehicles remains sensitive to battery cost, energy price, and fleet usage patterns. While total cost of ownership (TCO) is a useful benchmark, fleet operators and investors are equally concerned with investment performance metrics such as payback period (PB) and Internal Rate of Return (IRR), which better reflect financial risks and investment return timelines. This study develops a unified techno-economic framework that jointly evaluates TCO, PB, and IRR to determine when electrified trucks become cost-effective alternatives to diesel trucks. Building on a previously developed cost modeling tool and using real-world telematics data from a Class 8 drayage fleet at the Port of Savannah, the analysis incorporates projected battery cost trajectories, electricity and diesel price trends, vehicle efficiency improvements, and multiple battery capacities. Parameter ranges reflect widely cited projections and observed drayage-duty-cycle variability. A surrogate-modeling method approximates economic performance across thousands of battery cost–electricity price combinations, enabling high-resolution identification of conditions that achieve TCO parity, acceptable PB thresholds, and target IRR levels. Additionally, the study estimates the evolving share of the fleet that can feasibly electrify over time under multiple economic metrics. This integrated framework offers a novel, data-driven approach to inform risk-aware decision-making for fleet electrification and supports investment planning under evolving cost and operational conditions.
Sun, Ruixiao [ORNL] (ORCID:0000000341768676)↗
Exploring Building Retrofit Strategies Using AutoBEM Under Future Weather Scenarios
This study evaluates the long-term effectiveness of energy conservation measures (ECMs) on building energy consumption using AutoBEM, a scalable modeling framework driven by the high-resolution Model America dataset. We simulated 18,951 buildings in Flagstaff, Arizona under four climate scenarios using Future Typical Meteorological Year (fTMY) weather files for six time periods spanning from 1980 to 2099. Six ECMs were analyzed across electricity and gas usage, including HVAC fuel-switching, insulation upgrades, and infiltration control. While some measures, such as reducing space infiltration by percentage, showed minimal or even negative impact on total energy savings at the aggregate level, they proved highly effective for specific building types. Conversely, HVAC electrification offers high gas reduction but shifts demand to electricity, highlighting critical trade-offs under different climate trajectories. Building-type-specific analysis under SSP5-RCP8.5 (2080–2099) revealed significant variation in ECM performance, underscoring the need for targeted retrofit strategies. This study demonstrates the power of combining fTMY projections with large-scale simulations to inform data-driven retrofit planning.
Chowdhury, Shovan [ORNL]↗
Tracktable
Tracktable is a toolkit for analysis and visualization of the trajectories of moving objects. Its main focus is on air and sea traffic. It can also work with more abstract trajectories such as eye tracking data. We supply a set of core data structures, input/output routines, math and machine learning algorithms that operate on those data structures, and visualization algorithms to produce movies and still images of the results.
Wilson, Andrew↗
Instability Issue of Paralleled Dies in an SiC Power Module in Solid-State Circuit Breaker Applications
Paralleled dies in a power module could have instability issues during high current switching transients. Here, the instability is caused by the differential-mode oscillation among paralleled MOSFETs. Conventional analyses of paralleled MOSFETs’ stability are normally limited to a single operating point, which ignores the influences of the switching trajectory and nonlinear device parameters on stability. This article reveals that the switching trajectory can significantly influence parallel stability. The analysis is improved by solving eigenvalues of state-space modeling system matrices of all operating points that the switching trajectory goes through considering nonlinear device parameters. Higher voltage and current stresses result in greater real parts of complex eigenvalues, which explains why the paralleled MOSFETs are more unstable with higher voltage and current stresses. To improve stability in solid-state circuit breaker applications, we propose a method to manipulate the switching trajectory to avoid the unstable region where the conventional hard switching trajectory normally goes through. Experimental results show that the turn- off current capability can be increased from ~five times of rated current with the gate oscillation using the conventional turn- off trajectory to ~ten times of rated current without the gate oscillation using the optimal turn- off trajectory.
42 ENGINEERING↗
Cloud condensation nuclei characteristics at the Southern Great Plains site: role of particle size distribution and aerosol hygroscopicity
The activation ability of aerosols as cloud condensation nuclei (CCN) is crucial in climate and hydrological cycle studies, but their properties are not well known. We investigated the long-term measurements of atmospheric aerosol properties, CCN concentrations (N CCN ) at supersaturation (SS = 0.1%–1.0%), and hygroscopicity at the Department of Energy's Southern Great Plains (SGP) site to illustrate the dependence of N CCN on aerosol properties and transport pathways. Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aged biomass burning aerosols from Central America were characterized by higher accumulation mode particles (N accu ; median value 805 cm -3 ) and relatively high aerosol hygroscopicity (κ; median value ~0.25) values that result in the higher CCN activation and relatively high N CCN (median value 258–1578 cm -3 at a SS of 0.1%–1.0%). Aerosols from the Gulf of Mexico were characterized by higher N accu (~35%), and N CCN (230–1721 cm -3 at a SS of 0.1%–1.0%) with the lowest κ (~0.17). In contrast, relatively high nucleation mode particles (N nucl ; ~20%) and low N CCN (128–1553 cm -3 at a SS of 0.1%–1.0%) with higher κ (~0.30) values were observed on the aerosols associated with a westerly wind. The results indicate particle size as the most critical factor influencing the ability of aerosols to activate, whereas the effect of chemical composition was secondary. Our CCN closure analysis suggests that chemical composition and mixing state information are more crucial at lower SS, whereas at higher SS, most particles become activated regardless of their chemical composition and size. This study affirms that soluble organic fraction information is required at higher SS for better N CCN prediction, but both the soluble organics fraction and mixing state are vital to reduce the N CCN prediction uncertainty at lower SS.
54 ENVIRONMENTAL SCIENCES↗
Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors
Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes (“tadpoles” and “boomerangs”), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The cost of direct air capture and storage can be reduced via strategic deployment but is unlikely to fall below stated cost targets
Carbon dioxide removal (CDR) is necessary to minimize the impact of climate change by tackling hard-toabate sectors and historical emissions. Direct air capture and storage (DACS) is an important CDR technology, but it remains unclear when and how DACS can be economically viable. Here, we use a bottom-up engineering-economic model together with top-down technological learning projections to calculate plant-level cost trajectories for four DACS technologies. Our analysis demonstrates that the costs of these technologies can plateau by 2050 at around $\$$100-600 t-CO 2 -1 mainly via capital cost reduction through aggressive deployment, but still exceed the optimistic targets defined by countries such as the US (i.e., $\$$100 t-CO 2 -1 ). A further analysis of existing policy mechanisms indicates that strong, project-catered policy support will be required to create market opportunities, accelerate DACS scale-up and lower the costs further. Our work suggests that strategic DACS deployment and operation must be coupled with strong policies to minimise the cost of DACS and maximise the opportunity to make a planet-scale climate impact.
54 ENVIRONMENTAL SCIENCES↗
An Experimental and Numerical Investigation to Characterize the Low-Temperature Heat Release in Stoichiometric and Lean Combustion
This work reports on an experimental and modeling study on the low-temperature heat release (LTHR) characteristics for three RON 90 binary blends (n-heptane blended with isooctane, toluene and ethanol) in a Cooperative Fuel Research (CFR) engine at lean and stoichiometric conditions that are representative of homogeneous charge compression ignition (HCCI) and spark-ignition (SI) end-gas combustion conditions, respectively. An analysis of the end-gas temperature-pressure (T-P) trajectories was performed to identify the intake conditions leading to similar T-P trajectories between the two lambdas for each fuel blend. A heat release analysis was then conducted for the identified cases, where fuel-to-fuel differences in LTHR were identified and found to be sensitive to the operating condition. Simulations were conducted for these cases using a recently updated chemical kinetic model and a 0-D engine model, where good qualitative and reasonable quantitative agreements in LTHR were obtained. Sensitivity analysis was also performed directly on the rates of LTHR, to understand the controlling chemical reactions of LTHR, providing further insights into the fuel-to-fuel differences. The results demonstrate the significant promoting effect of n-heptane on LTHR rates, while inhibiting effects were seen for ethanol and toluene. Also highlighted was the importance of H atom abstraction reactions from the chemistry of each fuel component, which could lead to contradictory fuel behavior depending on the locations of the H site of the abstraction reaction due to the different ensuing pathways for the primary fuel radicals.
LTHR, RON 90 binary blends, sensitivity analysis↗
Velocity-space signatures of shock-drift acceleration at quasi-perpendicular collisionless shocks
The shock-drift acceleration of ions at quasi-perpendicular shocks is a well-known kinetic mechanism for the acceleration of a small fraction of incoming ions to high energy. Here, we use a suite of sixteen hybrid simulations of quasi-perpendicular collisionless shocks over the range of Alfvén Mach number 4.3 ≤ M A ≤ 15.8 (corresponding to a range of fast magnetosonic Mach numbers 2.6 ≤ M f ≤ 9.4) and shock-normal angle 45°≤ θ Bn ≤ 90° to identify the velocity-space signature of shock-drift acceleration using the field-particle correlation technique. We show that the features of the ion velocity distribution in the shock foot and ramp regions can be clearly interpreted by analysis of the single-particle trajectory of a reflected ion through the full 3D-3V phase space. The characteristic features of the velocity-space signature of shock-drift acceleration remain qualitatively robust over the full parameter range of our simulations, providing a potential means for its identification using single-point spacecraft measurements. At higher Alfvén Mach numbers M A ≳8 (M f ≳5), kinetic instabilities generate fluctuations of the electromagnetic fields within the shock transition region, leading to fluctuations in and smearing out of the resulting velocity-space signatures, but the signature remains generally robust and identifiable. The results on the shock-drift acceleration of ions presented here represent a novel means to determine more completely the partitioning of upstream bulk flow kinetic energy into plasma heating, particle acceleration, and electromagnetic fields in collisionless shocks.
Howes, Gregory G. [Univ. of Iowa, Iowa City, IA (U↗