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DOE OSTI2020

Direct Visualization of Electric-Field-Induced Structural Dynamics in Monolayer Transition Metal Dichalcogenides

Layered transition metal dichalcogenides offer many attractive features for next-generation low-dimensional device geometries. Due to the practical and fabrication challenges related to in situ methods, the atomistic dynamics that give rise to realizable macroscopic device properties are often unclear. Here in this study, in situ transmission electron microscopy techniques are utilized in order to understand the structural dynamics at play, especially at interfaces and defects, in the prototypical film of monolayer MoS 2 under electrical bias. Through our sample fabrication process, we clearly identify the presence of mass transport in the presence of a lateral electric field. In particular, we observe that the voids present at grain boundaries combine to induce structural deformation. The electric field mediates a net vacancy flux from the grain boundary interior to the exposed surface edge sites that leaves molybdenum clusters in its wake. Following the initial biasing cycles, however, the mass flow is largely diminished and the resultant structure remains stable over repeated biasing. We believe insights from this work can help explain observations of nonuniform heating and preferential oxidation at grain boundary sites in these materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Strym: A Python Package for Real-time CAN Data Logging, Analysis and Visualization to Work with USB-CAN Interface

In this report, we describe a data analysis tool developed for decoding and analyzing vehicle data obtained from a passenger vehicle’s onboard controller area network (CAN) bus. The tool developed in this paper provides a timeseries framework to perform domain-specific analysis at scale when interpreting data from a vehicle or a collection of vehicles in light of how to design intelligent vehicle applications. The tool, called Strym, exploits the CAN bus mechanism of modern vehicles to capture data using commercially available CAN-to-USB hardware Comma.ai Panda devices, managed through open-source software Libpanda. Strym permits the decoding of vendor-specific CAN messages in a vehicle-agnostic manner. Through this, a researcher can characterize data throughput, assess data quality, and perform analyses. Such analyses are useful in a number of research such as studying human driving behavior in mixed-autonomy, new driver models, rare-event detection, traffic flow estimation, and custom control of vehicles.

Performance evaluation, Smart cities, Intelligent ↗

DOE OSTI2021

Flow boiling in geometrically modified microchannels

Microchannels are a promising solution for high-heat-flux thermal management scenarios, including high-performance microelectronics cooling and power electronics cooling. However, thermohydraulic instabilities result from the rapid vapor bubble formation. The prior literature has examined several methods, including constricted inlet microchannels, expanding microchannels, and auxiliary jetting microchannels, to mitigate the effect of these instabilities. Computational fluid dynamics and heat transfer (CFD/HT) modeling of the flow boiling phenomena in these microchannel configurations has seen limited examination, and one-to-one numerical comparisons of the different mitigation strategies have not been performed. In the present investigation, CFD/HT analyses using a three-dimensional (3D) volume of fluid model coupled with a phase-change model for the interfacial heat and mass transfer were performed for multiple microchannel configurations (constricted inlet, expanding, and auxiliary jetting microchannels). A benchmark case of a rectangular microchannel was examined to quantify baseline thermohydraulic performance. Results demonstrated slight to significant thermal performance improvements for all cases, and significant pressure benefits for the expanding and jetting cases, consistent with experimental results in the literature. Bubble dynamics and visualization for the baseline and alternative configurations are provided to give insight into their underlying physics, and the differences in performance were investigated and compared with available literature.

Broughton, Justin (ORCID:000000026848457X)↗

DOE OSTI2025

Ultralow-temperature cryogenic transmission electron microscopy using a new helium flow cryostat stage

Advances in cryogenic electron microscopy have opened new avenues for probing quantum phenomena in correlated materials. This study reports the installation and performance of a new side-entry condenZero cryogenic cooling system for JEOL (Scanning) Transmission Electron Microscopes (S/TEM), utilizing compressed liquid helium (LHe) and designed for imaging and spectroscopy at ultra-low temperatures. The system includes an external dewar mounted on a vibration-damping stage and a pressurized, low-noise helium transfer line with a remotely controllable needle valve, ensuring stable and efficient LHe flow with minimal thermal and mechanical noise. Performance evaluation demonstrates a stable base temperature of 4.37 K measured using a Cernox bare chip sensor on the holder with temperature fluctuations within ±0.004 K. Complementary in-situ electron energy-loss spectroscopy (EELS) via aluminum bulk plasmon analysis was used to measure the local specimen temperature and validate cryogenic operation during experiments. The integration of cryogenic cooling with other microscopy techniques, including electron diffraction and Lorentz TEM, was demonstrated by resolving charge density wave (CDW) transitions in NbSe2 using electron diffraction, and imaging nanometric magnetic skyrmions in MnSi via Lorentz TEM. In conclusion, this platform provides reliable cryogenic operation below 7 K, establishing a low-drift route for direct visualization of electronic and magnetic phase transformations in quantum materials.

Charge density wave↗

DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Pre-Transient Characterization of Historic EBR-II Pins for Transient Testing

Current interest in sodium-cooled fast reactor (SFR) designs, such as TerraPower’s Natrium Reactor, has highlighted the need for advanced reactor fuel technology development. Modern U-Zr and U- Pu-Zr pin designs are primary candidates to fuel SFRs and boast high fuel utilization capacity, increased fuel-cladding compatibility, and improved safety through inherent feedback mechanisms. Despite over 60 years of metallic fuel irradiation, uncertainties exist in the performance of the fuel system, particularly under transient overpower (TOP) and loss of flow (LOF) scenarios. Throughout historical testing within the Experimental Breeder Reactor II (EBR-II) and the Fast Flux Test Facility (FFTF), fuel behavior has demonstrated benign response to transient reactor conditions; however, accurate predictions of failure thresholds to inform operational limitations rely heavily on fuel composition, burnup, and irradiation history. In expanding TOP and LOF testing, the Transient Heat sink Overpower Response (THOR) Capsule will be used to test modern fuel technologies in a static sodium environment in the Transient Reactor Test (TREAT) Facility. The THOR capsule is highly instrumented and will provide time-dependent thermal behavior of SFR fuel pins subjected to accident conditions within TREAT. The THOR-Metallic (THOR- M) campaign aims to validate and expand historical TOP and LOF testing on high burnup U-Zr and U-Pu- Zr fuel alloys previously irradiated in EBR-II by running the rods to failure. This contribution focuses primarily on the pre-transient engineering-scale destructive and non- destructive characterization that has been conducted on both the test and sibling pins used for the TOP and LOF tests. All pins underwent visual examination, neutron radiography, element contact profilometry, and precise gamma scan. The sibling pins used for each test were further analyzed using gas assay, sampling, and recharge analysis (GASR), and optical microscopy. The results from each technique confirmed that the fuel pins were intact and devoid of any atypical developments when compared to historical data. Additionally, the analyzed measurements establish a baseline for comparison to post-transient analysis. Key fuel behaviors quanitifed include axial elongation of the fuel column, diametral strain of the pin, patterns in fluff structure geometry, changes in axial isotope distribution, evolution of constituent redistribution, porosity, and fission gas release. The pre-transient measurements and changes attributed to transient behavior from post-transient measurement will be compared to historical data to capture the behavioral dependence on composition, burnup, and irradiation history. Results from this work advance the initiatives of the THOR-M campaign, which aid in informing fuel performance models and establishing safety criteria for SFR operational limits. The novel combination of test environment, in-situ instrumentation, and comprehensive suite of characterization methods provides greater understanding of transient fuel behavior. Overall, information on the time and condition of pin failure for high burnup U-Pu-Zr will greatly expand the limited existing TOP and LOF test data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Pre-Transient Characterization of Historic EBR-II Pins for Transient Testing

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Assessment of an E10 gasoline surrogate: Qualitative and quantitative comparisons of in-cylinder spray morphology

A minimum-component gasoline fuel surrogate that captures both chemical and physical behaviors of a full-distillate fuel is needed for high-fidelity CFD simulations. This study evaluates gasoline spray characteristics in a direct-injection spark-ignition engine under motored operation. Two fuels are compared; PACE-20, which is a 9-component surrogate formulation of RD5-87, is compared with its target fuel RD5-87, which is a full-boiling range research grade E10 gasoline. The spray morphologies of both fuels are recorded for a centrally-located direct-injection 8-hole spray subject to intake air cross-flow during the early part of the intake stroke. High-speed imaging recorded scattered light of the side and axial projections of the liquid spray. Quantitative metrics were developed and employed to facilitate comparison of spray morphologies as well as to identify the transition in spray morphology due to flash boiling. This paper builds on a previous study of RD5-87 where coolant temperature (20°C–100°C), in-cylinder pressure (40–110 kPa), engine speed (650–1950 rpm), and injection pressure (60–180 bar) were systematically changed to span operating conditions with and without flash boiling. Images of the PACE-20 morphology are selected for a sub-set of operating conditions from the previous study where distinctive morphology changes occurred. Visual inspection of the images and quantitative metrics demonstrate that the PACE-20 spray morphology is equivalent to that of the RD5-87 in most cases. The exception was for changes in the ambient-gas pressure where the flash-boiling transition occurred at ∼5 kPa higher in-cylinder pressure for PACE-20. Three empirical metrics, Merging Index, Asymmetry, and Flash Index are proposed here and they were found to be useful both as quantitative comparisons of the fuel morphologies, and for identifying the transition in spray morphology due to flash boiling.

Kim, Namho↗

DOE OSTI2024

Solution-phase sample-averaged single-particle spectroscopy of quantum emitters with femtosecond resolution

Here, the development of many optical quantum technologies depends on the availability of solid-state single quantum emitters with near-perfect optical coherence. However, a standing issue that limits systematic improvement is the significant sample heterogeneity and lack of mechanistic understanding of microscopic energy flow at the single emitter level and ultrafast timescales. Here we develop solution-phase single-particle pump-probe spectroscopy with photon correlation detection that captures sample-averaged dynamics in single molecules and/or defect states with unprecedented clarity at femtosecond resolution. We apply this technique to single quantum emitters in two-dimensional hexagonal boron nitride, which suffers from significant heterogeneity and low quantum efficiency. From millisecond to nanosecond timescales, the translation diffusion, metastable-state-related bunching shoulders, rotational dynamics, and antibunching features are disentangled by their distinct photon-correlation timescales, which collectively quantify the normalized two-photon emission quantum yield. Leveraging its femtosecond resolution, spectral selectivity and ultralow noise (two orders of magnitude improvement over solid-state methods), we visualize electron-phonon coupling in the time domain at the single defect level, and discover the acceleration of polaronic formation driven by multi-electron excitation. Corroborated with results from a theoretical polaron model, we show how this translates to sample-averaged photon fidelity characterization of cascaded emission efficiency and optical decoherence time. Our work provides a framework for ultrafast spectroscopy in single emitters, molecules, or defects prone to photoluminescence intermittency and heterogeneity, opening new avenues of extreme-scale characterization and synthetic improvements for quantum information applications.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Uncertainty quantification of fireball features extracted from nuclear test films using computer vision

Films from the US’s historic nuclear testing era comprise the only extensive collection of imagery depicting high-yield detonations. These films offer unique insights into the characteristics of flows occurring on scales that are difficult to replicate experimentally, and they are a valuable source of data for the validation of models used to describe nuclear detonations. In recent work, we implemented modern computer vision and machine learning techniques to extract features of the fireball following nuclear detonation. With a training dataset of fireball films, we fine-tuned a You Only Look Once 11 (YOLO11) model to detect and track the fireball. Applied to a video, the outer bounding box produced in each frame by YOLO11 is used as an input prompt to Meta’s Segment Anything Model 2 (SAM2), which is shown to accurately predict the boundary of the fireball over time with high resolution. These state-of-the-art computer vision foundation models exhibit impressive visual accuracy in their results but lack an output of values that robustly quantify uncertainty in scientific applications. In this paper, we develop procedures for uncertainty quantification of extracted fireball features. We outline the application of a parallel attention mechanism to calculate uncertainty ranges that complement and better pose model validation data. This higher quality fireball validation data may serve to improve prognostic models describing nuclear detonations in support of nuclear forensic and emergency response activities.

Khristy, Joel [ORNL] (ORCID:0000000209963060)↗

DOE OSTI2022

Visualization Tool for Comparing Low-Carbon Energy Options

This project developed a web based visualization tool for comparing current and future nuclear fuel cycle options to low-carbon and conventional energy technologies in the United States. While nuclear power is well established as the gold-standard for baseload power production and also as the technology with the lowest overall carbon intensity of any commercial form of electricity generation. This project develop a web-based tool for electricity producers and consumers to compare renewable and conventional energy technologies to the conventional and advanced nuclear fuel cycle options. The work leveraged data on land use, carbon intensity, unit cost and pricing data for renewables from the open literature. Input data from the Advanced Fuel Cycle Cost Basis report will be used for current and advanced nuclear power systems. We coupled these data to energy flow and lifecycle models for user-selected energy generation and storage types. We will display economic comparisons from the perspectives of generators and consumers, as well as carbon production, land use, and reliability comparisons.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

An instrument for in situ characterization of powder spreading dynamics in powder-bed-based additive manufacturing processes

In powder-bed-based metal additive manufacturing (AM), the visualization and analysis of the powder spreading process are critical for understanding the powder spreading dynamics and mechanisms. Unfortunately, the high spreading speeds, the small size of the powder, and the opacity of the materials present a great challenge for directly observing the powder spreading behavior. In this study, we report a compact and flexible powder spreading system for in situ characterization of the dynamics of the powders during the spreading process by high-speed x-ray imaging. The system enables the tracing of individual powder movement within the narrow gap between the recoater and the substrate at variable spreading speeds from 17 to 322 mm/s. The instrument and method reported here provide a powerful tool for studying powder spreading physics in AM processes and for investigating the physics of granular material flow behavior in a confined environment.

47 OTHER INSTRUMENTATION↗

DOE OSTI2026

A framework and tool for designing cost-effective, resilient, and circular net-zero supply chains under uncertainty with an application to multilayer plastic films

While 55% of Fortune 500 companies have committed to achieving net-zero emissions and/or zero-waste operations by 2035, only 2% are currently on track, revealing a critical gap between ambition and action. Designing supply chains that reduce both emissions and waste is a complex non-intuitive, multi-objective challenge, compounded by the high costs of new technologies and the need for resilient, profitable solutions. This paper aims to address this challenge by presenting a generic framework and multi-objective optimization formulation for designing cost-effective, circular, and resilient supply chains under uncertainty, implemented through a user-friendly decision-support tool with intuitive data visualization capabilities, enabling communication of results to both technical and non-technical stakeholders. We demonstrate the application of this framework in the context of multilayer plastic films (barrier films), which are widely used in food packaging and composite materials. The model quantifies trade-offs across three objectives: minimizing global warming potential, maximizing circularity, and minimizing cost. A key contribution of this work is the explicit modeling of technological resilience, the ability of supply chains to maintain function under disruption. In the cost-minimization case, the resilience constraint makes the design approximately three times more expensive in the short-term metric, but shifts the system from relying on a single recovery pathway to a portfolio of four recovery pathways, improving the robustness of the optimization solution under uncertainty. Lastly, we introduce TranZero, a decision-support tool that integrates material flow analysis, hotspot identification, and optimization-based scenario planning to support net-zero and circularity decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Josephson detection of time-reversal symmetry broken superconductivity in SnTe nanowires

A Josephson junction (JJ) couples the supercurrent flowing between two weakly linked superconductors to the phase difference between them via a current-phase relation (CPR). While a sinusoidal CPR is expected for conventional junctions with insulating weak links, devices made from some exotic materials may give rise to unconventional CPRs and unusual Josephson effects. In this work, we present such a case: we investigate the proximity-induced superconductivity in SnTe nanowires by incorporating them as weak links in JJs and observe a deviation from the standard CPR. We report on indications of an unexpected breaking of time-reversal symmetry in these devices, detailing the unconventional characteristics that reveal this behavior. These include an asymmetric critical current in the DC Josephson effect, a prominent second harmonic in the AC Josephson effect, and a magnetic diffraction pattern with a minimum in critical current at zero magnetic field. The analysis examines how multiband effects and the experimentally visualized ferroelectric domain walls give rise to this behavior, giving insight into the Josephson effect in materials that possess ferroelectricity and/or multiband superconductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Field‐Induced Ferroelectric Phase Evolution During Polarization “Wake‐Up” in Hf 0.5 Zr 0.5 O 2 Thin Film Capacitors

Abstract As an emerging nonvolatile memory technology, HfO 2 ‐based ferroelectrics exhibit excellent compatibility with silicon CMOS process flows; however, the reliability of polarization switching in these materials remains a major challenge. During repeated field programming and erase of the polarization state of initially pristine HfO 2 ‐based ferroelectric capacitors, the magnitude of the measured polarization increases, a phenomenon known as “wake‐up”. In this study, the authors attempt to understand what causes the wake‐up effect in Hf 0.5 Zr 0.5 O 2 (HZO) capacitors using nondestructive methods that probe statistically significant sample volumes. Synchrotron X‐ray diffraction reveals a concerted shift in HZO Bragg peak position as a function of polarization switching cycle number in films prepared under conditions such that they exhibit extremely large (≈3000%) wake‐up. In contrast, a control sample with insignificant wake‐up shows no such peak shift. Capacitance – voltage measurements show evolution in the capacitance loop with switching cycle number for the wake‐up sample and no change for the control sample. Piezoresponse force microscopy measurements are utilized to visualize the domain switching with wake‐up. The combination of these observations clearly demonstrates that wake‐up is caused by a field‐driven phase transformation of the tetragonal phase to the metastable ferroelectric orthorhombic phase during polarization switching of HZO capacitors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Non-Destructive, Three-Dimensional Imaging of Processes in the Rhizosphere Utilizing High Energy Photons

Soil structure, which can be described as the aggregation and distribution of pore spaces, regulates carbon, nutrient, and water cycling across the Earth system. Yet the inability to make quantitative, dynamic, in situ measurements of soil structure and rhizosphere carbon flow has prevented meaningful incorporation of soil structural processes into Earth System Models (ESMs). The key limitations are: (i) Lack of scale integration between micron-scale soil structure and ecosystem-scale models, (ii) Poor functional linkage between soil structural properties and biogeochemical processes, and (iii) Absence of dynamic 3D measurements of rhizosphere structural changes and carbon transformations. To address these challenges, we developed a new integrated positron emission tomography (PET) - microcomputed tomography (CT) imaging platform that enables the first 4D (spatial 3D and time), non-invasive, quantitative imaging of carbon allocation and rhizosphere structural dynamics in living plants and intact soils. The system combines: • Rhizo-PET (R-PET): a high-resolution positron emission tomography scanner optimized for 11 CO 2 tracing in plant roots. • a-Se micro-CT: a high-contrast, high-spatial resolution CT system based on amorphous selenium (a-Se) direct conversion technology, enabling micron-scale visualization of soil structure and root–soil interfaces. Together, these advances allow us to quantify how carbon exudates move, transform, and stabilize within the rhizosphere, directly informing missing processes in BER-relevant carbon cycle models.

42 ENGINEERING↗

DOE OSTI2021

Faraday rotation study of plasma bubbles in GeV wakefield accelerators

We visualize plasma bubbles driven by 0.67 PW laser pulses in a plasma of density ne≈5×1017cm−3 by imaging Faraday rotation patterns imprinted on linearly polarized probe pulses of wavelength λpr=1.05 μm and duration τpr=2 or 1 ps that cross the bubble's path at right angles. When the bubble captures and accelerates tens to hundreds of pC of electron charges, we observe two parallel streaks of length cτpr straddling the drive pulse propagation axis, separated by ∼45 μm, in which probe polarization rotates by 0.3° to more than 5° in opposite directions. Accompanying simulations show that they result from Faraday rotation within portions of dense bubble side walls that are pervaded by the azimuthal magnetic field of accelerating electrons during the probe transit across the bubble. Analysis of the width of the streaks shows that quasi-monoenergetic high-energy electrons and trailing lower energy electrons inside the bubble contribute distinguishable portions of the observed signals, and relativistic flow of sheath electrons suppresses Faraday rotation from the rear of the bubble. The results demonstrate favorable scaling of Faraday rotation diagnostics to 40× lower plasma density than previously demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Data Fusion for the Development of a Multimodal Freight Transload Facilities Dataset in the U.S.

To withstand the growing demand of commodity volume and its strain on the transportation infrastructure, it is necessary to identify the flow of commodities by route and mode. However, a national multimodal freight routing model does not exist for the U.S. The development of such model requires multiple building blocks, such as virtual representations of roadway, railway, and waterway networks, transload facilities (TFs), and access/egress links. Most of these blocks have a robust database in the U.S., except for the TFs. Here, this paper presents the fusion of dispersed and heterogeneous representations of multimodal TFs into a single, comprehensive, geospatial freight TF dataset. The TF dataset is derived from several sources, including the U.S. Army Corps of Engineers Master Docks Plus, the National Transportation Atlas Database, the Intermodal Association of North America, industry publications, and other public information. First, individual datasets were queried and reconciled. A geocoding/reverse geocoding process was applied to get the best street address and latitude/longitude location for each terminal. Then, duplicate terminals were identified by a fuzzy match algorithm based on terminal name and location, and removed. Validation was performed by visual inspection of random facilities. The main contributions of this work are: a publicly available version of the TF dataset, including facility location and multimodal transfer capability of 9,003 facilities, and an enterprise-version with the same facilities but including commodity handling capabilities. The main purpose of developing the TF dataset is to inform multimodal routing algorithms. The proposed TF dataset allows for credibly modeling the multimodal transfer of commodities within shipment routes.

Commodity Routing↗