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DOE OSTI2022

Observations of twinning microstructure in iron ramp-compressed through the α – ε phase transition

Single crystal iron was ramp-compressed along the [100] axis at 4 GPa/ns through the α–ϵ phase transformation at 13 GPa. Unlike shock experiments, in these ramp compression experiments the bcc lattice is observed to be nearly isotropically relaxed before the phase transition. There was a mixed α/ϵ phase region starting at ~13 GPa which was observed for 0.75 ns until the peak stress of 18 GPa was reached. In situ x-ray diffraction measurements show the formation of new hcp orientations not reported in shock or quasistatic compression experiments. The new hcp orientations appear to be caused by {10¯11} <10¯1 ¯2> → {¯1011} <¯101¯2> sequential twins that occur during the phase transition. This twinning mechanism relieves the shear strain caused by the bcc-hcp phase transition from the isotropically relaxed bcc phase while subject to uniaxial compression. Furthermore, these results show that in iron the induced microstructure through a phase transition and the phase transition mechanism depend on the loading history.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Squeezed light quantum imaging - experiment

This year, we focused on completing the light squeezing and building the imaging station. In this report, we present a detailed description of a quantum imaging experiment utilizing squeezed light. The entire experimental setup has two parts, namely, the squeezing station where we produce quantum-noise squeezed light where a light quadrature (either the amplitude of the phase) has reduced quantum error below the shot noise of coherent light, and the imaging station where the squeezed light is used to image an object. The squeezing station consists of an optical parametric oscillator operating below the laser threshold. We provide the status quo and the plans for the squeezing imaging experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

The scientific case for concurrent neutron and X-ray scattering and spectroscopy

The interrogation of materials with X-rays or neutrons to determine structure, energetics, and dynamics is fundamental to advancing physical and chemical materials science and enabling innovative material technologies. A persistent challenge in materials development is that progress depends on understanding structure and dynamics across multiple length and time scales in increasingly complex, multicomponent systems featuring interfaces, heterogeneity, and hierarchical organization. Despite rapidly growing demands on materials characterization, current experimental approaches are almost exclusively based on isolated X-ray or neutron scattering and spectroscopy, reflecting a paradigm largely unchanged for decades. To assess the scientific need for a new experimental paradigm, a 3-day workshop sponsored by the U.S. National Science Foundation (NSF) was held at the SpringHill Suites, San Jose, California, from June 2 to 4, 2022. The workshop brought together 70 national and international experts who critically evaluated opportunities enabled by concurrent neutron and X-ray (NeX) scattering, spectroscopy, and imaging experiments. The participants reached a clear consensus that establishing NeX capabilities is crucial for advancing the science of complex materials in the United States. This report illustrates the scientific drivers for NeX experiments through representative examples spanning biomaterials, energy materials, soft matter, nanomaterials, quantum materials, geoscience, and applied materials research. The complementarity of neutrons and X-rays is essential for robust model development and refinement, particularly in multiphase and multicomponent systems. While joint refinement of data from separate experiments is valuable, concurrent measurements uniquely eliminate uncertainties arising from sample evolution, environmental drift, and irreproducibility associated with experiments performed at different locations and times. Realizing NeX capabilities will require the development of new instrumentation, data analysis frameworks, and robust sample environments compatible with both neutron and X-ray probes. Addressing these challenges will enable unambiguous interpretation of complex materials behavior and open new frontiers in materials research.

X-ray↗

DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Solar PV

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) research platform. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence data centers and other variable loads. This dataset entry describes the behavior of a 1.25-MW proton exchange membrane MC250 electrolyzer system, manufactured by Nel Hydrogen , [1] when fed historical data generated by the 430-kW, fixed-axis solar photovoltaic (PV) array located at NLR’s Flatirons Campus. (While the electrolyzer balance of plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.) Solar PV power output data for the 2020 calendar year were categorized on a daily basis by total energy generation and standard deviation. Each day was then ranked by these metrics, and the 25th, 50th, and 100th percentiles were selected. The 75th percentile day did not exhibit sufficient variability to make for a valuable experiment. A similar process was used for the related historical wind dataset . [2] The historical days in 2020 that represented these percentiles are Dec. 19, March 29, and May 4, respectively. The entire solar day’s power profile was then fed through the MC250 electrolyzer. Due to its length, the 100th percentile day experiment was split into two parts, and the final 3 hours of the solar day were not captured. These final 3 hours contained no spikes or dips of interest and simply represented a slow decay of input solar power. Also, a single timestamp (13:13:47 on Jan. 14, 2026) was lost in the hydrogen system supervisory control and data acquisition. Finally, during the 25th percentile experiment (solar day Dec. 19, 2020) data recording was lost from 11:00:13 to 11:14:45. The roughly 15 minutes of the solar profile were rerun at the end of the experiment and spliced into this time slot during post-processing. The electrolysis system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operation of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical solar profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. For more details on the statistical analysis process, see the slide deck “Public Reference Data for Megawatt-Scale Hydrogen Electrolysis: NLR Historical Solar PV Analysis and Profile Generation” accessible with this data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single solar PV electrolysis experiment and is formatted as: {technology}_{percentile}_{scaling factor} For instance, “solarPV-430kW_25_2x.zip” reports the experiment using the 25th percentile solar data from the historical 2020 solar PV dataset, scaled to 200%. Scaling factors were applied to the generated solar PV power output files to more closely match the 1.25-MW capacity of the electrolyzer. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and solar power input. A PDF file detailing the historical solar data statistical analysis used to generate the solar profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all experiments combined into one dataset labeled "combined_solarPV_experiments.csv". [1] nelhydrogen.com/product/mc-series-electrolyser . [2] data.nlr.gov/submissions/316 .

08 HYDROGEN↗

DOE OSTI2024

Modeling delayed thermal runaway in nitric acid-soaked cat litter mixed with radioactive waste

Thermal ignition of radioactive waste within a 55-gallon drum was simulated by using a pressure-dependent waste decomposition model (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) calibrated with data from full-scale drum experiments (Parker et al. in The thermolytic response of a surrogate RNS waste mixture at the drum scale. Los Alamos National Laboratory Report LA-UR-16-21760, 2016) and validated with experiments from multiple laboratories (Hobbs et al. in Thermal analysis of aged nitric acid-soaked kitty litter in TRU waste drums-23370.WM2023 Conference, Phoenix, AZ, 2023). The acceleration of nitric acid chemistry reacting with an organic cat litter leading to thermal ignition was likely triggered by a restricted vent in the drum. Here, we address whether the form of the rate equation in (Hobbs et al. in Process Saf Environ Prot https://doi.org/10.1016/j.psep.2022.09.047, 2022) is sufficient to extrapolate thermal ignition within aged drums of similar content that have been stored in Texas for over nine years by investigating four different reaction rate forms for waste decomposition. A critical reaction rate reduction analysis is performed on each of these models to determine if delayed thermal runaway within vented aged waste is possible after nine years. We found that a pressure-dependent first-order rate expression not only predicted the accidental ignition of the waste drum, but the form also matches multiple experiments from different laboratories. Even though the waste composition decreases over time, the model predicts that acceleration leading to thermal runaway is possible if the waste is confined, even after 9 years. In conclusion, waste containing oxidizers such as nitric acid should not be mixed with organic adsorbents, especially if the waste is confined.

cookoff↗

DOE OSTI2020

Flexible Nuclear Energy for Clean Energy Systems

As part of the Nuclear Innovation: Clean Energy Future initiative, this report describes flexibility in nuclear systems, the value it can bring, and international experiences surrounding flexible nuclear energy. Flexible nuclear energy for this report is defined as “The ability of nuclear energy generation to economically provide energy services at the time and location they are needed by end-users. These energy services can include both electric and non-electric applications utilizing both traditional nuclear power plants and advanced integrated systems.” Flexibility in nuclear systems is enabled by three main mechanisms: core ramping, integrated energy systems with multiple byproducts, and thermal storage. The value of this flexibility on a $\$$/MW and a $\$$/MWh basis can be estimated through a combination of physics and economics modeling. International agencies describe their experiences in operating flexible nuclear systems and describe their plans for increasing nuclear flexibility in a clean energy system, likely with a high penetration of variable renewable energy.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Demonstration of Intelligent HVAC Load Management With Deep Reinforcement Learning: Real-World Experience of Machine Learning in Demand Control

We report that buildings account for 40% of total primary energy consumption and 30% of all CO 2 emissions worldwide. A large portion of building energy consumption is due to heating, ventilation, and air-conditioning (HVAC) systems. In the summer, for example, more than 50% of a building’s electricity consumption is used for cooling. With proper energy management, buildings can provide load shifting, peak shaving, frequency regulation, and many other demand response services.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

New Physics in the Hot Electron Furnace (Final Report)

The primary purpose of this award was experiments and simulations related to the idea of a ‘Hot Electron Furnace’ where nonlocal heat transport would allow unique new experimental opportunities at x-ray free electron lasers. The period of this award included beamtime at the MEC endstation of the LCLS, and the execution of those experiments was a primary goal. Unfortunately, the beamtime had limited success due to (1) inability of the LCLS to deliver the expected two-color operations mode, and (2) failure of the MEC endstation’s own software to save the cavity timing data that would have allowed inference of time delays for the few hours when two-color mode briefly operated. The beamtime was then switched to operate in single-color (one pulse) mode, and studies were performed of x-ray heating and probe, simultaneously. Two interesting manuscripts are finally near submission, having been delayed by student graduations, need for collaborator simulations of x-ray heating processes, and then COVID. I am hopeful that they will soon be submitted (especially the paper on x-ray heating of MgO) because one of the principal students involved has returned from industry to take a postdoc position at SLAC. Below, we first list all publications and other work products (including the two that are nearing submission) and then summarize several outcomes from this effort. During the term of this award three UW physics graduate students were at least partially supported, and all three received their Ph.D.’s with significant components of their supported work in the dissertation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Development of High-Performance Ni-base Alloys for Gas Turbine Wheels Using a Coprecipitation Approach (Final Technical Report)

In this project, a synergistic approach involving experiments informed by modelling was used to develop γ'/γ'' coprecipitation-strengthened Ni-base superalloys for land-based gas turbine wheels. In thick sections of such turbine wheels, the slow cooling rate normally observed, as well as variations in cooling rate could potentially result in drastically inhomogeneous and coarsened microstructure. Thus, ten alloy compositions were selected based on coprecipitation and sluggish γ’ growth and coarsening during three iterations of alloy development, assisted by extensive CALPHAD modeling. Phase equilibrium calculations, informed by the characterization of early alloys, were successful in predicting suitable aging treatments to obtain bimodal coprecipitate distribution in several alloys. These aging treatments were applied to the subsequent round of alloys and the resulting microstructures were characterized in detail. Two different cooling rates were used during each of these heat treatments to simulate the range of cooling rates observed in a thick section forging. The microstructures were used to calibrate a multi-phase field model (MPF), which was used to study the formation mechanisms of various coprecipitate morphologies observed in the experiments. Following this, the most promising alloys in each round were selected and studied using high temperature tensile and creep tests. Considering that a slower cooling rate would lead to a strength debit, while a faster cooling rate might lead to a decline in creep rupture life of a full-scale wheel, tensile tests were carried out for slower cooled samples, while creep tests were carried out for faster cooled samples. The deformation microstructures were then characterized using advanced characterization techniques such as Diffraction Contrast-Scanning Transmission Electron Microscopy (DC-STEM) and Electron Channeling Contrast Imaging (ECCI). Further, a mean-field creep model was developed and calibrated using these experimental findings to predict long-term creep behavior of these coprecipitation-strengthened alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2023

THOR-aLEU Report

The advanced low enriched uranium (aLEU)-THOR experiment vehicle is designed to irradiate fresh fuel rodlet specimens containing UO 2 (uranium dioxide) in the Temperature Heat-sink Overpower Response (THOR) capsule. The goal of the experiments are to compare the behaviors of standard UO 2 pellets to an aLEU concept in which molybdenum (Mo) foils separate UO 2 wafers increasing the thermal conductivity of the fuel. This experiment is designed to be conducted in the Transient Reactor Test facility (TREAT) using the Minimal Activation Retrievable Capsule Holder (MARCH) irradiation system. The goal of these experiments is to assess the effect of thermally conductive inserts in UO 2 by measuring their net effect on radial thermal conductivity using transient nuclear heating and then to determine their power-to-melt threshold in transient overpower ramps. The objective of the aLEU-THOR fuels experiment is to determine the viability and study the performance of UO 2 fuel pellets employing newly upgraded TREAT capability. A novel transient measurement technique will be used with the THOR capsule, which has a solid heat sink to generate the transient temperature gradient for conductivity measurement.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

AWAKEN Dual-Doppler Lidar (ADDLidar) Field Campaign Report

The AWAKEN Dual-Doppler Lidar (ADDLidar) experiment was conducted as part of the larger AWAKEN field campaign (https://www.nrel.gov/wind/awaken.html). The American Wake Experiment (AWAKEN) is an international, multi-institutional wind energy field campaign that was conducted from May 2022 to 2024, in the vicinity of the King Plains wind farm in north central Oklahoma. The goal of AWAKEN was to provide observations to better understand interactions between wind turbines in a wind farm and the interactions between the wind farm as a whole and the atmosphere. The focus of the ADDLidar campaign was to provide height-resolved measurements of wind speed and direction at key locations upwind of the wind farm to characterize the inflow and possible blockage effects upwind of the farm. Specifically, dual-Doppler scanning methods were employed to create a number of so-called virtual towers (Calhoun et al 2006, Debnath et al. 2017, Fernando et al. 2019, Hill et al. 2010, Newman et al. 2016, Newsom et al. 2008, 2015) upwind of the farm. The ADDLidar campaign involved the deployment of two U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility scanning Doppler lidars (S/N 236 and 237) to AWAKEN sites A4 (36.361894°, -97.356352°) and A7 (36.347259°, -97.389968°). Both sites are located approximately 29 km south of the ARM Southern Great Plains (SGP) observatory C1 site, as shown in Figure 1. These sites were chosen for their close proximity to the most southerly row of turbines in the King Plains wind farm.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

AWAKEN Dual-Doppler Lidar (ADDLidar) Field Campaign Report

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Curifactory: A research experiment manager

Curifactory is a command line tool and framework for organizing Python experiment code, configuration parameters, and results. It is an opinionated and lightweight approach to workflow management infrastructure and is primarily intended to support researchers conducting experiments on one machine. This software was developed to support the reproducibility of results for several data science projects in the Nuclear Nonproliferation Division at Oak Ridge National Laboratory. Curifactory is intended to be a general framework and is not specific to machine learning or data science. It can aid in any field in which experiments are primarily computation-based studies and can be implemented in Python (e.g., high-energy physics, astronomy, computational chemistry). Here, the design emphasizes the automated caching of intermediate data analysis artifacts to speed up development involving computationally intensive tasks. It also allows for data provenance and experiment reproduction. Individual experiment runs are tracked through logs and their output reports, and entire copies of a run with all cached data and metadata can be exported for others to run using Curifactory on another machine. Curifactory experiments can either be integrated into a project from the beginning or can be written on top of an existing codebase without needing significant modification. A few important views of the Curifactory library can be seen in Figure 1.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Improving the stability and performance of MagLIF implosions by applying dielectric coatings and increasing applied B z , fuel preheat, and load current

We report two magnetized liner inertial fusion (MagLIF) experiments that produced record thermonuclear D–D neutron yields of 2.11×10 13 and 2.33×10 13 . These yields are about a factor of two higher than previous MagLIF results. The experiments achieved ion temperatures of 3.0 and 3.3 keV and stagnation pressures of 1.6 and 1.3 Gbar. The inferred Lawson parameters were χ=0.2 and 0.1, which are the largest reported for MagLIF. The performance increase used a high-aspect-ratio beryllium liner with a dielectric coating and modest increases in preheat energy (∼2.2 kJ), peak current (18.5 MA), and axial magnetic field (15 T). Three-dimensional HYDRA simulations are consistent with the measured liner dynamics and fusion outputs. These results indicate a pathway to higher-yield MagLIF designs using coated, high-aspect-ratio liners and improved input parameters. Simulations further suggest that adding an ice fuel layer could increase yield by up to a factor of 2.5 by reducing liner convergence, instability feedthrough, and mix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Final Design for Thermal/Epithermal eXperiments (TEX) with Chloride Absorbers to Provide Validation Benchmarks for Y-12 Electrorefining Facility

Uranium electrorefining operations at Y-12 require validation for chlorine absorption and reflection. Plutonium chloride solution operations at Los Alamos National Laboratory require chlorine absorption validation. The growing need for chlorine validation is evident to the wider criticality safety community, with multiple attendees at the recent TEX 2.0 meeting at Lawrence Livermore National Laboratory (May 2023) requesting validation for chlorine (Idaho National Laboratory (INL), Institute de radioprotection et de surete nucleaire (IRSN), Savannah River Nuclear Site (SRNS), LANL, and Y-12). Los Alamos National Laboratory has recently performed, and benchmarked, an experiment titled Chlorine Worth Study (CWS) for the internal operations at the lab, but due to the difficulties in precisely characterizing the material compositions of the chlorine absorbers it is advantageous to perform a complimentary study with a different chlorine-based absorber material. Furthermore, having a uranium-based vs plutonium-based experiment provides a separate and important validation basis for criticality safety and nuclear data evaluation. The original final design report for the study of chlorine absorption using the TEX-HEU experimental base was presented in 2022, but used the same chlorine-bearing materials that were found to be difficult to characterize in the LANL benchmark. A complete redesign of the experiment has been performed looking at alternative absorber materials in various forms to produce an experiment that is fully characterizable. This report presents five novel chlorine experiments using the TEX-HEU test bed which provides direct comparison to the Y-12 and INL/Terrapower application needs, utilizing sodium chloride (NaCl) absorber plates. The absorber plates will consist of granulated NaCl (≥99.5% pure), which will be fully encapsulated in aluminum tins, providing a simple but effective chlorine-based absorber material that can be completely characterized. Of the five configurations presented in this report, it is expected that two or three configurations will be down selected for the actual experiment, with the other configurations being alternates. Three of the configurations are in the standard configuration, where the absorber is placed directly on the HEU fuel plates, and two in the sandwich configuration, where the absorber is surrounded by polyethylene moderators to force additional neutron thermalization prior to reaching the absorber. There are two thicknesses of NaCl absorber plates: 3/16” and 1/4” active thicknesses (i.e. not including the encapsulation). Both variations of the absorbers have an active absorber radius of 6” and a total radius of 7.5” to match the diameter of the HEU plates, with the outer 1.5” being aluminum encapsulation. The high-density polyethylene (HDPE) moderators are of the thicknesses: 27/16”, 7/4”, 1/8”, 11/16”, and 3/4”. The final configurations have six (one sandwich and one standard configuration), eight (one sandwich and one standard configuration), and 18 total fuel layers (standard configuration). The standard and sandwich configurations were designed such that the differences in moderator thicknesses are 1” HDPE, which were already procured for the original CED-2. The proposed configurations were precisely tuned to closely match the sensitivity profiles and neutron spectra of the Y-12 upset cases and were also compared to the INL/Terrapower upset cases. The assessment of experimental uncertainties of the non-absorber components was predicted to be 0.00114 Δk eff . The assessment of uncertainties resulting from the absorbers was predicted to be 0.00029 Δk eff . This results in a total uncertainty of 0.00118 Δk eff . Many of the largest uncertainties, namely the moderator densities, may be reduced with precision dimensional inspection of the components. The 1” HDPE moderators as well as the HDPE reflectors from the original CED-2 were incorporated in the final designs presented here. Additional HDPE moderator plates must be fabricated to complete the configurations. NaCl absorber plates will by fabricated at LLNL. The total additional cost is expected to be $\$$54,250 for the remaining components. Precise inspection, including dimensional, mass, density, and impurity, is recommended for all components. LLNL estimates that these costs are around $\$$12,000. It is expected, based on previous TEX-HEU experiments, that three weeks of experimental facility time is needed to complete the experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Lessons Learned from Ecosystem-Scale Experimental Field Studies (Workshop Report)

Efforts to understand and predict ecosystem responses to environmental change require long-term, large-scale, spatially representative experiments and observations that capture natural variability, test predictive models, and generate transferable knowledge. Such studies are indispensable for unraveling the complexities of terrestrial ecosystems and their responses to disturbances and evolving environmental conditions, while generating the data necessary for developing mechanistic models and predictive tools that inform decision-making processes. Having a rich history of designing and executing large-scale ecosystem experiments, the U.S. Department of Energy’s Environmental System Science program convened a workshop in January 2025 that brought together leaders in the field to distill critical lessons from decades of experience in large-scale experiments. The workshop aimed to (1) provide an ecosystem experiment primer for best practices, thus ensuring a high scientific return on investment for funding agencies, and (2) offer a robust framework for the design and management of future research initiatives. This report synthesizes insights and experiences from workshop participants and is structured to capture the entire research life cycle, from goal setting and design to operations, adaptive management, team dynamics, collaborations, and the often overlooked aspect of decommissioning. By synthesizing decision-making and lessons learned across diverse research approaches, the report aims to provide a template of essential factors to consider when designing successful long-term, large-scale ecosystem experiments.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

A Review of the Customer Experience at Public Charging Stations and its Effects on Electric Vehicle Purchase and Use

The electric vehicle (EV) market in the U.S. has grown rapidly. However, poor public charging reliability could challenge achieving widespread adoption. We reviewed peer-reviewed articles and market research reports to understand how the public charging experience affects the willingness to purchase EVs among first-time buyers and current owners. Ample literature identifies the measures of the public charging experiences, characterizes the current public charging experience, and identifies the effect of infrastructure availability on EV purchase decisions. However, there is no causal evidence linking the customer experience at public chargers to purchase decisions or intentions for current EV owners or prospective buyers.

33 ADVANCED PROPULSION SYSTEMS↗