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At least 721 records · Page 40

Design of a microbunched electron cooler energy recovery linac

Microbunched electron Cooling (MBEC), a type of Coherent electron Cooling (CeC), is a possible way to cool high energy protons; such an electron cooler can be driven by an energy recovery linac (ERL). The beam parameters of this design are based on cooling 275 and 100 GeV protons at the Electron-Ion Collider (EIC), requiring 150 and 55 MeV electrons, respectively. If implemented, a high energy cooler would serve to increase the average luminosity of the collider by mitigating the emittance growth caused by various processes. This ERL is designed to deliver a bunch charge of 1 nC, an average current of 100 mA, and strict requirements on the transverse emittance, slice energy spread, and longitudinal distribution profile. This paper covers the current state of the design.

Accelerator Physics

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have created great interest in using CO 2 electrolysis to produce chemical feedstocks and fuels such as carbon monoxide, ethylene, ethanol, and propanol. While research in CO 2 electrolysis has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices, the energy efficiency (electrical energy to-product) and carbon efficiency (CO 2 -to-product) of CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal reason for these low efficiencies is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH–) to form carbonate , which forces CO 2 electrolysis cells to operate under conditions that result in large voltage and CO 2 losses. This “CO 3 2 – problem” presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Multilayer Electrodes with Metalized Polymer Current Collector for High-Energy Lithium-Ion Batteries with Extreme-Fast-Charging Capability

The pursuit of batteries capable of extreme fast charging (XFC), that also satisfy high energy and safety criteria, poses a significant challenge to current lithium-ion battery technologies. Additionally, the increasing demand for aluminum (Al) and copper (Cu) in electrification, and vehicle light weighting is driving these metals towards near-critical status in the medium term. This study introduced metalized polymer films by depositing an Al or Cu thin layer onto two sides of a polyethylene terephthalate (PET) film – named mPET/Al and mPET/Cu, as lightweight, cost-effective alternatives to traditional metal current collectors in LIBs. We have utilized current collectors that significantly reduce weight (by 73%), thickness (by 33%), and cost (by 85%) compared to traditional metal foil counterparts. We conducted an extensive evaluation of their mechanical and electrical properties, including in-plane and through-plane resistivities, affirming their suitability for the roll-to-roll battery manufacturing process. Additionally, a novel XFC testing protocol was employed to thoroughly assess the cells' (both half and full-cell) performance across various C-rates and under long-term tests. These advancements have the potential to enhance energy density to 280 Wh/kg at the electrode level under 10-minute charging at 6C. Through testing, including a novel XFC protocol across various C-rates and long-term cycling (up to 1000 cycles) in different cell configurations, we have demonstrated the superior performance of these metalized polymer films. Notably, mPET/Cu and mPET/Al foils exhibited comparable capacities to conventional cells under XFC, with the mPET cells showing a 27% improvement in energy density at 6C and maintaining significant energy density after 1000 cycles. This study underscored the potential of mPET foils to revolutionize the roll-to-roll battery manufacturing process and significantly advance the performance metrics of LIBs in EV applications. Moreover, our results suggest that there is potential to enhance the performance of mPET foils, especially mPET/Al, by optimizing the manufacturing process to achieve higher conductivity.

99 GENERAL AND MISCELLANEOUS

Using Neural Networks for Low Energy Reconstruction and Neutron Identification in the MicroBooNE LArTPC

Identifying and reconstructing final-state neutrons from neutrino interactions in Liquid Argon Time Projection Chambers (LArTPCs) will enhance future oscillation measurements by recovering missing energy and improving neutrino interaction channel identification. However, neutrons are challenging to reconstruct as the majority leave only small, isolated charge signatures known as blips. Here we present initial efforts to identify neutrons in the MicroBooNE LArTPC with low energy protons from neutron-argon inelastic interactions that present as blips below the traditional tracking threshold in the TPC. Unlike for tracks, there is no algorithmic method to determine direction for blips since they span only a few wires. Therefore, we developed and trained a Recurrent Neural Network (RNN) to reconstruct the directionality of proton-induced blips, allowing us to separate signal from background by selecting blips that point back to the neutrino vertex. The model achieves a preliminary average angular resolution of 17 degrees when tested on a simulated sample of protons over 6 MeV in kinetic energy. This novel tool will enhance neutron detection in LArTPCs and expand a broad range of other low-energy physics searches such as for solar and supernova neutrinos.

Silva, Liani Isabel [Unlisted, US]

Multi-Scale Modeling of the Evolution of Structure and Properties in Materials for Nuclear Energy Applications [Slides]

Nuclear energy is an important component of an overall strategy to address climate change. Idaho National Laboratory (INL) is the U.S. Department of Energy’s primary facility for research and development in nuclear science and technology for energy generation, supporting the improvement and life extension of the existing reactor fleet and the development and licensing of new reactor designs. Computational modeling is an important component of these activities, particularly in the area of materials for nuclear applications, where experimental data can be very challenging and expensive to acquire, and where data is especially scarce for new reactor designs. INL has used multi-scale modeling – linking atomistic, mesoscale, and engineering scales – to improve the ability to predict the performance of materials for nuclear energy applications. In this talk, I will give an overview of the approach and tools used, and several examples of application, including performance of nuclear fuels, understanding radiation-driven formation of nanoscale void and gas bubble superlattices, and powder densification through electric field assisted sintering.

22 GENERAL STUDIES OF NUCLEAR REACTORS

MetaHeuristic Feature Selection for Energy Group Optimization and Analysis

Energy discretization is a crucial component of deterministic neutron transport simulations. Metaheuristic (MH) optimizers are effective algorithms to determine group structures that maximize both solution accuracy and computational efficiency. This project establishes a framework for optimizing group structures for PARTISN simulations using the Python library MEALPY. Group structure optimization is formulated as a binary feature selection problem, and results are investigated with permutation and material importance techniques to determine physically relevant energy bounds. We conclude that MH optimizers find group structures that drastically improve flux calculations while preserving k-effective accuracy. Further, we find that individual energy bounds are not necessarily physically relevant, but rather specific energy ranges are.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS

Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)

This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.

33 ADVANCED PROPULSION SYSTEMS

Design of a Microbunched Electron Cooler Energy Recovery Linac

Microbunched electron Cooling (MBEC), a type of Coherent electron Cooling (CeC), is a possible way to cool high energy protons; such an electron cooler can be driven by an energy recovery linac (ERL). The beam parameters of this design are based on cooling 275 and 100 GeV protons at the Electron-Ion Collider (EIC), requiring 150 and 55\,MeV electrons, respectively. If implemented, a high energy cooler would serve to increase the average luminosity of the collider by mitigating the emittance growth caused by various processes. This ERL is designed to deliver a bunch charge of 1\,nC, an average current of 100\,mA, and strict requirements on the transverse emittance, slice energy spread, and longitudinal distribution profile. This paper covers the current state of the design.

Deitrick, K. [Thomas Jefferson National Accelerato

Electron Energy-Loss Spectroscopy and Differential Phase Contrast Imaging with Active Decision in Multimodal Electron Microscopy: Isotopic detection at the atomic scale

Isotopic engineering provides a powerful route to control phonon behavior in crystalline solids, enabling fundamental studies of lattice dynamics and heat transport at the atomic scale. Here, we directly visualize isotope-dependent phonon propagation in epitaxial Cr 2 O 3 using aberration-corrected scanning transmission electron microscopy (STEM) combined with monochromated, high-energy-resolution electron energy-loss spectroscopy (EELS). Guided by ab initio phonon calculations, we demonstrate that optical phonon modes above 70 meV are predominantly oxygen-derived and exhibit measurable redshifts upon substitution of natural 16 O by enriched 18 O. Spatially resolved vibrational spectrum imaging reveals isotope-enriched tracer layers within Cr 2 O 3 thin films, correlating isotope concentration with phonon intensity variations and vibrational energy shifts. At the nanometer and atomic scales, vibrational EELS mapping uncovers coherent phonon propagation across isotopic interfaces, consistent with theoretical phonon density of states and dispersion relations. These results establish vibrational EELS as a quantitative probe for isotope-dependent phonon transport in materials, opening new possibilities for studying energy dissipation and lattice dynamics.

36 MATERIALS SCIENCE

TEAMER – Field Demonstration of MarineSitu’s Marine Energy Monitoring (Abstract)

In order to effectively monitor for marine life around marine energy devices and thus minimize the risk of collision, multiple sensors working in coordination and augmented with around-the-clock automated monitoring algorithms need to be installed in challenging high-energy tidal and wave environments. Such systems are often too expensive for widespread adoption, or lack sufficient sensors or smarts to enable around-the-clock, real-time monitoring without human involvement. MarineSitu has been working to tackle this problem by developing a low-cost, combined sonar and stereo camera sensor array with connected real-time AI-based algorithms for automatically detecting marine life in these marine energy suitable environments. In this TEAMER project with Pacific Northwest National Lab (PNNL), MarineSitu will be testing this novel sensor system for the first time in the high-energy tidal channel environment at PNNL’s Marine and Coastal Research Lab. Throughout this deployment, MarineSitu will be monitoring their system and running analytics on the sensor’s data in real-time. Meanwhile, PNNL Data Scientists and Ocean Engineers, will be evaluating the system’s effectiveness and ease of use both as a tool for plug-and-play environmental monitoring and novel environmental monitoring research. In doing so, the team will improve MarineSitu’s system and software, produce insightful data products, and develop novel visualizations and AI algorithms for combining and analyzing the data produced by systems like MarineSitu’s.

16 TIDAL AND WAVE POWER

Evaluating the feasibility of tidal energy extraction at non-operational gas platforms and effects of sedimentation and sea ice in Cook Inlet (Abstract)

Littoral Power Systems (LPS) has been granted a FERC preliminary permit for the Upper Cook Inlet Tidal Energy Project in an area that includes existing non-producing natural gas platforms. LPS is working to understand the feasibility of a 2 MW tidal energy project and is considering multiple technologies, the viability of using the platforms to support deployment and operation of the technologies, as well as the environmental conditions that will interact with tidal energy devices. The proposed TEAMER work will conduct a modeling study to understand 1) current velocity and turbulence; 2) the distribution of sea ice trajectories around the platform; and 3) the likelihood of seabed erosion and deposition through an analysis of shear stress in the seabed near the platforms. The results of this work will contribute to determining the feasibility of the site for tidal energy development.

16 TIDAL AND WAVE POWER

Human Factors and Technologies Design to Improve User Acceptance of Pooled Rideshare for Increasing Transportation System Energy Efficiency

This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.

Jia, Yunyi

Quantifying Uncertainties in Earth's Energy Budget by Cloud Feedback and Ocean Heat Uptake Using E3SM-Slab Ocean Configurations

In order to improve predictive skills of Earth System Model, we need to better understand processes that control Earth's energy budget via ocean, atmosphere, and cryosphere interactions. Simulated energy budget in comprehensive Earth System Models shows a wide range, leading to large uncertainties in predicting Earth system dynamic and thermodynamic variations and associated social-economic impacts. Uncertainties in cloud feedbacks have been identified as the main cause of the large inter-model spread, but oceanic adjustments, especially those associated with ocean heat uptake (OHU) and the Atlantic Meridional Overturning Circulation (AMOC), also play an important role. In this proposed work, we focus on understanding the individual and combined roles of cloud feedbacks and ocean adjustments on modulating Earth's energy balance. This research is motivated by our overarching hypothesis that oceanic adjustment is a key source of uncertainty, in addition to those associated with the cloud feedbacks; further, the ocean adjustment and associated OHU work through the cloud feedbacks to modulate Earth's energy budget and temperature variations. We test this hypothesis using numerical experiments where we systematically enable and disable cloud feedbacks in conjunction with perturbations to OHU.

58 GEOSCIENCES

Selection Effect in Dark Energy Survey Y1

The discovery that the Universe expansion is accelerated poses one of the most profound mysteries in physics. Cosmic acceleration could be a sign of the fact that General Relativity breaks down on cosmological scales and has to be replaced, or it could arise from an unknown form of energy that currently dominates our Universe. That is what we call dark energy and in this case the problem moves to the discovery of its nature. Dark Energy Survey aims to study the nature of dark energy and to test General Relativity and cosmological models. The cluster analysis of the first run of DES leads to results which are incomparable with what other surveys have obtained. In particular it turns out that the matter density of the Universe is $Ω_m = 0.179^{+0.031}_{−0.038}$, very different from the 0.3 value expected. In this work we build a procedure that can be followed in order to understand whether the solution of DES Y1 problem could be a selection effect or not.

43 PARTICLE ACCELERATORS

Measurement of the Energy Spread for CeC Project

The Coherent Electron Cooling requires small energy spread and uniformity of energy along the bunch. The diagnostics line is utilized for the measurement of the electron beam parameters. The beamline layout is shown in Fig. 1. Three quadrupoles after the linac are used to match beam into the common section. The main dipole is used to deflect beam towards common section. If it is switched off the beam goes to the diagnostics line. The beam optics in the diagnostics line is controlled by four quadrupoles. The deflecting cavity sweeping beam in the vertical direction follows the quadrupoles. Sector dipole is used for energy parameters measurement. It has deflection angle of 30 degrees. With diagnostics dipole switched off the beam propagated to the insertable slits system for emittance measurement. There are four profile monitors in the line, The first profile monitor (ACC YAG) is after the main dipole. The second profile monitor (YAG3) is in front of the diagnostics dipole after the deflecting cavity. YAG1 profile monitor is placed after the slits, and YAG2 profile monitor is placed after the diagnostics dipole. There is a solenoid between the deflecting cavity and YAG3. It is used for the beam energy measurement.

43 PARTICLE ACCELERATORS

Metamaterials as a Platform for the Development of Novel Materials for Energy Applications

To explore the fundamental properties of metamaterials (MMs) / metasurfaces and their potential for control of energy at the sub‐wavelength scale in support of the mission of the Department of Energy and the office of Basic Energy Sciences. Electromagnetic metamaterials provide a platform for the discovery and design of new materials with novel structures, functions, and properties. The PI proposes to advance the knowledge base of these materials through fundamental investigations of the experimental and theoretical properties of metamaterials for the discovery, prediction and design of new materials with novel structures, functions, and properties. The proposed research activities emphasize a complete basic research program including the conceptual / computational design, fabrication / synthesis of the materials, and the characterization and analysis of their electromagnetic properties. The proposed project explores the fundamental properties of metamaterials / metasurfaces and their potential for energy applications. There are three main topics which will be investigated: 1) Dispersion engineering with metamaterials and metasurfaces, 2) Epsilon near zero metamaterial absorbers and emitters, and 3) All dielectric metamaterials. The program implements a complete basic research program consisting of theory / design, modeling, characterization, and analysis, in order to fully characterize metamaterials and metasurfaces, while at the same time minimizing iterations necessary to achieve the proposal goals.

36 MATERIALS SCIENCE

Record of Decision: MEBT Energy Change

The LAMP Conceptual Design (LCD), as described in the LAMP Conceptual Design Report incorporates a radiofrequency quadrupole (RFQ) with an output beam energy of 3.0-MeV; the medium energy beam transport line (MEBT) transports beam from the end of the RFQ into the first LAMP drift tube linac (DTL) tank. The MEBT contains components, such as rebunchers and beam choppers, designed for the specific output energy of the RFQ, and the DTL tank is designed to accept this beam energy.

43 PARTICLE ACCELERATORS

Regional Energy Hardware Innovation Accelerator

E4 Carolinas, Inc., along with the Joules Accelerator and Savannah River National Laboratory received a grant from the DOE Office of Technology Commercialization as part of its Energy Program for Innovation Clusters (EPIC) program to develop a Regional Energy Hardware Innovation Accelerator. The project objective was to create a regional energy hardware cluster innovation and accelerator ecosystem (Accelerator) to enhance commercialization opportunities for U.S. energy startups (Ventures) and Corporate Ventures (a new venture originating within an established company).

24 POWER TRANSMISSION AND DISTRIBUTION