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DOE OSTI2026

Westcott g factors extended to arbitrary neutron energy spectra

Westcott 𝑔 factors are used in Neutron Activation Analysis (NAA) and Prompt Gamma-ray Activation Analysis (PGAA) to evaluate the impact of non-1∕𝑣 behavior in the neutron-capture cross sections of certain nuclei on activation product yields. This non-1∕𝑣 behavior arises from the presence of neutron resonances in the neutron- capture cross sections that overlap with the source neutron spectrum at low (< 5 eV) energies. Historically, Westcott 𝑔 factors that have been cataloged for NAA and PGAA applications are the result of calculations that assume a Maxwellian neutron flux distribution with a given temperature. In this work, we use this approach with updated neutron-capture cross sections from the Evaluated Nuclear Data File, version VIII.1 (ENDF/B-VIII.1) to tabulate Westcott 𝑔 factor values for a broad range of Maxwellian distribution temperatures, comparing the results against currently-available 𝑔 factors from International Atomic Energy Agency tables and other sources. Here, it was discovered during this analysis that the use of guided thermal and cold-neutron beams at certain facilities necessitates an approach for evaluating Westcott 𝑔 factors based on arbitrary non-Maxwellian spectra. In this paper, we present an approach for calculating 𝑔 factors with user-specified neutron spectra, and we demonstrate these methods to obtain Westcott 𝑔-factors for guided- and cold-neutron beams at the Budapest Research Reactor and the Forschungsreaktor München II reactor. As part of this work, open-source software has been developed that can be used to perform these calculations for applications in PGAA and NAA experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Energy-scaling behavior of intrinsic transverse-momentum parameters in Drell-Yan simulation

An analysis is presented based on models of the intrinsic transverse momentum (intrinsic 𝑘 T ) of partons in nucleons by studying the dilepton transverse momentum in Drell-Yan events. Using parameter tuning in event generators and existing data from fixed-target experiments and from hadron colliders, our investigation spans 3 orders of magnitude in center-of-mass energy and 2 orders of magnitude in dilepton invariant mass. The results show an energy-scaling behavior of the intrinsic 𝑘 T parameters, independent of the dilepton invariant mass at a given center-of-mass energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Analysis of Dynamic Behavior of the Target and the Deuterium-Tritium Ice in Magnetic-Field Assisted Implosions

The use of strong magnetic fields to augment the output energy of inertial confinement fusion experiments at the National Ignition Facility is of high interest. It offers the potential of reducing electron thermal conduction and increasing hot-spot alpha heating with little to no change in hohlraum behavior. In these magnetically assisted ignition experiments, the ultimate goal is to add a B-field in the form of a pulse ranging from 25 to 60 T to a high-performing hohlraum implosion several microseconds before impingement of the laser beams. This requires eliminating metallic components in the target and replacing them with electrically nonconducting materials. However, the strong eddy currents generated by the rapidly increasing high B-field, which were calculated to be as high as 2000 K, can heat the hohlraum. Here in this paper, we examine the transient effects of this rapid temperature change on the behavior of the target as well as the fuel layer composed typically of deuterium and tritium. Using simulations and calculations for limiting case scenarios, we find that the effect of the heating is not restrictive toward the performance of the target or the quality of the deuterium-tritium ice.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Integrated simulation of U-10Mo monolithic fuel swelling behavior

Here, a separate computational branch has been implemented within the DART (Dispersion Analysis Research Tool) computational code to simulate the swelling behavior of U-10Mo monolithic fuel under the operating conditions of high-power research and test reactors (RTRs). The monolithic branch of the DART code implements a mechanistic rate-theory-based fission-gas-behavior model for the calculation of fission gas swelling, as well as a suite of thermal, physical, and mechanical models to take into account various processes occurring in RTR fuels during irradiation. In order to accurately simulate and eventually predict U-10Mo monolithic fuel irradiation behavior, the code uses materials properties calculated with lower length-scale computational methods, such as gas atom diffusivity and U-Mo surface energy from atomic simulations and grain-morphology-specific recrystallization kinetics (recrystallized fuel volume fractions vs. fission density) predicted using the phase-field method. The remainder of fission gas behavior parameters used in the model were calibrated with measured intergranular bubble size distributions. With this integrated simulation approach, the swelling behavior of U-10Mo monolithic fuel was simulated for various initial grain sizes at different operating conditions and compared with measured data. Furthermore, because limited experimental data exist for parameter calibration detailed sensitivity studies for the important parameters used in the fission gas behavior model were performed in order to examine their impact on both intergranular gas bubble morphology at low fission density, and on total porosity at high fission density.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Melting and Ejecta Produced by High Velocity Microparticle Impacts of Steel on Tin

At sufficiently high velocities, a microparticle impacting a metal substrate can cause ejection of material from the substrate and impact-induced melting, both of which can result in erosion. Here, we directly image the impact of individual hard steel microparticles on soft tin substrates, at controlled impact velocities in the range of ~100 to 1000 m/s. By using scanning electron and laser scanning confocal microscopy, we characterize the surface morphology, depth, and volume of each impact crater. We observe a gradual onset of impact-induced melting in the craters, as well as the production of increasing amounts of ejecta from the target metal. By comparing measurements of impact and rebound velocity to an elastic-plastic model, we observe that at a high enough impact velocity, melting and ejection begin to consume additional kinetic energy beyond that expected by plastic deformation of the target material alone. By calculating the excess energy dissipation using this elastic-plastic model, we show that although this divergent behavior is associated with the onset of melting, the majority of the ejected volume must be solid rather than liquid.

Mechanics↗

DOE OSTI2021

Carbon‐Neutral Pathways for the United States

Abstract The Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C points to the need for carbon neutrality by mid‐century. Achieving this in the United States in only 30 years will be challenging, and practical pathways detailing the technologies, infrastructure, costs, and tradeoffs involved are needed. Modeling the entire U.S. energy and industrial system with new analysis tools that capture synergies not represented in sector‐specific or integrated assessment models, we created multiple pathways to net zero and net negative CO 2 emissions by 2050. They met all forecast U.S. energy needs at a net cost of 0.2–1.2% of GDP in 2050, using only commercial or near‐commercial technologies, and requiring no early retirement of existing infrastructure. Pathways with constraints on consumer behavior, land use, biomass use, and technology choices (e.g., no nuclear) met the target but at higher cost. All pathways employed four basic strategies: energy efficiency, decarbonized electricity, electrification, and carbon capture. Least‐cost pathways were based on >80% wind and solar electricity plus thermal generation for reliability. A 100% renewable primary energy system was feasible but had higher cost and land use. We found multiple feasible options for supplying low‐carbon fuels for non‐electrifiable end uses in industry, freight, and aviation, which were not required in bulk until after 2035. In the next decade, the actions required in all pathways were similar: expand renewable capacity 3.5 fold, retire coal, maintain existing gas generating capacity, and increase electric vehicle and heat pump sales to >50% of market share. This study provides a playbook for carbon neutrality policy with concrete near‐term priorities.

Williams, James H.↗

DOE OSTI2022

Scalable probabilistic estimates of electric vehicle charging given observed driver behavior

To prepare for rapid growth in global electric vehicle adoption, grid and policy planners depend on detailed forecasts of future charging demand. In this paper we propose a novel holistic, scalable, probabilistic framework to produce large-scale estimates of electric vehicle charging load for long-term planning that capture real drivers’ charging patterns. Our framework captures the uncertainty and stochasticity in charging demand by taking a graphical modeling approach. It has three core elements: driver groups, charging segment choices, and charging session time and energy requirements. The framework uses hierarchical clustering to group drivers by their charging histories, capturing their heterogeneous behaviors and preferences across different segments or types of charging. The framework uses probabilistic mixture models for each driver group’s sessions to identify the unique charging behaviors observed within each segment. We illustrate its application with a large data set from California, profiling the charging patterns and unique driver clusters it identifies. Using the model knobs representing drivers’ battery capacities, behavior, and segment access we present scenarios for California’s charging demand in 2030 with 8 million passenger electric vehicles. Peak charging demand ranged from 3.3 to 8.7 GW across scenarios. Furthermore, each was calculated in under 45 s on a laptop computer.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

DER Cybersecurity Detection and Response Suite

SAND2024-08475O The Distributed Energy Resource (DER) Cybersecurity Detection and Response Suite is a solution for distributed energy resource (DER) systems. The DER Security Orchestration, Automation, and Response (SOAR) solution that uses alerts from signature- and behavior-based Intrusion Detection Systems are intended to be deployed as bump-in-the-wire (BITW) devices in front of DER equipment. The fielded application would use multiple intrusion detection systems that report data to SOAR to respond to cyberattacks. The suite consists of two software components: • The proactive intrusion detection and mitigation system (PIDMS) secures grid-edge photovoltaic smart inverters and other equipment in distributed energy resource systems. It is a distributed BITW solution; cyber and physical data are automatically processed using network inspection tools and custom machine learning algorithms to detect abnormal events and correlate cyber-physical events. • The Security Orchestration, Automation, and Response for Distributed Energy Resources (SOAR4DER) application ingests data from several intrusion detection systems to quickly block attacks and revert DER systems to good states. Using a collection of intrusion detection system technologies on a BITW device, it incorporates physical and cyber data to detect abnormal and potential malicious behaviors. Multiple SOAR playbooks then use the intrusion detection system data streams to automatically defend the system. SOAR4DER system testing showed detection and response times under 30 seconds for all adversary reconnaissance, denial-of-service attacks, malicious Modbus commands, brute-force logins, and machine-in-the-middle attacks. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Johnson, Jay↗

DOE OSTI2023

The impact of non-ideal phase change properties on phase change thermal energy storage device performance

Phase change materials have been known to improve the performance of energy storage devices by shifting or reducing thermal/electrical loads. While an ideal phase change material is one that undergoes a sharp, reversible phase transition, real phase change materials do not exhibit this behavior and often have one or more non-idealities – glide, hysteresis, supercooling – associated with them. Experimental and modeling techniques to characterize these non-ideal properties are reasonably well understood, however, their impact on the performance of a thermal energy storage system is not fully understood. Herein, we analyze the performance of a heat exchanger with a phase change material as a function of the different non-idealities, for a heating and a cooling application. We focus on the impact of these non-ideal behaviors on different modes of operation of the thermal energy storage device, which will serve as a useful guide to researchers on the relative importance of the non-ideal properties, along with the necessary accuracy required during an experimental characterization.

25 ENERGY STORAGE↗

DOE OSTI2023

Understanding High-Voltage Behavior of Sodium-Ion Battery Cathode Materials Using Synchrotron X-ray and Neutron Techniques: A Review

Despite substantial research efforts in developing high-voltage sodium-ion batteries (SIBs) as high-energy-density alternatives to complement lithium-ion-based energy storage technologies, the lifetime of high-voltage SIBs is still associated with many fundamental scientific questions. In particular, the structure phase transition, oxygen loss, and cathode–electrolyte interphase (CEI) decay are intensely discussed in the field. Synchrotron X-ray and neutron scattering characterization techniques offer unique capabilities for investigating the complex structure and dynamics of high-voltage cathode behavior. In this review, to accelerate the development of stable high-voltage SIBs, we provide a comprehensive and thorough overview of the use of synchrotron X-ray and neutron scattering in studying SIB cathode materials with an emphasis on high-voltage layered transition metal oxide cathodes. We then discuss these characterizations in relation to polyanion-type cathodes, Prussian blue analogues, and organic cathode materials. Finally, future directions of these techniques in high-voltage SIB research are proposed, including CEI studies for polyanion-type cathodes and the extension of neutron scattering techniques, as well as the integration of morphology and phase characterizations.

25 ENERGY STORAGE↗

DOE OSTI2023

Review—Fundamental Uranium Electrochemistry and Spectroscopy in Molten Salt Systems

Uranium is a key element used for nuclear energy production. Some advanced reactor designs, specifically molten salt reactors, will continue to use uranium as the fissile material for energy production. These new technologies require an intimate understanding of uranium chemistry during and after energy production. This review covers contemporary research on the coordination chemistry and behavior of uranium with the coolant and pyroprocessing salts as proposed for use in future reactor designs. Discussed topics include the nature of U redox reactions involving the reduction of U(III) to U metal and oxidation of U(III) to U(IV). These systems have been interrogated using cyclic voltammetry, chronopotentiometry, and optical and X-ray absorption spectroscopies. Insights obtained into the electrode potentials, the uranium species, and their diffusion coefficients in alkali halide melts from decades of research are summarized selectively. Further, perspectives are provided on the importance of unifying studies for comparison across multiple institutions. The application of synchrotron radiation research and multimodal approaches involving two (or more) probes, such as the widespread combination of UV–visible spectroscopy and electroanalysis known as spectroelectrochemistry, can provide new knowledge about the main process of uranium electrorefining—diffusion, as will be demonstrated in this review through the lack of comparable results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Ibis Networks/WattIQ (IN2 Final Report)

Ibis Networks is a full-stack cleantech company that provides plug-level energy monitoring and control to solve energy and asset management problems for the enterprise. During DATES – DATES, an NREL research team worked with the Ibis team to validate their product, the InteliSocket. The Ibis InteliSocket is a pass-through plug-load energy monitor and controller that is designed to reduce energy wasted by common 120 V plug-in devices in commercial office buildings, such as computer peripherals, conference room AV equipment, and break-room appliances. The system can shut off supply power to these end uses via remote control, manual switches, pre-set schedules, or automated control algorithms. The scope of this IN2 project was the development and refinement of “smart” learning behavior algorithms (LBAs), which could help installation processes and dramatically expand the sockets’ capabilities and energy-saving potential by suggesting suitable control schedules that are based on monitored use patterns. While Ibis has the analytical and software expertise for algorithm development, the lack of test data, both in a controlled laboratory setting and in real-life deployment scenarios, represented a key barrier toward commercialization of the product. Assistance through the IN2 program provided an opportunity to conduct the needed “trial and error” algorithm development. The project included baseline field-data collection, laboratory testing, and field validation components, all of which were conducted at the NREL campus between April 2017 and July 2019.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Structure and mechanical properties of grain boundaries in molybdenum disulfide (MoS 2 )

Molybdenum disulfide (MoS 2 ) is a two-dimensional material widely used as a lubricant in many applications involving mechanical loading under a wide range of operating temperatures. Since many synthesis and processing techniques yield MoS 2 in its polycrystalline form, establishing grain boundary (GB) structure–property relations is key to designing MoS 2 microstructures with tailored properties. Here, we employ classical, reactive atomistic simulations to investigate the structure and mechanical behavior of a wide range of GBs in MoS 2 as a function of temperature. Using a bicrystal MoS 2 geometry, we characterize the atomic structure and calculate the energy of several low-angle GBs. Then, we simulate the tensile deformation behavior of MoS 2 bicrystals at several temperatures. Our results reveal that at temperatures above 100 K, the deformation of MoS 2 bicrystals is characterized by the nucleation of shear bands from GBs that grow, with subsequent loading, into the MoS 2 crystals. At low temperatures, the tensile deformation is characterized by the nucleation and propagation of deformation fronts, resulting in altered bond angles and bond lengths. Quantitative analysis reveals a decrease in the ultimate tensile stress and ultimate failure strain of MoS 2 bicrystals with the increase in temperature. Furthermore, our simulations of the mechanical behavior of metastable GBs reveal that the strength and ductility decrease with the increase in energy of these boundary structures. In broad terms, our work provides future avenues to employ GB engineering as a strategy to tailor the properties of MoS 2 microstructures.

Moore, Robert D. [Lehigh Univ., Bethlehem, PA (Uni↗

DOE OSTI2025

Emergent Nonthermal Fluid from Jets in the Massive Schwinger Model Using Tensor Networks

We analyze the correlation between the energy, momentum, and spatial entanglement produced by two luminal jets in the massive Schwinger model. Using tensor network methods, we show that for m/g > 1/π, in the vicinity of the strong- to weak-coupling transition, a nearly perfect and chargeless effective fluid behavior appears around the midrapidity region with a universal energy-pressure relationship. The evolution of energy and pressure is strongly correlated with the rise of the spatial entanglement entropy, indicating a key role of quantum dynamics. Some of these observations may be used to analyze high multiplicity jet fragmentation events, energy-energy and energy-charge correlators at current collider energies.

Ab initio calculations↗

DOE OSTI2023

A statistical mechanics framework for polymer chain scission, based on the concepts of distorted bond potential and asymptotic matching

To design increasingly tough, resilient, and fatigue-resistant elastomers and hydrogels, the relationship between controllable network parameters at the molecular level (bond type, non-uniform chain length, entanglement density, etc.) to macroscopic quantities that govern damage and failure must be established. Many of the most successful constitutive models for elastomers have been rooted in statistical mechanical treatments of polymer chains. Typically, such constitutive models have used variants of the freely jointed chain model with rigid links. However, since the free energy state of a polymer chain is dominated by enthalpic bond distortion effects as the chain approaches its rupture point, bond extensibility ought to be accounted for if the model is intended to capture chain rupture. To that end, a new bond potential is supplemented to the freely jointed chain model (as derived in the u FJC framework of Buche and Silberstein (2021) and Buche et al. (2022)), which we have extended to yield a tractable, closed-form model of single chain behavior that should be amenable to continuum-level constitutive model development. Inspired by the asymptotically matched u FJC model response in both the low/intermediate chain force and high chain force regimes, a simple, quasi-polynomial bond potential energy function is derived. This bond potential exhibits harmonic behavior near the equilibrium state and anharmonic behavior for large bond stretches tending to a characteristic energy plateau (akin to the Lennard-Jones and Morse bond potentials). Using this bond potential, approximate yet highly-accurate analytical functions for bond stretch and chain force dependent upon chain stretch are established. Then, using this polymer chain model, a stochastic thermal fluctuation-driven chain rupture framework is developed. This framework is based upon a force-modified tilted bond potential that accounts for distortional bond potential energy, allowing for the derivation and subsequent calculation of the dissipated chain scission energy. Here, the cases of rate-dependent and rate-independent scission are accounted for throughout the rupture framework. The impact of Kuhn segment number on chain rupture behavior is also investigated. The model is fit to single chain mechanical response data collected from atomic force microscopy tensile tests for validation and to glean deeper insight into the molecular physics taking place. Due to their analytical nature, this polymer chain model and the associated rupture framework can in the future be implemented in finite element models accounting for fracture and fatigue in polydisperse elastomer networks.

36 MATERIALS SCIENCE↗

DOE OSTI2026

VECTOR Phase 1 Dataset: CAV Trajectory and Energy Consumption Records

This dataset contains benchmark experimental data from Phase 1 of the VECTOR project, focusing on the energy impact of CAV hardware components. The dataset includes vehicle trajectory data (speed and position) and corresponding energy consumption records collected from a CAV platform equipped with lidar, cameras, onboard computation units, and communication modules. The primary objective is to quantify the baseline energy consumption attributable to sensing and computing systems, independent of any advanced cooperative control strategies. During experiments, the leading vehicle followed a predetermined velocity profile, and the following CAV mirrored this trajectory using a basic car-following control to ensure consistent driving behavior. This setup enables a reliable benchmark for assessing the energy cost introduced by onboard CDA hardware (e.g., lidar and GPU-based processing). The dataset is essential for evaluating energy baselines and supports future comparative studies involving additional cooperative strategies. ![system img](system.png) ![vector img](vector.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Molecular models for creep in oriented polyethylene fibers

Highly oriented and crystalline polyetheylene (PE) fibers have a large failure stress under rapid tensile loading but exhibit significant creep at much smaller stresses that limits applications. A possible mechanism is slip of chains due to stress-enhanced, thermally activated nucleation of dislocations at chain ends in crystalline regions. Molecular dynamics simulations are used to parameterize a Frenkel–Kontorova model that provides analytic expressions for the limiting stress and activation energy for dislocation nucleation as a function of stress. Results from four commonly used hydrocarbon potentials are compared to show that the qualitative behavior is robust and estimate quantitative uncertainties. In all cases, the results can be described by an Eyring model with values of the zero-stress activation energy Ea0≈1.5 eV and activation volume V* ≈ 45 Å3 that are consistent with the experimental results for increasingly crystalline materials. The limiting yield stress is ∼8 GPa. These results suggest that activated dislocation nucleation at chain ends is an important mechanism for creep in highly oriented PE fibers.

O’Connor, Thomas C. (ORCID:0000000293930295)↗

DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗