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DOE OSTI2026

Evaluation of the Room Temperature Field Quality Measurements of HL-LHC MQXFA Magnet Assemblies

As a member of the multi-lab U.S. High Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP), Lawrence Berkeley National Laboratory (LBNL) is assembling high-field Nb3Sn low-beta MQXFA quadrupole magnets for eventual installation at CERN as part of the HL-LHC upgrade. Each magnet undergoes room temperature magnetic measurements at two points during the assembly process: once after completion of the coil pack sub-assembly and once after the magnet is fully assembled and pre-loaded. Beyond its use to verify that each magnet assembly can meet operational requirements, the data from this two-stage measurement process allow for investigation into the impact of the pre-loading operation on field quality. Recent measurements on magnet rebuilds as well as exploratory coil pack reconfigurations also provide an opportunity to see in isolation the effects of changes to a magnet’s coil selection or coil layout. In this work, we present the magnetic measurement results of MQXFA magnets assembled or currently in process, focusing particularly on magnets with data corresponding to multiple builds, and discuss trends and insights which may be beneficial for the remaining MQXFA magnet production or for future Nb3Sn accelerator magnets.

Doyle, Jennifer [LBNL, Berkeley] (ORCID:0009000079↗

DOE OSTI2025

Implications of point defect accumulation on UO 2 thermal conductivity and fission gas release under accelerated fuel irradiation

Evaluation of thermal properties is a crucial factor for nuclear fuel performance. During reactor operation, the accumulation of fission products and irradiation-induced lattice defects are responsible for degradation in thermal conductivity. Consequently, it affects fuel temperature and fission gas release (FGR) among other Multiphysics processes important for economics and safety analysis. We analyze the implications of point defects (PD) accumulation described using a rate theory (RT) Model on lattice thermal conductivity of UO 2 . Here, we demonstrate that fission rate-dependent point defect concentrations have the largest impact on in-pile thermal conductivity in the periphery of light water reactor fuels below a temperature threshold governed by the migration barrier of defects. Our analysis provides a mechanistic description of this phenomena which current fuel performance codes treat empirically. The reduction of thermal conductivity in the low -temperature rim region acts as additional thermal resistance and leads to a temperature notably larger than suggested by Lucuta thermal conductivity correlation. These effects are anticipated to have notable impacts when fuels are exposed to accelerated radiation. The impact of such point defect-informed treatment of thermal conductivity on fuel performance is evaluated by a detailed analysis of fission gas behavior and its release. We consider several models capturing different stages of fission gas bubble evolution and fission gas release (FGR). Finally, a new fission rate-dependent correction to the Lucuta correlation is proposed. The results show a significant reduction in thermal conductivity at the fuels’ periphery and an increase in fuel centerline temperature specifically at low burnups. Ultimately a modified LC shows a higher FGR compared to the original LC, while the acceleration process results in a reduction in overall FGR.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Onshore U.S. Carbon Pipeline Deployment: Siting, Safety, and Regulation

Carbon capture, utilization, and storage technology has significant potential to reduce greenhouse gas emissions and mitigate the impact of climate change, particularly in hard-to-decarbonize industrial and commercial sectors. Unless utilization or storage occurs at the same location as carbon capture, which is rare, carbon must be transported from a point source to a utilization or storage site. Pipelines offer significant advantages for large-scale transportation of carbon dioxide over other methods. While studies show that reaching net-zero carbon emissions in the United States by 2050 will require between 29,000 and 66,000 miles of carbon pipelines, the U.S. had deployed fewer than 6,000 miles of carbon pipelines by 2022. Although closing this gap is important to achieving low-carbon goals, carbon pipelines operate in a complex and uncertain local, state and federal regulatory landscape and face public concerns about safety and siting. This report covers numerous regulatory issues surrounding carbon pipeline development, including the current narrow federal definition of carbon dioxide and the considerable variation in state and local governments’ laws and regulations. The report serves as a primer for regulators and stakeholders who seek to better understand the regulatory challenges and opportunities facing this critical infrastructure

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2022

Physical and Flow Properties of Glass Forming Chemicals (V2O5, SnO, SnO2, Cr2O3, FeCr2O4, and ZrSiO4) and Mixtures

For a sustainable nuclear waste vitrification process at the Hanford Tank Waste Treatment and Immobilization Plant (WTP), proper selection and consistent supply of glass-forming chemicals (GFCs) are crucial. Establishing rigorous acceptance criteria for the characterization of GFCs will be required to operate the vitrification facility and to mitigate any processing issues or failures. Low-activity wastes (LAW) are blended with GFCs to form slurry melter feeds and vitrified in a melter. To enhance properties of waste glasses, new chemicals are being introduced to the current GFC mixture (Vienna et al. 2016; Muller et al. 2017, 2019). In this study, three new GFCs were evaluated for enhanced LAW glass formulations: chromium oxide (Cr 2 O 3 ), vanadium oxide (V 2 O 5 ), and stannic oxide (SnO 2 ). These three oxide components are included in enhanced waste glass (EWG) formulations and GFCs with the appropriate physical and flow properties are needed. As a starting point, single metal oxide GFCs: Cr 2 O 3 , V 2 O 5 , and SnO 2 were sourced and tested. To characterize these new individual GFCs and mixtures of GFCs, the industrial bulk characterization consultant, Jenike and Johanson, was employed to measure physical and flow properties of individual GFCs and their mixtures. Pacific Northwest National Laboratory (PNNL) also measured several selected physical properties for data evaluation as a quality assurance step. In addition, PNNL measured physical and rheological properties of slurry melter feeds containing those GFCs. Subsequent data analyses and verification were conducted. The purpose of this report is to assess the applicability of these GFCs for LAW vitrification based on their properties. This report will help understand measured data and evaluate new GFCs for use. Moreover, this report may give useful insights to help troubleshoot any GFC and melter feed transport and mixing issues that arise during processing, leading to a successful cleanup mission at WTP.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Saltstone Paddles and Augers Materials of Construction Study

The Saltstone Production Facility (SPF) uses a 10-inch READCO continuous, co-rotating twin-screw mixer to mix the dry premix with the low-level radioactive waste (LLW) salt solution to produce fresh saltstone grout. The paddles and augers within the mixer degrade via erosion in the region where the salt solution is introduced into the mixer. After the paddles/augers erode to a point where the throughput impacts operations, the mixer is disassembled, the effected paddles/augers are replaced, and the mixer is reassembled. Saltstone Engineering indicated that this effort requires an approximately three-week outage. The objective of this task is to assess alternative materials of construction (MOCs) that will provide better erosion characteristics and decrease the frequency in which the paddles and augers need replacement. Previous Astralloy V studies looked only at Charpy Impact and Rockwell Hardness Testing. Each of these will be examined for different alloys as well as Miller Testing (abrasion to determine wear) which will provide a good assessment of an alloy’s erosion/wear characteristics. The following facts concerning the current and proposed alloys for Saltstone Paddles and Augers are provided in this report. • Current Astralloy V material and alloy E52100 had the most favorable Miller Testing Results. • Charpy Impact Testing did not correlate with Miller Testing Results. • Hardness Testing correlated with Miller Testing results meaning that higher hardness will provide more favorable wear resistance. • Further investigation of E52100 and various tool grade steels is recommended for achieving wear resistant properties.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Modeling of Stress Distribution in Molten Salt Thermal Energy Storage Tanks for In-Service Central Receiver Power Plants

Failures in molten nitrate salts thermal energy storage tanks (TES) have been occurring in several concentrating solar power (CSP) plants around the world after a few months or years of operation. These failures are mainly related to a combination of high stress, corrosion, large deformation, and thermal cycling. Most of these failures are a consequence of the infancy of this technology; technical standards for design, fabrication, implementation, and operation of molten salt tanks operating at temperatures up to 565 degrees Celsius do not exist and most of current in-service tanks have been designed using the recommendations from the American Petroleum Institute (API) 650 and the American Society of Mechanical Engineers ASME section II standards, which are applicable for TES tanks operating at lower temperatures. We have developed a 3-dimensional model of a representative molten salt hot tank design that uses typical CSP plant operation conditions and allows determining the temperature and stress distribution in the tank. The model also considers the initial floor residual stresses and distortion after its welding fabrication. We have identified critical thermal gradients in the tank floor and shell and locations in the tank where the stresses are high and could become susceptible points for failure.

concentrating solar power↗

DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Data optimization for large batch distributed training of deep neural networks

Distributed training in deep learning (DL) is common practice as data and models grow. The current practice for distributed training of deep neural networks faces the challenges of communication bottlenecks when operating at scale, and model accuracy deterioration with an increase in global batch size. Present solutions focus on improving message exchange efficiency as well as implementing techniques to tweak batch sizes and models in the training process. The loss of training accuracy typically happens because the loss function gets trapped in a local minima. We observe that the loss landscape minimization is shaped by both the model and training data and propose a data optimization approach that utilizes machine learning to implicitly smooth out the loss landscape resulting in fewer local minima. Our approach filters out data points which are less important to feature learning, enabling us to speed up the training of models on larger batch sizes to improved accuracy.

Gahlot, Shubhankar↗

DOE OSTI2021

High-performance photonic transformers for DC voltage conversion

Abstract Direct current (DC) converters play an essential role in electronic circuits. Conventional high-efficiency DC voltage converters, especially step-up type, rely on switching operation, where energy is periodically stored within and released from inductors and/or capacitors connected in a variety of circuit topologies. Since these energy storage components, especially inductors, are fundamentally difficult to scale down, miniaturization of switching converters proves challenging. Furthermore, the resulting switching currents produce significant electromagnetic noise. To overcome the limitations of switching converters, photonic transformers, where voltage conversion is achieved through light emission and detection processes, have been demonstrated. However, the demonstrated efficiency is significantly below that of the switching converter. Here we perform a detailed balance analysis and show that with a monolithically integrated design that enables efficient photon transport, the photonic transformer can operate with a near-unity conversion efficiency and high voltage conversion ratio. We validate the theory with a transformer constructed with off-the-shelf discrete components. Our experiment showcases near noiseless operation and a voltage conversion ratio that is significantly higher than obtained in previous photonic transformers. Our findings point to the possibility of a high-performance optical solution to miniaturizing DC power converters and improving the electromagnetic compatibility and quality of electrical power.

42 ENGINEERING↗

DOE OSTI2022

Fast response High Altitude Laser Optical Sensor (HALOS) for atmospheric water and temperature measurements

Advanced instrumentation and sensing methods are the key factor in the determination of many climate science research problems. In this Phase I STTR a laser-based diagnostic system for atmospheric temperature and water concentrations measurements was developed, this system, HALOS – High Altitude Laser Optical Sensor, employs a mid-infrared (MIR) quantum cascade laser (QCL) of the distributed feedback variety (DFB) powered by a 100 kHz rep rate ramp modulated current profile which enables spectral profiling. Measurements made during Phase I showed that HALOS can surpass the available hygrometers refresh rates while offering superior accuracy (<4%) from the low Frost Point (Tfrost) of -110°C to dew points (Tdew) at 35°C while being able to encompass sub ppm concentration at altitude and supersaturated conditions at ground level. Readings from HALOS include temperature sensitivity on the order of 0.2°C and absolute humidity sensitivity (AH) on the order of 0.010 μmol/m 3 (0.18 mg/m 3 ) at a data output rate exceeding 1 kHz. HALOS can be easily integrable in existing Department of Energy (DOE) or National Oceanic and Atmospheric Administration (NOAA) conventional or remote operated aircraft having either a fixed or rotary wing.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

4.6 V Moisture‐Tolerant Electrolytes for Lithium‐Ion Batteries

Abstract Commercial LiPF 6 ‐based electrolytes face limitations in oxidation stability (4.2 V) and water tolerance (10 ppm). While replacing LiPF 6 with lithium bis(trifluoromethane)sulfonimide (LiTFSI) improves water tolerance, it induces Al current collector corrosion above 3.7 V vs. Li/Li + . To address this, lithium cyano(trifluoromethanesulfonyl)imide (LiCTFSI) is proposed here as a non‐corrosive, moisture‐tolerant alternative. The 2.0 M LiCTFSI/propylene carbonate (PC)‐fluoroethylene carbonate (FEC) (7:3 by volume) electrolyte enables LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) cathodes to reach 210 mAh g −1 (2.8‐4.6 V) with a cycle life of 500. Full cells with NCM811||graphite (2.0 mAh cm −2 ) show 77.8% capacity retention after 500 cycles. Even with 2000 ppm moisture in the electrolyte, full cells maintain high cycling stability, reducing the need for costly dry rooms. The electrolyte’s low freezing point and high thermal stability enable the operation from ‐20 °C to 60 °C, delivering 168 mAh g −1 at ‐20 °C and retaining 94% capacity after 100 cycles at 60 °C. In contrast, cells with commercial LiPF 6 electrolyte deliver 71 mAh g −1 at ‐20°C and retain 52.7% after 100 cycles at 60 °C. This novel salt offers a cost‐effective solution for developing robust, high‐performance batteries suitable for extreme conditions.

Zhang, Nan↗

DOE OSTI2024

Neural architecture search via similarity adaptive guidance

Evolutionary neural network architecture search (ENAS) has attracted the attention of many experts due to its global optimization capabilities to automatically search for convolutional neural network architectures based on the target task. The current search space for ENAS is not to design a fully structured network, but to search for smaller cell architectures to reduce search costs. However, blind search strategies do not effectively utilize the potential experience of the population. In order to utilize the potential experience learned by the current population to guide the evolutionary search of the population, we propose a similarity guided neural network architecture search algorithm based on cell architecture, which utilizes the similarity between pairwise architectures in the population as empirical knowledge learned by the population. Our proposed algorithm provides a novel method for calculating architecture similarity, which calculates architecture similarity separately from the cell and macro-structure. Then we decouple the connections and operations in the cell and calculate connection and operation similarity separately. In addition, we propose adaptive similarity selection and binary tournament selection strategies to enhance the algorithm’s global and local search capabilities and effectively explore the search space. Finally, we design an improved single-point crossover operator to enhance the local search ability of the evolutionary operator. The experimental results show that SAGNAS is a competitive algorithm that achieves 97.44% and 81.60% in CIFAR10 and CIFAR100 with only 1.9 GPU-days spent.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Divertor detachment and heat exhaust mitigation control in KSTAR with tungsten divertor

KSTAR has recently undergone an upgrade to use a new tungsten divertor to run experiments in ITER-relevant scenarios. Even with a high melting point of tungsten, it is important to control the heat flux impinging on tungsten divertor targets to minimize sputtering and contamination of the core plasma. Heat flux on the divertor is often controlled by increasing the degree of detachment of scrape-off layer plasma from the target plates. In this work, we have demonstrated successful divertor detachment and heat exhaust dissipation control experiments using two different methods. The first method uses attachment fraction as a control variable which is estimated using ion saturation current measurements from embedded Langmuir probes in the divertor. The second method uses a novel machine-learning-based surrogate model of 2D UEDGE simulation database, DivControlNN. We demonstrated running inference operation of DivControlNN in realtime to estimate heat flux at the divertor and use it as the control variable in a feedback loop with impurity gas flow. We present interesting insights from these experiments including a systematic approach to tuning controllers and discuss future improvements in the control infrastructure and control variables for future burning plasma experiments.

KSTAR tungsten divertor operations↗

DOE OSTI2021

Proposed Risk-Informed Regulatory Framework for Approval of Microreactor Transportation Packages

Microreactors are very small nuclear reactors with a power output of about 20 megawatts electric or less that are designed to be factory-built, modular in nature, and highly portable. These compact reactors will be small enough to be transported by truck or even air and could help solve energy challenges in a number of areas, ranging from remote commercial or residential locations to military bases. Pacific Northwest National Laboratory is tasked to develop and evaluate transportation licensing options for microreactors. The work is funded by the National Reactor Innovation Center a National Department of Energy program led by Idaho National Laboratory for the Office of Nuclear Energy Research and Development which support demonstration of microreactor technology. Key transportation steps include the (1) initial movement of high-assay low enriched uranium fresh fuel, (2) transportation of an intact, but never-operated microreactor, and (3) transportation of an intact, previously-operated microreactor. The deliverables on the project consists of a documentation of applicable regulations and regulatory authority for transportation. The objective of this report is to propose a risk-informed regulatory framework for the licensing of the transportation of microreactors, including the transportation of irradiated nuclear fuel that is assumed to be an integral component of the microreactor transportation package. The framework lays out a viable regulatory pathway, including decision points for regulatory options and the supporting technical evaluations for those options in phases from near to long term. This report includes discussion of the (1) general microreactor design concepts including representative microreactor source terms, (2) options for regulatory approval of microreactor transportation based on current regulation and historical precedence, (3) regulatory basis for including risk information in microreactor transportation licensing activities, and (4) description of a risk-informed regulatory framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Proposed Risk-Informed Regulatory Framework for Approval of Microreactor Transportation Packages

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Unraveling the impact of initial choices and in-loop interventions on learning dynamics in autonomous scanning probe microscopy

The current focus in Autonomous Experimentation (AE) is on developing robust workflows to conduct the AE effectively. This entails the need for well-defined approaches to guide the AE process, including strategies for hyperparameter tuning and high-level human interventions within the workflow loop. This paper presents a comprehensive analysis of the influence of initial experimental conditions and in-loop interventions on the learning dynamics of Deep Kernel Learning (DKL) within the realm of AE in scanning probe microscopy. We explore the concept of the “seed effect,” where the initial experiment setup has a substantial impact on the subsequent learning trajectory. Additionally, we introduce an approach of the seed point interventions in AE allowing the operator to influence the exploration process. Using a dataset from Piezoresponse Force Microscopy on PbTiO 3 thin films, we illustrate the impact of the “seed effect” and in-loop seed interventions on the effectiveness of DKL in predicting material properties. The study highlights the importance of initial choices and adaptive interventions in optimizing learning rates and enhancing the efficiency of automated material characterization. This work offers valuable insights into designing more robust and effective AE workflows in microscopy with potential applications across various characterization techniques.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Null Space Monte Carlo Evaluation of the Plateau to River Model

The Plateau to River Groundwater Model (P2R Model) is a groundwater flow and contaminant fate and transport (F&T) simulation model used to support remedial activities conducted by CH2M HILL Plateau Remediation Company at the Hanford Site in Washington State. Figure 1-1 illustrates the P2R Model extents, discretization, and boundary conditions. The P2R Model provides a computational framework to simulate the F&T of contaminants in groundwater associated with the 200-PO-1, 200-UP-1, 200-BP-5, and 200-ZP-1 Groundwater Operable Units (OUs) in the Hanford Site Central Plateau. In addition, the model includes adjacent areas and facilities (e.g., the State Approved Land Disposal Site). Intended and anticipated uses of the model include calculating water levels, hydraulic gradients, and groundwater flows throughout the model domain (encompassing the 200 West and 200 East Areas) for use in subsequent F&T calculations for contaminants of concern and developing scale-appropriate, telescopic-mesh refinement models for detailed evaluation of areas within the model domain where required. The overall objective of the modeling effort is to provide a basis for making informed remedial action decisions based on descriptions of current and expected future contaminant concentrations in groundwater at decision points within the OU boundaries. The objective for the model development phase is to create a common modeling platform that can be used for investigations of the Central Plateau groundwater OUs and areas downgradient toward the Columbia River. The P2R Model calibration to historical data observed at the Hanford Site is documented in CP-57037, Model Package Report for the Plateau to River Model Version 8.3. The purpose of this environmental calculation is to describe a null space Monte Carlo (NSMC) evaluation was conducted with the historic calibration of the P2R model. Use of numerical groundwater models is always accompanied with uncertainty in the results produced by a model because models are approximations of reality. Thus, by definition, lack the detail to fully represent observed behavior. Use of numerical techniques, such as a NSMC analysis, can help in identifying and quantifying the potential uncertainties associated with a numerical model such as the P2R Model. Use of the NSMC approach results in 100 groundwater flow models that are variants of the calibrated P2R Model. These variant models can be used to evaluate uncertainty in model predictions made by the calibrated P2R Model for other analyses. A secondary purpose of the environmental calculation is to establish these variant models for use with other applications.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

In Situ Alloying Enabled by Active Liquid Metal Filler for Self‐Healing Composite Polymer Electrolytes

Abstract Solid inorganics, known for kinetically inhibiting polymer crystallization and enhancing ionic conductivity, have attracted significant attention in solid polymer electrolytes. However, current composite polymer electrolytes (CPEs) are still facing challenges in Li metal batteries, falling short of inhibiting severe dendritic growth and resulting in very limited cycling life. This study introduces Ga 62.5 In 21.5 Sn 16 (Galinstan) liquid metal (LM) as an active liquid alternative to conventional passive solid fillers, aiming at realizing self‐healing protection against dendrite problems. Compared to solid inorganics, for example silica, LM droplets could more significantly reduce polymer crystallinity and enhance Li‐ion conductivity due to their liquid nature, especially at temperatures below the polymer melting point. More importantly, LMs are unraveled as dynamic chemical traps, which are capable of blocking and consuming lithium dendrites upon contact via in situ alloying during battery operation and further inhibiting dendritic growth due to the lower deposition energy barrier of the formed Li‐LM alloy. As a proof of concept, by strategically designing an asymmetric CPE with the active LM filling, a solid‐state Li/LiFePO 4 battery achieves promising full‐cell functionality with notable rate performance and stable cycle life. This active filler‐mediated self‐healing approach could bring new insights into the battery design in versatile solid‐state systems.

Wu, Kai↗