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At least 1,369 records · Page 76

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DOE OSTI2019

Using in situ and operando methods to characterize phase changes in charged lithium nickel cobalt aluminum oxide cathode materials

Lithium ion batteries have been extensively explored in recent decades in order to improve their electrochemical performance, address safety concerns, and reduce costs in larger-scale applications. Electrode materials are key components which govern the properties of the battery at the system level. Cathode materials are of particular importance as they are a limiting factor for achieving high energy density. Lithium nickel cobalt aluminum oxide (LiNi 0.8 Co 0.15 Al 0.05 O 2 , referred to subsequently as NCA) is one of successful cathode materials since it can deliver higher capacity than other cathode materials such as lithium cobalt oxide or lithium iron phosphate. However, structural instabilities that occur NCA during charging or at high temperatures is believed to be the primary reason for performance degradation as well as a possible safety threat. Furthermore, understanding the structural evolution that occurs in NCA is of importance to acquire fundamental insights for taking full advantage of the high capacity of NCA materials. Beyond static information, in situ and operando characterization approaches allow us to observe structural changes under external stimulus or in a working condition, providing a deeper understanding of the routes by which structure evolve. In this review, we will describe the use of both in situ and operando characterization performed with both synchrotron X-ray based techniques and advanced electron microscopy, as the combination of these techniques have been shown to be particularly effective at providing structural information at complementary length scales.

25 ENERGY STORAGE↗

DOE OSTI2024

FENIX: An Open-Source Multiphysics Integrated Framework Enabling Collaborative Development of Plasma Facing Component Modeling Capabilities

Advanced modeling and simulation tools have a crucial role to play in accelerating fusion energy deployment as a sustainable power source. Multiphysics, high-fidelity computational tools can help understand, model, and quantify the complex interactions between materials performance, plasma and neutron exposure, and engineering processes. As a result, they accelerate the design, safety analysis, and performance evaluation of fusion systems. This webinar introduces the Fusion ENergy Integrated multiphys-X (FENIX) framework, an open-source multiphysics tool for plasma facing component modeling. FENIX leverages the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which has been developed by the United States Department of Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. FENIX couples various MOOSE capabilities such as heat transfer, thermomechanics, thermal hydraulics, electromagnetics, and plasma kinetics with the MOOSE-based applications Cardinal (neutronics) and TMAP8 (tritium transport). During the webinar, we will present FENIX and discuss how its modularity, openness, software quality assurance processes, and licensing approach supports effective collaborations, including public-private partnerships.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Multilevel Monte Carlo Estimators For Derivative-Free Optimization Under Uncertainty

Optimization is a key tool for scientific and engineering applications; however, in the presence of models affected by uncertainty, the optimization formulation needs to be extended to consider statistics of the quantity of interest. Optimization under uncertainty (OUU) deals with this endeavor and requires uncertainty quantification analyses at several design locations; i.e., its overall computational cost is proportional to the cost of performing a forward uncertainty analysis at each design location. An OUU workflow has two main components: an inner loop strategy for the computation of statistics of the quantity of interest, and an outer loop optimization strategy tasked with finding the optimal design, given a merit function based on the inner loop statistics. Here, in this work, we propose to alleviate the cost of the inner loop uncertainty analysis by leveraging the so-called multilevel Monte Carlo (MLMC) method, which is able to allocate resources over multiple models with varying accuracy and cost. The resource allocation problem in MLMC is formulated by minimizing the computational cost given a target variance for the estimator. We consider MLMC estimators for statistics usually employed in OUU workflows and solve the corresponding allocation problem. For the outer loop, we consider a derivative-free optimization strategy implemented in the SNOWPAC library; our novel strategy is implemented and released in the Dakota software toolkit. We discuss several numerical test cases to showcase the features and performance of our approach with respect to its Monte Carlo single fidelity counterpart.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Additively manufactured strain sensors for in-pile applications

Accurate, real-time monitoring of strain in fuel, cladding, and structural components of nuclear reactors is critical to better understand radiation induced phenomena during reactor tests and operations. The data provided is crucial to verify physics-based, multiscale modeling and simulation efforts, which aim to shorten the timeline for the development of new nuclear materials. Resistive strain gauges have limited performance during in-pile experiments due to the harsh operating conditions and limited physical space between fuel and cladding components. In this work, aerosol jet printing using silver nanoparticle inks was used to fabricate interdigitated electrode capacitive strain gauges on aluminum alloy 6061 tensile specimens. Here to simulate the temperatures of a traditional light water reactor, the capacitive strain gauges were tested with a mechanical test frame up to 300 °C and compared to commercially available bondable resistive strain gauges. The printed capacitive strain gauges exhibited a gauge factor of 1.0 and showed higher reproducibility and predictability of strain sensing performance than the resistive strain gauge. The results demonstrate the potential of aerosol jet printing to fabricate strain sensors with predictable performance and reduced invasiveness for high-temperature applications with confined spacing.

36 MATERIALS SCIENCE↗

DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗

DOE OSTI2021

Direct Recycling of Blended Cathode Materials by Froth Flotation

We report that direct Li-ion battery recycling involves separating cathode active materials in the solid phase while preserving their electrochemical performance. To reuse the recycled ones in new batteries, it is necessary to separate individual cathode components, which would typically occur prior to the rejuvenation and any compositional reformulation processes. Herein, a froth flotation process is developed to separate pristine lithium nickel-manganese-cobalt oxide (LiNi 0.333 Mn 0.333 Co 0.333 O 2 , NMC111) and lithium manganese oxide (LMO) materials. The flotation results show that with multiple stages of the separation processes, a satisfactory separation is achieved with 95% grade or above of NMC111 in the froth product and 95% grade of LMO in the tailing product. The electrochemistry results show that the flotation chemicals have negligible impact on the electrochemical performance of recycled active materials, whereas the NMC111 exhibits a minor capacity fade after being in contact with deionized water at 2% solid concentration. An improvement in both the rate and cycling performance is achieved at 10% solid concentration or higher. It is found that there is little compositional and structural change to the aqueous recycled NMC111 powders. An effective and low-cost separation method for direct recycling mixed cathode compositions is demonstrated.

25 ENERGY STORAGE↗

DOE OSTI2024

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Microstructure analysis of laser beam weldments performed on neutron-irradiated 304L steel containing 3 and 8 appm helium

We report that AISI 304 L austenitic stainless steel is one of the major structural materials used in light water reactors (LWRs). In the future, 304 L components may require repair, and several welding techniques have been proposed as candidates. In this study, laser beam welding using the low-energy contribution approach was performed in ~2016 on neutron-irradiated AISI 304 L steel with nominal values of 3 and 8 appm helium (He). The goal was to investigate the impact of helium on the irradiated material weldability and evaluate helium-associated damage. The weld and heat-affected zone (HAZ) microstructure was studied using scanning electron microscopy, electron backscatter diffraction, and transmission electron microscopy (TEM). Analysis of the weldment cross-sections did not reveal severe cracking. Still, evidence of incipient helium-associated damage was observed in the HAZ, manifesting as degraded grain boundaries (GBs) “decorated” by pore chains and mostly small (i.e., ≤ 25-30 µm) scattered cracks. The largest observed crack was ~50 µm in length. Helium-associated damage was localized within ~200-300 µm of the weld pool boundary, and the fraction of the compromised GBs, as a rule, was below ~9-11% of the total GB network. TEM analysis showed significant annealing of the radiation-induced defects at distances up to ~300 µm from the weld pool boundary. Inside the HAZ, the cavities (likely, helium bubbles) tended to form at GBs and inclusions, such as manganese sulfide precipitates in the grain interior. Crystallography analysis of the HAZ damage showed that random high-angle boundaries were most susceptible to helium-associated damage. In contrast, low-angle random boundaries and twin boundaries appeared to be strongly resistant to degradation from the combined effects of helium and welding.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Enabling Industrial Re-Use of Large-Format Additive Manufacturing Molding and Tooling

Large-format additive manufacturing (LFAM) is an enabling manufacturing technology capable of producing large parts with highly complex geometries for a wide variety of applications, including automotive, infrastructure/construction, and aerospace mold and tooling. In the past decade, the LFAM industry has seen widespread use of bio-based, glass, and/or carbon fiber reinforced thermoplastic composites which, when printed, serve as a lower-cost alternative to metallic parts. One of the highest-volume materials utilized by the industry is carbon fiber (CF)-filled polycarbonate (PC), which in out-of-autoclave applications can achieve comparable mechanical performance to metal at a significantly lower cost. Previous work has shown that if this material is recovered at various points throughout the manufacturing process for both the lab and pilot scale, it can be mechanically recycled with minimal impacts on the functional performance and printability of the material while significantly reducing the feedstock costs. End-of-life (EOL) CF-PC components were processed through industrial shredding, melt compounding, and LFAM equipment, followed by evaluation of the second-life material properties. Experimental assessments included quantitative analysis of fiber length attrition, polymer molecular weight degradation using gel permeation chromatography (GPC), density changes via pycnometry, thermal performance using dynamic mechanical analysis (DMA), and mechanical performance (tensile properties) in both the X- and Z-directions. Results demonstrated a 24.6% reduction in average fiber length compared to virgin prints, accompanied by a 21% decrease in X-direction tensile strength and a 39% reduction in tensile modulus. Despite these reductions, Z-direction tensile modulus improved by 4%, density increased by 6.8%, and heat deflection temperature (HDT) under high stress retained over 97% of its original value. These findings underscore the potential for integrating mechanically recycled CF-PC into industrial LFAM applications while highlighting the need for technological innovations to mitigate fiber degradation and enhance material performance for broader adoption. This critical step toward circular material practices in LFAM offers a pathway to reducing feedstock costs and environmental impact while maintaining functional performance in industrial applications.

additive manufacturing↗

DOE OSTI2025

Convergence study of wakefield simulations with GdfidL and ECHO3D

The interaction of charged particle beams with vacuum chamber components gives rise to electromagnetic wakefields, whose frequency-domain representation is known as beam coupling impedance. Geometric impedance arising from discontinuities and transitions in the vacuum chamber is the focus of this study. Minimizing this impedance is essential to mitigate adverse collective effects in modern storage rings operating with high-intensity particle beams. Accurate and reliable impedance simulations is a key factor of the vacuum chamber design. This paper presents the results of a convergence study of two widely used electromagnetic solvers, GdfidL and ECHO3D, applied to key vacuum-chamber components of the National Synchrotron Light Source II (NSLS-II) storage ring. Detailed comparisons are performed for several geometries, including flange absorbers, RF bellows, button-type beam position monitors, and an in-vacuum undulator (IVU). The results show notable differences in convergence and computational efficiency between the two codes. While GdfidL provides highly resolved results and serves as a common benchmark tool, ECHO3D yields consistent results with coarser meshes, significantly reducing simulation time and memory demands. Simulations with a full-geometry IVU model demonstrate that simplified taper-transition models can miss important impedance contributions. In conclusion, these findings provide practical guidelines for efficient and accurate impedance modeling to optimize design of vacuum chamber components for accelerators.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗

DOE OSTI2019

Point-node gap structure of the spin-triplet superconductor UTe 2

In this work, low-temperature electrical and thermal transport, magnetic penetration depth, and heat capacity measurements were performed on single crystals of the actinide superconductor UTe 2 to determine the structure of the superconducting energy gap. Heat transport measurements performed with currents directed along both crystallographic a and b axes reveal a vanishingly small residual fermionic component of the thermal conductivity. The magnetic field dependence of the residual term follows a rapid, quasilinear increase consistent with the presence of nodal quasiparticles, rising toward the a -axis upper critical field where the Wiedemann-Franz law is recovered. Together with a quadratic temperature dependence of the magnetic penetration depth up to T / T c = 0.3 , these measurements provide evidence for an unconventional spin-triplet superconducting order parameter with point nodes. Millikelvin specific heat measurements performed on the same crystals used for thermal transport reveal an upturn below 300 mK that is well described by a divergent quantum-critical contribution to the density of states (DOS). Modeling this contribution with a T - 1 / 3 power law allows restoration of the full entropy balance in the superconducting state and a resultant cubic power law for the electronic DOS below T c , consistent with the point-node gap structure determined by thermal conductivity and penetration depth measurements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Sulfonate Group Improves the Solubility and Electrocatalytic Performance of Ru‐Based bda‐ and pda‐Type Water Oxidation Catalysts under Neutral Conditions

Four ruthenium water oxidation catalysts that bear carboxylate and sulfonate groups in the active site have been synthesized and analyzed for their catalytic activity. Here, the sulfonate‐containing catalysts show higher electrochemical activity in pH 7 phosphate buffer with 4 times larger catalytic current, improved durability with sacrificial oxidant, and increased solubility compared to similar species containing two carboxylate groups. Density functional theory calculations suggest that the sulfonate group provides a more favorable geometry for water nucleophilic attack, which is both the energetically most favorable mechanism calculated and the experimentally predicted mechanism under electrochemical conditions. Further experimental studies have been performed to show that under certain conditions catalysts can perform well electrochemically under pH conditions as low as 1.6 and that various structural components can greatly change solubility and catalytic operation.

14 SOLAR ENERGY↗

DOE OSTI2026

Process-driven roadmap for depositing super duplex stainless steel via wire Arc additive manufacturing

Here, this study systematically investigates the effects of shielding gas, bead spacing, weld mode, and travel speed on the phase balance, porosity, and hardness of wire arc additively manufactured (WAAM) super duplex stainless steel (ER2594). Robotic WAAM was employed to fabricate multilayer walls under systematically varied process conditions, followed by phase transformation simulations, X-ray computed tomography (XCT), electron backscatter diffraction (EBSD), and microhardness evaluation. Thermodynamic simulations predicted rapid cooling of AM process can suppress the potential formation of deleterious precipitates which was later validated via cross-sectional microstructure analyses of printed samples. XCT revealed porosity levels below 0.2% for all deposits, with reduced travel speed significantly lowering defect volume. Microstructural analyses revealed the evolution of various austenite precipitates, including grain boundary austenite (GBA), Widmanstätten austenite (WA), and intergranular austenite (IGA), sequentially upon cooling of the ferrite phase. Among all process parameters, weld transfer mode exhibited the strongest influence on phase balance; pulsed mode promoted higher ferrite retention (~ 36%) compared to RapidX mode. No consistent relationship between stabilized phase fraction and captured microhardness was observed. This work provides critical insights for optimizing WAAM parameters to control phase balance and mechanical performance, which is essential for producing high-integrity super duplex stainless-steel components for nuclear and marine applications.

Grain orientation↗

DOE OSTI2022

Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars

Oleaginous yeasts have received significant attention due to their substantial lipid storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. Furthermore, this analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Automated compatibility checking of prefabricated components using 3D as-built models and BIM

There have been recent efforts to use reality capture technologies to perform remote quality control in construction. However, there is a lack of research efforts in detecting construction incompatibilities in modular construction using reality capture technologies. The construction incompatibilities in modular construction often cause reworks and delays in the project schedule. To address this issue, this paper presents a general compatibility analysis method that propose scanning the modules in manufacturing plant and construction site, and check module-to-module compatibility remotely, prior to the shipment and installation. This study provides three sample module-to-module compatibility scenarios to validate the proposed compatibility analysis. The case study results show that the compatibility analysis method was able to identify the compatibility issues with high accuracy. Lastly, the compatibility analysis method was validated in terms of accuracy and time performance in six scenarios that was defined on the modules.

42 ENGINEERING↗

DOE OSTI2022

Dry in-pile fracture test (DRIFT) for separate-effects validation of ceramic fuel fracture models

Fracture is an important component of nuclear fuel behavior, and significant efforts have been invested into developing fuel performance models that are capable of accurately representing fracture. Usable data on the process of fracture propagation in nuclear fuel under realistic service conditions are very limited. To address this need, a series of separate-effects experiments were developed and performed at Idaho National Laboratory's Transient Reactor Test (TREAT) facility. These experiments employ a heat sink to radially remove heat from the fuel in a manner that approximates the effect of coolant in an operating light-water reactor (LWR). The test holder for these experiments is known as the Dry In-pile Fracture Test (DRIFT). A series of experiments employing DRIFT and TREAT were performed to provide data on the extent and nature of fracture in fresh fuel at various points during a ramp to full power. Novel aspects of these experiments include the way they employ a heat sink to replicate steady-state LWR conditions, as well as the use of fiber optic sensors for in-reactor thermal instrumentation. Details on the development of this experiment, experimental conditions, and resulting data (including in situ thermal measurements and post-irradiation imaging of fracture) are provided in this work. LWR-equivalent powers ranging from 10 to 25 kW/m were tested using this apparatus. Cracking was visible at all power levels, with increasing cracking extent as the power level increased, although there was little difference in the cracking between the two highest-power tests, which had LWR-equivalent powers of 20 and 25 kW/m.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Electrochemical dynamics of imidazolium ionic liquids at graphene electrodes for energy storage applications

Electric double layer capacitors (EDLCs) are prominent energy storage systems that constitute the foundation of more reliable and sustainable energy infrastructures. Modern EDLCs often incorporate ionic liquids (ILs) as a key component in their electrolytes, leveraging the high electrochemical stability of ILs to enhance device performance. The performance and functionality of these capacitors also hinge on the interfacial behavior of ILs at electrode surfaces, which remain insufficiently understood. Here, we performed synchrotron infrared nanospectroscopy (SINS) in combination with density functional theory (DFT) calculations to investigate the electric double layers (EDLs) of three imidazolium-based ILs in a custom-designed graphene liquid cell. This approach revealed new insights into the dynamics of IL EDLs and the underpinning factors originating from the IL structures. Variations in anion size and structure were found to tune the ILs’ ability to form EDLs with compact and closely-correlated ion arrangements, which are critical for enhancing their capacitive performance. These findings highlight the intricate interactions between ions governed by their structures and charge behaviors, which underscores the opportunities for targeted design of IL-based electrolytes to optimize EDLC functionality.

Electric double layers↗