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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Corrosion Testing Of Additively Manufactured Stainless Steel 316H In Molten Salt Environments

The development of a new ASTM standard for evaluating the corrosion resistance of additive manufactured (AM) stainless steel (SS) 316H in chloride molten salts is critical for the use of these materials in extreme environments such as molten salt reactors (MSRs). This report pertains to a work package of the Advaned Materials and Manufacturing Technologies (AMMT) developing a systematic methodology to link changes in AM fabrication parameters, namely surface finishing, porosity, microstructure, and chemical heterogeneity, to corrosion performance in NaCl-MgCl2 salt, a proposed secondary coolant for MSRs. During Fiscal Year 2024, Idaho National Laboratory investigators in the AMMT program, utilized SS316H bars, fabricated with laser bed powder fusion at Los Alamos National Laboratory, to establish and optimize the workflow for evaluating these process-to-performance relationships. Standard practices for specimen preparation were established using these specimens, with particular focus on descaling and sectioning methods that align with ASTM guidelines. A comprehensive experimental design for static corrosion testing was developed, with pre- and post-exposure analysis utilizing optical microscopy and scanning electron microscopy. So far standard descaling techniques were optimized, one static corrosion test was conducted on the LANL AM SS316H specimens, and pre- and post-corrosion practices were established. In addition, the work package yielded a review paper on corrosion testing gaps for AM materials in nuclear applications and submitted a proposal for a rapid-turnaround experiment to the Nuclear Science User Facilities Program to investigate the combined effects of proton irradiation and corrosion on AM SS316H. This work package establishes a foundation for evaluating processing-to-performance relationships for AM SS316H in harsh conditions, contributing to the safe and efficient design of components for next-generation nuclear reactors. The creation of a standardized methodology and the generation of relevant publications and future research pathways represent significant strides towards integrating AM materials into critical applications where corrosion resistance is paramount.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Testing to Evaluate Processes Expected to Occur during MSR Salt Spill Accidents

Obtaining a license for a new nuclear reactor requires the identification and assessment of the potential consequences of specified accident scenarios, which are achieved using accident progression models. Those models need to be parameterized and validated using experimental data, but existing experimental data addressing processes relevant to molten salt reactor accidents are sparse. Specifically, experimental data that quantify the sensitives of important processes to the initial conditions of the spill, the ambient environment, and the containment features are needed to parameterize individual process models. Integrated experiments that simulate accident scenarios are also needed to provide data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation. The overarching objectives of this work are to develop the methods for simulating the targeted processes, to determine the effectiveness of the methods in producing the data required for model development, to generate data that can be used to parameterize individual process models, and to provide key insights into the behavior of spilled molten salt that should be considered in models. Experimental methods were designed to quantify aspects of individual processes expected to occur during or after a molten salt spill accident that will affect the fate of spilled molten salt and the radionuclides within. These processes include 1) molten salt spreading and heat transfer, 2) molten salt flowing and freezing in tubing, 3) stainless steel corrosion kinetics in molten salt, and 4) molten salt splashing and aerosol generation. The initial tests described in this report were conducted using eutectic FLiNaK to demonstrate the test methods, the data that are generated, and the analyses of the data to derive values needed for modeling. The primary variables that were tested include initial salt temperature and the presence of volatile surrogate fission products (e.g., cesium and iodine). The developed methods are shown to be effective in quantifying the desired processes and can be applied to study more complex salt compositions of interest to molten salt reactor developers, a wide range of environmental conditions of interest to modelers, and additional variables relevant to salt spill accidents. The developed methods and insights gained from laboratory tests can also be incorporated in future large-scale integrated tests used to simulate molten salt spill accidents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Combining data and theory for derivable scientific discovery with AI-Descartes

Abstract Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Experimental Protocols for Studying Organic Non-aqueous Redox Flow Batteries

We report that Redox flow batteries (RFBs) are promising devices for grid-scale energy storage due to the decoupling of power and energy, which can be independently scaled by the electrode area and storage tank size, respectively. To date, only aqueous RFBs, such as the vanadium RFB, have been implemented commercially. Nevertheless, the limited energy densities and high-cost materials may preclude their wider market penetration. Organic non-aqueous redox-flow batteries (O-NRFBs), which utilize redox-active organic molecules (ROMs), have been offered as an attractive alternative. Many possible advantages include the use of earth-abundant elements (C, H, N, O, S, F), wherein the ROMs can be prepared from low-cost and sustainable materials. Additionally, a large variety of electroactive moieties are accessible as building blocks, providing a synthetic platform to tune the properties of ROMs through rational design. As a consequence, the development of novel ROMs has attracted researchers with diverse backgrounds, prompting remarkable innovations in the past decade. However, consistency in experimental protocols (e.g., electrochemical methods, cycling stability, experimental conditions) has not coincided with this uptick in research, leading to sometimes ambiguous and incomparable results. This is further convoluted by the complexity innate to battery development, such as cell design, detection, and characterization of reactions and active components. The O-NRFB application imposes stringent requirements on the physical or/and chemical processes involved in electrochemical cycling. Yet such considerations are often overlooked. Further, while quantum mechanical calculations provide a convenient tool for evaluating and selecting ROM candidates, this simulation is not always performed. Thus, in this Energy Focus, we detail a means to standardize experimental protocols for studies of O-NRFBs and suggest practices to facilitate fundamental understanding and development of ROMs.

25 ENERGY STORAGE↗
DOE OSTI2022

Embedded, Real-Time, and Distributed Traveling Wave Fault Location Method Using Graph Convolutional Neural Networks

This work proposes and develops an implementation of a fault location method to provide a fast and resilient protection scheme for power distribution systems. The method analyzes the transient dynamics of traveling waves (TWs) to generate features using the discrete wavelet transform (DWT), which are then used to train several graph convolutional network (GCN) models. Faults are simulated in the IEEE 34-node system, which is divided into three protection zones (PZs). The goal is to identify the PZ in which the fault occurs. The GCN models create a distributed protection scheme, as all nodes are able to retrieve a prediction. Given that message-passing between nodes occurs both during training and in the execution of the model, the resiliency of such schemes to communication losses was analyzed and demonstrated. One of the models, which only uses voltage measurements, was implemented on a Texas Instruments F28379D development board. The execution times were monitored to assess the speed of the protection scheme. It is shown that the proposed method can be executed in approximately a millisecond, which is comparable to existing TW protection in the transmission system. For experimental purposes, a DWT-based detection method is employed. A design of a setup to playback TWs using two development boards is also addressed.

Jiménez-Aparicio, Miguel (ORCID:000000016864461X)↗
DOE OSTI2024

Perovskite/Perovskite Tandem Photoelectrodes for Low-Cost Unassisted Photoelectrochemical Water Splitting

In this project, we aim to address the challenges of achieving efficient and cost-effective unassisted photoelectrochemical water splitting using perovskite/perovskite tandem photoelectrodes. We utilized the following unique approaches to advance our innovation. (1) We developed stable and efficient low-E g (1.2 – 1.4 eV) perovskites as the bottom electrodes. We demonstrated approaches to improve the photovoltaic performance and photothermal stability of low-E g Sn-Pb iodide perovskite solar cells. (2) We developed a low-temperature synthesis route to fabricate wide-E g (>1.8 eV) perovskite top electrodes. By combining theoretical and experimental investigation, we found methods to reduce the formation of defects and dislocations in the wide-E g mixed halide perovskites and suppress halide segregation. (3) We developed a robust metal oxide-based interconnecting layer to integrate two perovskite layers into tandem photoelectrodes. Our monolithically integrated tandem devices feature a high V OC of more than 2 V and a high J SC of more than 15 mA/cm 2 . We showed the new design of the tandem photoelectrodes that is critical to the stable operation of tandem photoelectrodes for unassisted PV/PEC water splitting. (4) We demonstrated a water-impermeable barrier of carbon paste/epoxy/metal foil composite, which can prevent photocorrosion and water ingress of perovskite active layers. This surface protection enabled the operation of perovskite photoelectrodes in water and significantly enhanced the long-term stability of our tandem devices. (5) We conducted standardized PEC characterization in collaboration with NREL and reported accurate determination of solar-to-hydrogen conversion efficiencies of perovskite/perovskite tandem photoelectrodes. At the end of the project, we demonstrated perovskite/perovskite tandem photoelectrodes with STH efficiencies of up to 18% and less than 20% efficiency loss after continuous operation for more than 500 hours in water. Our results demonstrate the potential to develop a low-cost, durable, and efficient water-splitting system that meets the DOE 2026 and 2031 cost targets for hydrogen production.

08 HYDROGEN↗
DOE OSTI2020

Computational Methods to Accelerate Development of Corrosion Resistant Coatings for Industrial Gas Turbines

Oxidation resistant overlay coatings protect the underlying superalloy component in industrial gas turbines from oxidation attack. Rate of depletion of the Al-rich β-phase in the bond coat governs the lifetime of these coatings. The applicability of a computational method in accelerating the development of corrosion resistant coatings and significantly reducing the extensive experimental effort to predict coating lifetimes and microstructural changes in three-coated Ni-based superalloys for real operational durations (20–40 kh) was undertaken in the present study. Scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and electron microprobe analysis (EPMA) were employed to characterize MCrAlY-coated superalloy substrates (1483, 247 and X4) after exposure at 900 °C in air + 10% H 2 O for up to 20,000 h. The model predicted the longest coating lifetime for the coating on X4 substrate. Precipitation of γ' in the coatings was correctly predicted for all three coating systems. Additionally, the model was able to predict the formation of topologically close packed (TCP)-phases in the investigated coating systems.

Pillai, Rishi R.↗
DOE OSTI2024

Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing

Detecting anomaly in fatigue and fracture experimental materials science is an interesting yet challenging topic. The reasons are threefold. First, the anomalous microstructure feature that gives rise to structural failure is small, sometimes in the order of 10 -7 of the interrogated volume. This, in turn, results in a highly imbalanced classification problem in machine learning (ML). Second, the consequence is high, in the sense that the test specimen is destructed in such case. Third, the convolution between microstructure stochasticity and the small probability of void nucleation, growth, and coalescence makes failure and fracture a hard-to-predict and challenging problem in materials science due to its irreproducibility, even experimentally. In this paper, we developed a materials digital twin and applied anomaly detection methods to detect voids and anomaly in additive manufacturing (AM). The materials digital twin is driven by two integrated computational materials engineering (ICME) models, which are kinetic Monte Carlo (kMC) and crystal plasticity finite element method (CPFEM). In conclusion, we demonstrated that by using anomaly detection, it is possible to detect voids and other defects in materials digital twin, which paves way for future research in integrating materials digital twin with its physical counterpart.

ICME↗
DOE OSTI2025

Machine learning models for volumetric swelling in uranium nitride

Machine learning methods are applied to predict the volumetric swelling rate of the nuclear fuel uranium nitride (UN) over various temperatures, irradiation conditions, and power densities. Both kernel-based methods and symbolic regression models for UN swelling are developed and compared with multiple experimental datasets. We find that the UN pellet geometry and dimensions must be taken into account to accurately model swelling behavior. Strong agreement is observed between the developed machine learning models and the data. The predictive error generated by the machine learning models improves on empirical models taken from the literature. Sensitivity analysis is performed to determine which properties such as temperature, burnup, and power density, are most important in the swelling process. We find that machine learning can be used to quickly develop accurate swelling models for nuclear materials. In conclusion, the presented results illustrate the potential of machine learning to determine volumetric swelling in UN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

On-line Inductively Coupled Plasma Mass Spectrometry Reveals Material Degradation Dynamics of Au and Cu Catalysts during Electrochemical CO 2 Reduction

A significant challenge in commercializing electrochemical CO 2 reduction (CO 2 R) is achieving catalyst durability. Here, in this study, online inductively coupled mass spectrometry (ICP–MS) was used to investigate catalyst degradation via nanoparticle detachment and/or dissolution into metal ions under CO 2 R operating conditions in 0.1 M KHCO 3 . We developed an experimental framework with ex situ characterization to validate the online ICP–MS method for in situ evaluation of degradation from metal foils. By varying the applied potential and microenvironment (CO 2 vs N 2 -saturated electrolyte), we gained insights into the degradation of Au and Cu foils under CO 2 R and hydrogen evolution reaction (HER) conditions. While both Au and Cu foils were observed to be stable to dissolution in these regimes, degradation via nanoparticle detachment from the foil surface at the femtogram scale was observed as a function of reaction conditions, providing new insights into material degradation mechanisms. When applying potential steps at −0.1 and −1.0 V vs the reversible hydrogen electrode (RHE), Au was found to degrade via nanoparticle detachment under CO 2 R operating conditions more than under HER conditions, while Cu was found to degrade via nanoparticle detachment in similar amounts during both reactions. Au lost ∼1.8× more mass and ∼7.5× more nanoparticles than Cu under CO 2 R operating conditions. This study demonstrates the use of online ICP–MS to gain insight into the degradation of Au and Cu, the importance of studying unconventional degradation mechanisms such as nanoparticle detachment, and that online ICP–MS can be further utilized to gain fundamental understanding of catalyst durability for a variety of reaction systems.

Yan, Katherine [Stanford Univ., CA (United States)↗
DOE OSTI2021

Tuning the electronic structure of Ag-Pd alloys to enhance performance for alkaline oxygen reduction

Alloying is a powerful tool that can improve the electrocatalytic performance and viability of diverse electrochemical renewable energy technologies. Herein, we enhance the activity of Pd-based electrocatalysts via Ag-Pd alloying while simultaneously lowering precious metal content in a broad-range compositional study focusing on highly comparable Ag-Pd thin films synthesized systematically via electron-beam physical vapor co-deposition. Cyclic voltammetry in 0.1 M KOH shows enhancements across a wide range of alloys; even slight alloying with Ag (e.g. Ag 0.1 Pd 0.9 ) leads to intrinsic activity enhancements up to 5-fold at 0.9 V vs. RHE compared to pure Pd. Based on density functional theory and x-ray absorption, we hypothesize that these enhancements arise mainly from ligand effects that optimize adsorbate–metal binding energies with enhanced Ag-Pd hybridization. This work shows the versatility of coupled experimental-theoretical methods in designing materials with specific and tunable properties and aids the development of highly active electrocatalysts with decreased precious-metal content.

25 ENERGY STORAGE↗
DOE OSTI2021

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-based Inverters

Grid-forming inverters rely upon an internal reference to regulate the grid 's voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller's clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller's clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗
DOE OSTI2022

The importance of phonon spectrum measurements for accurate prediction of thermal scattering laws [Slides]

Although approximate phonon spectra (e.g. Debye model) are sufficient to reproduce integral quantities (e.g. total INS cross section) in reasonable agreement with the measured data, more accurate phonon spectra are needed to achieve agreement with the differential data. SANS component is essential for reproducing the total scattering cross section; this is the case for nanodiamonds and other materials where SANS components are present (such as porous materials like nuclear graphite). A format proposal for SANS data in ENDF or GNDS is needed. Therefore, differential (e.g. phonon spectrum) and integral (e.g. total cross section) measurements are necessary in the process of creating an ENDF evaluation. We have successfully developed a method by which ENDF evaluations can be directly compared to the relevant experimentally measured quantities. INS experiments at SNS, ILL, ISIS, and, in the future, ESS, as well as total cross section measurements at the VESUVIO instrument at ISIS, are accessible through user programs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Empirical Evaluation of GPS Clock Accuracy for Isochronous Droop-Based Inverters: Preprint

Grid-forming inverters rely upon an internal reference to regulate the grid’s voltage and frequency. Without a reliable reference, issues such as loss of synchronism, frequency instability, and unequal power sharing can occur. One proposed internal phase reference for grid-forming inverters is generated by the controller’s clock, but this is affected by nonidealities in the crystal oscillator leading to time drift in the phase reference. To improve the controller’s clock accuracy, the Global Positioning System (GPS) can be used to calibrate the internal clock. Previously, GPS-based clock calibration was explored theoretically and various methods were developed for mitigating frequency/phase drift at the power system level. This paper experimentally validates the direct performance of GPS time-calibration at the controller level and justifies its use in maintaining an accurate phase reference for droop-based grid-forming inverters.

clock drift↗