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DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Assessment of integral models for non-Boussinesq lazy plumes using numerical simulations

Integral modelling of turbulent buoyant plumes is crucial for rapid predictions of plume characteristics. While the governing equations are typically derived using self-similarity and a Boussinesq approximation, these assumptions may not hold for plumes originating from finite-area sources with large density ratios. Here, this work evaluates the accuracy of integral-scale models for non-Boussinesq lazy plumes using high-fidelity numerical simulations of turbulent helium plumes. We analyse the plume kinematics by computing vertical fluxes, plume radius and radial profiles, establishing some disparities between common practice and physical accuracy. We identify how the definition of the plume radius changes the perception of the plume structure when the flow is not self-similar and derive a relationship between the flux-based and threshold-based definitions without requiring self-similarity. We then examine the plume dynamics by evaluating the source terms from the governing plume equations. Our results support neglecting diffusive and viscous effects but emphasise the importance of the mean pressure gradient, even in the self-similar regime. Two coefficients need to be modelled: the well-known entrainment coefficient and the lesser-known momentum correction coefficient, which is a correction required for the momentum equation to account for self-similar and slender approximations. The momentum correction coefficient is found to be approximately constant and slightly greater than the assumed value of 1. The standard entrainment coefficient models perform well up to a local Richardson number three times the asymptotic value but overpredict entrainment for larger Richardson numbers. We propose a correction using the known finite limit of entrainment at infinite Richardson number.

Meehan, Michael Alexander [Sandia National Laborat↗

DOE OSTI2022

Data-driven model for divertor plasma detachment prediction

We present a fast and accurate data-driven surrogate model for divertor plasma detachment prediction leveraging the latent feature space concept in machine learning research. Our approach involves constructing and training two neural networks: an autoencoder that finds a proper latent space representation (LSR) of plasma state by compressing the multi-modal diagnostic measurements and a forward model using multi-layer perception (MLP) that projects a set of plasma control parameters to its corresponding LSR. By combining the forward model and the decoder network from autoencoder, this new data-driven surrogate model is able to predict a consistent set of diagnostic measurements based on a few plasma control parameters. In order to ensure that the crucial detachment physics is correctly captured, highly efficient 1D UEDGE model is used to generate training and validation data in this study. The benchmark between the data-driven surrogate model and UEDGE simulations shows that our surrogate model is capable of providing accurate detachment prediction (usually within a few per cent relative error margin) but with at least four orders of magnitude speed-up, indicating that performance-wise, it has the potential to facilitate integrated tokamak design and plasma control. Comparing with the widely used two-point model and/or two-point model formatting, the new data-driven model features additional detachment front prediction and can be easily extended to incorporate richer physics. This study demonstrates that the complicated divertor and scrape-off-layer plasma state has a low-dimensional representation in latent space. Understanding plasma dynamics in latent space and utilising this knowledge could open a new path for plasma control in magnetic fusion energy research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Autonomous aerial flight path inspection using advanced manufacturing techniques

Robotic systems have shown capabilities to perform inspection tasks in dangerous and difficult-to-access environments, such as those found in different components of power plants. However, most of the current robotic inspection technology is designed for specific components. Aerial robots, commonly termed as Drones, have raised an option to inspect a wider range of structural components. Nevertheless, current aerial inspecting technology still relies on a human pilot with limited line of sight, field of view and a reduced perception as the drone flies away, which prevents performing close-quarter inspection in intricate, structurally complex and GPS-denied environments. This work introduces offline inspection path generation methods based on robotics-integrated to manufacturing techniques. One method uses computer-aided manufacturing (CAM) techniques and the other an additive manufacturing (AM) approach to generate the flight path. That is to say, the drone would fly along the path described by a 3D (Three Dimensional) printer’s extruder or a CNC (Computer Numerical Control) machining tool, enabling to fly very close the structure even in physical structures with a complex geometry. Once the trajectories are generated, they are introduced for its validation in the Gazebo robotics simulator. Simulation results demonstrate the proper performance of the method and confirm that this approach can be used for close inspection of structural components.

42 ENGINEERING↗

DOE OSTI2025

Molecular Mass Growth Processes to Polycyclic Aromatic Hydrocarbons through Radical–Radical Reactions Exploiting Photoionization Reflectron Time-of-Flight Mass Spectrometry

Polycyclic aromatic hydrocarbons (PAHs) represent critical building blocks in molecular mass growth processes to carbonaceous nanoparticles, referred to as interstellar and circumstellar grains along with soot particles in astrophysical environments and combustion systems, respectively. Recent advancements on elucidating elementary steps to PAHs have utilized reactions of aromatic radicals, resonantly stabilized free radicals, and aliphatic radicals with closed shell hydrocarbons. However, the role of radical–radical reactions (RRRs) leading to PAHs has remained largely unexplored on the molecular level due to preceding experimental challenges in producing sufficiently high number densities of radical reactants for isomer-selective detection of products from bimolecular and termolecular reactions. This Account offers the latest developments in our knowledge on the mechanisms and pathways to PAHs via RRRs probed in a chemical microreactor at temperatures as high as 1600 K. Product preservation in a molecular beam coupled with synchrotron vacuum ultraviolet photoionization reflectron time-of-flight mass spectrometry and photoelectron photoion coincidence spectroscopy enabled isomer-selective detection of PAHs of up to three rings by their photoionization efficiency curves, which were fit with a linear combination of reference curves for identification. Experiments were combined with computational fluid dynamics modeling of the physicochemical processes in the microreactor, as well as high-level electronic structure calculations to reveal the reaction pathways of each system. Six distinct reaction mechanisms were discovered in this work: propargyl addition─benzannulation (PABA), methyl addition─ring expansion (MARE), cyclopentadienyl addition─naphthylization (CPAN), fulvenallenyl addition─cyclization─aromatization (FACA), benzyl addition─aromatization (BAA), and phenyl addition─pentacyclization (PAP). By systematically varying the number of carbon atoms in the radical reactants, molecular mass growth processes involving reactions between radicals with odd numbers of carbon atoms access aromatics carrying one, two, or three six-membered rings, whereas reactions between even- and odd-carbon-numbered radicals produce aromatics combining five- and six-membered rings. Our investigations reveal unconventional cycloadditions on excited state triplet surfaces, additions of radicals to low spin density carbon-centered radicals, spiroaromatic and fulvene-type intermediates, and highly strained bicyclic reaction intermediates, challenging current perceptions of PAH molecular mass growth processes. All of the listed mechanisms, except for FACA, feature endoergic reactions or barriers which lie above the separated reactants and therefore might be central to circumstellar environments of carbon-rich stars and planetary nebulae as their descendants, but they play no role in the gas phase of cold molecular clouds where temperatures as low as 10 K dominate. Altogether, this work provides detailed reaction mechanisms of PAH growth processes, advancing our knowledge of the chemistry of carbonaceous matter in the universe.

Addition reactions↗

DOE OSTI2025

Postfire Biogeochemical Processes: Implications to Source Water Quality in Fire-Influenced Watersheds

Forested watersheds are instrumental in providing purified and reliable water to millions of people worldwide. The changing climate has increased the frequency and severity of global fire events. Forested watersheds and their ecosystem functions are greatly disrupted during fire activity. Postfire concerns in forested watersheds include unpredictable and potentially simultaneous alterations in source water quality and hydro-biogeochemical processes. Here, the degree of fire severity can complexly modify water quality through the production of fire-transformed constituents on the burned forest floor (i.e., nutrients, metal(loid)s, dissolved organic matter, and the formation of disinfection byproducts). Correspondingly, fire severity and postfire rainfall patterns can refine hydro-biogeochemical processes that influence the transport of the fire-transformed constituents (i.e., vegetation function, soil structure, hydrological pathways, and microbial communities). Postfire alterations to water quality and hydro-biogeochemical processes introduce further complexity with varying temporal influence, which ranges from months to decades. As postfire water quality and watershed response research progresses, it is essential to homogenize interdisciplinary expertise to bridge knowledge gaps between fields ranging from forest ecology, hydrology, microbiology, and geochemistry. A multidisciplinary approach in wildfire research will facilitate a comprehensive perception of the diverse water quality risks associated with fire activity and mitigate fire concerns on a global level.

Disinfection Byproducts↗

DOE OSTI2018

Analysis of the Frequency and Diversity of 1,3-Dialkylimidazolium Ionic Liquids Appearing in the Literature

The hypothetical assertion that there are potentially millions of ionic liquids (ILs) can be validated using basic knowledge of IL precursors and simple calculations. While it is an interesting thought exercise to ponder the possibilities of ILs, it is important to investigate how many discrete ILs (i.e., unique cation and anion pairings) have actually been synthesized and reported in the literature. A complete analysis of all ILs is a daunting task, especially if the definition of what constitutes an IL is broad. Nonetheless, insight can be gained into the use of ILs over the past ~20 years from a focused analysis of systematically varied 1,3-dialkylimidazolium-based ILs (i.e., [R 1 R 2 im][X], where R 1 and R 2 are n-alkyl chains and X is either a halide or molecular anion). This family of ILs includes many of the most widely used and most thoroughly studied IL substances, including 1-butyl-3-methylimidazolium hexafluorophosphate ([C 4 mim][PF 6 ]) and 1-ethyl-3-methylimidazolium bistriflimide ([C 2 mim][Tf 2 N]). Using data retrieved from SciFinder searches, we analyzed the variety and frequency of 1,3-dialkylimidazolium-based ILs appearing in the literature. Our analysis reveals that there is a relatively large number of simple 1,3-dialkylimidazolium cations which have not yet been synthesized. Our findings indicate that despite the broad possibilities of IL structures available, there are but a handful of ILs that are commonly used and studied. Within the 1248 [R 1 R 2 im][X] ILs studied, there were only 12 cations extensively used, which included [R 1 R 2 im] + (R 1 = C 1 and R 2 = C 1 –C 12 ). Of the 16 anions studied, only 5, including [BF 4 ] – , [Cl] – , [PF 6 ] – , [Tf 2 N] – , and [Br] – , were used significantly. Thus, it appears that although ILs can be used as designer solvents with task-specific properties, there is a small default subset of ILs, which are “go-to” or “one-size-fits-all.” Here, we rationalize the current state of the IL landscape in terms of the historical perceptions (and misconceptions) around ILs, familiarity, availability and cost of starting materials, commercial availability of ILs, and the motivations from which researchers choose to synthesize and characterize new ILs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

In the Mix : A Workshop Merging Computational Chemistry and Electrochemistry Alongside Data Science

As chemistry expands to more complex and interdisciplinary areas, a new generation of diverse researchers must engage with science and learn effective cross-disciplinary collaboration and communication. To these ends, we designed and implemented In the Mix, a graduate student-led, two-day workshop for undergraduate students promoting collaborative science in the context of energy storage innovations. Here, the interactive workshop was designed for future and emerging researchers to gain hands-on experience with data science, computational chemistry, and electrochemistry techniques that are critical for developing materials for battery technologies. Participants also visited commercial renewable energy facilities to help them connect discovery-based research with industry and broader societal considerations. The workshop content and structure ensured that participants experienced the interrelatedness of the fields and understood the importance of collaborative research to yield scientific advances with real-world applications. An external team evaluated the workshop and participants’ perceptions of their experiences. While our research context was energy storage, the workshop goals and outcomes are applicable to other contexts. Interdisciplinary, experiential workshops are a key avenue to broadening participation in science and research, and the ideas presented here can be readily modified for other scientific contexts and/or incorporated as broader impact activities.

25 ENERGY STORAGE↗

DOE OSTI2024

Catalytic Reaction Triggered by Magnetic Induction Heating Mechanistically Distinguishes Itself from the Standard Thermal Reaction

As a recent advancement in chemical engineering, magnetic induction heating (MIH) is utilized to initiate the intended reactions by enabling the self-heating of the ferromagnetic catalyst particles. While MIH can be energy-efficient and industrially scalable, its full potential has been underappreciated in catalysis because of the perception that MIH is merely an alternative heating approach. Unexpectedly, we show that the MIH-triggered reaction could go beyond standard thermal catalysis. Specifically, by probing the representative Pt/Fe 3 O 4 catalysts with CO oxidation in both thermal and MIH modes with consistent temperature profiles and catalyst structures, we found that the MIH mode boosts the reactivity more than 25 times by modifying Pt-FeO x interfacial synergies and promoting facile oxidation of the adsorbed carbonyl species by atomic oxygen. Further, as we preliminarily observed, this beneficial MIH-catalysis can be translational to other thermal reactions, potentially paving the way to launch MIH-catalysis as a distinct reaction category.

CO oxidation↗

DOE OSTI2021

Polarization-Insensitive Medium-Switchable Holographic Metasurfaces

The adoption of metasurfaces has led to revolutionary advances in holography due to improved compactness, integrability, and performance. Switchable meta-holograms projecting different replay field images in a controllable manner are highly desirable. Still, existing technologies generally rely on the use of polarized light and additional optics to facilitate switching. Consequently, the potential benefits afforded through the use of metasurfaces are limited both by the system complexity and a fixed relationship between the optical input and output. In this manuscript, we demonstrate polarization-insensitive metasurfaces encoding arbitrary and independent holograms, which can be switched between by changing the refractive index of the infiltration medium while maintaining identical illumination conditions. Finally, by sidestepping the requirements for high-performance light sources, switching optics, or delicate alignment, this approach points toward ultracompact and cost-effective switchable meta-holograms for various practical applications, such as holographic image projection, eye-perceptible sensors, optical information storage, processing, and security.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Where Are White Roofs More Effective in Cooling the Surface?

Solar reflective roofs (also called white or cool roofs) are a common heat mitigation strategy. By reflecting more sunlight than regular roofs, cool roofs experience lower surface temperatures and produce less heating of the surrounding air. The effectiveness of cool roofs, quantified by the surface temperature difference between cool roofs and regular roofs ??????, is known to vary spatially. A common perception is that ?????? is controlled by solar radiation that reaches the roof surface. Here we use an Earth System Model and a surface energy balance model to show that the spatial variability of ??????, when normalized by the albedo difference between cool roofs and regular roofs (????), is in fact more controlled by an energy distribution factor that encodes the efficiencies of surface energy balance components in dissipating heat. Our results suggest that painting the roof white is more effective in reducing the roof surface temperature when the roof has less water holding capacity and smaller thermal admittance and is located in places with more solar radiation, less precipitation, and lower wind speed.

Wang, Linying↗

DOE OSTI2026

Comparative Analysis of Report-Back of Research Results Strategies for Personal Chemical Exposure Data

Background. Report-back of research results (RBRR) is ethically supported and highly requested by participants yet lacks broadly transferable guidelines for RBRR. Effective RBRR must be responsive to target audience needs and may not be addressed by a ‘one-size-fits-all’ approach. Objective. Within a subset of our 19 studies on RBRR, we had the unique opportunity to carry out a comparative analysis of RBRR strategies across cohorts with similar development and evaluation methods, yet distinct in life stage, geography, number and type of chemicals assessed, and community contexts. Methods. We highlight key outcomes from three environmental health studies: an ongoing New York, NY cohort (Fair Start; n=486) and a Detroit, MI cohort (CLEAR; n=34) assessing exposure to ambient urban pollution during pregnancy, and a longitudinal cohort in Houston, TX (Houston-3H) following Hurricane Harvey (n=312). Focus group and survey data were analyzed to identify lessons learned and explore how RBRR supports understanding of environmental health. Results. Commonalities emerged in RBRR development, design, organization, and data visualization, as well as in how RBRR can contribute to an understanding of health-environment connections. Differences included preferences for individual versus community level findings, as well as distinguishable contextual considerations. For pregnancy cohorts, messaging was framed with cultural sensitivity, and to avoid unintended consequences of parental guilt due to prenatal exposures. In the post-disaster Houston-3H study, participants requested additional transparency regarding sampling design and study rationale. Significance. All RBRR case studies reported chemicals without known regulatory or health guidelines, so results were contextualized within the study population. Participants across cohorts requested multi-study comparisons to better understand their results beyond their communities. While foundational RBRR elements (e.g. plain language, graphic organizers) may supersede cohort-specific differences, RBRR should be personalized to encompass perceptions of health across different life-stage, cultural, and environmental contexts.

Vogel, Taylor J.↗

DOE OSTI2020

Structural signatures in EPR3 define a unique class of plant carbohydrate receptors

Abstract Receptor-mediated perception of surface-exposed carbohydrates like lipo- and exo-polysaccharides (EPS) is important for non-self recognition and responses to microbial associated molecular patterns in mammals and plants. In legumes, EPS are monitored and can either block or promote symbiosis with rhizobia depending on their molecular composition. To establish a deeper understanding of receptors involved in EPS recognition, we determined the structure of the Lotus japonicus ( Lotus ) exopolysaccharide receptor 3 (EPR3) ectodomain. EPR3 forms a compact structure built of three putative carbohydrate-binding modules (M1, M2 and LysM3). M1 and M2 have unique βαββ and βαβ folds that have not previously been observed in carbohydrate binding proteins, while LysM3 has a canonical βααβ fold. We demonstrate that this configuration is a structural signature for a ubiquitous class of receptors in the plant kingdom. We show that EPR3 is promiscuous, suggesting that plants can monitor complex microbial communities though this class of receptors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Alloying–realloying enabled high durability for Pt–Pd-3d-transition metal nanoparticle fuel cell catalysts

Abstract Alloying noble metals with non-noble metals enables high activity while reducing the cost of electrocatalysts in fuel cells. However, under fuel cell operating conditions, state-of-the-art oxygen reduction reaction alloy catalysts either feature high atomic percentages of noble metals (>70%) with limited durability or show poor durability when lower percentages of noble metals (<50%) are used. Here, we demonstrate a highly-durable alloy catalyst derived by alloying PtPd (<50%) with 3d-transition metals (Cu, Ni or Co) in ternary compositions. The origin of the high durability is probed by in-situ/operando high-energy synchrotron X-ray diffraction coupled with pair distribution function analysis of atomic phase structures and strains, revealing an important role of realloying in the compressively-strained single-phase alloy state despite the occurrence of dealloying. The implication of the finding, a striking departure from previous perceptions of phase-segregated noble metal skin or complete dealloying of non-noble metals, is the fulfilling of the promise of alloy catalysts for mass commercialization of fuel cells.

25 ENERGY STORAGE↗

DOE OSTI2022

Native lattice strain induced structural earthquake in sodium layered oxide cathodes

Abstract High-voltage operation is essential for the energy and power densities of battery cathode materials, but its stabilization remains a universal challenge. To date, the degradation origin has been mostly attributed to cycling-initiated structural deformation while the effect of native crystallographic defects induced during the sophisticated synthesis process has been significantly overlooked. Here, using in situ synchrotron X-ray probes and advanced transmission electron microscopy to probe the solid-state synthesis and charge/discharge process of sodium layered oxide cathodes, we reveal that quenching-induced native lattice strain plays an overwhelming role in the catastrophic capacity degradation of sodium layered cathodes, which runs counter to conventional perception—phase transition and cathode interfacial reactions. We observe that the spontaneous relaxation of native lattice strain is responsible for the structural earthquake (e.g., dislocation, stacking faults and fragmentation) of sodium layered cathodes during cycling, which is unexpectedly not regulated by the voltage window but is strongly coupled with charge/discharge temperature and rate. Our findings resolve the controversial understanding on the degradation origin of cathode materials and highlight the importance of eliminating intrinsic crystallographic defects to guarantee superior cycling stability at high voltages.

25 ENERGY STORAGE↗

DOE OSTI2022

The incongruity of validating quantitative proteomics using western blots

Similar to the age-old reviewer request for quantitative PCR validation of RNA sequencing data, nearly every researcher using proteomics technologies has, at one time or another, been asked by a reviewer to provide “western blot validation” of their mass spectrometry-based protein abundance data. We believe this request demonstrates a lack of awareness amongst the plant biology community about the extraordinary improvements in cost, sensitivity and reliability the field of mass spectrometry-based proteomics has made in recent years. Here, in this study, as a group of experts in different domains of quantitative plant proteomics, we explain why “western blot validation” of quantitative proteomics data is both unnecessary and invalid. Furthermore, we invite our colleagues in the plant science community to update their perception of quantitative mass spectrometry as a sensitive and reliable method of protein identification and quantitation.

Mehta, Devang↗

DOE OSTI2023

Emergent topological quantum orbits in the charge density wave phase of kagome metal CsV 3 Sb 5

The recently discovered kagome materials AV 3 Sb 5 (A = K, Rb, Cs) attract intense research interest in intertwined topology, superconductivity, and charge density waves (CDW). Although the in-plane 2 × 2 CDW is well studied, its out-of-plane structural correlation with the Fermi surface properties is less understood. In this work, we advance the theoretical description of quantum oscillations and investigate the Fermi surface properties in the three-dimensional CDW phase of CsV 3 Sb 5 . We derived Fermi-energy-resolved and layer-resolved quantum orbits that agree quantitatively with recent experiments in the fundamental frequency, cyclotron mass, and topology. We reveal a complex Dirac nodal network that would lead to a π Berry phase of a quantum orbit in the spinless case. However, the phase shift of topological quantum orbits is contributed by the orbital moment and Zeeman effect besides the Berry phase in the presence of spin-orbital coupling (SOC). Therefore, we can observe topological quantum orbits with a π phase shift in otherwise trivial orbits without SOC, contrary to common perception. Our work reveals the rich topological nature of kagome materials and paves a path to resolve different topological origins of quantum orbits.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Low-temperature formation of polycyclic aromatic hydrocarbons in Titan’s atmosphere

The detection of benzene in Titan’s atmosphere led to the emergence of polycyclic aromatic hydrocarbons (PAHs) as potential nucleation agents triggering the growth of Titan’s orange-brownish haze layers. However, the fundamental mechanisms leading to the formation of PAHs in Titan’s low-temperature atmosphere have remained elusive. We provide persuasive evidence through laboratory experiments and computations that prototype PAHs like anthracene and phenanthrene (C 14 H 10 ) are synthesized via barrierless reactions involving naphthyl radicals (C 10 H 7 •) with vinylacetylene (CH 2 =CH–C≡CH) in low-temperature environments. These elementary reactions are rapid, have no entrance barriers, and synthesize anthracene and phenanthrene via van der Waals complexes and submerged barriers. This facile route to anthracene and phenanthrene—potential building blocks to complex PAHs and aerosols in Titan—signifies a critical shift in the perception that PAHs can only be formed under high-temperature conditions, providing a detailed understanding of the chemistry of Titan’s atmosphere by untangling elementary reactions on the most fundamental level.

79 ASTRONOMY AND ASTROPHYSICS↗