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DOE OSTI2023

In Situ Wind and Turbulence Measurements in a Field of Full-Size Parabolic Trough Solar Collectors

Concentrated Solar Power (CSP) is a promising method for using Solar power for electricity generation with thermal energy storage. One of the primary drivers of structural design costs of CSP collector structures is wind loading. To date, the design of these structures has relied on data from wind tunnels that do not adequately capture the dynamic effects observed at scale. NREL initiated a field measurement campaign at the operational Nevada Solar One (NSO) powerplant that uses parabolic troughs as solar collectors. The aim of the project is a detailed characterization of prevailing wind and turbulence conditions and resulting operational loads on parabolic troughs, providing insights on structural dynamic response, and generating a first-of-a-kind, comprehensive, high-resolution wind-loading dataset available for validating simulations of wind loading on collector structures. The measurements at NSO consist of Sonic anemometers on masts at different heights to characterize the incoming flow and conditions within and above the trough field, in combination with a Doppler Lidar scanning the horizontal plane above the troughs. The wind measurements at NSO have been continuously operating since October 2021 and provide a year-long dataset characterizing wind and turbulence conditions. The structural load measurements start in November 2022 and will complement the wind measurements. In this poster, we present first results of the wind measurement campaign by highlighting days with different atmospheric flow conditions. We identified three main factors altering the flow over the parabolic troughs: Wind speed, wind direction, and the angle of the parabolic troughs. The highest loads are expected when the wind blows perpendicular to the trough rows. In this case, the first rows experience the highest loads and block the subsequent rows, creating conditions with decreased wind speed and enhanced turbulence within the trough field. Also, turbulent length scales change. These affected conditions produce unique load cases on the structures that will be captured by the load measurements. If the wind blows along the trough rows, wind and turbulence conditions are less influenced by the troughs.

atmospheric turbulence↗

DOE OSTI2023

In Situ Wind and Turbulence Measurements in a Field of Full-Size Parabolic Trough Collectors

concentrated solar power↗

DOE OSTI2024

Candidate ferroelectrics via ab initio high-throughput screening of polar materials

Ferroelectrics are a class of polar and switchable functional materials with diverse applications, from microelectronics to energy conversion. Computational searches for new ferroelectric materials have been constrained by accurate prediction of the polarization and switchability with electric field, properties that, in principle, require a comparison with a nonpolar phase whose atomic-scale unit cell is continuously deformable from the polar ground state. For most polar materials, such a higher-symmetry nonpolar phase does not exist or is unknown. Here, we introduce a general high-throughput workflow that screens polar materials as potential ferroelectrics. We demonstrate our workflow on 1978 polar structures in the Materials Project database, for which we automatically generate a nonpolar reference structure using pseudosymmetries, and then compute the polarization difference and energy barrier between polar and nonpolar phases, comparing the predicted values to known ferroelectrics. Focusing on a subset of 182 potential ferroelectrics, we implement a systematic ranking strategy that prioritizes candidates with large polarization and small polar-nonpolar energy differences. To assess stability and synthesizability, we combine information including the computed formation energy above the convex hull, the Inorganic Crystal Structure Database id number, a previously reported machine learning-based synthesizability score, and ab initio phonon band structures. To distinguish between previously reported ferroelectrics, materials known for alternative applications, and lesser-known materials, we combine this ranking with a survey of the existing literature on these candidates through Google Scholar and Scopus databases, revealing ~130 promising materials uninvestigated as ferroelectric. Our workflow and large-scale high-throughput screening lays the groundwork for the discovery of novel ferroelectrics, revealing numerous candidates materials for future experimental and theoretical endeavors.

36 MATERIALS SCIENCE↗

DOE OSTI2023

ECAR-6589 Reflector Support Structure Analysis: Project #33526

The MARVEL microreactor consists of five main systems: MRS (MARVEL Reactor Structure), PGS (Power Generation System), FCS (Fuel Core System), RCS (Reactivity Control System), and ICS (Instrument Control System). The RSS (Reflector Control System) is a sub system of the MRS which contains the upper and lower reflector support plates which support and locate the stationary core reflector and provide vertical support for the control drums. They are suspended from the Primary Coolant System by bolted structural straps which utilize a turnbuckle to allow for adjustment and leveling of the support plates. The stainless-steel support plates are each formed from four quarter circle segments which are bolted together around the lower core barrel. Bearing plates of non-galling Nitronic 60 alloy are fitted to the inner diameter of the support plates to prevent adhesive wear between the plates and the core barrel as the barrel expands and contracts due to changes in the temperature of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Gravitational Form Factors of the Proton from Lattice QCD

The gravitational form factors (GFFs) of a hadron encode fundamental aspects of its structure, including its shape and size as defined from, e.g., its energy density. This Letter presents a determination of the flavor decomposition of the GFFs of the proton from lattice QCD, in the kinematic region 0 ≤−𝑡 ≤2 GeV 2 . The decomposition into up-, down-, strange-quark, and gluon contributions provides first-principles constraints on the role of each constituent in generating key proton structure observables, such as its mechanical radius, mass radius, and 𝐷 term.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Multifunctional nitrile additives for inducing pseudo-concentration gel-polymer electrolyte: Enabling stable high-voltage lithium metal batteries

High-voltage lithium metal batteries (LMBs) are promising for next-generation high-energy storage systems. Unfortunately, their implementation has been severely plagued by the interfacial instability between the high-voltage cathodes/lithium metal (LM) anodes and electrolytes. To tackle these challenges, a novel nitrile additive, 1,4-dicyanobenzene (DCB) (Synonyms: terephthalonitrile), is added to the in situ polymerized pentaerythritol tetraacrylate-based gel polymer electrolyte (GPE). The DCB additive, as demonstrated both theoretically and experimentally, plays a crucial role in altering the Li+ coordinated solvation structure within the GPE. This alteration leads to the formation of a pseudo-concentrated electrolyte with a tightly packed Li+ cluster, expanding the electrochemical stability window of the electrolyte. Moreover, the DCB-included GPE significantly improves its compatibility with both LM anode and high-voltage cathode, attributed to the modified solvation structure and the generated LiF-rich electrolyte/electrode interphases. Accordingly, the GPE enables stable cyclic performance of LMBs based on a 4.9 V LiNi 0.5 Mn 1.5 O 4 cathode at a low relative negative/positive ratio of 4, achieving a high reversible capacity of 123.8 mAh g -1 with a capacity retention of 87.7% over 500 cycles at 0.5 C. This work provides new insights into enhancing the cyclability of high-voltage LMBs via the synergistic effect of additives and GPE.

25 ENERGY STORAGE↗

DOE OSTI2025

Predicting metal-binding proteins and structures through integration of evolutionary-scale and physics-based modeling

Metals are essential elements in all living organisms, binding to approximately 50% of proteins. They serve to stabilize proteins, catalyze reactions, regulate activities, and fulfill various physiological and pathological functions. While there have been many advancements in determining the structures of protein-metal complexes, numerous metal-binding proteins still need to be identified through computational methods and validated through experiments. Here, to address this need, we have developed the ESMBind workflow, which combines evolutionary scale modeling (ESM) for metal-binding prediction and physics-based protein-metal modeling. Our approach utilizes the ESM-2 and ESM-IF models to predict metal-binding probability at the residue level. In addition, we have designed a metal-placement method and energy minimization technique to generate detailed 3D structures of protein-metal complexes. Our workflow outperforms other models in terms of residue and 3D-level predictions. To demonstrate its effectiveness, we applied the workflow to 142 uncharacterized fungal pathogen proteins and predicted metal-binding proteins involved in fungal infection and virulence.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Developing an Interactive OpenMP Book with Large Language Models

Abstract. This paper presents an approach to authoring a textbook titled Interactive OpenMP Programming with the assistance of Large Language Models (LLMs). The writing process utilized state-of-the-art LLMs, including Gemini Pro 1.5, Claude 3, and ChatGPT-4, to generate the initial structure and outline of the book, as well as the initial content for specific chapters. This content included detailed descriptions of individual OpenMP constructs and practical programming examples. The outline and content have then undergone extensive manual revisions to meet our book goals. In this paper, we report our findings about the capabilities and limitations of these LLMs. We address critical questions concerning the necessity of textbook resources and the effectiveness of LLMs in creating fundamental and practical programming content. Our findings suggest that while LLMs offer significant advantages in generating textbook content, they require careful integration with traditional educational methodologies to ensure depth, accuracy, and pedagogical effectiveness. The Interactive OpenMP Programming book is developed with the framework of Jupyter Book, enabling the execution of code within the book from the web browser, providing instant feedback and a dynamic learning experience that stands in contrast to traditional educational resources. The book represents a significant step towards modernizing programming education, offering insights into practical strategies for generating the textbook through advanced AI tools.

Large Language Model · OpenMP · Interactive Book ·↗

DOE OSTI2023

The interaction of wholesale electricity market structures under futures with decarbonization policy goals: A complexity conundrum

Competitive wholesale electricity markets can help facilitate energy system decarbonization by incentivizing investments in clean energy technologies that meet evolving system needs. We explore market structure impacts on generator operations and deployment by risk-averse, heterogeneous investor firms using the Electricity Markets and Investment Suite - Agent-based Simulation (EMIS-AS) model. Here we apply clean energy targets of 45%-100% by 2035 considering energy, ancillary services, capacity, and clean energy credit products and pricing and eligibility rules. Results highlight a complexity conundrum, whereby finding the "right" market design to achieve decarbonization goals and avoid unintended consequences can be a highly-nuanced, non-incremental challenge. Carefully designed energy-only markets can achieve the same clean energy targets as capacity market structures but with different revenue and profitability outcomes. Operating reserve demand curve-based scarcity pricing can substitute capacity markets for similar deployment outcomes. Carbon pricing alone is most effective at achieving decarbonization levels at low clean energy targets, and clean energy credit markets and carbon pricing are substitutionary at high clean energy targets. Restricting technology participation in capacity and operating reserve markets can impact deployment and operations, even for nonrestricted technologies. Adding an inertia product with fast frequency response yields insufficient provision at high clean energy targets, but work is needed to understand frequency requirements and capabilities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Light-trapping structures fabricated in situ for ultrathin III-V solar cells

Here, we describe a fully in situ method of fabricating light-scattering structures on III-V materials that generates a rough morphology via vapor phase etching and redeposition. Fully in situ methods support higher industrial throughput by utilizing the growth reactor to generate the light-trapping structures after device growth without removal from the reactor. We use HCl and PH 3 to etch and redeposit scattering morphologies on Ga 0.5 In 0.5 P in a dynamic hydride vapor phase epitaxy (D-HVPE) reactor. We show that the addition of PH 3 leads to redeposition during the vapor phase HCl etching of Ga 0.5 In 0.5 P and that HCl flow rate and time exposed to HCl-PH 3 each independently cause a linear increase in the redeposited feature size, indicating that redeposition proceeds by island growth in a III-Cl-limited, hydride-enhanced HVPE regime. Auger electron spectroscopy and scanning transmission electron microscopy with energy dispersive spectroscopy (STEM-EDS) reveal redeposition to be highly Ga-rich GaInP, i.e., Ga(In)P. The Ga-rich nature of the redeposition results from the higher thermodynamic driving force for Ga incorporation than for In during HVPE growth and the difference in the volatility of the III-Cl etch products. The resulting morphologies have high broadband scattering, as determined by normal specular reflectance and integrating sphere measurements, indicating effectiveness as light-scattering structures. In a 270-nm-thick GaAs photovoltaic device with a textured back surface, we achieve a 4.9% increase in short circuit current density (J SC ) without any loss in open-circuit voltage (V OC ) relative to a planar control using only a 60 s in situ texturing treatment.

14 SOLAR ENERGY↗

DOE OSTI2020

The influence of lattice defects, recombination, and clustering on thermal transport in single crystal thorium dioxide

Thermal transport is a key controlling property for thorium dioxide in many applications where defect-generating radiation fields are present. An understanding of the effect of nanoscale lattice defects on thermal transport in this material is currently unavailable due to a lack of high-quality, single crystal material from which unit processes may be investigated. In this work, a series of thorium dioxide single crystals are exposed to 2 MeV proton irradiation at room temperature and 600°C to create microscale regions with varying densities and types of point and extended defects. Defected regions are investigated using spatial domain thermoreflectance to quantify the change in thermal conductivity as a function of ion fluence as well as transmission electron microscopy and Raman spectroscopy to interrogate the structure of the generated defects. Together, this com- bination of methods provides important initial insight into defect formation, recombination, and clustering in thorium dioxide and the effect of those defects on thermal transport. These methods also provide a promising pathway for the quantification of the smallest-scale defects which cannot be captured using traditional microscopy techniques and play and outsized role in degrading thermal performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Multislice forward modeling of coherent surface scattering imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle X-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent surface scattering imaging (CSSI) is a powerful yet non-invasive technique similar to coherent X-ray diffractive imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Identification of Novel Microcystins Using High-Resolution MS and MS n with Python Code

Cyanotoxins called microcystins (MCs) are highly toxic and can be present in drinking water sources. Determining the structure of MCs is paramount because of its effect on toxicity. Though over 300 MC congeners have been discovered, many remain unidentified. In this work, a method is described for the putative identification of MCs using liquid chromatography (LC) coupled with high-resolution (HR) Orbitrap mass spectrometry (MS) and a new bottom-up sequencing strategy. Maumee River water samples were collected during a harmful algal bloom and analyzed by LC–MS with simultaneous HRMS and MS/MS. Unidentified ions with characteristic MC fragments (135 and 213 m/z) were recognized as possible novel MC congeners. An innovative workflow was developed for the putative identification of these ions. Python code was written to generate the potential structures of unidentified MCs and to assign ions after the fragmentation for structural confirmation. The workflow enabled the putative identification of eight previously reported MCs for which standards are not available and two newly discovered congeners, MC-HarR and MC-E(OMe)R.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Tuning 3-D Nanomaterial Architectures Using Atomic Layer Deposition to Direct Solution Synthesis

The ability to synthesize nanoarchitected materials with tunable geometries provides a means to control their functional properties, with applications in biological, environmental, and energy fields. To this end, various bottom-up and top-down synthesis processes have been developed. However, many of these processes require prepatterning or etching steps, making them challenging to scale-up to complex, nonplanar substrates. Furthermore, the ability to integrate nanomaterials into hierarchical arrays with precise control of feature spacing and orientation remains a challenge. One approach to overcome these patterning challenges is the use of surface modification layers to guide the resulting geometry of nanomaterial architectures grown from the substrate. A powerful strategy to accomplish this is what we will refer to as “surface-directed assembly,” where the resulting geometric parameters (feature size, shape, orientation) are predetermined by the initial surface layer. In particular, the use of Atomic Layer Deposition (ALD) to form a surface layer, followed by solution-based growth processes, has the ability to synthesize architected structures with tunable geometries on complex, nonplanar surfaces. Over the past decade, we have reported a series of studies where surface-directed assembly is used to synthesize ZnO nanowires (NWs) on top of a variety of substrates. In this case, a thin film of ZnO is deposited onto the substrate using ALD, which can guide the NW diameter, spacing, and angular orientation with respect to the substrate by controlling epitaxial relationships. Furthermore, we have shown that by depositing a submonolayer overcoat of a secondary material (e.g., amorphous TiO 2 ), nucleation sites are partially blocked, which can further tune the spacing between nanowires while minimizing changes to their other geometric properties. This approach can be used to generate multilevel hierarchical structures, such as hyperbranched NW arrays with tunable control of each level of hierarchy using ALD. Finally, we have demonstrated that the tunable control of geometric parameters can be scaled-up to curved, nonplanar substrates. This highlights the power of ALD to conformally and uniformly deposit the seed layers on complex substrates with subnanometer precision. To complement these seeded hydrothermal approaches, we expanded this strategy to include conversion chemistry of the initial ALD seed layers. For example, by replacing ZnO with Al 2 O 3 as the seed layer without changing the hydrothermal growth conditions, Al–Zn layered-double hydroxide nanosheets can be formed instead of nanowires. In another example of conversion chemistry, a solution anion-exchange process was used to incorporate sulfur into ALD metal oxide films. In both of these conversion processes, the properties of the initial ALD film enabled tuning of the resulting nanostructure geometry. In this Account, we describe the use of ALD to guide the growth of diverse nanomaterial systems, with tunable control over their geometry and composition. We further show how these approaches can be used to tune functional properties for a range of applications, including superomniphobic surfaces, antibiofouling coatings, and photocatalysis. In conclusion, we conclude with an outlook on how the combination of ALD and solution synthesis can enable future directions in scalable nanomanufacturing to overcome the limitations of traditional top-down and bottom-up approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Structural and functional insights into the interaction between the bacteriophage T4 DNA processing proteins gp32 and Dda

Abstract Bacteriophage T4 is a classic model system for studying the mechanisms of DNA processing. A key protein in T4 DNA processing is the gp32 single-stranded DNA-binding protein. gp32 has two key functions: it binds cooperatively to single-stranded DNA (ssDNA) to protect it from nucleases and remove regions of secondary structure, and it recruits proteins to initiate DNA processes including replication and repair. Dda is a T4 helicase recruited by gp32, and we purified and crystallized a gp32–Dda–ssDNA complex. The low-resolution structure revealed how the C-terminus of gp32 engages Dda. Analytical ultracentrifugation analyses were consistent with the crystal structure. An optimal Dda binding peptide from the gp32 C-terminus was identified using surface plasmon resonance. The crystal structure of the Dda–peptide complex was consistent with the corresponding interaction in the gp32–Dda–ssDNA structure. A Dda-dependent DNA unwinding assay supported the structural conclusions and confirmed that the bound gp32 sequesters the ssDNA generated by Dda. The structure of the gp32–Dda–ssDNA complex, together with the known structure of the gp32 body, reveals the entire ssDNA binding surface of gp32. gp32–Dda–ssDNA complexes in the crystal are connected by the N-terminal region of one gp32 binding to an adjacent gp32, and this provides key insights into this interaction.

Biochemistry & Molecular Biology↗

DOE OSTI2022

End-to-end learning of multiple sequence alignments with differentiable Smith–Waterman

Abstract Motivation Multiple sequence alignments (MSAs) of homologous sequences contain information on structural and functional constraints and their evolutionary histories. Despite their importance for many downstream tasks, such as structure prediction, MSA generation is often treated as a separate pre-processing step, without any guidance from the application it will be used for. Results Here, we implement a smooth and differentiable version of the Smith–Waterman pairwise alignment algorithm that enables jointly learning an MSA and a downstream machine learning system in an end-to-end fashion. To demonstrate its utility, we introduce SMURF (Smooth Markov Unaligned Random Field), a new method that jointly learns an alignment and the parameters of a Markov Random Field for unsupervised contact prediction. We find that SMURF learns MSAs that mildly improve contact prediction on a diverse set of protein and RNA families. As a proof of concept, we demonstrate that by connecting our differentiable alignment module to AlphaFold2 and maximizing predicted confidence, we can learn MSAs that improve structure predictions over the initial MSAs. Interestingly, the alignments that improve AlphaFold predictions are self-inconsistent and can be viewed as adversarial. This work highlights the potential of differentiable dynamic programming to improve neural network pipelines that rely on an alignment and the potential dangers of optimizing predictions of protein sequences with methods that are not fully understood. Availability and implementation Our code and examples are available at: https://github.com/spetti/SMURF. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Understanding the structural basis of HIV-1 restriction by the full length double-domain APOBEC3G

APOBEC3G, a member of the double-domain cytidine deaminase (CD) APOBEC, binds RNA to package into virions and restrict HIV-1 through deamination-dependent or deamination-independent inhibition. Mainly due to lack of a full-length double-domain APOBEC structure, it is unknown how CD1/CD2 domains connect and how dimerization/multimerization is linked to RNA binding and virion packaging for HIV-1 restriction. We report rhesus macaque A3G structures that show different inter-domain packing through a short linker and refolding of CD2. The A3G dimer structure has a hydrophobic dimer-interface matching with that of the previously reported CD1 structure. A3G dimerization generates a surface with intensified positive electrostatic potentials (PEP) for RNA binding and dimer stabilization. Unexpectedly, mutating the PEP surface and the hydrophobic interface of A3G does not abolish virion packaging and HIV-1 restriction. The data support a model in which only one RNA-binding mode is critical for virion packaging and restriction of HIV-1 by A3G.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Probabilistic Multi-Hazard Performance Assessment of Concrete Structures in Nuclear Installations

Concrete structures in nuclear installations are subject to time-dependent degradation mechanisms that can deteriorate their physical and mechanical properties, potentially exacerbating the risk of structural failure under external forces such as a seismic event. Previous research has extensively investigated the seismic response of nuclear concrete structures and the associated risk, as well as their effect on structural components safety margins. However, substantial work is still necessary to incorporate concrete aging effects into such evaluations. In fact, most models in the literature assume pristine concrete conditions and do not account for the impact of aging on the structural components’ fragility curves. This work identifies relevant time-dependent degradation mechanisms and provides simplified models to predict the the evolution of key material properties based on data from the literature. Namely, this work focuses on the aging effects of corrosion, alkali–silica reaction (ASR), and irradiation on reinforced concrete within US Department of Energy (DOE) nuclear facilities and nuclear power plants (NPP) structures. Furthermore, degradation models based on literature data are presented that define the relationship between probabilistic material properties and the concrete’s age. In this work, sampled material properties served as input for a simplified finite element model (FEM) of a critical nuclear structural system, with the output of the FEM being the seismic response for a given ground motion. The results of the FEM were then used within a probabilistic performance assessment with a statistically significant number of samples. The research presented herein addresses the detrimental effects of hazards caused by natural phenomena on deteriorated concrete elements of nuclear installations. This work directly benefits the safety analysis performed on US DOE/ National Nuclear Security Administration (NNSA) nuclear facilities located in areas prone to seismic activity. The results presented herein could aid in the improvement of DOE-STD-1020, the DOE Standard that addresses seismic risk analysis and capacity evaluation in DOE facilities. DOE-STD-1020 refers to the requirements in American Society of Civil Engineers (ASCE) 4-98, now superseded by ASCE 4-16, that shall be met in performing dynamic response analyses and generating in-structure response spectra, provided that such requirements are consistent with the requirements of ASCE/Structural Engineering Institute (SEI) 43-05. Moreover, the results presented herein could also aid in the updating of section C3.1.1. of ASCE 4-16 to account for the effects of aging on the stiffness of reinforced elements and American Concrete Institute (ACI) 349.3R-18, “Report on Evaluation and Repair of Existing Nuclear Safety-Related Concrete Structures.” Ultimately, this work can assist the risk assessment of potential lifetime extension of the existing US commercial nuclear fleet (light water reactors) and the safety analysis of the emerging advanced nuclear reactors. The proposed proof-of-concept methodology employs open-source DOE computational tools and is transferable to commercial software commonly used by engineering firms.

42 ENGINEERING↗