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ECAR-8823 Rev 0 Structural Evaluation of the MARVEL Support Frame in Dry Critical Configuration
The purpose of this ECAR is to structurally evaluate the MARVEL reactor support frame during the dry critical (DryCrit) start-up testing. The ECAR includes evaluation of the DryCrit configuration for tip-over of the frame during a seismic event, floor loading of the frame on the MFC-720 (TREAT) operating floor, stress analysis of the adapter ring, and stress analysis of the frame itself for gravity and seismic loads.
Review of analytical studies on seismic fluid-structure interaction of base-supported cylindrical tanks
Analytical solutions for seismic fluid-structure interaction (FSI) of tanks are used by analysts and engineers for a number of purposes, including preliminary sizing, risk assessment, and verification of numerical models. Analytical solutions for seismic FSI of tanks were first developed in the 1930s and have been extended and/or modified in the following nine decades to accommodate different seismic inputs and boundary conditions. This report reviews published analytical solutions for rigid and flexible, base-supported, cylindrical tanks subjected to unidirectional horizontal motion of a small amplitude. The studies parsed the fluid-structure (FSI) response into an impulsive and a convective component, and addressed frequencies of lateral motions of the tank (i.e., impulsive frequencies), hydrodynamic pressures, frequencies of waves (i.e., convective frequencies), wave heights, and reactions at the base. The solutions were categorized into exact and approximate solutions based on the methodologies used. Herein, FSI responses are calculated and compared for a range of tank dimensions using the analytical solutions from the different studies. The responses presented here are normalized to be unitless, and can be used for tanks with different dimensions and mechanical properties, and subjected to different input motions. A sample steel water tank is analyzed using the normalized solutions for two earthquake ground motions with different frequency contents. Ignoring tank flexibility may significantly underestimate seismic responses of the tank and its contained fluid. The approximate solutions, which have been widely used for decades, may not be sufficiently accurate in the modern era. Calculation errors in the reviewed studies are identified and corrected, and differences are quantified for the sample tank.
Politics of problem definition: Comparing public support of climate change mitigation policies using machine learning
Public support is a key contributor to successful policy adoption and implementation. Given the urgency of climate change mitigation, scholars have explored various determinants that affect public support for climate change mitigation policy. However, the relative decisiveness of these factors in shaping public support is insufficiently examined. Therefore, we deploy interpretable machine learning to understand which factors, among many previously investigated, are most decisive for structuring public support for various climate change mitigation policies. In this paper, we particularly look at the decisiveness of problem definition for shaping public support among various factors. Using U.S national survey data, we find that how individuals define the issue of climate change is more decisive for structuring public support for promoting renewable energy and regulating pollutants to mitigate the risks associated with climate change. However, the results also indicate that the most decisive factors associated with public support vary depending on the types of mitigation policy. Here, we conclude that different strategies should be utilized to increase public support for various climate change mitigation policy options. Our findings contribute to a scholarly understanding of the specific politics of problem definition in the context of environmental and climate change policy.
Graphite Oxidation Rate Study on ET-10 and ETU-10 Grades - Task 4: QA Support and Testing for Structural Graphite Oxidation
INL performed targeted oxidation tests to measure oxidation rates for samples of ET-10 and ETU-10 graphite under CRADA No. 21CRA22 Mod. 3, Annex A, “Tritium Testing to Support Kairos Power Advanced Reactor Demonstration” (04/02/2024). All testing was conducted within INL’s Carbon Characterization Laboratory (CCL) using test standard ASTM D7542-21 "Standard Test Method for Air Oxidation of Carbon and Graphite in the Kinetic Regime" [ASTM International, 2021]. Kairos Power provided all test specimens through its graphite vendor Ibiden, Inc. to INL and ASTM specimen specified dimensions. Information within this report only provides the Arrhenius oxidation rate plots as a function of temperature for each graphite grade tested. The raw mass loss per time data will be provided on the Nuclear Data Management and Analysis System (NDMAS) portal located on the INL information system.
Leveraging State Clean Water Revolving Funds to Expand Clean Energy Financing
To meet clean energy goals, states will need significant capital. Federal funding from the Inflation Reduction Act and the Infrastructure Investment and Jobs Act will help, including by capitalizing clean energy state revolving loan funds (RLFs). States can leverage state clean water revolving funds to finance even more clean energy improvements. New York and Pennsylvania have used this innovative mechanism to extend the impact of their clean energy loan programs. For states looking to extend the reach of their clean energy financing programs, the brief: -Explains how each state leveraged their state revolving funds, -Identifies critical success factors for doing so, and -Offers key elements for replicating this model In New York, New York State Energy Research and Development Authority structured a sale of bonds secured by the repayments from a portfolio of residential energy efficiency loans from its Green Jobs – Green New York Program, with the additional support of a guarantee from the state’s clean water revolving fund. The Pennsylvania Treasury Department received a direct investment of funds from Pennsylvania’s clean water revolving fund to support the relaunch of the Keystone Home Energy Loan Program (HELP), which had previously been shuttered due to lack of support funding. From our review of these two case studies, when facilitating state clean water revolving fund transactions to support clean energy lending, the following critical success factors emerged: -Reference to preventing atmospheric deposition resulting from the combustion of fossil fuels in the state’s Clean Water Act Section 319 Nonpoint Source Pollution Management Plan, which sets out that state’s strategy for reducing pollution into state waterways. -Strong relationships and trust between the clean water revolving fund administrator and the state agency administering the clean energy loan program. -Limited funding exposure for the clean water revolving funds—which are generally large and well capitalized—to ensure that any losses experienced by clean water revolving funds would have a negligible impact on the fund’s ability to support core water and wastewater projects. -Willingness, on the part of the clean water revolving fund administrator, to innovate and engage in careful analysis to support transaction structuring, and support from state energy partner organizations. The brief provides case studies of these states’ experiences, critical success factors, and key elements for replicating the model.
Insights into the Structure–Activity Relationships in Metal–Organic Framework-Supported Nickel Catalysts for Ethylene Hydrogenation
Solid supports play an indispensable role in heterogeneous catalysis, as they can directly affect the catalytic activity and selectivity of supported catalysts. However, the specific roles of such supports remain to be demystified owing to the difficulties in obtaining precise structural information on supported catalysts. To understand the effects of MOF topology, pore environment, and metal identity of node supports on the catalytic activity, a Ni catalyst was supported on eight Zr- or Hf-MOFs based on 8-connected nodes: namely M-NU-1200, M-NU-1000, M-NU-1008, and M-NU-1010 (M = Zr, Hf). Single-crystal X-ray diffraction (SCXRD), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and X-ray photoelectron spectroscopy (XPS) were employed to characterize the supported catalyst structures. To investigate the support effects on their activities, the supported Ni catalysts were evaluated by using ethylene hydrogenation as a model reaction. The results revealed that all Hf-based-MOF-supported Ni catalysts exhibited higher catalytic reactivity with TOF (turnover frequency) values at least double of those isostructural Zr counterparts. Additionally, MOFs with less congested metal anchoring sites, as a result of the topology and surrounding pore environment, yielded higher TOFs, suggesting the importance of supports in dictating both the catalyst accessibility and activity. Computational analysis complemented the experimental observations and provided insights into reaction barrier differences and their performance variation. Furthermore, this study demonstrates the essential role of the supports and provides a thought for selecting/designing suitable supports in heterogeneous catalysis.
Template Assisted Lithium Superoxide Growth for Lithium-Oxygen Batteries
Developing batteries with energy densities comparable to internal combustion technology is essential for a worldwide transition to electrified transportation. Li-O2 batteries are seen as the ‘holy grail’ of battery technologies since they have the highest theoretical energy density of all battery technologies. Current lithium-oxygen (Li-O2) batteries suffer from large charge overpotentials related to electronic resistivity of the insulating lithium peroxide (Li2O2) discharge product. One potential solution is the formation and stabilization of a lithium superoxide (LiO2) discharge intermediate that exhibits good electronic conductivity. However, LiO2 is reported to be unstable at ambient temperature despite its favorable formation energy at -1.0 eV/atom. In this paper, based on our recent work on the development of cathode materials for aprotic lithium oxygen batteries including two intermetallic compounds, LiIr3 and LiIr, that are found to form good template interfaces with LiO2, a simple goodness of fit R factor to gauge how well a template surface structure can support LiO2 growth is developed. The R factor is a quantitative measurement to calculate the geometric difference in the unit cells of specific Miller Index 2D planes of the template surface and LiO2. Using this as a guide, the R factors for LiIr3, LiIr, and La2NiO4+, are found to be good. This guide is attested by simple extension to other noble metal intermetallics with electrochemical cycling data including LiRh3, LiRh, and Li2Pd. Finally, the template concept is extended to main group elements and the R factors for LiO2 (111) and Li2Ca suggest that Li2Ca is a possible candidate for the template assisted LiO2 growth strategy.
Supplemental Structural Analyses Used in Support of Certification of the Defense Programs Package 3
The Defense Programs Package (DPP)-3 is to be certified by the National Nuclear Security Administration (NNSA) Packaging and Transportation Division (PTD). Certification is based on successful physical testing of the package, and six certification test units (CTUs) have been subjected to the normal conditions of transport (NCT) and hypothetical accident conditions (HAC) outlined in Title 10 of the Code of Federal Regulations Part 71 (10 CFR 71). During regulatory testing of one of the CTUs, the drum lid closure bolt closest to the impact surface failed during the HAC 30-ft side drop. One of the testing goals for this CTU was to minimize the thermal pathway from the drum exterior shell to the containment vessel (CV) flange and O-rings, leading to the maximum damage scenario in preparation for thermal testing at 1475 °F. Therefore, the puncture bar impact proceeded as originally planned by striking the side wall of the package exterior closest to the location of the CV flange. This puncture bar impact did not attempt to exploit the region of the failed drum lid closure bolt to potentially cause more damage to the package. After the conclusion of regulatory testing, the DPP-3 package finite element model was used to numerically evaluate the effects of puncture bar impacts to the drum exterior in the vicinity of the failed drum lid closure bolt to further demonstrate the robustness of the DPP-3 design. Three alternate puncture bar impact locations and orientations were evaluated to demonstrate that these puncture bar impacts would not substantially reduce the effectiveness of the DPP-3 packaging. This paper describes the supplemental finite element models performed and structural analysis results that demonstrate the alternate HAC 40-in. puncture bar impact tests would have no deleterious effect on the performance of the DPP-3.
Structure and activity of supported bimetallic NiPd nanoparticles: influence of preparation method on CO 2 reduction
Here, bimetallic Ni-Pd and monometallic reference catalysts were prepared by decomposing organometallic precursors, Ni(cod) 2 and Pd 2 (dba) 3 , leading to nanoparticles with sizes ranging from 3 to 6 nm. Two different synthesis procedures were followed: i) solution synthesis using capping ligand (hexadecylamine) followed by impregnation of pre-formed nanoparticles on SiO 2 , called Sol-immobilization (SI); and 2) direct precursor decomposition onto SiO 2 , without stabilizer, called Direct Decomposition (DD). Samples prepared by SI procedure are alloyed bimetallic nanoparticles, whereas samples obtained by DD one show phase segregation. Interestingly, DD samples show better activity for CO 2 hydrogenation into CO (reverse water-gas shift reaction - RWGS) than SI ones. The best compromise between activity for CO 2 activation (at lower temperature) and CO selectivity was achieved with Ni DD and NiPd DD catalysts. Moreover, the addition of palladium increased the concentration of surface undercoordinated sites, which chemisorb CO weakly, thus improving activity and selectivity, in opposition to other samples that chemisorb CO strongly, in multiband configuration. In the presence of Pd, different decomposition rates drive the formation of smaller and more active Ni clusters. The knowledge acquired here on the influence of synthesis conditions on the catalytic properties of Ni-Pd catalysts should guide us to better catalysts for CO 2 transformations into valuable products.
Electronic Structure of Atomically Dispersed Supported Iridium Catalyst Controls Iridium Aggregation
Supported iridium complexes, Ir(C 2 H 4 ) 2 /support, were characterized by X-ray absorption spectroscopy during a temperature ramp to 120 °C in flowing H 2 . Iridium in complexes bonded to weak and moderate electron-donor supports, SiO 2 and γ-Al 2 O 3 , underwent aggregation, forming nanoparticles and clusters, respectively. When the support was a strong electron-donor (MgO), iridium remained site-isolated. Density functional theory calculations confirm the dependence of iridium–support bond strength on the support’s electron-donor character. Coating the SiO 2 -supported complexes with 1-n-ethyl-3-methyl-imidazolium acetate enhanced electron density on the iridium, hindering its aggregation. Finally, these results demonstrate opportunities for stabilizing atomically dispersed supported noble metals under reducing conditions by choice of support/ionic liquid sheath combinations.
Probing the structure–property relationships of supported copper oxide nanoclusters for methane activation
Amorphous metal-oxide nanoclusters are investigated using DFT and machine learning for selective oxidation of methane.
Improved high-current-density hydrogen evolution reaction kinetics on single-atom Co embedded in an order pore-structured nitrogen assembly carbon support
Single-atom metal embedded in nitrogen-doped carbon show high HER performance, with Co-NAC reaching 200 mA cm −2 at 310 mV overpotential.
Cluster Structures with Machine Learning Support in Neutron Star M-R relations
Neutron stars (NS) are compact objects with strong gravitational fields, and a matter composition subject to extreme physical conditions. The properties of strongly interacting matter at ultra-high densities and temperatures impose a big challenge to our understanding and modelling tools. Some difficulties are critical, since one cannot reproduce such conditions in our laboratories or assess them purely from astronomical observations. The information we have about neutron star interiors are often extracted indirectly, e.g., from the star mass-radius relation. The mass and radius are global quantities and still have a significant uncertainty, which leads to great variability in studying the micro-physics of the neutron star interior. This leaves open many questions in nuclear astrophysics and the suitable equation of state (EoS) of NS. Recently, new observations appear to constrain the mass-radius and consequently has helped to close some open questions. In this work, utilizing modern machine learning techniques, we analyze the NS mass-radius (M-R) relationship for a set of EoS containing a variety of physical models. Our objective is to determine patterns through the M-R data analysis and develop tools to understand the EoS of neutron stars in forthcoming works.
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.
Atomically dispersed zeolite-supported rhodium complex: Selective and stable catalyst for acetylene semi-hydrogenation
In this study, supported rhodium catalysts are known to be unselective for semi-hydrogenation reactions. Here, by tuning the electronic structure of supported mononuclear rhodium sites determined by the metal nuclearity and the electron-donor properties of the support, we report that atomically dispersed HY zeolite-supported rhodium with reactive acetylene ligands affords a stable ethylene selectivity > 90 % for acetylene semi-hydrogenation at 373 K and atmospheric pressure, even when ethylene is present in a large excess over acetylene. Infrared and X-ray absorption spectra and measurements of rates of the catalytic reaction complemented with calculations at the level of density functional theory show how the catalyst performance depends on the electronic structure of the rhodium, influenced by the support as a ligand that is a weak electron donor.
Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments
Presentation slides on "Basin-Scale Structural Features Database: Spatial Datasets to Support Carbon Storage Resource Assessments" for CCUS 2025 Annual Meeting. The Basin-Scale Structural Features database contains a series of basin-scale spatial datasets representing structural features, including faults, fractures, folds, and earthquakes. Designed to support carbon storage feasibility and resources assessments for Carbon Capture and Storage (CCS) projects, the database leverages publicly available data resources from authoritative sources (e.g. US Geological Survey, State Geologic Surveys), and aims to help users better understand basin-scale structural features, as well as potential data gaps in areas with sparse information.
The role of surface chemistry in the synthesis of supported CuPd bimetallic/intermetallic catalysts for selective hydrogenation reactions
Understanding and controlling the structure of supported bimetallic/intermetallic catalysts are crucial for many heterogeneous catalytic reactions. However, commonly used synthesis techniques such as coimpregnation and coadsorption often yield nonuniform alloying and phase segregation, largely owing to the lack of interactions between different metal precursors. Here we show that by adopting sequential adsorption of complex metal cations and anions with the assistance of a proper ligand, the interaction between different metal precursors is enhanced, thus resulting in uniformly alloyed intermetallic catalysts. Importantly, the supported CuPd intermetallic catalyst exhibits greatly improved selectivity towards monoolefins in the semihydrogenation of acetylene and butadiene compared to those random CuPd alloys synthesized via coimpregnation and coadsorption methods.