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At least 1,009 records · Page 56

In-situ irradiation of uranium carbide

Uranium carbide (UC) is a leading candidate fuel for Generation IV reactors due to its high uranium density and thermal conductivity. However, its irradiation performance—particularly gas bubble swelling and defect dynamics—remains poorly characterized. Using in-situ transmission electron microscopy (TEM), we irradiated UC with 300 keV Xe + and 1 MeV Kr 2+ ions at temperatures up to 900 °C to quantify swelling behavior and dislocation loop evolution. The swelling remained below 0.6 % across all temperatures, suggesting the dimensional stability of UC under irradiation at these temperatures. Dislocation loops grew faster in UC than in UO 2 or UN, correlating with its lower homologous temperature. Notably, nanograin structures emerged in thin regions of the lamellar, mirroring phenomena previously observed in UO 2 and ZrC. These results address critical knowledge gaps in the radiation tolerance of UC and provide insight into its suitability for advanced reactor systems.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Affinity propagation clustering of full-field, high-spatial-dimensional measurements for robust output-only modal identification: A proof-of-concept study

Determination of the model order is a challenging problem in system identification, especially in output-only or operational modal identification where some modes are weakly excited. While existing methods such as the stabilization diagram method (spectral information) are effective, they do not scale to high-dimensional data, which is usually needed for high-fidelity characterization of structural dynamics and has been made available in the emerging full-field measurement techniques using optical methods such as photogrammetry and laser vibrometers. In this proof-of-concept study we present a new non-parametric, data-driven approach for robust output-only identification of high-spatial-dimensional modal parameters of basic structures by efficiently processing and interactively exploiting the full-field measurement (i.e., very dense spatial measurement points). Specifically, we first over-estimate the system model once, producing a pool of candidate modes associated with their modal frequencies and full-field, high-spatial-dimensional mode shapes. This is accomplished by a data-driven method termed affinity propagation clustering (APC), where the active clusters, which are the active modes in our formulations, emerge from the "message-passing" procedure and does not require a pre-determination of the cluster number (mode or model order). Next, rather than using the spectral information to distinguish the physical and spurious modes in the stabilization diagram method, we exploit and visualize the spatial, full-field mode shape associated with each candidate mode to do so. We conduct extensive experiments on basic structural models with comparisons to a few existing methods. The results indicate that the new method is computationally efficient for identifying high-spatial-dimensional modal parameters, and robust to identify weak modes by exploiting the full-field measurement. We also discuss its applicability and limitations for structures with complex geometry (shapes).

42 ENGINEERING↗

Dynamic recrystallization behavior of an as-cast TiAl alloy during hot compression

High temperature compressive deformation behaviors of as-cast Ti–43Al–4Nb–1.4W–0.6B alloy were investigated at temperatures ranging from 1050 °C to 1200 °C, and strain rates from 0.001 s{sup −1} to 1 s{sup −1}. Electron back scattered diffraction technique, scanning electron microscopy and transmission electron microscopy were employed to investigate the microstructural evolutions and nucleation mechanisms of the dynamic recrystallization. The results indicated that the true stress–true strain curves show a dynamic flow softening behavior. The dependence of the peak stress on the deformation temperature and the strain rate can well be expressed by a hyperbolic-sine type equation. The activation energy decreases with increasing the strain. The size of the dynamically recrystallized β grains decreases with increasing the value of the Zener–Hollomon parameter (Z). When the flow stress reaches a steady state, the size of β grains almost remains constant with increasing the deformation strain. The continuous dynamic recrystallization plays a dominant role in the deformation. In order to characterize the evolution of dynamic recrystallization volume fraction, the dynamic recrystallization kinetics was studied by Avrami-type equation. Besides, the role of β phase and the softening mechanism during the hot deformation was also discussed in details. - Highlights: • The size of DRXed β grains decreases with increasing the value of the Z. • The CDRX plays a dominant role in the deformation. • The broken TiB{sub 2} particles can promote the nucleation of DRX.

36 MATERIALS SCIENCE↗

Tuning the Mechanical Properties of Shape Memory Metallic Glass Composites with Brick and Mortar Designs

We use molecular dynamics simulations to characterize the tensile deformation and failure of shape memory alloy-bulk metallic glass composites (BMGCs). As the failure in BMGCs shifts from the MG matrix to the second phase different strategies are required to further improve their mechanical properties. Results show that a staggered brick BMGC displays enhanced ductility with mild strength loss following a homogeneously distributed plasticity. This demonstrates that judiciously designed BMGCs can effectively synergize the mechanical properties of metallic glasses and shape memory alloys by effectively distributing stress and preventing the generation of critical shear bands and premature failure while preserving strength.

36 MATERIALS SCIENCE↗

Tuning the mechanical properties of nanoglass-metallic glass composites with brick and mortar designs

We use molecular dynamics simulations to characterize the tensile deformation and failure of metallic glass (MG)-nanoglass (NG) composites designed with a brick and mortar architecture consisting of a 3 nm-grain-size NG matrix and a MG second phase. Results show that the overall strength of the matrix is significantly improved by the second phase without sacrificing the large NG matrix ductility. The mechanical synergy of the two phases is optimized by arranging the MG bricks in a staggered way, which effectively delocalizes the plastic deformation, hindering the buildup of local stress hot spots and the generation of critical shear bands.

36 MATERIALS SCIENCE↗

Stream lamination and rapid mixing in a microfluidic jet for X-ray spectroscopy studies

Microfluidic mixers offer new possibilities for the study of fast reaction kinetics down to the microsecond time scale, and methods such as soft X-ray absorption spectroscopy are powerful analysis techniques. These systems impose challenging constraints on mixing time scales, sample volume, detection region size and component materials. The current work presents a novel micromixer and jet device which aims to address these limitations. The system uses a so-called ‘theta’ mixer consisting of two sintered and fused glass capillaries. Sample and carrier fluids are injected separately into the inlets of the adjacent capillaries. At the downstream end, the two streams exit two micron-scale adjoining nozzles and form a single free-standing jet. The flow-rate difference between the two streams results in the rapid acceleration and lamination of the sample stream. This creates a small transverse dimension and induces diffusive mixing of the sample and carrier stream solutions within a time scale of 0.9 microseconds. The reaction occurs at or very near a free surface so that reactants and products are more directly accessible to interrogation using soft X-ray. We use a simple diffusion model and quantitative measurements of fluorescence quenching (of fluorescein with potassium iodide) to characterize the mixing dynamics across flow-rate ratios.

Huyke, Diego A. (ORCID:0000000283356613)↗

Lesion Sensing during Initial Binding by Yeast XPC/Rad4: Toward Predicting Resistance to Nucleotide Excision Repair

Nucleotide excision repair (NER) excises a variety of environmentally derived DNA lesions. However, NER efficiencies for structurally different DNA lesions can vary by orders of magnitude; yet the origin of this variance is poorly understood. Our goal is to develop computational strategies that predict and identify the most hazardous, repair-resistant lesions from the plethora of such adducts. In the present work, we are focusing on lesion recognition by the xeroderma pigmentosum C protein complex (XPC), the first and required step for the subsequent assembly of factors needed to produce successful NER. We have performed molecular dynamics simulations to characterize the initial binding of Rad4, the yeast orthologue of human XPC, to a library of 10 different lesion-containing DNA duplexes derived from environmental carcinogens. These vary in lesion chemical structures and conformations in duplex DNA and exhibit a wide range of relative NER efficiencies from repair resistant to highly susceptible. We have determined a promising set of structural descriptors that characterize initial binding of Rad4 to lesions that are resistant to NER. Key initial binding requirements for successful recognition are absent in the repair-resistant cases: There is little or no duplex unwinding, very limited interaction between the β-hairpin domain 2 of Rad4 and the minor groove of the lesion-containing duplex, and no conformational capture of a base on the lesion partner strand. By contrast, these key binding features are present to different degrees in NER susceptible lesions and correlate to their relative NER efficiencies. Furthermore, we have gained molecular understanding of Rad4 initial binding as determined by the lesion structures in duplex DNA and how the initial binding relates to the repair efficiencies. The development of a computational strategy for identifying NER-resistant lesions is grounded in this molecular understanding of the lesion recognition mechanism.

60 APPLIED LIFE SCIENCES↗

A Novel Multiagent Resource Sharing Algorithm for Control of Advanced Energy Systems

This paper implements a novel resource sharing control strategy on a fuel cell–gas turbine hybrid power system at the National Energy Technology Laboratory’s Hybrid Performance Facility (Hyper). In a fuel cell–gas turbine hybrid power system, the simultaneous interaction of the gas turbine and the fuel cell creates a tightly coupled environment characterized by conflicting dynamics. In this paper, a model-free control approach is applied to solve the tightly coupled control problem posed by this challenging environment. Specifically, this control problem is presented as a resource sharing problem that can be solved using a resource sharing algorithm that is defined based on the distribution construction concept. This algorithm creates computational agents and solves the problem through the distribution and redistribution of shared resources defined as blocks. Furthermore, two agents were created; the first agent (agent 1) controls the gas turbine speed by adjusting the electric load, and the second agent (agent 2) controls the cathode mass flow through the fuel cell using the cold-air bypass valve. A parametric study was performed over the course of 15 experimental tests for both agents 1 and 2 through an evaluation of the responses based on setpoint changes. The algorithm was shown to have behavior comparable to a previously implemented multi-input multioutput state-space controller, which was designed through a model-based control approach. The resource sharing algorithm was able to find stable performance during run-time operations without any prior system knowledge identification on the power plant and without creating models used in traditional control strategies.

25 ENERGY STORAGE↗

Using Density-Corrected DFT to Understand Density-Driven and Functional-Dependent Errors in Ab Initio Simulations of the Hydrated Electron

The hydrated electron, an excess electron in liquid water, plays a crucial role in a plethora of chemical processes, motivating extensive research efforts to characterize its structure, dynamics, and reactivity in solution. Recent theoretical approaches to understanding this intriguing object have involved ab initio simulations based on density functional theory (DFT). Although DFT allows for the study of hydrated electron reactivity and quantum mechanical behavior, it is well-known that anionic systems can suffer from significant density-driven errors (DDEs). Density-corrected DFT (DC-DFT) provides a framework to mitigate such errors; the method reduces DDEs by replacing the self-consistent (SC) density associated with a given density functional with the Hartree–Fock (HF) density. Since HF densities tend to be more localized than DFT SC densities, the DC-DFT scheme significantly improves errors in calculations where the SC density is spuriously delocalized. Here, we investigate how the use of density correction affects the calculated properties of the DFT-simulated (PBEh) hydrated electron, a particularly challenging diffuse anionic system to simulate. First, we analyze charge delocalization in a system consisting of a model octahedral hydrated electron water cluster (the so-called Kevan structure) along with a spatially separated sulfur atom. We show that the use of density correction indeed reduces DDEs in comparison to a standard DFT global hybrid functional. We then propagate molecular dynamics trajectories of the hydrated electron using DC-DFT, where we find that DC further localizes electron density in the cavity region, a signature of reduced charge delocalization. Unfortunately, the decreased radius of gyration of the spin density and corresponding tightening of the local solvation structure from density correction causes predicted observables to deviate further from experimental measurements than when density correction is not employed. Here, we argue that DC’s worse agreement with experiment results from the removal of a fortuitous cancellation of errors that is intrinsic to the PBEh functional. This indicates that the difficulties with DFT to simulate hydrated electrons are primarily due to the inherent approximations in DFT rather than to density-driven errors.

Density functional theory↗

Mechanics of Gold Nanoparticle Superlattices at High Hydrostatic Pressures

Pressure-driven assembly of ligand-grafted gold nanoparticle superlattices is a promising approach for fabricating gold nanostructures, such as nanowires and nanosheets. Optimizing this fabrication method will require extending our understanding of superlattice mechanics to regimes of high pressures. We use molecular dynamics simulations to characterize the response of alkanethiol-grafted gold nanoparticle superlattices to applied hydrostatic pressures up to 15 GPa. At low applied pressures, intrinsic voids govern the mechanics of compaction. As applied pressures increase, the void collapse and ligand compression depend significantly on the ligand length. These microstructural observations correlate directly with trends in bulk modulus and elastic constants. For short ligands, core–core contact between gold nanoparticles is observed at high pressures, which augurs irreversible response and eventual sintering. In conclusion, this presintering behavior was unexpected under hydrostatic loading and is observed only for the shortest ligands.

36 MATERIALS SCIENCE↗

Onsager Transport Coefficients and Transference Numbers in Polyelectrolyte Solutions and Polymerized Ionic Liquids

Electrolytes featuring negatively charged polymers, such as nonaqueous polyelectrolyte solutions and polymerized ionic liquids, are currently under investigation as potential high cation transference number (t+) electrolytes for lithium-ion batteries. Herein, we use coarse-grained molecular dynamics simulations to characterize the Onsager transport coefficients of polyelectrolyte solutions as a function of chain length and concentration. For all the systems studied, we find that the rigorously computed transference number is substantially lower than that approximated by the ideal solution (Nernst-Einstein) equations typically used to characterize these systems due to the presence of strong anion-anion and cation-anion correlations. None of the polyelectrolyte solutions achieve t+ greater than that of the conventional binary salt electrolyte, with some solutions having negative t+. Overall, this work demonstrates that the Nernst-Einstein assumption does not provide a physically meaningful estimate of the transference number in these solutions and calls into question the expectation of polyelectrolytes to exhibit a high cation transference number.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Role of Molecular Architecture on Ion Transport in Ethylene oxide-Based Polymer Electrolytes

This work aims to develop a detailed mechanistic understanding of the role of a graft polymer architecture on lithium ion (Li + ) transport in poly(ethylene oxide)-based polymer electrolytes. Specifically, we compare Li + transport in poly-(ethylene oxide) (PEO) versus poly(oligo oxyethylene methacrylate) (POEM) polymers doped with lithium bis( trifluoromethanesulfonyl) (LiTFSI) salts, using both experimental electrochemical characterization and molecular dynamics (MD) simulations. Furthermore, our results indicate that POEM exhibits a range of relaxation processes that cannot be interpreted solely in terms of glass-transition temperature (T g ) effects. Due to its side-chain architecture, the segmental relaxation of POEM is nonuniform across ether oxygens (EOs) and shows a more pronounced sensitivity to temperature above T g compared to PEO. Moreover, POEM also exhibits a nonuniform Li + coordination behavior, in which Li + is primarily solvated by two different chains in POEM, compared to a single chain in PEO. Li + transport in POEM occurs via two events with distinct characteristic times: a fast intrachain hopping along side chains and a slow interchain hopping between side chains. Taken together, the relaxation processes and ion transport mechanisms identified in POEM provide useful insights into design of more effective solid polymer electrolytes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing Hydrated Polymers via Dielectric Relaxation Spectroscopy: Connecting Relative Permittivity, State of Water, and Salt Transport Properties of Sulfonated Polysulfones

Sulfonated polysulfone is a promising membrane material for separation and energy generation processes that rely on membranes to control the rates of small-molecule (e.g., water and ions) transport. The interactions among water molecules, ions, and the sulfonate groups in these polymers play a key role in controlling these rates of transport, but much remains unknown about these fundamental interactions in sulfonated polymers. In this study, we used dielectric relaxation spectroscopy to characterize water molecule dynamics in sulfonated polysulfone and Nafion. We found that the charged sulfonate groups contribute to a restriction of water molecule dynamics (i.e., a reduction in the characteristic time scale of dipolar motions) in a manner that is governed by the concentration and nature (i.e., conjugate base strength) of the sulfonate group. Additionally, we develop strategies to use these data to aid in modeling ion transport in sulfonated polysulfone. These results may be useful to guide engineering strategies for polymeric membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gerischer Electrochemistry Today

Semiconductor photoelectrochemistry is a dynamic and interdisciplinary field at the forefront of research in solar fuels, energy conversion, and catalysis. Here, this Perspective captures the collective insights from the second Gerischer Electrochemistry Today Symposium, held at Colorado State University in Fort Collins, CO, in August 2024, which convened leading researchers, early-career scientists, and industry partners to define the critical next steps for the field. Through interactive sessions, technical talks, panel discussions, and training initiatives─including a Semiconductor Electrochemistry Bootcamp─the symposium emphasized three pillars of advancement: (i) facilitating the exchange of new ideas in semiconductor electrochemistry and charge separation; (ii) fostering the development of future researchers, research topics, and participation in the semiconductor workforce; and (iii) building community. This Energy Focus distills key themes from the meeting and identifies major knowledge gaps in the following areas: mechanisms of charge separation and recombination, role of defects and disorder, dynamic and operando characterization methods, interfacial chemistry and surface passivation, theoretical and modeling limitations, and standardization and benchmarking. The inclusive and collaborative structure of the symposium enabled the generation of this comprehensive report that will serve as a roadmap for fundamental and applied research in the rapidly evolving field of semiconductor electrochemistry over the next decade.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Monitoring a Silent Phase Transition in CH 3 NH 3 PbI 3 Solar Cells via Operando X-ray Diffraction

The relatively modest temperature of the tetragonal-to-cubic phase transition in CH 3 NH 3 PbI 3 perovskite is likely to occur during real world operation of CH 3 NH 3 PbI 3 solar cells. In this work, we simultaneously monitor the structural phase transition of the active layer along with solar cell performance as a function of the device operating temperature. The tetragonal to cubic phase transition is observed in the working device to occur reversibly at temperatures between 60.5 and 65.4 degrees C. In these operando measurements, no discontinuity in the device performance is observed, indicating electronic behavior that is insensitive to the structural phase transition. Here, this decoupling of device performance from the change in long-range order across the phase transition suggests that the optoelectronic properties are primarily determined by the local structure in CH 3 NH 3 PbI 3 . That is, while the average crystal structure as probed by X-ray diffraction shows a transition from tetragonal to cubic, the local structure generally remains well characterized by uncorrelated, dynamic octahedral rotations that order at elevated temperatures but are unchanged locally.

14 SOLAR ENERGY↗

High-throughput simulations reveal membrane-mediated effects of alcohols on MscL gating

The mechanosensitive channels of large conductance (MscL) are bacterial membrane proteins that serve as last resort emergency release valves in case of severe osmotic downshock. Sensing bilayer tension, MscL channels are sensitive to changes in the bilayer environment and are, therefore, an ideal test case for exploring membrane protein coupling. Here, we use high-throughput coarse-grained molecular dynamics simulations to characterize MscL gating kinetics in different bilayer environments under the influence of alcohols. We performed over five hundred simulations to obtain sufficient statistics to reveal the subtle effects of changes in the membrane environment on MscL gating. MscL opening times were found to increase with the addition of the straight-chain alcohols ethanol, octanol, and to some extent dodecanol but not with hexadecanol. Increasing concentration of octanol increased the impeding effect, but only up to 10–20 mol %. Our in silico predictions were experimentally confirmed using reconstituted MscL in a liposomal fluorescent efflux assay. Our combined data reveal that the effect of alcohols on MscL gating arises not through specific binding sites but through a combination of the alcohol-induced changes to a number of bilayer properties and their alteration of the MscL–bilayer interface. Finally, our work provides a key example of how extensive molecular simulations can be used to predict the functional modification of membrane proteins by subtle changes in their bilayer environment.

59 BASIC BIOLOGICAL SCIENCES↗

Structure, Dynamics, and Reactivity for Light Alkane Oxidation of Fe(II) Sites Situated in the Nodes of a Metal–Organic Framework

Metal organic frameworks (MOFs), with their crystalline, porous structures, can be synthesized to incorporate a wide range of catalytically active metals in tailored surroundings. These materials have potential as catalysts for conversion of light alkanes, feedstocks available in large quantities from shale gas that are changing the economics of manufacturing commodity chemicals. Mononuclear high-spin (S = 2) Fe(II) sites situated in the nodes of the MOF MIL-100(Fe) convert propane via dehydrogenation, hydroxylation, and overoxidation pathways in reactions with the atomic oxidant N 2 O. Pair distribution function analysis, N 2 adsorption isotherms, X-ray diffraction patterns, and infrared and Raman spectra confirm the single-phase crystallinity and stability of MIL-100(Fe) under reaction conditions (523 K in vacuo, 378–408 K C 3 H 8 + N 2 O). Density functional theory (DFT) calculations illustrate a reaction mechanism for the formation of 2-propanol, propylene, and 1-propanol involving the oxidation of Fe(II) to Fe(III) via a high-spin Fe(IV)$=$O intermediate. The speciation of Fe(II) and Fe(III) in the nodes and their dynamic interchange was characterized by in situ X-ray absorption spectroscopy and ex situ Mössbauer spectroscopy. Furthermore, the catalytic relevance of Fe(II) sites and the number of such sites were determined using in situ chemical titrations with NO. N 2 and C 3 H 6 production rates were found to be first-order in N 2 O partial pressure and zero-order in C3H8 partial pressure, consistent with DFT calculations that predict the reaction of Fe(II) with N 2 O to be rate determining. DFT calculations using a broken symmetry method show that Fe-trimer nodes affecting reaction contain antiferromagnetically coupled iron species, and highlight the importance of stabilizing high-spin (S = 2) Fe(II) species for effecting alkane oxidation at low temperatures (<408 K).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Machine Learning Assisted Development of a Model for the Populations of Convective and Stratiform Clouds

Abstract Traditional parameterizations of the interaction between convection and the environment have relied on an assumption that the slowly varying large‐scale environment is in statistical equilibrium with a large number of small and short‐lived convective clouds. They fail to capture nonequilibrium transitions such as the diurnal cycle and the formation of mesoscale convective systems as well as observed precipitation statistics and extremes. Informed by analysis of radar observations, cloud‐permitting model simulation, theory, and machine learning, this work presents a new stochastic cloud population dynamics model for characterizing the interactions between convective and stratiform clouds, with the goal of informing the representation of these interactions in global climate models. Fifteen wet seasons of precipitating cloud observations by a C‐band radar at Darwin, Australia are fed into a machine learning algorithm to obtain transition functions that close a set of coupled equations relating large‐scale forcing, mass flux, the convective cell size distribution, and the stratiform area. Under realistic large‐scale forcing, the derived transition functions show that, on the one hand, interactions with stratiform clouds act to dampen the variability in the size and number of convective cells and therefore in the convective mass flux. On the other, for a given convective area fraction, a larger number of smaller cells is more favorable for the growth of stratiform area than a smaller number of larger cells. The combination of these two factors gives rise to solutions with a few convective cells embedded in a large stratiform area, reminiscent of mesoscale convective systems.

54 ENVIRONMENTAL SCIENCES↗