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At least 1,441 records · Page 80

New insights into Mn 2+ and Mg 2+ inhibition of calcite growth

Impurity ion and isotope partitioning into carbonate minerals provide a window into the molecular processes occurring at the fluid-mineral interface during crystal growth. Here, we employ calcium isotope fractionation together with process-based modeling to elucidate the mechanisms by which two divalent cations with starkly contrasting compatibility, magnesium and manganese, inhibit calcite growth and incorporate into the mineral lattice. Calcite growth inhibition by Mg 2+ is log-linear and K Mg is on the order of 0.02–0.03 throughout the range of {Mg 2+ }/{Ca 2+ } studied here (0.01–2.6). Mn 2+ exhibits much stronger log-linear growth rate inhibition at low Mn 2+ concentrations (fluid {Mn 2+ }/{Ca 2+ } = 0.001–0.02). Mn 2+ is readily incorporated into the calcite lattice to form a calcite-rhodochrosite solid solution, with large partition coefficients (K Mn 4.6–15.6) inversely correlated to growth rate. For both Mn 2+ and Mg 2+ , calcium isotope fractionation is found to be invariant with {Me 2+ }/{Ca 2+ } despite more than an order of magnitude decline in growth rate. This invariant Δ 44/40 Ca suggests that the presence of Mn 2 + or Mg 2+ does not significantly change the relative rates of Ca 2+ attachment and detachment at kink sites during growth, indicative of a dominantly kink blocking inhibition mechanism. Because the partitioning behavior dictates that Mn 2+ must attach to the surface significantly faster than Ca 2+ , attachment of Mn 2+ is likely to be as a non-monomer species such as an ion pair or possibly a larger polynuclear cluster. We propose that calcite growth rate inhibition by Mn is determined by the kinetics of carbonate attachment at Mn-occupied kink sites, potentially due to slow re-orientation kinetics of carbonate ions that have formed an inner-sphere complex with Mn 2+ at the surface but must reorient to incorporate into the lattice. We demonstrate that patterns in Mg 2+ partitioning and inhibition behavior are broadly consistent with growth inhibition driven by slow Mg 2+ -aquo complex dehydration relative to Ca 2+ but argue that this mechanism likely represents one endmember scenario, seen in Mg-calcite growth at low supersaturations and net precipitation rates. During growth at faster net precipitation rates, some portion of Mg 2+ is likely incorporated as a partially hydrated or otherwise complexed species, but calcite growth remains significantly inhibited by the kinetics of CO 3 2- attachment at Mg 2+ kink sites. These findings suggest a hybrid classical/nonclassical growth mechanism whereby Ca 2+ incorporates largely as a free ion at kink sites while Mn 2+ and some portion of Mg 2+ are incorporated via non-monomer attachment. This pattern may be generalizable; trace constituent cations with aquo-complex desolvation rates significantly slower than the mineral growth rate preferentially incorporate as a non-monomer species during otherwise classical crystal growth.

58 GEOSCIENCES↗

Automated Credibility Assessments of User Features in Scientific Software

Scientific software (SciSoft) is complex, often containing a mixture of production capabilities co-mingled with features under active research and development. Furthermore, SciSoft is often developed over decades by non-computer scientists who may not have a strong background in or prioritize software architecture design, testing, and quality (e.g., test coverage). These conditions lead to difficulty in understanding which software components or functions implement what user-facing features and therefore those features’ software quality pedigree. This lack of understanding poses challenges in assessing readiness and credibility of user features, and often relies on a SciSoft subject matter expert’s (SME) laborious investigation and assertion. This final report of a one-year Computing and Information Sciences Lab Directed Research and Development project presents a general framework for modeling SciSoft architecture as a direct relationship between user features and the software components/functions that implement them. Our approach leverages automated labeling of the SciSoft’s regression test suite and employs machine learning algorithms to construct the architecture model. We demonstrate this framework on the Solid Mechanics component of the SIERRA multi-physics engineering analysis suite developed at Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗

A coarse-grained model of clay colloidal aggregation and consolidation with explicit representation of the electrical double layer

The aggregation of clay minerals in liquid water exemplifies colloidal self-assembly in nature. These negatively charged aluminosilicate platelets interact through multiple mechanisms with different sensitivities to particle shape, surface charge, aqueous chemistry, and interparticle distance and exhibit complex aggregation structures. Experiments have difficulty resolving the associated colloidal assemblages at the scale of individual particles. Conversely, all-atom molecular dynamics (MD) simulations provide detailed insight on clay colloidal interaction mechanisms, but they are limited to systems containing a few particles. We develop a new coarse-grained (CG) model capable of representing assemblages of hundreds of clay particles with accuracy approaching that of MD simulations, at a fraction of the computational cost. Our CG model is parameterized based on MD simulations of a pair of smectite clay particles in liquid water. A distinctive feature of our model is that it explicitly represents the electrical double layer (EDL), i.e., the cloud of charge-compensating cations that surrounds the clay particles. Our model captures the simultaneous importance of long-range colloidal interactions (i.e., interactions consistent with simplified analytical models, already included in extant clay CG models) and short-range interactions such as ion correlation and surface and ion hydration effects. The resulting simulations correctly predict, at low solid-water ratios, the existence of ordered arrangements of parallel particles separated by water films with a thickness up to ~10 nm and, at high solid-water ratios, the coexistence of crystalline and osmotic swelling states, in agreement with experimental observations.

54 ENVIRONMENTAL SCIENCES↗

Solvent-Driven Transformation of Zn/Cd 2+ -Deoxycholate Assemblies

Deoxycholic acid (DOC) is a unique, biologically derived surfactant with facial amphiphilicity that has been exploited, albeit minimally, in supramolecular assembly of materials. Here, we present the synthesis and structural characterization of three hybrid metal (Zn 2+ and Cd 2+ )-DOC compounds. Analysis by single-crystal Xray diffraction reveals the many interactions that are possible between these facial surfactants and the influence of solvent molecules that drive the assembly of materials. These structures are the first metal- DOC complexes besides those obtained from alkali and alkaline earth metals. We isolated polymeric chains of both Cd and Zn (Zn poly -DOC and Cd poly -DOC) from water. Major interactions between DOC molecules in these phases are hydrophobic in nature. Cd poly -DOC exhibits unique P1 symmetry, with complete interdigitation of the amphiphiles between neighboring polymeric chains. Zn 4 -DOC, obtained from methanol dissolution of Zn poly -DOC, features the OZn 4 tetrahedron, widely known in basic zinc acetate and MOF-5 (metal organic framework). We document a solvent-driven, roomtemperature transition between Zn poly -DOC and Zn 4 -DOC (in both directions) by scanning and transmission electron microscopies in addition to small-angle X-ray scattering, powder X-ray diffraction, and infrared spectroscopy. These studies show the methanoldriven transition of Zn poly -DOC to Zn 4 -DOC occurs via an intermediate with no long-range order of the Zn 4 clusters, indicating the strongest interactions driving assembly are intramolecular. On the contrary, water-driven solid-to-solid transformation from Zn 4 -DOC to Zn poly -DOC exhibits crystal-to-crystal transformation. Zn poly -DOC is robust, easy to synthesize, and comprised of biologically benign components, so we demonstrate dye absorption as a proxy for water treatment applications. It favors absorption of positively charged dyes. These studies advance molecular level knowledge of the supramolecular assembly of facial surfactants that can be exploited in the design of organic-inorganic hybrid materials. This research also highlights the potential of solvent for tuning supramolecular assembly processes, leading to new hybrid materials featuring facial surfactants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions↗

Information theory optimization of signals from small-angle scattering measurements

Small-angle X-ray scattering (SAXS) of particles in solution informs on the conformational states and assemblies of biological macromolecules (bioSAXS) outside of cryo- and solid-state conditions. In bioSAXS, the SAXS measurement under dilute conditions is resolution limited, and through an inverse Fourier transform, the measured SAXS intensities directly relate to the physical space occupied by the particles via the P (r)-distribution. Yet, this inverse transform of SAXS data has been historically cast as an ill-posed, ill-conditioned problem requiring an indirect approach. Here, we show that through the applications of matrix and information theories, the inverse transform of SAXS intensity data is a well-conditioned problem. The so-called ill-conditioning of the inverse problem is directly related to the Shannon number. By exploiting the oversampling enabled by modern detectors, a direct inverse Fourier transform of the SAXS data is possible, provided the recovered information does not exceed the Shannon number. The Shannon limit corresponds to the maximum number of significant singular values that can be recovered in a SAXS experiment, suggesting this relationship is a fundamental property of band-limited inverse integral transform problems. This correspondence reduces the complexity of the inverse problem to the Shannon limit and maximum dimension. We propose a hybrid scoring function using an information theory framework that assesses both the quality of the model-data fit as well as the quality of the recovered P (r)-distribution. The hybrid score utilizes the Akaike information criteria and Durbin-Watson statistic that considers parameter-model complexity, i.e., degrees of freedom, and the randomness of the model-data residuals. The described tests and findings extend the boundaries for bioSAXS by completing the information theory formalism initiated by Peter B. Moore to enable a quantitative measure of resolution in SAXS, robustly determine maximum dimension, and more precisely define the best parameter model appropriately representing the observed scattering data.

Rambo, Robert P. [Science and Technology Facilitie↗

Charting the chemical space of Zintl phases with graph neural networks and bonding insights

A large number of Zintl phases have been discovered by solid-state chemists driven by empirical knowledge, chemical intuition and in some cases, through serendipitous accidents. These discoveries have only scratched the surface, given the vast compositional and structural diversity that Zintl phases can accommodate. The large chemical space of Zintl phases, as well as intermetallic compounds in general, remain under-explored. Here, we use graph neural networks and the upper bound energy minimization approach to efficiently scan a large chemical space of >90 000 hypothetical Zintl phases and accurately discover 1810 new thermodynamically stable phases with 90% precision, as validated with first-principles calculations. We show that our approach is more than 2× more accurate in predicting DFT stability than M3GNet (40% precision) on the same dataset. Using a random forest model and SHAP analysis, we demonstrate the critical role of ionic bonding in the thermodynamic stability of Zintl phases. Our results not only expand the known chemical landscape of Zintl phases but also highlight the efficacy of machine learning frameworks combined with domain knowledge in uncovering chemically meaningful insights across complex intermetallics.

36 MATERIALS SCIENCE↗

Mesoscale Effects of Composition and Calendering in Lithium-Ion Battery Composite Electrodes

Macrohomogeneous battery models are widely used to predict battery performance, necessarily relying on effective electrode properties, such as specific surface area, tortuosity, and electrical conductivity. While these properties are typically estimated using ideal effective medium theories, in practice they exhibit highly non-ideal behaviors arising from their complex mesostructures. In this paper, we computationally reconstruct electrodes from X-ray computed tomography of 16 nickel–manganese–cobalt-oxide electrodes, manufactured using various material recipes and calendering pressures. Due to imaging limitations, a synthetic conductive binder domain (CBD) consisting of binder and conductive carbon is added to the reconstructions using a binder bridge algorithm. Reconstructed particle surface areas are significantly smaller than standard approximations predicted, as the majority of the particle surface area is covered by CBD, affecting electrochemical reaction availability. Finite element effective property simulations are performed on 320 large electrode subdomains to analyze trends and heterogeneity across the electrodes. Significant anisotropy of up to 27% in tortuosity and 47% in effective conductivity is observed. Electrical conductivity increases up to 7.5× with particle lithiation. We compare the results to traditional Bruggeman approximations and offer improved alternatives for use in cell-scale modeling, with Bruggeman exponents ranging from 1.62 to 1.72 rather than the theoretical value of 1.5. We also conclude that the CBD phase alone, rather than the entire solid phase, should be used to estimate effective electronic conductivity. This study provides insight into mesoscale transport phenomena and results in improved effective property approximations founded on realistic, image-based morphologies.

25 ENERGY STORAGE↗

The Role of Helium on Ejecta Production in Copper

The effect of helium (He) concentration on ejecta production in OFHC-Copper was investigated using Richtmyer–Meshkov Instability (RMI) experiments. The experiments involved complex samples with periodic surface perturbations machined onto the surface. Each of the four target was implanted with a unique helium concentration that varied from 0 to 4000 appm. The perturbation’s wavelengths were λ ≈ 65 μ m, and their amplitudes h 0 were varied to determine the wavenumber ( 2 π / λ ) amplitude product k h 0 at which ejecta production beganfor Cu with and without He. The velocity and mass of the ejecta produced was quantified using Photon Doppler Velocimetry (PDV) and Lithium-Niobate (LN) pins, respectively. Our results show that there was an increase of 30% in the velocity at which the ejecta cloud was traveling in Copper with 4000 appm as compared to its unimplanted counterpart. Our work also shows that there was a finer cloud of ejecta particles that was not detected by the PDV probes but was detected by the early arrival of a “signal” at the LN pins. While the LN pins were not able to successfully quantify the mass produced due to it being in the solid state, they did provide information on timing. Our results show that ejecta was produced for a longer time in the 4000 appm copper.

36 MATERIALS SCIENCE↗

Interplay Between Stereochemically Active Lone Pair Repulsions, Sigma Hole Interactions, and Delocalized Redox Processes in Topochemical Fluoride‐Ion Insertion

Topochemical insertion/extraction of cations has emerged as a generalizable strategy for modulating the crystal and electronic structure of periodic solids. In contrast, strategies for topochemical anion insertion are poorly explored and fundamental principles for designing insertion hosts to accommodate anions remain scarce. Here, we observe reversible room-temperature fluoride-ion insertion within tunnels of Sn 2 TiO 4 defined by the stereochemical expression of Sn 5 s 2 lone pairs. X-ray scattering studies of fluoride-ion-insertion-induced crystal structure modulation and X-ray absorption/emission spectroscopy probes of electronic structure along with magnetic susceptibility measurements and first-principles calculations are used to decipher design principles underpinning reversible fluoride-ion insertion and bulk diffusion. Fluoride-ion insertion is enabled by a combination of a large, polarizable tunnel, delocalized redox at Ti─O─Sn centers, inherent repulsion between the fluoride-ion and Sn 5 s 2 electron lone pairs, and the formation of dative interactions between Sn-centered σ-holes and fluoride-ions, yielding a reversible capacity of 0.5 fluoride-ions per Sn 2 TiO 4 formula unit. Our results demonstrate that the complex interplay between dative interactions and stereochemically active lone pair repulsions is critical to defining the thermodynamics and kinetics controlling fluoride-ion insertion and diffusion. As such, the design of fluoride-ion insertion hosts for anion batteries requires site-selective modification to modulate lattice—ion interactions.

36 MATERIALS SCIENCE↗

Kinetic Probes of the Origin of Activity in MOF-Based C–H Oxidation Catalysis

The development of homogeneous catalysis is enabled by the availability of a rich toolkit of kinetics experiments, such as the Hgdrop test, that differentiate catalytic activity at ligand-supported metal complexes from potential heterogeneous catalysts derived from decomposition of molecular species. Metal-organic frameworks (MOFs) have garnered significant attention as platforms for catalysis at site-isolated, interstitial catalyst sites. Unlike homogeneous catalysis, relatively few strategies have been advanced to evaluate the origin of catalytic activity in MOF-promoted reactions. Many of the MOFs that have been examined as potential catalysts are comprised of molecular constituents that represent viable catalysts in the absence of the extended MOF lattice, and thus interfacial sites and leached homogeneous species represent potential sources of catalyst activity. Here, we demonstrate that analysis of deuterium kinetic isotope effects (KIEs) and olefin epoxidation diastereoselectivity provides probes of the origin of catalytic activity in MOF-promoted oxidation reactions. These analyses support involvement of lattice-based Fe sites in the turnover-limiting step of C–H activation with Fe-MOF-74-based materials (i.e., the MOF functions as a bona fide catalyst) and evidence that Cu 2 -based MOF MIL-125-Cu 2 O 2 functions as a solid-state initiator for solution-phase oxidation chemistry and is not involved in the turnover limiting step (i.e., the MOF does not function as a catalyst for substrate functionalization). furthermore, we anticipate that the simple experiments described here will provide a valuable tool for clarifying the role of MOFs in C–H oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Gamma radiation-induced defects in KCl, MgCl 2 , and ZnCl 2 salts at room temperature

Room temperature post-irradiation measurements of diffuse reflectance and electron paramagnetic resonance spectroscopies were made to characterize the long-lived radiation-induced species formed from the gamma irradiation of solid KCl, MgCl 2 , and ZnCl 2 salts up to 100 kGy. The method used showed results consistent with those reported for electron and gamma irradiation of KCl in single crystals. Thermal bleaching of irradiated KCl demonstrated accelerated disaggregation of defect clusters above 400 K, due to decomposition of Cl 3 - . The defects formed in irradiated MgCl 2 comprised a mixture of Cl 3 - , F-centers, and Mg + associated as M-centers. Further, Mg metal cluster formation was also observed at 100 kGy, in addition to accelerated destruction of F-centers above 20 kGy. Irradiated ZnCl 2 afforded the formation of Cl 2 - due to its high ionization potential and crystalline structure, which decreases recombination. The presence of aggregates in all cases indicates the high diffusion of radicals and the predominance of secondary processes at 295 K. Additionally, thermal bleaching studies showed that chloride aggregates’ stability increases with the ionization potential of the cation present. The characterization of long-lived radiolytic transients of pure salts provides important information for the understanding of complex salt mixtures under the action of gamma radiation.

36 MATERIALS SCIENCE↗

Y(III) Sorption at the Orthoclase (001) Surface Measured by X-ray Reflectivity

Interactions of heavy metals with charged mineral surfaces control their mobility in the environment. Here, we investigate the adsorption of Y(III) onto the orthoclase (001) basal plane, the former as a representative of rare earth elements and an analogue of trivalent actinides and the latter as a representative of naturally abundant K-feldspar minerals. In this study, we apply in situ high-resolution X-ray reflectivity to determine the sorption capacity and molecular distribution of adsorbed Y species as a function of the Y 3+ concentration, [Y 3+ ], at pH 7 and 5. With [Y 3+ ] ≥ 1 mM at pH 7, we observe an inner-sphere (IS) sorption complex at a distance of ~1.5 Å from the surface and an outer-sphere (OS) complex at 3–4 Å. Based on the adsorption height of the IS complex, a bidentate, binuclear binding mode, in which Y 3+ binds to two terminal oxygens, is proposed. In contrast, mostly OS sorption is observed at pH 5. The observed maximum Y coverage is ~1.3 Y 3+ /A UC (A UC : area of the unit cell = 111.4 Å 2 ) for all the investigated pH values and Y concentrations, which is in the expected range based on the estimated surface charge of orthoclase (001).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Study of ablation and shock generation across three orders of magnitude of laser intensity with 100 ps laser pulses

The laser ablation and subsequent shock generation in solid targets plays an important role in a variety of research topics from equation of state models for materials to inertial confinement fusion. One of the long-standing issues is the knowledge of ablation depth in the picosecond time regime. Here, we report on a direct technique for determining the ablation depth in aluminum using x-ray diffraction data from Linac Coherent Light Source at the Stanford Linear Accelerator Center. This technique gives a direct measurement of the shock wave propagation in the bulk target, enabling an ability to discern early timescale physics from late timescale effects not available in postmortem analysis. We find that the ablation depths only vary by 0.2 μm across three orders of magnitude of laser intensity, while the pressure increased by a factor of 10 following a square root dependence on laser pulse energy. We further observe that the ablation depth in this intensity range (10 11 –10 13 W/cm 2 in intensity, corresponding to 0.8–80 J/cm 2 in fluence) cannot be modeled by a universal scaling law, given the complexity of the mechanisms governing laser ablation in this intensity regime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗

Complete Evaluation on Advanced Reactor Machine Learning Subversion Attacks (Final)

Navigating through the world of Artificial Intelligence (AI) in nuclear reactors and their Instrumentation and Control (I&C) systems demands a careful, deliberate journey. AI’s capability to manage massive datasets and streamline control systems has indeed carved out a significant role in various sectors, including nuclear energy. However, while AI, and particularly Large Language Models (LLMs), bring a lot to the table in terms of operational efficiency and anomaly detection, they also expose the sector to a new breed of cybersecurity threats, like Inference Attacks, Adversarial Attacks, and Trojan Attacks. This guide is designed to be a straightforward manual, diving deep into the intertwining worlds of AI and cybersecurity within nuclear reactors, and tailoring insights for three crucial audiences: I&C Vendors/Developers, Nuclear Regulators, and Nuclear Reactor Operators and Cyber Defense Teams. (1) Section 2, directed at I&C Vendors/Developers, will provide a clear and focused look at several cybersecurity attacks, offering practical recommendations and detailed scenarios related to AI cybersecurity. This section isn’t just about identifying problems but also about giving solid, usable solutions. (2) Section 3, meant for Nuclear Regulators, gets straight to the point about regulations, policy suggestions, and guidelines that are needed to lay down a robust, secure, and ethical foundation for the application of AI in nuclear operations. The focus is on making sure that everything adheres to international standards and laws while being practicable and clear-cut. (3) Section 4, aimed at Nuclear Reactor Operators and Cyber Defense Teams, offers an exhaustive exploration and technical reports, with clear recommendations and scenario analyses vital to protect operational environments and guarantee the secure application of AI in nuclear reactor operations. The goal is simple: as we step into an era where AI becomes a fundamental element of our technological and energy infrastructures, this guide is here to act as a clear, direct handbook, ensuring that AI is implemented within the nuclear sector in a manner that is secure, responsible, and practical. It’s about striking a balance – optimizing the undeniable benefits offered by AI while securing and shielding against potential cyber threats as we move through this new and complex landscape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Local structural distortions drive magnetic molecular field in compositionally complex spinel oxide

Understanding how local distortions determine the functional properties of high entropy materials, containing five or more elements at the same crystallographic site, is an open challenge. We address this for a compositionally complex spinel oxide (Mn 0.2 Co 0.2 Ni 0.2 Cu 0.2 Zn 0.2 )Cr 2 O 4 (A 5 Cr 2 O 4 ). By comparatively examining extended X-ray absorption fine structure on A 5 Cr 2 O 4 and its parent counterparts, ACr 2 O 4 , along with density functional theory calculations for multiple configurations, we find that the element-specific distortions go beyond the first neighbor. Specifically, the strong Jahn-Teller distortion present in CuCr 2 O 4 is found to be completely suppressed in A 5 Cr 2 O 4 even locally. Instead, there is a broad distribution of Cu-O and Cu-Cr bond distances, while other A-O distances acquire certain specific values. This study demonstrates the additional flexibility of a cationic sublattice in maintaining a uniform long-range structure, in contrast to previous reports showing only the accommodative anionic sublattice. The mean-field magnetic interactions of A 5 Cr 2 O 4 exhibit a striking resemblance to those of NiCr 2 O 4 , despite the presence of multiple magnetic ions and variable bond lengths. This originates from the comparability of bond lengths around Cr in both materials. Our study paves the way for a deeper understanding of the impact of local structural distortions on the physical properties of compositionally complex quantum materials.

36 MATERIALS SCIENCE↗

Steric augmentation of three-coordinate Cu( I ) β-diketiminate isocyanide chromophores to achieve microsecond excited-state lifetime

Copper(I) complexes are promising alternatives to noble metal-based photosensitizers. A recently developed class of three-coordinate copper(I) charge-transfer chromophores, pairing β-diketiminate ligands with aryl isocyanides, exhibits excited-state lifetimes that are responsive to the steric profile of the isocyanide, reaching a value of nearly 300 nanoseconds when a substituted m-terphenyl isocyanide was used. In this work, we show that extreme steric augmentation of the β-diketiminate and m-terphenyl isocyanide ligands can lead to further improvements in excited-state lifetime, with one example surpassing 1 µs. This study includes a series of eight compounds of the general formula Cu(RNacNac)(CN-Ar X2 ), where RNacNac is the substituted β-diketiminate and CN-Ar X2 is the substituted m-terphenyl isocyanide. All eight compounds are crystallographically characterized, and their excited-state properties are thoroughly evaluated by a combination of steady-state and time-resolved photoluminescence studies. This combined structural/photophysical approach unveils a correlation between common steric parameters, derived from buried volume (%V bur ) and solid angle analysis, and the excited-state lifetime. Our investigation reveals that the steric profile of the β-diketiminate has a much larger impact on the steric profile and lifetime, whereas the m-terphenyl isocyanide substituents have an unsystematic and subtle influence on these two correlated parameters. Nevertheless, judicious pairing of the two ligands is critical for achieving long excited-state lifetimes.

Kumar, Ashish [University of Houston, TX (United S↗