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At least 325 records · Page 18

Perturbation of 1 J C,F Coupling in Carbon–Fluorine Bonds on Coordination to Lewis Acids: A Structural, Spectroscopic, and Computational Study

A lithiated m-terphenyl ligand bearing fluorine atoms at the ortho positions of the flanking aryl rings was synthesized and characterized using single crystal X-ray diffraction, variable-temperature multinuclear NMR spectroscopy, and computational methods. Here, changes in 1 J C,F on coordination to lithium as a spectroscopic observable parametrizing the strength of the C–F···Li interaction are described, and a general, qualitative relationship between C–F bond lengths, Δ 1 J C,F values, and the extent of C–F bond activation as a result of Lewis acid coordination is proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Suppressed Lone Pair Electrons Explain Unconventional Rise of Lattice Thermal Conductivity in Defective Crystalline Solids

Manipulating thermal properties of materials can be interpreted as the control of how vibrations of atoms (known as phonons) scatter in a crystal lattice. Compared to a perfect crystal, crystalline solids with defects are expected to have shorter phonon mean free paths caused by point defect scattering, leading to lower lattice thermal conductivities than those without defects. While this is true in many cases, alloying can increase the phonon mean free path in the Cd-doped AgSnSbSe 3 system to increase the lattice thermal conductivity from 0.65 to 1.05 W m –1 K –1 by replacing 18% of the Sb sites with Cd. It is found that the presence of lone pair electrons leads to the off-centering of cations from the centrosymmetric position of a cubic lattice. X-ray pair distribution function analysis reveals that this structural distortion is relieved when the electronic configuration of the dopant element cannot produce lone pair electrons. Furthermore, a decrease in the Grüneisen parameter with doping is experimentally confirmed, establishing a relationship between the stereochemical activity of lone pair electrons and the lattice anharmonicity. The observed “harmonic” behavior with doping suggests that lone pair electrons must be preserved to effectively suppress phonon transport in these systems.

36 MATERIALS SCIENCE↗

Cross-species analysis of FcγRIIa/b (CD32a/b) polymorphisms at position 131: structural and functional insights into the mechanism of IgG- mediated phagocytosis in human and macaque

Introduction Antibodies play a critical role in immunity in part by mediating clearance of pathogens and infected cells by antibody-dependent cellular phagocytosis (ADCP) through engagement of Fc gamma receptors (FcγRs) on innate immune cells. Among these, FcγRIIa (CD32a) is a key activating receptor expressed on macrophages, dendritic cells, and other antigen-presenting cells. Its affinity for IgG and ability to mediate ADCP is influenced by allelic polymorphisms. In humans, a single amino acid polymorphism at position 131, where histidine (H) is substituted with arginine (R), leads to decreased IgG1 and IgG2 subclass binding affinity and, consequently, lower efficiency of phagocytic responses. Rhesus macaques ( Macaca mulatta ), which are widely used as nonhuman primate models, exhibit a similar polymorphism at position 131 of FcγRIIa, but with arginine replaced by proline (P). Here, we investigated structure-function relationships associated with the FcγRIIa polymorphism at position 131 in both species, specifically with respect to IgG1 and IgG2. Methods We determined the structures of complexes formed by each variant with IgG1 Fc and those formed by the higher affinity variant with IgG2 Fc for both species by x-ray crystallography and linked these structures to affinity and activity using SPR and an ADCP assay. We also determined the structure of human inhibitory FcγRIIb (CD32b) in complex with IgG1 Fc by x-ray crystallography. Results Through analysis of these structures, our studies reveal that FcγRIIa engagement is minimally influenced by Fc glycan composition, distinguishing it from FcγRIIIa whose affinity is strongly influenced by glycan-composition. Comparative structures of human and macaque FcγRIIa variants demonstrate species- and allele-specific differences in Fc binding, but our functional assays showed only minimal allele-specific effects in humans. In contrast, allele-specific effects in macaques were highly significant; the macaque P 131 variant showing uniformly reduced IgG affinity. Conclusion These insights highlight fundamental interspecies and allelic distinctions that are critical for interpreting FcγRIIa-mediated effector functions in macaque models and for optimizing translational antibody and vaccine design.

Tolbert, William D.↗

Temperature and Solvent Effects on H 2 Splitting and Hydricity: Ramifications on CO 2 Hydrogenation by a Rhenium Pincer Catalyst

The catalytic hydrogenation of carbon dioxide holds immense promise for applications in sustainable fuel synthesis and hydrogen storage. Mechanistic studies that connect thermodynamic parameters with the kinetics of catalysis can provide new understanding and guide predictive design of improved catalysts. Reported here are thermochemical and kinetic analyses of a new pincer-ligated rhenium complex ( tBu POCOP)Re(CO) 2 ( tBu POCOP = 2,6-bis(di-tert-butylphosphinito)phenyl) that catalyzes CO 2 hydrogenation to formate with faster rates at lower temperature. Because the catalyst follows the prototypical “outer sphere” hydrogenation mechanism, comprehensive studies of temperature and solvent effects on the H 2 splitting and hydride transfer steps are expected to be relevant to many other catalysts. Strikingly large entropy associated with cleavage of H2 results in a strong temperature dependence on the concentration of [( tBu POCOP)Re(CO) 2 H] – present during catalysis, which is further impacted by changing the solvent from toluene to tetrahydrofuran to acetonitrile. New methods for determining the hydricity of metal hydrides and formate at temperatures other than 298 K were developed, providing insight into how temperature can influence the favorability of hydride transfer during catalysis. These thermochemical insights guided the selection of conditions for CO 2 hydrogenation to formate with high activity (up to 364 h –1 at 1 atm or 3330 h –1 at 20 atm of 1:1 H 2 CO 2 ). In cases where hydride transfer is the highest individual kinetic barrier, entropic contributions to outer sphere H 2 splitting lead to a unique temperature dependence: catalytic activity increases as temperature decreases in tetrahydrofuran (200-fold increase upon cooling from 50 to 0 °C) and toluene (4-fold increase upon cooling from 100 to 50 °C). Furthermore, the ramifications on catalyst structure-function relationships are discussed, including comparisons between “outer sphere” mechanisms and metal–ligand cooperation mechanisms.

14 SOLAR ENERGY↗

Breaking the Brønsted–Evans–Polanyi Relation with Dual-Metal Sites

Linear scaling relationships impose inherent limitations on catalyst activity; the Brønsted−Evans−Polanyi (BEP) relation, which correlates activation and reaction energies, is a prominent example. Here we report a dual-metal site catalyst (DMSC) on ceria that breaks the BEP relation for C−C coupling of methyl intermediates an elementary step in methane coupling to form ethane. The DMSC structure on CeO 2 (111) was discovered by density-functional theory (DFT) structural exploration and confirmed to be stable via ab initio thermodynamics and ab initio molecular dynamics. Homonuclear and heteronuclear DMSCs of Ni, Pd, Pt, Fe, Ru, Os, Co, Rh, and Ir (45 pairs in total) were examined for methyl affinity and methyl−methyl coupling activation energy. We found that many heteronuclear DMSCs break the BEP linear scaling due to a mixed low-affinity/high-affinity coadsorption of the two methyl groups, decoupling the step responsible for the activation energy (E a ) at the low-affinity site from the overall reaction energy (ΔE) determined by both sites. This mechanism of breaking the BEP relationship via the DMSCs offers a catalyst design principle for C−C coupling reactions.

Chen, Yiming [Vanderbilt Univ., Nashville, TN (Uni↗

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Oxygen redox activities governing high-voltage charging reversibility of Ni-rich layered cathodes

A schematic illustration indicative of the improved structural reversibility through stabilizing oxidized oxygen by Al doping. The chemical reactions and phase transitions at high voltages are generally considered to determine the electrochemical properties of high-voltage layered cathodes such as Ni-rich rhombohedral oxides. Even if significantly higher SOCs (states-of-charge) are utilized above the capability of transition metal redox (primarily Ni and Co), the effect of oxygen redox on Ni-rich rhombohedral oxides still looks mysterious thereby necessitating research that can clarify the relationship between redox reactions and phase transitions. Here, we performed a comprehensive and comparative study of the cationic and anionic redox reactions, as well as the structural evolution of a series of commercial Ni-rich layered oxides with and without Al doping. We combined the results from X-ray spectroscopy, operando electrochemical mass spectrometry, and neutron diffraction with electrochemical properties and thereby revealed the different oxygen redox activities associated with structural and electrochemical degradations. We reveal that Al doping suppresses the irreversible oxygen release but enhances the lattice oxygen oxidization. With this modulated oxygen redox activity, the Ni-rich layered oxides’ notorious H2–H3 structural phase transition becomes highly reversible. Our findings disentangle the different oxygen redox activities during high-voltage cycling and clarify the role of dopants in the Ni-rich layered oxides in terms of structural and electrochemical stability, shedding light on the future direction of optimizing layered cathode materials for safer high energy-density secondary batteries.

Lee, Gi-Hyeok↗

Access to Ru(IV)–Ru(V) and Ru(V)–Ru(VI) Redox in Layered Li 7 RuO 6 via Intercalation Reactions

The push to increase the capacity of oxides to store charge as Li-ion battery cathodes has challenged our knowledge of the boundaries of redox chemistry and its relationship to the atomic structure. Layered phases with Ru are now classical models in the quest for refined theories. Current understanding dictates that the highest formal state that can be reached in them is Ru(V), after which activity centered at the oxide anions is triggered. Yet, this picture is challenged by this investigation of the intercalation chemistry of Li 7 RuO 6 . Coupling structural and spectroscopic analysis with computational simulations, we show that Li 7 RuO 6 is capable of highly reversible lithiation to Li 8 RuO 6 through the Ru(V)/Ru(IV) redox couple. Further, Li 7 RuO 6 can also undergo anodic Li deintercalation, showing clear evidence of the reversible formation of Ru(VI) with octahedral coordination, an unusual state that is not accessible in other layered oxides. The results highlight the versatility of the Ru-O bond to undergo distinct redox transitions depending on the specific layered arrangements. They enrich our understanding of redox chemistry in solids while underscoring the need for descriptions of charge compensation that reflect the nuance of covalent interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Relating Geometric Nanoconfinement and Local Molecular Environment to Diffusion in Ionic Polymer Membranes

Understanding structure-diffusion relationships in ionic polymer membranes not only illuminates fundamental mechanisms for membrane transport, but also informs further membrane development. In this study, we employ NMR diffusometry and molecular dynamics (MD) simulations to investigate diffusion coefficients and activation energies of diffusion (Ea) for both a lithium-form perfluorosulfonic acid membrane and aqueous solutions of lithium triflate. NMR shows that, at high water/ion molar ratio (?), Ea for water diffusion is slightly lower in the membrane than in solution. Conversely, membrane transport exhibits much higher Ea at low hydration as compared to solutions. MD simulations of a model system consisting of carbon nanotubes with varying diameter reveal that Ea of diffusion clearly relates to both the geometric nanoconfinement of the hydrophilic pathways in the membrane as well as the local molecular environment. These results demonstrate that Ea of diffusion can serve as a revelatory tool for the study of molecular transport processes and the coupling of morphology with transport at the nanoscale. This study thus provides new insights and new experimental and computational models for understanding transport in a wide range of polymer membranes, such as those used in molecular separations applications.

Zhang, Rui↗

Controlling Molecular Structure and Spin with Multiconfigurational Quantum Chemistry (Final Technical Report)

For many first-row transition metal complexes, structure-property relationships can be obtained from high-level molecular geometry optimizations and subsequent electronic structure studies. The project funded under this award utilized newly implemented fully internally contracted (FIC) nuclear gradients for extended multi-state (XMS) complete active space second-order multireference perturbation theory (CASPT2) to explore geometry changes in first-row transition metal coordination complexes. At the start of the project, only one full geometry optimization using FIC-CASPT2 analytical gradients had been reported (J. Chem. Theory Comput., 2016, 12 (8), 3781), and many open-questions regarding the performance and achievable accuracy in applying such computations to larger complexes persisted. Key deliverables in the report include the implementation of the numerical Hessian and subsequent vibrational analysis in the BAGEL program package. This includes both full Hessian vibrational analysis (FHVA) and a partial Hessian vibrational analysis (PHVA). The latter of which allows us to reduce the significant cost of computing the vibrational frequencies in a large molecule by focusing on the modes of highest interest. The gradient code also proved useful in the development of an approach to improve the Hubbard-U correction by removing bias in predicting spin-splitting in Fe(II) complexes via plane-wave density functional theory (DFT). Finally, we showed for three families of complexes (spin-crossover (SCO) complexes, metallocorroles complexes, and those with metal-metal bonds) that CASPT2 can result in good molecular geometries and established best practices in undertaking this work. We are now using this approach in collaborative projects with experimental groups, which would not have been possible at the start of this project. A common theme also arose through this work that static and dynamic correlation must be recovered in a balanced way to yield quantitative results. By systematically varying how both effects were included, we were able to make key chemical insights. This work supported the training of two postdoctoral scholars, one graduate student, and one undergraduate student in applying high-level wavefunction based methods to challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Profiling the molecular destruction rates of temperature and humidity as well as the turbulent kinetic energy dissipation in the convective boundary layer

A simultaneous deployment of Doppler, temperature, and water-vapor lidars is able to provide profiles of molecular destruction rates and turbulent kinetic energy (TKE) dissipation in the convective boundary layer (CBL). Horizontal wind profiles and profiles of vertical wind, temperature, and moisture fluctuations are combined, and transversal temporal autocovariance functions (ACFs) are determined for deriving the dissipation and molecular destruction rates. These are fundamental loss terms in the TKE as well as the potential temperature and mixing ratio variance equations. These ACFs are fitted to their theoretical shapes and coefficients in the inertial subrange. Error bars are estimated by a propagation of noise errors. Sophisticated analyses of the ACFs are performed in order to choose the correct range of lags of the fits for fitting their theoretical shapes in the inertial subrange as well as for minimizing systematic errors due to temporal and spatial averaging and micro- and mesoscale circulations. We demonstrate that we achieve very consistent results of the derived profiles of turbulent variables regardless of whether 1 or 10 s time resolutions are used. We also show that the temporal and spatial length scales of the fluctuations in vertical wind, moisture, and potential temperature are similar with a spatial integral scale of ≈160 m at least in the mixed layer (ML). The profiles of the molecular destruction rates show a maximum in the interfacial layer (IL) and reach values of ϵ m ≃ 7 x 10 -4 g 2 kg −2 s −1 for mixing ratio and ϵ θ ≃ 1.6 x 10 -3 K 2 s −1 for potential temperature. In contrast, the maximum of the TKE dissipation is reached in the ML and amounts to ≃ 10 -2 m 2 s −3 . We also demonstrate that the vertical wind ACF coefficient k w ∝ $\overline{w'^{2}}$ and the TKE dissipation ϵ ∝ ($\overline{w'^{2}}$) 3/2 . For the molecular destruction rates, we show that ϵ m ∝ $\overline{m'^{2}}$ ($\overline{w'^{2}}$) 1/2 and ϵ θ ∝ $\overline{θ'^{2}}$ ($\overline{w'^{2}}$) 1/2 . These equations can be used for parameterizations of ϵ, ϵ m , and ϵ θ . All noise error bars are derived by error propagation and are small enough to compare the results with previous observations and large-eddy simulations. The results agree well with previous observations but show more detailed structures in the IL. Consequently, the synergy resulting from this new combination of active remote sensors enables the profiling of turbulent variables such as integral scales, variances, TKE dissipation, and the molecular destruction rates as well as deriving relationships between them. The results can be used for the parameterization of turbulent variables, TKE budget analyses, and the verification of large-eddy simulations.

dissipation rate↗

Palladium/Zeolite Low Temperature Passive NOx Adsorbers (PNA): Structure-Adsorption Property Relationships for Hydrothermally Aged PNA Materials

Zeolites with different framework structures (SSZ-13, ZSM-5, BEA) but similar Si/Al ratios and Pd loading (~1 wr%) were synthesized and evaluated as low temperature passive NOx adsorbers (PNA). These materials exhibit high NOx adsorption efficiency with atomically dispersed Pd the active adsorption site. Hydrothermal aging at 750 ºC for 16 hours in the presence of 10% water vapor in air resulted in the formation of PdO nanoparticles in all three samples as evidenced by high energy XRD. Hydrothermal aging of the small-pore Pd/SSZ-13 (Si/Al = 6), which contain ~100-90% atomically dispersed palladium ions, decreases its PNA performance only by ~10-20%. High-field solid state 27Al NMR studies on the fresh and aged samples substantiate dealumination and significant changes in the distribution of Al (and thus, Bronsted acid) sites after hydrothermal aging. FTIR measurements with NO probe molecule and titration of Bronsted acid sites with nitrosyl (NO+) ions further corroborate the 27Al NMR data. Because framework aluminum atoms are the anchoring sites for atomically dispersed Pd ions, their elution from the framework causes the loss of active atomically dispersed Pd species. Furthermore, with the aid of HAADF-STEM imaging and synchrotron XRD studies, we further confirm and visualize the fate of these Pd species – they agglomerate into PdO nanoparticles on the external surface of zeolite. Consequently, these changes lead to the decrease in PNA performance of these materials after hydrothermal aging. The thus formed agglomerates cannot be re-dispersed back to their ionic state due to the loss of framework Al T-sites and/or inherent stability of such large PdO particles. Our study clearly demonstrates that, unlike in previous studies that found increased PNA performance upon HTA , high temperatures hydrothermal aging of PNA materials that contain atomically dispersed Pd initially, results in a decrease in NOx storage efficiency due mostly to the formation of PdO agglomerates. However, we also highlight the high hydrothermal stability of predominantly atomically dispersed 1-3 wt% Pd/SSZ-13 (Si/Al = 6), whose performance decreases only marginally after prolonged hydrothermal aging at 750 ºC. Overall, this study shows that hydrothermally stable passive NOx materials can be prepared using small-pore SSZ-13 zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modern analogs for understanding pollen-vegetation dynamics in a Mediterranean mosaic landscape (Balearic Islands, Western Mediterranean)

This paper presents the study of modern pollen analogs from the Balearic Islands. While similar studies have been largely applied to mainland areas, research focused on modern vegetation dynamics on Mediterranean islands remains very rare. In this research, we combine vegetation surveys, pollen analysis and multivariate statistics to understand landscape composition. The main objectives of are: (1) to examine pollen-vegetation relationships in relation to environmental and land-use variables; (2) to understand modern pollen representation in a mosaic landscape structure; and (3) to propose pollen indicators that characterize the primary vegetation types from the Balearic Islands to better interpret past pollen records in Mediterranean island environments. Pollen results and Redundancy Analysis (RDA) distinguish three major groups: (a) Holm oak and box formations; (b) maquis and garrigues; and (c) anthropogenic and open habitats. Landscape form, mean decadal rainfall, mean decadal temperature, fire activity, trampling, slope percentage, wet/flooded soil, saline soil, distance to agropastoral cells, gHM index, domestic herbivory presence, agropastoral use, and soil type are the major variables explaining modern pollen assemblage variation in our research. Poaceae undiff., Plantago sp., Apiaceae undiff., Cerealia-t, and Cichorieae are highly correlated to human activities but should be interpreted cautiously when occurring in low values. Quercus ilex-t, Hypericum, and Buxus are correlated to humid locations while Pistacia, Pinus, Juniperus-t, and Olea to high mean decadal temperatures. Our study indicates how pollen analysis and multivariate analysis are powerful tools for characterizing the mosaic landscape, with special focus on the main vegetation types of the Balearic Islands.

Geology↗

Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning

Abstract The elementary excitations in metallic glasses (MGs), i.e., β processes that involve hopping between nearby sub-basins, underlie many unusual properties of the amorphous alloys. A high-efficacy prediction of the propensity for those activated processes from solely the atomic positions, however, has remained a daunting challenge. Recently, employing well-designed site environment descriptors and machine learning (ML), notable progress has been made in predicting the propensity for stress-activated β processes (i.e., shear transformations) from the static structure. However, the complex tensorial stress field and direction-dependent activation could induce non-trivial noises in the data, limiting the accuracy of the structure-property mapping learned. Here, we focus on the thermally activated elementary excitations and generate high-quality data in several Cu-Zr MGs, allowing quantitative mapping of the potential energy landscape. After fingerprinting the atomic environment with short- and medium-range interstice distribution, ML can identify the atoms with strong resistance or high compliance to thermal activation, at a high accuracy over ML models for stress-driven activation events. Interestingly, a quantitative “between-task” transferring test reveals that our learnt model can also generalize to predict the propensity of shear transformation. Our dataset is potentially useful for benchmarking future ML models on structure-property relationships in MGs.

36 MATERIALS SCIENCE↗

Surface-Doped Zinc Gallate Colloidal Nanoparticles Exhibit pH-Dependent Radioluminescence with Enhancement in Acidic Media

As abnormal acidic pH symbolizes dysfunctions of cells, it is highly desirable to develop pH-sensitive luminescent materials for diagnosing disease and imaging-guided therapy using high-energy radiation. Herein, we explored near-infrared-emitting Cr-doped zinc gallate ZnGa 2 O 4 nanoparticles (NPs) in colloidal solutions with different pH levels under X-ray excitation. Ultrasmall NPs were synthesized via a facile hydrothermal method by controlling the addition of ammonium hydroxide precursor and reaction time, and structural characterization revealed Cr dopants on the surface of NPs. The synthesized NPs exhibited different photoluminescence and radioluminescence mechanisms, confirming the surface distribution of activators. It was observed that the colloidal NPs emit pH-dependent radioluminescence in a linear relationship, and the enhancement reached 4.6-fold when pH = 4 compared with the colloidal NPs in the neutral solution. This observation provides a strategy for developing new biomaterials by engineering activators on the nanoparticle surfaces for potential pH-sensitive imaging and imaging-guided therapy using high-energy radiation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Colloidal Platinum–Copper Nanocrystal Alloy Catalysts Surpass Platinum in Low-Temperature Propene Combustion

Low-temperature removal of noxious environmental emissions plays a critical role in minimizing the harmful effects of hydrocarbon fuels. Emission-control catalysts typically consist of large quantities of rare, noble metals (e.g., platinum and palladium), which are expensive and environmentally damaging metals to extract. Alloying with cheaper base metals offers the potential to boost catalytic activity while optimizing the use of noble metals. In this work, we show that Pt x Cu 100–x catalysts prepared from colloidal nanocrystals are more active than the corresponding Pt catalysts for complete propene oxidation. By carefully controlling their composition while maintaining nanocrystal size, alloys with dilute Cu concentrations (15–30% atomic fraction) demonstrate promoted activity compared to pure Pt. Complete propene oxidation was observed at temperatures as low as 150 °C in the presence of steam, and five to ten times higher turnover frequencies were found compared to monometallic Pt catalysts. Additionally, through DFT studies and structural and catalytic characterization, the remarkable activity of dilute Pt x Cu 100–x alloys was related to the tuning of the electronic structure of Pt to reach optimal binding energies of C* and O* intermediates. This work provides a general approach toward investigation of structure–property relationships of alloyed catalysts with efficient and optimized use of noble metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GNATFinder

SAND2023-05510O GNATFinder is a software tool for extracting graphical neural activity threads (GNATs) from spiking neural networks. GNATFinder efficiently extracts GNATs from spiking neural network data. A GNAT is a graph that represents the causal relationships between individual spikes in a spiking network using a combination of the network connectivity structure and the timing of individual spikes. The software allows for identifying similar, repeating threads that often reappear in a dataset. Using quadtree data structures to recursively subdivide the time interval over which spikes were produced by the spiking network, GNATFinder allows for efficient pairwise comparisons of spike times to determine the degree of causal relatedness among all pairs of spikes in a dataset. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

Local Structure Analysis and Modelling of Lignin‐Based Carbon Composites through the Hierarchical Decomposition of the Radial Distribution Function

Abstract Carbonized lignin has been proposed as a sustainable and domestic source of activated, amorphous, graphitic, and nanostructured carbon for many industrial applications as the structure can be tuned through processing conditions. However, the inherent variability of lignin and its complex physicochemical structure resulting from feedstock and pulping selection make the Process‐Structure‐Property‐Performance (PSPP) relationships hard to define. In this work, radial distribution functions (RDFs) from synchrotron X‐ray and neutron scattering of lignin‐based carbon composites (LBCCs) are investigated using the Hierarchical Decomposition of the Radial Distribution Function (HDRDF) modelling method to characterize the local atomic environment and develop quantitative PSPP relationships. PSPP relationships for LBCCs defined by this work include crystallite size dependence on lignin feedstock as well as increasing crystalline volume fraction, nanoscale composite density, and crystallite size with increasing reduction temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗