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Complex Structural Disorder in the Zintl Phases Yb 10 MnSb 9 and Yb 21 Mn 4 Sb 18
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Complex Structure of Molten NaCl–CrCl 3 Salt: Cr–Cl Octahedral Network and Intermediate-Range Order
Not Available
Revealing the Chemical and Structural Complexity of Electrochemical Ion Exchange in Layered Oxide Materials
Not Available
Complex Structure of Molten FLiBe (2 Li F – Be F 2 ) Examined by Experimental Neutron Scattering, X-Ray Scattering, and Deep-Neural-Network Based Molecular Dynamics
The use of molten salts as coolants, fuels, and tritium breeding blankets in the next generation of fission and fusion nuclear reactors benefits from furthering the characterization of the molecular structure of molten halide salts, paving the way to predictive capability of the chemical and thermophysical properties of molten salts. Due to its neutronic, chemical, and thermochemical properties, 2 Li F - Be F 2 is a candidate molten salt for several fusion- and fission-reactor designs. We performed neutron and x-ray total-scattering measurements to determine the atomic structure of liquid 2 Li F - Be F 2 . We also performed and neural-network molecular-dynamics simulations to predict the structure obtained by neutron- and x-ray-diffraction experiments. The use of machine learning provides improvements to the efficiency in predicting the structure at a longer length scales than is achievable with simulations at significantly lower computational expense while retaining near accuracy. We found that the NNMD simulations accurately predicted the Be F 4 2 − oligomer formations seen in the experimental first-structure-factor peak. Our combination of high-resolution measurements with large-scale molecular dynamics provided an avenue to explore and experimentally verify the intermediate-range ordering beyond the first-nearest neighbor that has posed too many experimental and computational challenges in previous works. With a deeper understanding of the salt structure and ion ordering, the evolution of salt chemistry over the lifetime of a reactor can be better predicted, which is crucial to the licensing and operation of advanced fission and fusion reactors that employ molten salts. To this end, this work will serve as a reference for future studies of salt structure and macroscopic properties with and without the addition of solutes. Published by the American Physical Society 2024
Unraveling and Exploiting Complex Structures in Optimization Using OptiGraphs.
Abstract not provided.
Generation of Models of Materials with Complex Structure
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Developing a National Structural Complexity Database for U.S. Saline Basins
For presentation at the 2023 FECM / NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 28-September 1, 2023
Developing a National Structural Complexity Database for U.S. Saline Basins
For presentation at the 2023 FECM/NETL Carbon Management Research Project Review Meeting, Pittsburgh, PA, August 28-September 1, 2023.
Developing a National Structural Complexity Database for U.S. Saline Basins
For presentation at the Geological Society of America 2023 Annual Meeting, Pittsburgh, PA, October 15-18, 2023.
A Micelle Electrolyte Enabled by Fluorinated Ether Additives for Polysulfide Suppression and Li Metal Stabilization in Li-S Battery
The Li-S battery is a promising next-generation technology due to its high theoretical energy density (2600 Wh kg -1 ) and low active material cost. However, poor cycling stability and coulombic efficiency caused by polysulfide dissolution have proven to be major obstacles for a practical Li-S battery implementation. In this work, we develop a novel strategy to suppress polysulfide dissolution using hydrofluoroethers (HFEs) with bi-functional, amphiphlic surfactant-like design: a polar lithiophilic "head" attached to a fluorinated lithiophobic "tail." A unique solvation mechanism is proposed for these solvents whereby dissociated lithium ions are readily coordinated with lithiophilic "head" to induce self-assembly into micelle-like complex structures. Complex formation is verified experimentally by changing the additive structure and concentration using small angle X-ray scattering (SAXS). These HFE-based electrolytes are found to prevent polysulfide dissolution and to have excellent chemical compatibility with lithium metal: Li||Cu stripping/plating tests reveal high coulombic efficiency (>99.5%), modest polarization, and smooth surface morphology of the uniformly deposited lithium. Li-S cells are demonstrated with 1395 mAh g-1 initial capacity and 71.9% retention over 100 cycles at >99.5% efficiency-evidence that the micelle structure of the amphiphilic additives in HFEs can prohibit polysulfide dissolution while enabling facile Li + transport and anode passivation.
Accurate Thermochemistry of Complex Lignin Structures via Density Functional Theory, Group Additivity, and Machine Learning
A molecular-level understanding of lignin structures and bond dissociation energies could facilitate depolymerization technologies. Still, this information is currently limited due to the lack of databases and the simplification of surrogate models. Here, substitution effects on seven common linkages in lignin polymers are systematically investigated. An automated reaction network generator is employed to create a database of structures. A new group additivity (GA) model based on principal component analysis (PCA) descriptors is introduced and trained on gas-phase density functional theory data of 4100 species at the M06-2X/6-311++G(d,p) level. Hydrogen bonds, local steric, and nonaromatic ring contributions are also incorporated. Lastly, we improve the accuracy of the group additivity model to reach the G4 theory by computing a data set of 770 species at this level and using a data fusion approach.
Uncertainty-Aware, Structure-Preserving Machine Learning Approach for Domain Shift Detection From Nonlinear Dynamic Responses of Structural Systems
Complex structural systems deployed for aerospace, civil, or mechanical applications must operate reliably under varying operational conditions. Structural health monitoring (SHM) systems help ensure the reliability of these systems by providing continuous monitoring of the state of the structure. SHM relies on synthesizing measured data with a predictive model to make informed decisions about structural states. However, these models—which may be thought of as a form of a digital twin—need to be updated continuously as structural changes (e.g., due to damage) arise. We propose an uncertainty-aware machine learning model that enforces distance preservation of the original input state space and then encodes a distance-aware mechanism via a Gaussian process (GP) kernel. The proposed approach leverages the spectral-normalized neural GP algorithm to combine the flexibility of neural networks with the advantages of GP, subjected to structure-preserving constraints, to produce an uncertainty-aware model. This model is used to detect domain shift due to structural changes that cannot be observed directly because they may be spatially isolated (e.g., inside a joint or localized damage). This work leverages detection theory to detect domain shift systematically given statistical features of the prediction variance produced by the model. The proposed approach is demonstrated on a nonlinear structure being subjected to damage conditions. In conclusion, it is shown that the proposed approach is able to rely on distances of the transformed input state space to predict increased variance in shifted domains while being robust to normative changes.
Imaging Complex Subsurface Structures for Geothermal Exploration at Pirouette Mountain and Eleven-Mile Canyon in Nevada
Accurate imaging of subsurface complex structures with faults is crucial for geothermal exploration because faults are generally the primary conduit of hydrothermal flow. It is very challenging to image geothermal exploration areas because of complex geologic structures with various faults and noisy surface seismic data with strong and coherent ground-roll noise. In addition, fracture zones and most geologic formations behave as anisotropic media for seismic-wave propagation. Properly suppressing ground-roll noise and accounting for subsurface anisotropic properties are essential for high-resolution imaging of subsurface structures and faults for geothermal exploration. We develop a novel wavenumber-adaptive bandpass filter to suppress the ground-roll noise without affecting useful seismic signals. This filter adaptively exploits both characteristics of the lower frequency and the smaller velocity of the ground-roll noise than those of the signals. Consequently, this filter can effectively differentiate the ground-roll noise from the signal. We use our novel filter to attenuate the ground-roll noise in seismic data along five survey lines acquired by the U.S. Navy Geothermal Program Office at Pirouette Mountain and Eleven-Mile Canyon in Nevada, United States. We then apply our novel anisotropic least-squares reverse-time migration algorithm to the resulting data for imaging subsurface structures at the Pirouette Mountain and Eleven-Mile Canyon geothermal exploration areas. The migration method employs an efficient implicit wavefield-separation scheme to reduce image artifacts and improve the image quality. Our results demonstrate that our wavenumber-adaptive bandpass filtering method successfully suppresses the strong and coherent ground-roll noise in the land seismic data, and our anisotropic least-squares reverse-time migration produces high-resolution subsurface images of Pirouette Mountain and Eleven-Mile Canyon, facilitating accurate fault interpretation for geothermal exploration.
Selective deuteration of an RNA:RNA complex for structural analysis using small-angle scattering
The structures of RNA:RNA complexes regulate many biological processes. Despite their importance, protein-free RNA:RNA complexes represent a tiny fraction of experimentally determined structures. Here, we describe a joint small-angle X-ray and neutron scattering (SAXS/SANS) approach to structurally interrogate conformational changes in a model RNA:RNA complex. Using SAXS, we measured the solution structures of the individual RNAs and of the overall RNA:RNA complex. With SANS, we demonstrate, as a proof of principle, that isotope labeling and contrast matching (CM) can be combined to probe the bound state structure of an RNA within a selectively deuterated RNA:RNA complex. Furthermore, we show that experimental scattering data can validate and improve predicted AlphaFold 3 RNA:RNA complex structures to reflect its solution structure. In conclusion, our work demonstrates that in silico modeling, SAXS, and CM-SANS can be used in concert to directly analyze conformational changes within RNAs when in complex, enhancing our understanding of RNA structure in functional assemblies.
Synthesis, structure, electronic characterization, and halogenation of gold(III) phlorin complexes
The metalation chemistry of the phlorin, which is a non-aromatic tetrapyrrole macrocycle containing a single sp 3 -hybridized meso-carbon has remained underdeveloped, as compared to that of more traditional tetrapyrroles such as porphyrins, corroles and phthalocyanines. There have been few prior efforts to prepare metallophlorins, and those that have been reported have relied on either reduction or nucleophilic attack of parent metalloporphyrins, rather than direct metalation of freebase phlorin constructs. In this work, an alternate synthetic approach for preparation of gold(III) phlorin complexes that involves the first direct metalation of two different freebase phlorin derivatives (3H(Phl tBu ) and 3H(Phl F )) with AuBr 3 to produce the stable and fully isolable gold(III) phlorin complexes Au(Phl tBu ) and Au(Phl F ) is reported. The first structural characterization of a metallophlorin bearing geminal dimethyl substituents at the sp 3 -hybridized meso-carbon via X-ray crystallography is also reported. In addition to the preparation of Au(Phl tBu ) and Au(Phl F ), the UV-vis absorption and redox properties of these two gold(III) phlorins in comparison to those of their freebase homologues is also detailed. Notably, the metallophlorins are characterized by panchromatic absorbance profiles and intense and broad bands that span the long-visible and into the near-IR regions, as well as two fully reversible oxidation and reduction waves as probed by cyclic voltammetry. Lastly, the chlorination of Au(Phl tBu ) using PhI(Cl 2 ) was probed and it was found that this regioslective reaction generates monochlorinated (Au(Phl tBu Cl)) and dichlorinated (Au(Phl tBu Cl 2 )) products, which were both structurally characterized by X-ray crystallography.
A chiral alkali metal capped Ni 4 cubane complex: Synthesis, structure, magnetic and catalytic bromination studies
A new chiral NaO 2 Ni 4 O 2 N 2 cluster has been developed with a distorted capped cubane-type structure. The structure was determined by single crystal X-ray diffraction. The tetradentate Schiff-base ligand was synthesized by the condensation of o-vanillin and $\textit{D}$-(-)–threo-2-amino-1-(4-nitrophenyl)-1,3-propanediol. X-ray structure reveals that the complex possesses a Ni 4 cubane cluster where sodium ion is anchored on the face of the cubane structure. Continuous shape measurement studies revealed that all the Ni centres are in distorted octahedral geometry and sodium ion adopts the spherical square pyramidal geometry. Further structural exploration reveals that the complex shows local distortions of the coordination geometries at each metal site, and these distortions govern the magnetic anisotropy associated with each Ni II ion. For the present case, an elongation ($d_{str}$ > 0) of the octahedral coordination sphere results in a local easy-plane anisotropy, with a positive $D_{Ni(II)}$ parameter. Temperature dependant magnetization measurements showed a predominant ferromagnetic interaction amongst the four Ni centres. This complex is also catalytically active towards bromination of aromatic phenolic compounds. Initial catalytic activity was verified with the conversion of phenol red to bromophenol blue. Different phenolic substances show good conversion to their corresponding bromo derivatives. The complex showed good catalytic activity towards bromination of aromatic phenolic compounds, offering up to 99% conversion with 100% selectively to their corresponding bromo derivatives.
Symmetry in Seeded Metal Nanocrystal Growth
Symmetry underpins the structure and function of the world around us and is also captured in modern nanomaterials, where changing the symmetry of a nanocrystal or the interparticle spacing and orientation of nanocrystal building blocks in a superlattice can give new function. However, the synthesis and assembly of nanocrystals have been limited largely to simple compositions and structures. It remains a grand challenge to achieve nanocrystals with compositional and structural complexity while maintaining the monodispersity required for their use. This Account will illustrate through recent examples that seeded methods enable the synthesis of compositionally and structurally complex multimetallic crystals with defined and predictable symmetries for applications in plasmonics and catalysis. This outcome arises because the barrier for heterogeneous nucleation (i.e., seeded) is lower than that of homogeneous nucleation, where seeds can serve as preferential sites for the growth of complex structures and crystal phases. Our analysis begins by considering metal overgrowth from single-crystalline seeds of different shapes and symmetries, where the kinetics of adatom addition to seeds relative to their diffusion across seeds accounts for the expressed nanocrystal shapes. These results are then compared to overgrowth from seeds with different internal structures (i.e., planar defects), where the relationships between nanocrystal size and volumetric strain energy and surface energy are discussed. A major finding from this analysis is that often the underlying symmetry of seeds can be predictably transferred to the final crystals during overgrowth processes. Consequences of this finding are the predictable syntheses of crystals with different hierarchies akin to snowcrystals as well as nanocrystals with complex compositions (e.g., quaternary nanoparticles). Yet, there are subtle aspects to seeded growth that pave a path toward examples where nanocrystal symmetry has been reduced compared to the original seeds in a controlled manner. As we found, both the concentrations of metal precursors and capping agents can impact whether symmetry is transferred or reduced during overgrowth. Examples from our laboratory will be placed in context to other reported strategies for symmetry breaking. As will be argued, understanding what conditions favor symmetry preservation versus symmetry reduction during seeded crystal growth is central to accessing next-generation crystal forms. The Account concludes by outlining synthetic challenges associated with forming nanoscale heterostructures with precise 3-D placement of different materials within a given nanocrystal as well as facet control within different material domain and interface engineering. Furthermore, we envision meeting these challenges through regioselective and chemoselective seeded syntheses for which a foundation is outlined herein.