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Here, the electronic structure and local coordination of binary (Mo 6 T 8 ) and ternary Chevrel Phases (M x Mo 6 T 8 ) are investigated for a range of metal intercalant and chalcogen compositions. We evaluate differences in the Mo L 3 -edge and K-edge X-ray absorption near edge structure across the suite of chalcogenides M x Mo 6 T 8 (M = Cu, Ni, x = 1–2, T = S, Se, Te), quantifying the effect of compositional and structural modification on electronic structure. Furthermore, we highlight the expansion, contraction, and anisotropy of Mo 6 clusters within these Chevrel Phase frameworks through extended X-ray absorption fine structure analysis. Our results show that metal-to-cluster charge transfer upon intercalation is dominated by the chalcogen acceptors, evidenced by significant changes in their respective X-ray absorption spectra in comparison to relatively unaffected Mo cations. These results explain the effects of metal intercalation on the electronic and local structure of Chevrel Phases across various chalcogen compositions, and aid in rationalizing electron distribution within the structure.
Environmental biotic and abiotic factors and soil physical, mineralogical, and chemical properties control the chemical composition of soil organic matter (SOM). Particularly, soil mineralogy and the presence of multivalent cations affect SOM labile fraction composition, stability, and environmental persistence. The persistence of SOM in aridic or limestone deposit derived soils, i.e., calcareous soils, has been partially attributed to SOM stabilization through adsorption or inclusion into the calcite mineral structure. Recently, however, it was shown that Ca(aq) released during calcite dissolution formed aqueous Ca–organic associations with OM components, which were unbound to mineral surface sites. This study investigates the structure, composition, and coordination of these associations by characterizing lyophilized Ca–organic containing solutions with spectromicroscopy [Scanning Transmission X-ray Microscopy (STXM)] and with a nanoimaging chemical probe [Infrared scattering-Scanning Nearfield Optical Microscopy (IR s-SNOM)]. Chemical stability of Ca–organic associations is furthermore determined with pyrolysis mass spectrometry analysis. The results demonstrate that Ca–organic associations are formed in the presence of dissolving calcite and OM components relevant to soil chemistry, i.e., lignin and amino acids. This study further reveals a spatial homogeneity of solution-derived (bi) carbonate in Ca–organic associations indicating for the first time that an inorganic anion, such as (bi)carbonate, may be part of these associations. Most likely, Ca ions are bound to both the (bi)carbonate and the organic components. These Ca (bi)carbonate–organic associations seem to have greater chemical stability than the pristine organic mixtures and, possibly, a higher environmental stability and reduced mineralization rate.
Explicit structure-preserving geometric particle-in-cell (PIC) algorithm in curvilinear orthogonal coordinate systems is developed. The work reported represents a further development of the structure-preserving geometric PIC algorithm achieving the goal of practical applications in magnetic fusion research. The algorithm is constructed by discretizing the field theory for the system of charged particles and electromagnetic field using Whitney forms, discrete exterior calculus, and explicit non-canonical symplectic integration. In addition to the truncated infinitely dimensional symplectic structure, the algorithm preserves exactly many important physical symmetries and conservation laws, such as local energy conservation, gauge symmetry and the corresponding local charge conservation. As a result, the algorithm possesses the long-term accuracy and fidelity required for first-principles-based simulations of the multiscale tokamak physics. The algorithm has been implemented in the SymPIC code, which is designed for high-efficiency massively-parallel PIC simulations in modern clusters. The code has been applied to carry out whole-device 6D kinetic simulation studies of tokamak physics. A self-consistent kinetic steady state for fusion plasma in the tokamak geometry is numerically found with a predominately diagonal and anisotropic pressure tensor. The state also admits a steady-state sub-sonic ion flow in the range of 10 km s -1 , agreeing with experimental observations and analytical calculations Kinetic ballooning instability in the self-consistent kinetic steady state is simulated. It is shown that high-n ballooning modes have larger growth rates than low-n global modes, and in the nonlinear phase the modes saturate approximately in 5 ion transit times at the 2% level by the E × B flow generated by the instability. These results are consistent with early and recent electromagnetic gyrokinetic simulations.
Organic linkers play a crucial role in constructing lanthanide (Ln) coordination polymers (CPs), influencing structural topologies and physicochemical properties. Herein, we introduce 6-oxo-1,6-dihydro-2,5-pyridinedicarboxylic acid (2,5-H 3 PODC) as a new ligand for constructing lanthanide coordination polymers that integrates the structural features of terephthalic acid with the chelation capabilities of pyridinone-based functional groups. Six lanthanide-based coordination polymers were synthesized with 2,5-H 3 PODC, forming two types of CPs – type 1: [Ln(HPODC)(Ox) 0.5 (H 2 O) 2 ] (where (Ox) = oxalic acid and Ln = Pr 3+ (1), Nd 3+ (2)) and type 2: [Ln(H 2 PODC)(HPODC)(H 2 O)] (Ln = Eu 3+ (3), Gd 3+ (4), Dy 3+ (5), Er 3+ (6)). All compounds were structurally characterized by single-crystal and powder X-ray diffraction, and both compound types are 2D ladder-like networks with cem topologies where the trivalent metal centers are bridged via HPODC 2− and Ox 2− ligands in type 1 structures and H 2 PODC − and HPODC 2− linkers in type 2 structures. Thermogravimetric analysis (TGA) demonstrated that the metal–organic networks of type 1 and type 2 compounds exhibit distinct decomposition patterns, and the photoluminescent properties of 3 were also examined, revealing efficient ligand based sensitization and characteristic emission bands for Eu(III).
Alkali fluorides are often thought of as archetypical ionic compounds whose structures can be understood in terms of the packing of rigid spheres. At ambient pressure, they assume the rocksalt (B1) structure, while under only a few GPa of pressure, the cesium chloride (B2) structure, with higher coordination numbers, is assumed for KF, RbF, and CsF. NaF requires almost 10 times more pressure to undergo this same phase transition, which has not been observed for LiF. Herein, we provide a detailed analysis, based upon quantum chemical calculations, explaining this behavior. We show that for the heavier alkali metals, the semicore p orbitals engage in metal-metal bonding in the B2 phase, facilitating the pressure-induced B1 → B2 structural transition. Furthermore, these findings suggest that the semicore orbitals of heavy alkali metals can be activated without the need of strong oxidants at very mild levels of compression, resulting in the formation of chemical bonds, challenging both traditional and modern core-valence distinctions. In addition, we argue that Cs 5p-5p bonding in CsCl occurs already at ambient pressure, stabilizing the B2 phase, and suggest experiments that may be able to detect signatures of such bonding.
The nonlinearities present in structural systems are often found in isolated regions within the structure, such as those containing joints or interfaces. However, despite the localized nature of these nonlinearities their presence serves to couple together the modes of the underlying linear system and significantly complicate the development of appropriate reduced-order models; the localized nonlinearities have a global effect on the dynamics of the system. Further, in the presence of evolving structural health the nonlinearities can arise from accumulating damage, with dynamics distinct from those observed in the healthy state. The present work develops a data-driven formulation to identify and include the contributions of the isolated nonlinearities on the dynamics of the underlying linear structure. A novel coordinate separation is developed that decomposes those nonlinearities restricted to the isolated subdomain from the known linear system defined over the entire domain, and the influence of the isolated nonlinearities is reintroduced as an appropriately identified traction at the boundary of the isolated subdomain, referred to as the deviatoric force. In the region exterior to the nonlinear subdomain the response of the ideal linear system recovers that of the original nonlinear system. In this work, the deviatoric force component is predicted using a structure-preserving multilayer perceptron, based only on measured responses at the boundary of the isolated subdomain. Therefore introduction of the perceptron is able to bypass the direct numerical simulation of the nonlinearities within the isolated subdomain. This approach is illustrated through a simple structural system in which an interior region contains cubic nonlinearities and hysteretic damping. Once trained, the machine learning system is able to accurately predict the deviatoric force so that the ideal system recovers the response of the original system in the region outside the isolated nonlinear subdomain. Moreover, the data-driven approach is able to accurately predict the response when the system is subject to differing initial conditions and external excitation without the need for retraining, so that the proposed approach provides a robust description of the structural dynamics of the overall system.
Summary Evolutionary history plays a key role driving patterns of trait variation across plant species. For scaling and modeling purposes, grass species are typically organized into C 3 vs C 4 plant functional types (PFTs). Plant functional type groupings may obscure important functional differences among species. Rather, grouping grasses by evolutionary lineage may better represent grass functional diversity. We measured 11 structural and physiological traits in situ from 75 grass species within the North American tallgrass prairie. We tested whether traits differed significantly among photosynthetic pathways or lineages (tribe) in annual and perennial grass species. Critically, we found evidence that grass traits varied among lineages, including independent origins of C 4 photosynthesis. Using a rigorous model selection approach, tribe was included in the top models for five of nine traits for perennial species. Tribes were separable in a multivariate and phylogenetically controlled analysis of traits, owing to coordination of important structural and ecophysiological characteristics. Our findings suggest grouping grass species by photosynthetic pathway overlooks variation in several functional traits, particularly for C 4 species. These results indicate that further assessment of lineage‐based differences at other sites and across other grass species distributions may improve representation of C 4 species in trait comparison analyses and modeling investigations.
Pair distribution function measurement of SiO 2 glass up to 120 GPa reveals changes in the first-, second-, and third-neighbor distances associated with an increase in Si coordination number C Si to >6 above 95 GPa. Here, packing fractions of Si and O determined from the first- and second-neighbor distances show marked changes accompanied with the structural evolution from C Si = 6 to >6. Structural constraints in terms of ionic radius ratio of Si and O, and ratio of nonbonded radius to bonded Si-O distance support the structural evolution of SiO 2 glass with C Si > 6 at high pressures.
Effectively separating critical materials, including intra-lanthanide separations, is crucial for meeting growing application demands. Liquid–liquid extraction (LLE) is the industry standard for lanthanide separations, where the selectivity can depend on small changes in metal coordination. In this work, we investigate representative lanthanide Eu coordination with a neutral malonamide extractant in an imidazolium bistriflimide ionic liquid (IL) solvent. Through systematic titrations of the water and extractant and under extraction conditions, we observe surprising cooperative Eu solvation with the IL anion and extractant. Time-resolved fluorescence spectroscopy measurements show strong extractant coordination in water-saturated IL. Lifetime measurements show no water coordination, and extended X-ray fine structure spectroscopy data provide a coordination number of 10. Molecular dynamics simulations confirm this coordination number and reveal IL anion coordination in the final Eu complex, even though it is ordinarily a significantly weaker ligand compared to water. The lack of water in the final extracted complex and IL anion coordination potentially explain the increased extraction in LLE systems using ILs, as evidenced by higher distribution ratios for cation exchange extraction, despite the energetic cost of cation transfer to the aqueous phase. These results highlight the opportunities for tuning metal coordination to drive extraction in unique solvent systems.
In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.
Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.
Preorganized ligands such as bis-lactam-1,10-phenanthroline (BLPhen) offer unique selectivity trends in solvent extraction of rare-earth ions, particularly from aqueous nitrate solutions. However, due to the ligand’s lipophilicity it is experimentally challenging to obtain crystal structures of the corresponding lanthanide (Ln):ligand complexes to describe the local structure of the first coordination shell and the role of the nitrate ions in the organic phase. In this work, we report first principles molecular dynamics (FPMD) simulations of the complexation of trivalent lanthanide ions (La, Nd, and Eu) with the BLPhen ligand in the presence of nitrate ions in the dichloroethane (DCE) solvent. We find that two nitrate anions are present in the first solvation shell and the third nitrate anion is far from the first solvation shell in all three [Ln(BLPhen) 2 ] 3+ complexes examined. Moving along the lanthanide series from La to Nd to Eu, the binding pocket formed by the two BLPhen ligands shrinks in size; as a result, the two nitrate configuration changes from one-monodentate/one-bidentate binding mode for La and Nd to all monodentate for Eu. Meanwhile, the total coordination number drops from 11 for La and Nd to 10 for Eu. More interestingly, the bidentate binding in [La(BLPhen) 2 ] 3+ and [Nd(BLPhen) 2 ] 3+ complexes is highly dynamic, frequently switching to monodentate and back. The FPMD insights into the differing modes and dynamics of nitrates in the first coordination shell will be useful for further atomistic understanding of the complex structure, formation, and stability in the organic phase.
We report low valent nickelates R n+1 Ni n O 2n+2 (R = rare earth) containing Ni 1+ (d 9 ) with a quasi-two-dimensional (quasi-2D) square-planar coordination geometry possess structural and electronic properties that are similar to those of high T c cuprates, including superconductivity itself in the doped infinite-layer (n = ∞) RNiO 2 system. Within this R n+1 Ni n O 2n+2 nickelate family, the crystallographic isomorphs Pr 4 Ni 3 O 8 and La 4 Ni 3 O 8 exhibit singularly different ground states: Pr 4 Ni 3 O 8 is metallic, and La 4 Ni 3 O 8 is a charge- and spin-stripe-ordered insulator. To explore and understand the ground state evolution from metallic Pr 4 Ni 3 O 8 to stripe-ordered La 4 Ni 3 O 8 in the R 4 Ni 3 O 8 family, we have grown a series of isovalent, substituted single crystals (Pr 1-x La x ) 4 Ni 3 O 8 . Combining thermodynamic, transport, magnetic, and synchrotron X-ray single crystal diffraction measurements, we reveal a T = 0 transition between metallic and stripe-insulator phase regions, with this putative quantum phase transition at x ≈ 0.45. We propose two possible models for (Pr 1-x La x ) 4 Ni 3 O 8 : an electronically inhomogeneous system that could serve as a candidate for exploring quantum Griffiths phase physics or a homogeneous system with a clean quantum critical point at the phase boundary
Given their natural abundance and thermodynamic stability, fluoride salts may appear as evolving components of electrochemical interfaces in Li-ion batteries and emergent multivalent ion cells. This is due to the practice of employing electrolytes with fluorine-containing species (salt, solvent, or additives) that electrochemically decompose and deposit on the electrodes. Operando X-ray absorption spectroscopy (XAS) can probe the electrode–electrolyte interface with a single-digit nanometer depth resolution and offers a wealth of insights into the evolution and Coulombic efficiency or degradation of prototype cells, provided that the spectra can be reliably interpreted in terms of local oxidation state, atomic coordination, and electronic structure about the excited atoms. Here we explore fluorine K-edge XAS of mono- (Li, Na, and K) and di-valent (Mg, Ca, and Zn) fluoride salts from a theoretical standpoint and discover a surprising level of detailed electronic structure information about these materials despite the relatively predictable oxidation state and ionicity of the fluoride anion and the metal cation. Utilizing a recently developed many-body approach based on the ΔSCF method, we calculate the XAS using density functional theory and experimental spectral profiles are well reproduced despite some experimental discrepancies in energy alignment within the literature, which we can correct for in our simulations. We outline a general methodology to explain shifts in the main XAS peak energies in terms of a simple exciton model and explain line-shape differences resulting from the mixing of core-excited states with metal d character (for K and Ca specifically). Given ultimate applications to evolving interfaces, some understanding of the role of surfaces and their terminations in defining new spectral features is provided to indicate the sensitivity of such measurements to changes in interfacial chemistry.
Although metal-organic frameworks (MOFs) have been reported as important porous materials for the potential utility in metal ion separation, coordinating the functionality, structure, and component of MOFs remains a great challenge. Herein, a series of anionic rare earth MOFs (RE-MOFs) were synthesized via a solvothermal template reaction and for the first time explored for uranium(VI) capture from an acidic medium. The unusually high extraction capacity of UO2 2 + (e.g., 538 mg U per g of Y-MOF) was achieved through ion-exchange with the concomitant release of Me 2 NH 2 + , during which the uranium(VI) extraction in the series of isostructural RE-MOFs was found to be highly sensitive to the ionic radii of the metal nodes. That is, the uranium(VI) adsorption capacities continuously increased as the ionic radii decreased. Finally, in-depth mechanism insight was obtained from molecular dynamics simulations, suggesting that both the accessible pore volume of the MOFs and hydrogen-bonding interactions contribute to the strong periodic tendency of uranium(VI) extraction.
Open-circuit voltage deficits are limiting factors in kesterite solar cells. Addressing this issue by suppressing band tailing and nonradiative charge recombination is essential for enhancing the performance. We employ ab initio nonadiabatic molecular dynamics to elucidate the origin of band tailing and charge losses and propose a mitigation strategy. The simulations show that Cu–Zn disorder, associated with antisite defect clusters [Cu Zn +Zn Cu ], is a significant source of band tailing in kesterites, as evidenced by the much larger Urbach energy in disordered than ordered kesterites. Cu–Zn disorder gives rise to new sulfur-centered coordination polyhedra, increases structural inhomogeneity, changes electrostatic potential at sulfur centers, and shifts the S(3p) orbital energy. Differences in the S(3p)/Cu(3d) and S(3p)/Sn(5s) hybridization strengths and the S(3p) orbital energy shift reduce the band gap by 0.37 eV. Furthermore, Cu–Zn disorder enhances vibrational motion of sulfur anions and surrounding cations, increasing band gap fluctuations by 15 meV. The stronger electron–phonon interactions reduce charge carrier lifetimes and limit the kesterite solar cell efficiency. Partial substitution of Zn with Cd facilitates structural ordering and significantly suppresses band tailing, particularly in disordered systems. The improvement can be attributed to the larger atomic radius and mass of Cd, which weakens bonding around the anion, suppresses S-related vibrations within the covalent tetrahedra, and reduces nonadiabatic coupling, thereby increasing charge carrier lifetimes. The reported results establish the key influence of cation disorder on band tailing and reduced charge carrier lifetimes in kesterites and highlight cation disorder engineering as a strategy to achieve high-efficiency kesterite solar cells.
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