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Nitrogenases, the enzymes that convert N2 to NH3, also catalyze the reductive coupling of CO to yield hydrocarbons. CO-coordinated species of nitrogenase clusters have been isolated and used to infer mechanistic information. However, synthetic FeS clusters displaying CO ligands remain rare, which limits benchmarking. Starting from a synthetic cluster that models a cubane portion of the FeMo cofactor (FeMoco), including a bridging carbyne ligand, we report a heterometallic tungsten-iron-sulfur cluster with a single terminal CO coordination in two oxidation states with a high level of CO activation (νCO = 1851 and 1751 cm-1). The local Fe coordination environment (2S, 1C, 1CO) is identical to that in the protein making this system a suitable benchmark. Computational studies find an unusual intermediate spin electronic configuration at the Fe sites promoted by the presence the carbyne ligand. This electronic feature is partly responsible for the high degree of CO activation in the reduced cluster.
RESUMEN
The catalytic relevance of Fe(IV) species in non-heme iron catalysis has motivated synthetic advances in well-defined five- and six-coordinate Fe(IV) complexes for a better understanding of their fundamental electronic structures and reactivities. Herein, we report the syntheses of FeDipp2 and FeMes2, a pair of unusual four-coordinate non-heme formally Fe(IV) complexes with S=1 ground states supported by strongly donating bisamide ligands. By combining spectroscopic characterization and computational modeling, we found that small variations in ligand aryl substituents resulted in substantial changes in both structures and bonding. This work highlights the strong donor capabilities and modularity of the bisamide ligand set. More broadly, it is a critical contribution to the utilization of ligand design to modulate molecular geometries and electronic structures of low-coordinate, high-valent iron complexes.
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We report on the geometric and electronic structures of a series of V2+/3+ tren-bridged iminopyridine complexes [tren = tris(2-aminoethyl)amine] that enable the observation of an unexpected doublet ground state for a nominally 3d3 species. Tren undergoes condensation reactions with picolinaldehyde or methyl-6-formylnictonate to form the respective tripodal ligand sets of (py)3tren and (5-CO2Mepy)3tren. The (py)3tren ligand is coordinated to V2+ and V3+ metal centers to form complex salts [1-H](OTf)2 and [1-H](OTf)3, respectively (OTf- = CF3SO3-). For [1-H]2+, strong metal-ligand π-covalency with respect to the V2+ (3d3) and iminopyridine ligands weakens its interelectronic repulsion. For [1-H]3+, the bridgehead nitrogen of the tren scaffold forms a seventh coordinate covalent bond with a V3+ (3d2) metal center. The coordination of (5-CO2Mepy)3tren to a V2+ metal center results in the redox noninnocent and heptacoordinate compound [1-CO2Me](OTf)2 with a doublet (S = 1/2) ground state that we support with magnetic susceptibility and spectroscopy measurements. The complexes are uniformly characterized experimentally with single-crystal X-ray diffraction, electronic absorbance, and electrochemistry, and electronic structures are corroborated by computational techniques. We present a new computational procedure that we term the spin-optimized approximate pair (SOAP) method that enables the visualization and quantification of electron-electron interactions.
RESUMEN
A recently reported description of the photophysical properties of V2+ polypyridyl systems has highlighted several distinctions between isoelectronic, d3, Cr3+, and V2+ tris-homoleptic polypyridyl complexes of 2,2'-bipyridine (bpy) and 1,10-phenanthroline (phen). Here, we combine theory and experimental data to elucidate the differences in electronic structures. We provide the first crystallographic structures of the V2+ complexes [V(bpy)3](BPh4)2 (V-1B) and [V(phen)3](OTf)2 (V2) and observe pronounced trigonal distortion relative to analogous Cr3+ complexes. We use electronic absorption spectroscopy in tandem with TD-DFT computations to assign metal-ligand charge transfer (MLCT) properties of V-1B and V2 that are unique from the intraligand transitions, 4(3IL), solely observed in Cr3+ analogues. Our newly developed natural transition spin density (NTρα,ß) plots characterize both the Cr3+ and V2+ absorbance properties. A multideterminant approach to DFT assigns the energy of the 2E state of V-1B as stabilized through electron delocalization. We find that the profound differences in excited state lifetimes for Cr3+ and V2+ polypyridyls arise from differences in the characters of their lowest doublet states and pathways for intersystem crossing, both of which stem from trigonal structural distortion and metal-ligand π-covalency.
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Noncovalent interactions are traditionally defined within the context of their attractive components, such as electrostatics and dispersion. Sources of molecular strain are derived through the destabilization of Coulombic and exchange repulsion. Due to this binary designation, the underlying origin of geminal stability with respect to alkanes (referred to as protobranching) has been an active subject for debate between these competing perspectives. We recast this stabilization as a complementary (Gestalt) interaction between dispersion and exchange repulsion, each impacting the other. We use triplet hydrogen and argon dimer as foundational van der Waals adducts to develop a procedure for the visualization and quantification of both exchange repulsion, ΔρSCF, and medium-range correlation, ΔΔρ, as perturbations in electron density. We use the framework of the DFT-D3 correction to reproduce the shape of the dispersion potential at medium range and successfully model the trend in stability for the eighteen isomers of octane with a diverse series of functionals: BLYP, B3LYP, BP86, PBE, and PBE0. Collectively, our findings show that protobranching is a manifestation of steric repulsion-reduction in vibrational enthalpy and medium-range electron correlation.
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We present evidence of a spin-state change that accompanies desilylation reactions performed on two related Fe(II) iminopyridine coordination complexes. To probe these systems, we performed titrations with CsF in solution and analyzed the speciation with in situ magnetometry, electrochemistry, and mass spectrometry techniques. We find that pendant tert-butyldimethylsilyl groups are readily cleaved under these conditions, and the resulting desilylated complexes exhibit overall decreased solution magnetic susceptibility values. Density functional theory and ab initio computations probe the impact of substituent identity (prior to- and post-desilylation) on the metal-ligand σ-donor and π-acceptor bonding properties. We attribute the observed spin-state changes to the decrease in entropy associated with the conformational freedom of the silylated high-spin complex, resulting in a more favored low-spin state upon desilylation.
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The immense scale and complexity of neuronal electron microscopy (EM) datasets pose significant challenges in data processing, validation, and interpretation, necessitating the development of efficient, automated, and scalable error-detection methodologies. This paper proposes a novel approach that employs mesh processing techniques to identify potential error locations near neuronal tips. Error detection at tips is a particularly important challenge since these errors usually indicate that many synapses are falsely split from their parent neuron, injuring the integrity of the connectomic reconstruction. Additionally, we draw implications and results from an implementation of this error detection in a semi-automated proofreading pipeline. Manual proofreading is a laborious, costly, and currently necessary method for identifying the errors in the machine learning based segmentation of neural tissue. This approach streamlines the process of proofreading by systematically highlighting areas likely to contain inaccuracies and guiding proofreaders towards potential continuations, accelerating the rate at which errors are corrected.
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Insect neural systems are a promising source of inspiration for new navigation algorithms, especially on low size, weight, and power platforms. There have been unprecedented recent neuroscience breakthroughs with Drosophila in behavioral and neural imaging experiments as well as the mapping of detailed connectivity of neural structures. General mechanisms for learning orientation in the central complex (CX) of Drosophila have been investigated previously; however, it is unclear how these underlying mechanisms extend to cases where there is translation through an environment (beyond only rotation), which is critical for navigation in robotic systems. Here, we develop a CX neural connectivity-constrained model that performs sensor fusion, as well as unsupervised learning of visual features for path integration; we demonstrate the viability of this circuit for use in robotic systems in simulated and physical environments. Furthermore, we propose a theoretical understanding of how distributed online unsupervised network weight modification can be leveraged for learning in a trajectory through an environment by minimizing orientation estimation error. Overall, our results may enable a new class of CX-derived low power robotic navigation algorithms and lead to testable predictions to inform future neuroscience experiments.