RESUMO
This work reports the observation and characterization of heterobinuclear transition-metal main-group metal oxide carbonyl complex anions, RuGeO(CO)n- (n = 3-5), by combining mass-selected photoelectron velocity map imaging spectroscopy and quantum chemistry calculations. The experimentally determined vertical electron detachment energy of RuGeO(CO)3- surpasses those of RuGeO(CO)4- and RuGeO(CO)5-, which is attributed to distinctive bonding features. RuGeO(CO)3- manifests one covalent σ and two Ru-to-Ge dative π bonds, contrasting with the sole covalent σ bond present in RuGeO(CO)4- and RuGeO(CO)5-. Unpaired spin density distribution analysis reveals a 17-electron configuration at the Ru center in RuGeO(CO)3- and an 18-electron configuration in RuGeO(CO)4- and RuGeO(CO)5-. This work closes a gap in the quantitative physicochemical characterization of heteronuclear oxide carbonyl complexes, enhancing our insights into catalytic processes of CO/GeO on the metal surface at the molecular level.
RESUMO
The heteronuclear group 14 M-iron tetracarbonyl clusters MFe(CO)4- (M = Si, Ge, Sn) anions have been generated in the gas phase by laser ablation of M-Fe alloys and detected by mass and photoelectron spectroscopy. With the support of quantum chemical calculations, the geometric and electronic structures of MFe(CO)4- (M = Si, Ge, Sn) are elucidated, which shows that all the MFe(CO)4- clusters have the M-Fe bonded, iron-centered, and carbonyl-terminal M-Fe(CO)4 structure with the C2v symmetry and a 2B2 ground state. The M-Fe bond can be considered a double bond, which includes one σ electron sharing bond and one π dative bond. The C-O bonds in those anionic clusters are calculated to be elongated to different extents, and in particular, the C-O bonds in SiFe(CO)4- are elongated more. The Si-Fe alloy thus turns out to be a better collocation to activate the C-O bonds in the gas phase among group 14. The present findings have important implications for the rational development of high-performance catalysts with isolated metal atoms/clusters dispersed on supports.
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Spectroscopic characterization of ketenylidene complexes is of essential importance for understanding the structure-reactivity relationships of the catalytic sites. Here, we report a size-specific photoelectron velocity map imaging spectroscopic study of the reactions of carbon monoxide with nickel carbide. Quantum chemical calculations have been conducted to search for the energetically favorable isomers and to recognize the experimental spectra. The target products with the chemical formula of NiC(CO)n- (n = 3-5) are characterized to have an intriguing ketenylidene CCO unit. The evolution from NiC(CO)3- to NiC(CO)4- involves the breaking and formation of the Ni-C bond and the coordination conversion between the terminal and bridging carbonyls. Experimental and theoretical analyses reveal an efficient C-C bond formation process within the reactions of carbon monoxide and laser-vaporized nickel carbide. This work highlights the pivotal roles played by metal carbides in the C-C bond formation and also proposes new ideas for the design and chemical control of a broad class of complexes with unique physical and chemical properties.
RESUMO
Nitrogen fixation is confronted with great challenges in the field of chemistry. Herein, we report that single metal carbides PtCn- and PtCnN2- (n = 4-6) are indispensable intermediates in the process of nitrogen fixation by mass spectrometry coupled with anionic photoelectron spectroscopy, quantum chemical calculations, and simulated density-of-state spectra. The most stable isomers of these cluster anions are characterized to have linear chain structures. The fixation and activation of dinitrogen are facilitated by the charge transfer from Pt and Cn to N2. The significance of π back-donation of the 5d orbital of the Pt atom to the antibonding π orbits of N2 for dinitrogen fixation and activation is discussed in detail. This study not only provides a theoretical basis at the molecular level for the activation of dinitrogen by mononuclear metal carbide clusters but also provides a new paradigm for dinitrogen fixation.
RESUMO
With the increasing of data in wastewater treatment, data-driven machine learning models are useful for modeling biological processes and complex reactions. However, few data-driven models have been developed for simulating the microbial electrolysis cells (MECs) and traditional models are too ambiguous to comprehend the mechanisms. In this study, a new general data-driven two-stage model was firstly developed to predict CH4 production from in-situ biogas upgrading in the biocathode MECs via direct electron transfer (DET), named NARX-BP hybrid neural networks. Compared with traditional one-stage model, the model could well predict methane production via DET with excellent performance (all R2 and MES of 0.918 and 6.52 × 10-2, respectively) and reveal the mechanisms of biogas upgrading, for the new systematical modeling approach could improve the versatility and applicability by inputting significant intermediate variables. In addition, the model is generally available to support long-term prediction and optimal operation for anaerobic digestion or complex MEC systems.