the intermittent renewable energy (such as solar and wind) into the present electricity grid. [1] With liquid redox electrolyte flowing in and out, mutual conversions between chemical energy of electrolyte and electricity can be realized. [2] Because the redox electrolyte is stored externally rather than in the electrode compartment, the capacity can be tailored independently from the power output which scales with the stack configuration and the number of cells. [3] Thus, to acquire RFBs with high capacity, designing of redox-active species with large solubility and reversible electron numbers is potential orientation.However, most RFBs utilize highly acidic or basic electrolyte to enhance the solubility and stability of the redox-active species. For example, vanadium species are only highly stable in high concentrated acid supporting electrolyte, [4] while many organic redox-active species, such as quinones, [5] azobenzene, [6] and phenazine [7] were found with good performance in strong alkaline electrolyte. However, strong acidic and alkaline conditions can result in high operating and maintenance cost of RFBs, and further diminish the serving life of whole systems. Those issues appeal to develop advanced characterization techniques to understand the structure evolution and stability of those redox couples. In this regard, in-situ and in-operando spectroscopy technologies, such as EPR, [8] nuclear magnetic resonance (NMR), [9] and Fourier transform infrared (FT-IR) [10] etc., are effective tools to characterize the stability of the redox-active materials during charge and discharge process. For example, in-situ EPR and coupled EPR/NMR methods can monitor the decomposition of 2,6-dihydroxfyanthraquinone electrolytes in RFB and elucidate the electron delocalization in the redox process of anthraquinone. [8] This in turn raises the high requirement to develop new redox-active species with high performances to be operated at mild pH conditions. [11] Recently, aqueous organic redox species, such as 4-HO-TEMPO, methyl viologen, [12] and 9,10-anthraquinone-2,7-disulfonic diammonium salt (AQDS-(NH 4 ) 2 ) [13] were found to have many merits at neutral pH, such as fast redox kinetics and large solubility. [14] However, smallsized organic compounds always accompany traces decomposition and non-negligible cross contamination during each redox process, leading to limited cycle performance and low A highly soluble Li 5 BW 12 O 40 cluster delivers 2 e − redox reaction with fast electron transfer rates (2.5 × 10 −2 cm s −1 ) and high diffusion coefficients (≈2.08 × 10 −6 cm 2 s −1 ) at mild pH ranging from 3 to 8. In-operando aqueousflowing Raman spectroscopy and density functional theory calculations reveal that Raman shift changing of {BW12} clusters is due to the bond length changing between W-O b -W and W-O c -W at different redox states. The structure changing and redox chemistry of Li 5 BW 12 O 40 are highly reversible, which makes the Li 5 BW 12 O 40 cluster versatile to construct all-anion aqueous redox flow batt...
Surface-enhanced Raman spectroscopy (SERS), providing near-single-molecule-level fingerprint information, is a powerful tool for the trace analysis of a target in a complicated matrix and is especially facilitated by the development of modern machine learning algorithms. However, both the high demand of mass data and the low interpretability of the mysterious black-box operation significantly limit the well-trained model to real systems in practical applications. Aiming at these two issues, we constructed a novel machine learning algorithm-based framework (Vis-CAD), integrating visual random forest, characteristic amplifier, and data augmentation. The introduction of data augmentation significantly reduced the requirement of mass data, and the visualization of the random forest clearly presented the captured features, by which one was able to determine the reliability of the algorithm. Taking the trace analysis of individual polycyclic aromatic hydrocarbons in a mixture as an example, a trustworthy accuracy no less than 99% was realized under the optimized condition. The visualization of the algorithm framework distinctly demonstrated that the captured feature was well correlated to the characteristic Raman peaks of each individual. Furthermore, the sensitivity toward the trace individual could be improved by least 1 order of magnitude as compared to that with the naked eye. The proposed algorithm distinguished by the lesser demand of mass data and the visualization of the operation process offers a new way for the indestructible application of machine learning algorithms, which would bring push-to-the-limit sensitivity toward the qualitative and quantitative analysis of trace targets, not only in the field of SERS, but also in the much wider spectroscopy world. It is implemented in the Python programming language and is open-source at https://github.com/3331822w/Vis-CAD.
Interfacial host–guest complexation offers a versatile way to functionalize nanomaterials. However, the complicated interfacial environment and trace amounts of components present at the interface make the study of interfacial complexation very difficult. Herein, taking the advantages of near-single-molecule level sensitivity and molecular fingerprint of surface-enhanced Raman spectroscopy (SERS), we reveal that a cooperative effect between cucurbit[7]uril (CB[7]) and methyl viologen (MV2+2I−) in aggregating Au NPs originates from the cooperative adsorption of halide counter anions I−, MV2+, and CB[7] on Au NPs surface. Moreover, similar SERS peak shifts in the control experiments using CB[n]s but with smaller cavity sizes suggested the occurrence of the same guest complexations among CB[5], CB[6], and CB[7] with MV2+. Hence, an unconventional exclusive complexation model is proposed between CB[7] and MV2+ on the surface of Au NPs, distinct from the well-known 1:1 inclusion complexation model in aqueous solutions. In summary, new insights into the fundamental understanding of host–guest interactions at nanostructured interfaces were obtained by SERS, which might be useful for applications related to host–guest chemistry in engineered nanomaterials.
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