**3. Summary and future research direction**

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surface area and the unique 2D structure of siloxene, the heterogeneous electron transfer (HET) is high, which beneficial for selective electrochemical bio-marker detections. We have recently demonstrated the siloxene-based novel electrochemical dopamine sensor and obtained remarkable achievements in dopamine detection by the siloxene modified sensor [11]. Dopamine (DA) is an important neurotransmitter that plays a crucial role in the central nervous system and cardiovascular systems. A variety of materials have been employed for electrochemical DA detection in the past decades. However, the high selectivity of DA is limited to the existing materials. As a result of high HET rates, large surface area, and improved mass transportation, siloxene possessed high selectivity for DA detection (**Figure 6**). Siloxene modified glassy carbon electrode showed a well-defined redox peak in the cyclic voltammetry technique towards DA detection. Excellent linearity has been achieved for the siloxene electrode in the presence of a different concentration of DA, and the modified electrode exhibited a detection limit of 0.327 μM. Besides, the proposed

sensor revealed a wide linear range from 10 to 1100 μM (**Figure 6(b)**).

The DA detection performance by the 2D siloxene sheets is remarkably higher than that of other reported 2D graphene and g-C3N4 modified electrodes. Siloxene sheets owned a higher response for the detection limit and showed high selectivity for DA detection. The stronger π-π interaction between the siloxene planar structure and the dopamine phenyl structure enables faster electron transportation during the DA oxidation process, making the high selectivity characteristic of the siloxene modified electrode. On the other hand, the π-π interaction of the siloxene structure with other biomolecules such as ascorbic acid, uric acid, etc., is weak, resulting in

*(a-d) Electrochemical differential pulsed voltammetry response and linear range of siloxene modified electrode* 

*for DA detections (reproduced from [11] with permission from Elsevier).*

**164**

**Figure 6.**

In conclusion, this chapter deals with the comprehensive review of the raising star 2D siloxene based electrochemical energy and sensor applications. The siloxene synthesis process and the siloxene structure affecting parameters have been reviewed in detail. The functional groups in siloxene and the oxidation level can be varied at different synthesis times and the annealing temperature. Compared to pristine siloxene, high temperature treated siloxene possessed an excellent performance in the electrochemical supercapacitors because of its reduced functional groups. Besides, the siloxene and its composite have been used as anode materials for LIBs and showed a significant capacity and Coulombic efficiency. Li-storage has influenced by the oxidation level in siloxene due to the presence of different atomic percentages of Si functional groups. However, both supercapacitors and LIBs applications, siloxene derivatives such as SiOx, SiOC showed improved performance as the results of its better electrical conductivity and Li-ion diffusivity compared to the bare siloxene. The reported siloxene works have focused on the performance of siloxene in supercapacitors and LIBs. But many works failed to investigate the insight of the electrochemistry of siloxene and its derivatives for better energy density, capacity, and cyclic stability. Thus, the research direction should be focused more on the study of electrochemistry of siloxene. On the other hand, the 2D siloxene sheets proved as a novel electrochemical sensor for highly selective dopamine detection. Moreover, the size and thickness of the layer can influence the HET rate, specific surface area, and active sites for DA detection, which need to be optimized in the near future.

#### **Acknowledgements**

This work was supported in part by the National Natural Science Foundation of China (Project No. 51950410598), in part by Shenzhen Science and Technology Innovation Committee (Projects No. JCYJ20170412154426330), and in part by Guangdong Natural Science Funds (Project No.: 2016A030306042 and 2018A050506001). Also, this work was supported by the Major Program of Guangdong Basic and Applied Research (No. 2019B030302009).

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