Li Xinyi, Fu Ying-Huan, Wei Nannan, Yu Ru-Jia, Bhatti Huma, Zhang Limin, Yan Feng, Xia Fan, Ewing Andrew G, Long Yi-Tao, Ying Yi-Lun
State Key Laboratory of Analytical Chemistry for Life Science, School of Chemistry and Chemical Engineering, Nanjing University, 210023, Nanjing, P. R. China.
School of Electronic Science and Engineering, Nanjing University, 210023, Nanjing, P. R. China.
Angew Chem Int Ed Engl. 2024 Apr 22;63(17):e202316551. doi: 10.1002/anie.202316551. Epub 2024 Mar 15.
Single-entity electrochemistry is a powerful tool that enables the study of electrochemical processes at interfaces and provides insights into the intrinsic chemical and structural heterogeneities of individual entities. Signal processing is a critical aspect of single-entity electrochemical measurements and can be used for data recognition, classification, and interpretation. In this review, we summarize the recent five-year advances in signal processing techniques for single-entity electrochemistry and highlight their importance in obtaining high-quality data and extracting effective features from electrochemical signals, which are generally applicable in single-entity electrochemistry. Moreover, we shed light on electrochemical noise analysis to obtain single-molecule frequency fingerprint spectra that can provide rich information about the ion networks at the interface. By incorporating advanced data analysis tools and artificial intelligence algorithms, single-entity electrochemical measurements would revolutionize the field of single-entity analysis, leading to new fundamental discoveries.
单实体电化学是一种强大的工具，可用于研究界面处的电化学过程，并深入了解单个实体的内在化学和结构异质性。信号处理是单实体电化学测量的一个关键方面，可用于数据识别、分类和解释。在本综述中，我们总结了单实体电化学信号处理技术在过去五年中的进展，并强调了它们在获取高质量数据和从电化学信号中提取有效特征方面的重要性，这些技术通常适用于单实体电化学。此外，我们还介绍了电化学噪声分析，以获得单分子频率指纹光谱，该光谱可以提供有关界面处离子网络的丰富信息。通过结合先进的数据分析工具和人工智能算法，单实体电化学测量将彻底改变单实体分析领域，带来新的基础发现。
