Journal
CHEMISTRY OF MATERIALS
Volume -, Issue -, Pages -Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.chemmater.2c02707
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Redox bioelectronics utilizes electrochemical methods to connect with biology's native redox modality, which involves electron exchange through redox reactions. This study explores electrodes coated with redox-active but non-conducting catechol-containing hydrogels, which are emerging as important materials in redox-based bioelectronics. By increasing the dimensionality of dynamic optical measurements and employing a deterministic network model, the researchers reveal the intrinsic structure of the additional data, enhancing their capabilities for signal detection and interpretation in redox-based bioelectronics.
Redox bioelectronics enlists electrochemical methods to connect to biology through biology's native redox modality. The activities of this redox modality involve the exchange of electrons through redox reactions, and often, individual redox reactions are embedded within larger redox-reaction networks. Here, we examined electrodes coated with redox-active but non-conducting catechol-containing hydrogels that are emerging as important materials in redox-based bioelectronics. Previous studies have shown that electron flow through these catechol hydrogels involves redox reactions, and in some cases, catechol's redox-state switching can be observed by orthogonal electrical and optical measurements. Here, we extend analysis by increasing the dimensionality of dynamic optical measurements from a single wavelength to a broader spectrum and adapt a minimal deterministic network model to reveal the intrinsic structure of this additional data. This increased dimensionality enhances our capabilities for detecting and interpreting discriminating signals, and we demonstrate these capabilities by comparing the response characteristics of conducting versus redox-active hydrogels and redox networks with different topologies. We discuss the importance of increasing measurement dimensionality to enhance both data -driven and theory-guided approaches for information processing in redox-based bioelectronics.
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