(Invited) Nanoarray Configured Monoliths for Self-Monitored Multi-Phase Reactive Processes

Abstract

The incorporation of multiple functions synergistically into one device or platform can enable additions of application merits such as light weight, ease for system integration, reduced system complexity, cost-effectiveness, and programmability. This is especially true for usually complex energy, environmental, and biological systems with the integration need of many active or passive devices and components of various functionalities. In this work, we demonstrated a compact nanoarray configured monolith design with the ability to function as both a catalyst and a sensor to enable the self-monitoring of the complex multi-phase catalytic reaction processes during operation. A bimodular approach has been realized using both electrical and electrochemical interrogation modes for reactive gas and solid phase monitoring directly using the built-in catalysts. This new type of compact and built-in monolithic sensor configuration can lower the catalytic energetics and detect gas/solid composition semi-quantitatively at room temperature up to elevated temperature. Robust calibration curves of built-in sensor responses can be achieved with facile data processing and analyzing. The built-in monolith sensor shows good sensitivity and good selectivity sufficient for the self-monitoring of the reaction process. Besides, the nanoarray based monolith device has shown good environmental tolerance toward practical applications. Such compact monolithic device can serve as a self-monitored reactor, filter, and other function component that can potentially allow in-situ and real time monitoring and functional process control in complex and reactive physical and chemical environments. With further refining of the design and functional integration, this new type of smart monolithic device can provide necessary data and knowledge for future computation-driven situational awareness prediction and intelligent control of various complex dynamic processes and systems.