A map of control for cold atmospheric plasma jets: From physical mechanisms to optimizations

Abstract

The study of cold atmospheric plasma (CAP) began about a decade ago. Currently, multiple applications of CAP have been discovered including biomedicine, nanomaterials, agriculture, and water purifications. At the current stage of these research fields, it is obvious that the next move will be CAP optimization for each specific application. For example, in the field of plasma-based cancer treatment, due to the different responses of cell lines, CAP can activate different biological pathways in different cells, i.e., to be selective. One of the most commonly used CAP types is the cold atmospheric plasma jet (CAPJ). However, without a full understanding of CAPJ physics, it is impossible to optimize the plasma for every application condition. Moreover, since each research team is equipped with its own CAPJ generator, the hardware behaviors vary significantly across researchers. Therefore, a complete big picture of CAPJ control and parameters is a critical milestone for future CAPJ optimization in these research fields. This Review provides a summary of how CAPJ parameters can be manipulated with the control inputs and hardware design to extend that the chemical compositions can be modified by the gas flow rate, discharge waveform, target properties, and local environment. Based on the control map summarized in this work, CAPJ users can easily optimize their device for a certain specific purpose, such as maximizing OH and H2O2 for cancer treatment or maximizing O3 and ultraviolet for sterilization. Therefore, this study sheds light on the general theory of CAPJ control and can be a basis for future optimization of low-temperature plasma devices. Consideration of the plasma control based on machine learning methods has been receiving interest recently and certainly will become a future hot topic.