4.8 Review

More Than Energy Harvesting in Electret Electronics-Moving toward Next-Generation Functional System

Journal

ADVANCED FUNCTIONAL MATERIALS
Volume 33, Issue 17, Pages -

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/adfm.202214859

Keywords

energy harvesting; electret electronics; internet of things; machine learning; sustainable systems

Ask authors/readers for more resources

This review summarizes the progress of electret-based electronics, focusing on enhanced energy harvesting, multi-functional applications, and machine learning-enabled methodologies. Electrets, which can convert mechanical vibration into electrical power without friction, have the potential to greatly benefit energy harvesters, sensors, and sustainable systems. In addition, the application of machine learning in electret electronics can contribute to the development of reliable and sustainable intelligent systems.
Electrets are normally applied for energy conversion from mechanical vibration sources in the environment to electrical power without any friction, which induces electric device sustainability and mechanically robust. It functions for electron storage and electrostatic/triboelectric effect, whose electrical/mechanical performance dramatically benefits energy harvesters, self-powered sensors, and even intelligent/sustainable systems. To summarize the progress of electret-based electronics, this review proposes three key issues around enhanced energy harvesting toward sensors and sustainable systems. First, with the properties of long-term charge storage characteristics and the contactless mechanism for energy harvesting, the enhancement effect in electret from MEMS devices, porous microstructure devices, and multilayer electret devices are carefully assessed with the output power from various devices. Second, the multi-functional applications aspect along with the triboelectric coupling effect and artificial piezoelectric materials are discussed as future electret devices, for example, polydimethylsiloxane materials. Third, more than energy harvesting, machine learning-enabled methodology in electret electronics can be more reliable and sustainable, dramatically contributing to the living standard of the society. Electret technologies on the future development trends are finally analyzed and strengthened toward multifunctional, sustainable, and intelligent systems along with the upcoming technologies in coupling mechanism, artificial composite materials, and machine learning in data fusion.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available