The triboelectric nanogenerator (TENG), which can convert mechanical energy into electricity, is widely used in various self-powered sensors. It is considered as the most promising energy source for the sensor nodes in the Internet of Things (IoTs).  

Energy manipulation from the mechanical power source is an essential segment for self-powered electronics and the potential application in IoTs.

Inspired by the concept of programming, a research team led by Dr. WANG Hao from the Shenzhen Institutes of Advanced Technology (SIAT) of the Chinese Academy of Sciences proposed programmed-triboelectric nanogenerators (P-TENGs) using mechanical switches regulation methodology for energy manipulation. Their study was published in Nano Energy. 

The conventional TENG device involves three unit operations, i.e., charge generation by friction, charge transfer by capacitance change, and power output on the external load. Its operation principle is a loop of a specific combination and sequence of three unit-operations, which is considered as the most basic program.  

Based on this principle, Dr. WANG's team proposed three different programs for the three unit-operations with more complex combination and sequence, enabling charge accumulation on one of the electrode plate.

The energy can increase with the operation loops and saturates at a certain point when the internal voltage reaches the threshold of capacitive breakdown. 

Compared with the conventional TENG, the programmable TENG is fundamentally different in three aspects.  

The maximum voltage/output is not determined by the materials of the friction surfaces. The surface charge density on the friction surface only affects the duration required to reach the maximum output.

The maximum output is limited by the capacitive breakdown voltage between electrode plates.

There are an infinite number of feasible programs for charge accumulation. Each program requires a specific mechanical structure for its physical realization.  

The proposed mechanical switches regulation methodology can enable an alternative approach to the research of triboelectric nanogenerators.