A Signal Processing And Mechanical Design Approach To Understanding Triboelectric And Piezoelectric Nanogenerators’ Output

Author

Nicholas Rose, University of Central FloridaFollow

Keywords

Piezoelectricity, Triboelectricity, TENG, PENG

Abstract

Scalable energy harvesters—capable of converting motion into electrical output—provide promising solutions to increasing energy demands. This thesis was inspired by the potential biomedical applications of piezoelectric nanogenerators (PENG) and triboelectric nanogenerators (TENG). In theory, these devices could convert mechanical energy from the body into usable electricity for self-powered electronics such as pacemakers or cochlear implants. In line with this goal, this project worked to design a sustainable and biocompatible PENG; however, early devices produced inconsistent voltage. These output inconsistencies motivated an exploration of device reproducibility, but characterizing piezoelectric output signals is a particular challenge in the field. Subtle to significant changes in the rate and amplitude of compression decrease the predictability of output peaks and exacerbate waveform irregularities. Further, recent discoveries highlight how triboelectric charge transfer complicates waveforms and, ultimately, the perceived output of piezoelectric generators. Thus, this thesis developed algorithms to characterize TENG, PENG, and hybrid output. The first algorithm exploits electrical peak periodicity to automatically isolate the peak compressive voltage in laboratory and human motion testing conditions. The algorithm can generate quantitative metrics regarding device output, isolate PENG and TENG signals from hybrid devices, and smooth out waveforms. The second program enhances a widely used material science instrument (TA.XTplusC) by expanding its frequency capabilities and offering precise control over frequency, force, and distance variables.

Thesis Completion Year

2025

Thesis Completion Semester

Spring

Thesis Chair

Crawford,Kaitlyn

College

College of Engineering and Computer Science

Department

Materials Science and Engineering

Thesis Discipline

Materials Science and Engineering

Language

English

Access Status

Open Access

Length of Campus Access

None

STARS Citation

Rose, Nicholas, "A Signal Processing And Mechanical Design Approach To Understanding Triboelectric And Piezoelectric Nanogenerators’ Output" (2025). Honors Undergraduate Theses. 339.
https://stars.library.ucf.edu/hut2024/339