Robust optimization of the output voltage of nanogenerators by statistical design of experiments

Song, Jinhui; Xie, Huizhi; Wu, Wenzhuo; Roshan Joseph, V.; Jeff Wu, C. F.; Wang, Zhong Lin

Robust optimization of the output voltage of nanogenerators by statistical design of experiments

Type

Article

Authors

Song, Jinhui
Xie, Huizhi
Wu, Wenzhuo
Roshan Joseph, V.
Jeff Wu, C. F.
Wang, Zhong Lin

Online Publication Date

2010-09-09

Print Publication Date

2010-09

Date

2010-09-09

Abstract

Nanogenerators were first demonstrated by deflecting aligned ZnO nanowires using a conductive atomic force microscopy (AFM) tip. The output of a nanogenerator is affected by three parameters: tip normal force, tip scanning speed, and tip abrasion. In this work, systematic experimental studies have been carried out to examine the combined effects of these three parameters on the output, using statistical design of experiments. A statistical model has been built to analyze the data and predict the optimal parameter settings. For an AFM tip of cone angle 70° coated with Pt, and ZnO nanowires with a diameter of 50 nm and lengths of 600 nm to 1 μm, the optimized parameters for the nanogenerator were found to be a normal force of 137 nN and scanning speed of 40 μm/s, rather than the conventional settings of 120 nN for the normal force and 30 μm/s for the scanning speed. A nanogenerator with the optimized settings has three times the average output voltage of one with the conventional settings. © 2010 Tsinghua University Press and Springer-Verlag Berlin Heidelberg.

Citation

Song J, Xie H, Wu W, Roshan Joseph V, Jeff Wu CF, et al. (2010) Robust optimization of the output voltage of nanogenerators by statistical design of experiments. Nano Research 3: 613–619. Available: http://dx.doi.org/10.1007/s12274-010-0029-1.

Acknowledgements

This research was supported by the Basic Energy Science, U.S. Department of Energy (BES DOE) (No. DE-FG02-07ER46394), the National Science Foundation (NSF) (Nos. DMS0706436, CMMI 0403671), and the King Abdullah University of Science and Technology (KAUST) Global Research Partnership.