Issue 1, 2015

Tunable reverse electrodialysis microplatform with geometrically controlled self-assembled nanoparticle network

Abstract

Clean and sustainable energy generation from ambient environments is important not only for large scale systems, but also for tiny electrical devices, because of the limitations of batteries or external power sources. Chemical concentration gradients are promising energy resources to power micro/nanodevices sustainably without discharging any pollutants. In this paper, an efficient microplatform based on reverse electrodialysis, which enables high ionic flux through three dimensional nanochannel networks for high power energy generation, is demonstrated. Highly effective cation-selective nanochannel networks are realized between two microfluidic channels with geometrically controlled in situ self-assembled nanoparticles in a cost-effective and simple way. The nano-interstices between the assembled nanoparticles have a role as collective three-dimensional nanochannel networks and they allow higher ionic flux under concentration gradients without decreasing diffusion potential, compared to standard one-dimensional nanochannels. An in-depth experimental study with theoretical analysis shows that the electrical power of the presented system can be flexibly tuned or further optimized by changing the size, material, and shape of the assembled nanoparticles or by the geometric control of the microchannel. This microfluidic power generation system can be readily integrated with existing lab on a chip systems in the near future and can also be utilized to investigate nanoscale electrokinetics.

Graphical abstract: Tunable reverse electrodialysis microplatform with geometrically controlled self-assembled nanoparticle network

Supplementary files

Article information

Article type
Paper
Submitted
03 Sep 2014
Accepted
01 Oct 2014
First published
01 Oct 2014

Lab Chip, 2015,15, 168-178

Tunable reverse electrodialysis microplatform with geometrically controlled self-assembled nanoparticle network

E. Choi, K. Kwon, D. Kim and J. Park, Lab Chip, 2015, 15, 168 DOI: 10.1039/C4LC01031K

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