4.4 Article

Silicon-chip based electromagnetic vibration energy harvesters fabricated using wafer-level micro-casting technique

Journal

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1361-6439/abdb77

Keywords

energy harvesters; electromagnetic solenoids; vibration to electricity conversion; micro-casting technique

Funding

  1. National Science Foundation of China Projects [61834007, 62074151, 61674160, 61527818]
  2. Ministry of Science and Technology of China [2016YFA0200800]
  3. National Key Research and Development Program of China [2016YFA0200803]

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This paper presents a silicon-chip based electromagnetic vibration energy harvester fabricated with a wafer-level micro-casting technique. The harvester efficiently collects vibration energy and exhibits superior normalized power density compared to other types of harvesters.
This paper reports a silicon-chip based electromagnetic (EM) vibration energy harvester that is fabricated with a wafer-level micro-casting technique to form on-chip integrated 3D metal solenoids and magnet sliding channels. Many solenoids of 150-turn coil are simultaneously formed by filling molten ZnAlx alloy into the pre-micromachined solenoid moulds in one wafer within 7 min. After saw dicing to obtain the solenoid chips, a sliding permanent magnet for responding to environmental vibration is inserted into the pre-etched silicon channel inside the solenoid. Excited by external vibration, the magnet can slide in the channel to generate electricity. The size of the micro electro mechanical systems (MEMS) harvester chip is only 10.5 x 2.5 x 1.7 mm(3). The experimental results show that the energy harvester can efficiently collect vibration energy in the environment. Under excited acceleration-amplitude of 49 m s(-2) (i.e. 5 g) at the frequency of 24 Hz, the normalized power density (NPD) generated from the harvester reaches 12.38 mu W cm(-3) g(-2). By comparing with reported non-MEMS wire-wound EM harvesters and on-chip piezoelectric/electrostatic ones, this silicon-chip based EM harvester exhibits much superior NPD.

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