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Cited by 171

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Patterned piezo-, pyro-, and ferroelectricity of poled polymer electrets

Open access
Qiu, Xunlin·2010·Journal of Applied Physics

Abstract

Polymers with strong piezo-, pyro-, and ferroelectricity are attractive for a wide range of applications. In particular, semicrystalline ferroelectric polymers are suitable for a large variety of piezo- and pyroelectric transducers or sensors, while amorphous polymers containing chromophore molecules are particularly interesting for photonic devices. Recently, a new class of polymer materials has been added to this family: internally charged cellular space-charge polymer electrets (so-called “ferroelectrets”), whose piezoelectricity can be orders of magnitude higher than that of conventional ferroelectric polymers. Suitable patterning of these materials leads to improved or unusual macroscopic piezo-, pyro-, and ferroelectric or nonlinear optical properties that may be particularly useful for advanced transducer or waveguide applications. In the present paper, the piezo-, pyro-, and ferroelectricity of poled polymers is briefly introduced, an overview on the preparation of polymer electrets with patterned piezo-, pyro-, and ferroelectricity is provided and a survey of selected applications is presented.

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Metadata

Authors
Qiu, X.
Venue
Journal of Applied Physics
Published
2010-07-01
Volume
108
Issue
1
ISSN
  • 0021-8979 (ISSN-L)
  • 1089-7550
OpenAlex
W2056534199
Cited by
171
References
1
FWCI
10.56
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Patterned piezo-, pyro-, and ferroelectricity of poled polymer electrets. https://app.cochat.ai/papers/10.1063/1.3457141
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Qiu, X. (2010). Patterned piezo-, pyro-, and ferroelectricity of poled polymer electrets. Journal of Applied Physics. https://doi.org/10.1063/1.3457141

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.