Literature DB >> 29130311

Decoding Apparent Ferroelectricity in Perovskite Nanofibers.

Rajasekaran Ganeshkumar1, Suhas Somnath, Chin Wei Cheah1, Stephen Jesse, Sergei V Kalinin, Rong Zhao1.   

Abstract

Ferroelectric perovskites are an important group of materials underpinning a wide variety of devices ranging from sensors and transducers to nonvolatile memories and photovoltaic cells. Despite the progress in material synthesis, ferroelectric characterization of nanoscale perovskites is still a challenge. Piezoresponse force microscopy (PFM) is one of the most popular tools for probing and manipulating nanostructures to study the ferroelectric properties. However, the interpretation of hysteresis data and alternate signal origins are critical. Here, we use a family of scanning probe microscopy (SPM) techniques to systematically investigate the ferroelectric behavior of electrospun potassium niobate (KNbO3) nanofibers. Band Excitation (BE) SPM scans reveal that PFM signals are dominated by changes in resonant frequency due to rough nanofiber surfaces, rather than the actual local piezoelectric strength. We investigate the bias-induced charge injection properties and electrostatic interactions on the PFM response of the nanofiber using contact mode Kelvin probe force microscopy (cKPFM). Furthermore, the impact of relative humidity on the KNbO3 nanofiber's piezoresponse, switching behavior, and tip-induced charges are explored. The resultant data from BE scans were utilized to estimate the piezoelectric constants of the KNO nanofiber. These observations will provide clarity in studying newly developed ferroelectric nanostructures and unambiguously interpreting the PFM data.

Entities:  

Keywords:  PFM; band excitation PFM; cKPFM; electrospinning; ferroelectricity; nanofibers; polarization switching; potassium niobate

Year:  2017        PMID: 29130311     DOI: 10.1021/acsami.7b14257

Source DB:  PubMed          Journal:  ACS Appl Mater Interfaces        ISSN: 1944-8244            Impact factor:   9.229


  1 in total

Review 1.  Self-assisted wound healing using piezoelectric and triboelectric nanogenerators.

Authors:  Fu-Cheng Kao; Hsin-Hsuan Ho; Ping-Yeh Chiu; Ming-Kai Hsieh; Jen-Chung Liao; Po-Liang Lai; Yu-Fen Huang; Min-Yan Dong; Tsung-Ting Tsai; Zong-Hong Lin
Journal:  Sci Technol Adv Mater       Date:  2022-01-07       Impact factor: 8.090

  1 in total

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