Low-breakdown, high-α SrTiO3 varistors via grain-boundary engineering with ZnBi2O4.

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Title: Low-breakdown, high-α SrTiO3 varistors via grain-boundary engineering with ZnBi2O4.
Authors: Hsiang, Hsing-I.1 (AUTHOR) hsingi@mail.ncku.edu.tw, Lin, Che-Cheng1 (AUTHOR)
Source: Journal of Materials Science: Materials in Electronics. May2026, Vol. 37 Issue 15, p1-15. 15p.
Abstract: SrTiO3 varistors are promising alternatives to ZnO for low-voltage applications when their grain-boundary barrier response is properly controlled. Here, ZnBi2O4 (ZB) addition and post-sintering reoxidation were employed to modify the electrical behavior of La-doped SrTiO3 ceramics. The optimized composition exhibited a low breakdown voltage, high nonlinearity coefficient, and reduced leakage current. Linearized C–V analysis indicated an increase in the effective grain-boundary barrier height after ZB addition and reoxidation, while impedance and AC conductivity results showed reduced grain-boundary carrier transport. Fracture-surface XPS revealed a reduced Ti3+ fraction and a modest increase in adsorbate-related oxygen species after reoxidation. Although direct grain-boundary-resolved chemical evidence was not obtained, the combined results consistently indicate that ZB addition and reoxidation strengthen the functional grain-boundary barrier network. This study demonstrates a practical grain-boundary engineering strategy for low-voltage SrTiO3-based varistors. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Materials Science: Materials in Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Hsiang%2C+Hsing-I%2E%22">Hsiang, Hsing-I.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hsingi@mail.ncku.edu.tw</i><br /><searchLink fieldCode="AR" term="%22Lin%2C+Che-Cheng%22">Lin, Che-Cheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Materials+Science%3A+Materials+in+Electronics%22">Journal of Materials Science: Materials in Electronics</searchLink>. May2026, Vol. 37 Issue 15, p1-15. 15p.
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: SrTiO3 varistors are promising alternatives to ZnO for low-voltage applications when their grain-boundary barrier response is properly controlled. Here, ZnBi2O4 (ZB) addition and post-sintering reoxidation were employed to modify the electrical behavior of La-doped SrTiO3 ceramics. The optimized composition exhibited a low breakdown voltage, high nonlinearity coefficient, and reduced leakage current. Linearized C–V analysis indicated an increase in the effective grain-boundary barrier height after ZB addition and reoxidation, while impedance and AC conductivity results showed reduced grain-boundary carrier transport. Fracture-surface XPS revealed a reduced Ti3+ fraction and a modest increase in adsorbate-related oxygen species after reoxidation. Although direct grain-boundary-resolved chemical evidence was not obtained, the combined results consistently indicate that ZB addition and reoxidation strengthen the functional grain-boundary barrier network. This study demonstrates a practical grain-boundary engineering strategy for low-voltage SrTiO3-based varistors. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Materials Science: Materials in Electronics is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10854-026-17592-3
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        Text: English
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              Text: May2026
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