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From raw materials to functional material: synthesis and piezoelectric characterization of PIN–PT binary relaxor material

  • Bomkesh Bhoi ORCID logo and Pranati Purohit ORCID logo EMAIL logo
Published/Copyright: December 18, 2024
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Abstract

Lead indium niobate holds particular attention as a functional piezoelectric material as it can transit from a disordered phase to an organized one with exposure to heat for a long time. Obtaining pure-phase perovskite lead indium niobate ceramics without any pyrochlore phase using the conventional mixed oxide method poses significant challenges. This difficulty arises from the low tolerance and electronegativity difference of lead indium niobate in comparison to other perovskite compounds. The dielectric properties of lead indium niobate can be enhanced by adding lead titanate to its composition. In this study, a binary system of lead indium niobate with lead titanate is synthesised close to the morphotropic phase boundary composition by taking 35, 40 and 45 mol.% of lead titanate by using two-step sintering method. Out of the different compositions, the lead indium niobate with 35 mol.% of lead titanate shows high piezoelectric properties and can be a suitable material for energy harvesting.


Corresponding author: Pranati Purohit, School of Physics, Gangadhar Meher University, Sambalpur, 768004 Odisha, India, E-mail:

Acknowledgments

The authors would like to thank Department of Higher Education Odisha (OURIIP SEED fund- 2020/51-Physics) for the financial support to carry out the research work. We also acknowledge IISER, Bhopal for providing support of XRD facility, COE-NPT, Sambalpur university for FTIR facility, and Dr. B. Behera, School of Physics, Sambalpur University for providing facility to study of piezoelectric property.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: There is no use of Large Language Models, AI and Machine Learning Tools.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: This work was supported by the Department of Higher Education Odisha (OURIIP SEED fund- 2020/51-Physics).

  7. Data availability: The raw data can be obtained on request from the corresponding author.

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Received: 2024-02-15
Accepted: 2024-11-08
Published Online: 2024-12-18
Published in Print: 2024-11-26

© 2024 Walter de Gruyter GmbH, Berlin/Boston

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