Startseite Impact of gadolinium and manganese co-doping on the structural, dielectric and electrical characteristics of BST
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Impact of gadolinium and manganese co-doping on the structural, dielectric and electrical characteristics of BST

  • Prachi Bhanwala , Preeti Saroha , Preeti , Md. Ahamad Mohiddon ORCID logo und Anshu Gaur ORCID logo EMAIL logo
Veröffentlicht/Copyright: 4. Juli 2025
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Abstract

Crystal structure, surface morphology, dielectric and electrical characterisation of manganese and gadolinium co-modified barium strontium titanate (BST) composite is reported. In the present work, Mn and Gd co-modified BST, i.e. Ba0.76(Gd0.5Mn0.5)0.04 Sr0.2TiO3 composite is synthesised by sol-gel reaction technique. The crystallographic phase formation of calcined powder is confirmed by the X-ray diffraction technique. Unit cell parameters are extracted from Rietveld refinement of the XRD data using X’Pert High-score plus software. Average crystallite size and lattice strain are estimated from full-width half maxima of diffraction peaks following Scherrer’s equation and Haldar–Wagner’s method. The dielectric and electrical investigations are carried out by measuring the dielectric constant on the sintered pellets as a function of temperature from room temperature to 300 °C at the AC field frequencies of 100 Hz – 1 MHz.


Corresponding author: Anshu Gaur, School of Physics, University of Hyderabad, Prof C R Rao Road, Gachibowli, Hyderabad, 500046, Telangana, India, E-mail:

Acknowledgement

The authors acknowledge Prof. S. Srinath and the School of Physics, University of Hyderabad for providing the characterisation facilities.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. Prachi Bhanwala: Sample Preparation, Preeti Saroha: Sample Preparation, Preeti: Dielectric Characterization, Md. Ahamad Mohiddon: Conceptualization and Manuscript writing, Anshu Gaur: Data Analysis, Manuscript editing.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

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

  6. Research funding: Dr. Anshu acknowledges DST (Ref. No.: SR/WOS-A/ET-38/2018) for providing the funds during this work.

  7. Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2024-01-26
Accepted: 2025-03-31
Published Online: 2025-07-04

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