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Surface morphological and optoelectrical characteristics of silicon nitride featured with magnesium oxide nano coating

  • Gopal Kaliyaperumal , Nagabhooshanam Nagarajan ORCID logo , Prahalad Singh Parihar , Nilesh Bhosle , Supriya Subrahmanian , Vadali Surya Narayana Kumar , Ramya Maranan , Rajendran Srinivasan ORCID logo EMAIL logo and Subbarayan Sathiyamurthy
Published/Copyright: December 16, 2025

Abstract

The silicon nitride (Si3N4) solar cell is well-known for its use in solar energy applications due to its passivation properties, which minimize surface recombination, improve thermal stability, and enhance chemical resistance. However, Si3N4 is found to increase processing complexity due to uneven particle dispersion, and a higher concentration of Si3N4 leads to microcracks in areas of high stress concentration, which limit the optoelectrical properties. This research aims to overcome processing difficulties and to enrich the functional characteristics of Si3N4 solar cells with 20, 30, and 40 nm of magnesium oxide (MgO) nanocoating via a vacuum-assisted chemical vapour deposition (CVD) process. The effects of MgO and vacuum on the surface morphology during the CVD process were analyzed, revealing a fine-grain structure without microcracks, resulting in enhanced optoelectrical properties compared to those of the monolithic Si3N4 solar cell. Likewise, X-ray diffraction analysis confirms the presence of MgO in Si3N4 and its crystalline size. Furthermore, the Si3N4 layer with 40 nm MgO is found to have an optimum drain current density of 2.8 × 10−3 A, an improved photocurrent density of 2.6 mA/cm2, a reduced transmittance of 58 %, and a superior solar conversion efficiency of 24.1 %. It is suitable for thin-film solar cell applications.


Corresponding author: Rajendran Srinivasan, Department of Mechanical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS, Chennai, 602105, Tamil Nadu, India, e-mail:

  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.

  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: None declared.

  7. Data availability: Not applicable.

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Received: 2025-08-22
Accepted: 2025-12-02
Published Online: 2025-12-16

© 2025 IUPAC & De Gruyter

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