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Predicting wire electrical discharge machined surface roughness of C355/silicon nitride/graphene hybrid nanocomposites using simulation, statistical and machine learning techniques

Crossref DOI link: https://doi.org/10.1038/s41598-026-41376-8

Published Online: 2026-02-27

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Vellingiri, Suresh https://orcid.org/0000-0002-3993-4260
Tata, Ravi Kumar

Manne, Sumalatha https://orcid.org/0009-0006-1934-4278
Natarajan, Arul https://orcid.org/0000-0002-8397-5633
Ismail, Sikiru O. https://orcid.org/0000-0003-1451-1736
Murugan, Arundeep https://orcid.org/0000-0003-4646-7469
Paulraj, Prabhu

Jeyaramalingam, Senthil Kumar
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Text and Data Mining valid from 2026-02-27

Version of Record valid from 2026-04-03
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Article History

Received: 23 December 2025

Accepted: 19 February 2026

First Online: 27 February 2026

Declarations

:

: The authors declare no competing interests.

: of conflicting interests .

: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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