Reliable predictive frameworks for thermal conductivity of ester biofuels using artificial intelligence approaches

Abstract Ester biofuels have emerged as promising renewable alternatives to fossil fuels due to their environmental compatibility and favorable combustion characteristics. Accurate knowledge of their liquid thermal conductivity (LTC) is essential for optimizing energy systems, engine performance, an...

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Detalhes bibliográficos

Principais autores:	Walid Abdelfattah, Ramdevsinh Jhala, Ramachandran Thulasiram, Ahmed Mohsen, Aman Shankhyan, Manoj Kumar Ojha, Dhirendra Nath Thatoi, Fereydoon Ranjbar
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Nature Portfolio 2025-10-01
coleção:	Scientific Reports
Assuntos:	Ester biofuels Liquid thermal conductivity (LTC) Machine learning Intelligent modeling Correlation
Acesso em linha:	https://doi.org/10.1038/s41598-025-19893-9
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