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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Hlavní autoři:	Walid Abdelfattah, Ramdevsinh Jhala, Ramachandran Thulasiram, Ahmed Mohsen, Aman Shankhyan, Manoj Kumar Ojha, Dhirendra Nath Thatoi, Fereydoon Ranjbar
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Nature Portfolio 2025-10-01
Edice:	Scientific Reports
Témata:	Ester biofuels Liquid thermal conductivity (LTC) Machine learning Intelligent modeling Correlation
On-line přístup:	https://doi.org/10.1038/s41598-025-19893-9
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