Towards Machine Learning-Driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis

Towards Machine Learning-Driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis

Fischer-Tropsch synthesis (FTS) offers a promising route for producing sustainable jet fuels from syngas. However, optimizing the catalyst design and operating conditions to maximize the desired C8-C16 jet fuel range is a challenging task. This study introduces the application of a machine learning...

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Bibliographic Details
Main Authors: Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano-Garcia
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2024-12-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/15003
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