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Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification

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Bibliographic Details
Published in:Journal of Petroleum Exploration and Production Technology
Format: Online Article RSS Article
Published: 2026
Subjects:
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container_title Journal of Petroleum Exploration and Production Technology
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
RSS Article
genre Journal Article
id rss_article:23057
institution FRELIP
journal_source_facet Journal of Petroleum Exploration and Production Technology
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
Petroleum, Oil and Gas
Technology & Engineering — Aerospace & Applied Tech
Technology & Engineering
sub_discipline_display Technology & Engineering — Aerospace & Applied Tech
sub_discipline_facet Technology & Engineering — Aerospace & Applied Tech
subject_display Petroleum, Oil and Gas
Technology & Engineering — Aerospace & Applied Tech
Technology & Engineering
Petroleum, Oil and Gas
Technology & Engineering — Aerospace & Applied Tech
Technology & Engineering
subject_facet Petroleum, Oil and Gas
Technology & Engineering — Aerospace & Applied Tech
Technology & Engineering
title Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_auth Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_full Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_fullStr Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_full_unstemmed Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_short Machine learning–based PSO optimization of SiO₂-TOMAC nanocomposites for efficient crude oil demulsification
title_sort machine learning–based pso optimization of sio₂-tomac nanocomposites for efficient crude oil demulsification
topic Petroleum, Oil and Gas
Technology & Engineering — Aerospace & Applied Tech
Technology & Engineering
url https://link.springer.com/article/10.1007/s13202-026-02145-5