2026, Vol. 15, Issue 3

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Reviews

Recent advances in machine learning for the design and performance prediction of corrosion inhibitors

• J.A. Khalilov^1,2, F.A. Otamuradov³, K.T. Toshov⁴, S.Z. Khodjamkulov⁵, N.B. Chorieva⁵, N. Urakov⁶, G.J. Mukumova⁷, Z.E. Jumaeva⁷, A.I. Kholboyeva⁷ and Z.M. Kurbonova⁸

¹ Tashkent State Technical University, Tashkent 100095, Uzbekistan
² University of Economics and Pedagogy, Karshi 100000, Uzbekistan
³ Termez branch of Tashkent State Medical University, Termez, 190100, Uzbekistan
⁴ Department of Social Sciences, Education, Termiz University of Economics and Service, Termez 190111, Uzbekistan
⁵ Department of Chemical Engineering, Termez State University of Engineering and Agrotechnologies, Termez, 190100, Uzbekistan
⁶ Department of metrology and technological machines, Termez State University of Engineering and Agrotechnologies, Termez, 190100, Uzbekistan
⁷ Faculty of Chemistry, Termez State University. Termez, 190100, Uzbeksitan
⁸ Department of Pedagogy, Termez State Pedagogical Institute, Termez 190111, Uzbekistan

Int. J. Corros. Scale Inhib., 2026, 15, no. 3, 1-26
doi: 10.17675/2305-6894-2026-15-3-1

Environmentally friendly green inhibitors used for corrosion inhibition of oil pipeline

• A.M. Salim¹, Kh.M. Abed², N.M. Dawood² and Z. Al-Khafaji^3,4

¹ Polytechnic College, Al-Furat Al-Awsat Technical University, 54003 Kufa, Najaf, Iraq
² College of Materials Engineering, University of Babylon, 51001 Hillah, Babylon, Iraq
³ Department of Civil Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
⁴ Imam Ja’afar Al-Sadiq University, Al-Qahira District, 10011 Baghdad, Iraq

Int. J. Corros. Scale Inhib., 2026, 15, no. 3, 27-57
doi: 10.17675/2305-6894-2026-15-3-2

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