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1 Retraction Note: Bull. Mater. Sci., Vol. 35, No. 6, November 2012, pp. 1019–1029. https://doi.org/10.1007/s12034-012-0380-9
The Chief Editor of Bulletin of Materials Science has retracted this Article due to significant overlap with a number of other articles which were previously published [1] or under consideration at the same time [2,3,4,5,6,7,8] without proper cross-referencing. An independent expert confirmed the similarities between the articles.
Ali Nazari has not responded to correspondence from the Chief Editor about this retraction.
References
Riahi S, Nazari A and Ghasemi D 2012 RETRACTED: Prediction of Resistance to Water Damage of Geopolymers with Seeded Fly Ash and Rice Husk Bark Ash by Fuzzy Logic. International Journal of Damage Mechanics 21 822–842. https://doi.org/10.1177/1056789511419984
Nazari A 2013 RETRACTED ARTICLE: Artificial neural networks for prediction compressive strength of geopolymers with seeded waste ashes. Neural Comput & Applic 23 391–402. https://doi.org/10.1007/s00521-012-0931-4
Nazari A and Riahi S 2013 RETRACTED ARTICLE: Artificial neural networks to prediction total specific pore volume of geopolymers produced from waste ashes. Neural Comput & Applic 22 719–729. https://doi.org/10.1007/s00521-011-0760-x
Nazari A 2013 RETRACTED ARTICLE: Artificial neural networks application to predict the compressive damage of lightweight geopolymer. Neural Comput & Applic 23 507–518. https://doi.org/10.1007/s00521-012-0945-y
Nazari A 2012 Experimental study and computer-aided prediction of percentage of water absorption of geopolymers produced by waste fly ash and rice husk bark ash. International Journal of Mineral Processing 110 74–81. https://doi.org/10.1016/j.minpro.2012.04.007
Nazari A 2019 RETRACTED ARTICLE: Prediction water absorption resistance of lightweight geopolymers by artificial neural networks. Neural Comput & Applic 31 759–766. https://doi.org/10.1007/s00521-012-1136-6
Nazari A, Khalaj G and Riahi S 2013 RETRACTED ARTICLE: ANFIS-based prediction of the compressive strength of geopolymers with seeded fly ash and rice husk–bark ash. Neural Comput & Applic 22 689–701. https://doi.org/10.1007/s00521-011-0751-y
Nazari A and Khalaj G 2012 Prediction total specific pore volume of geopolymers produced from waste ashes by fuzzy logic. Materials Research 15 242–252. https://doi.org/10.1590/S1516-14392012005000010
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Nazari, A. Retraction Note: Artificial neural networks for prediction of percentage of water absorption of geopolymers produced by waste ashes. Bull Mater Sci 45, 64 (2022). https://doi.org/10.1007/s12034-022-02691-8
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DOI: https://doi.org/10.1007/s12034-022-02691-8