L
Lotfi Mouni
Researcher at University of Bouira
Publications - 76
Citations - 1853
Lotfi Mouni is an academic researcher from University of Bouira. The author has contributed to research in topics: Chemistry & Adsorption. The author has an hindex of 17, co-authored 41 publications receiving 1270 citations. Previous affiliations of Lotfi Mouni include University of Béjaïa.
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Removal of Methylene Blue from aqueous solutions by adsorption on Kaolin: Kinetic and equilibrium studies
Lotfi Mouni,Lazhar Belkhiri,Jean-Claude Bollinger,Abdelkrim Bouzaza,Aymen Amine Assadi,Amar Tirri,Farid Dahmoune,Khodir Madani,Houcine Remini +8 more
TL;DR: In this article, the removal of methylene blue (MB) from aqueous solutions using a raw Algerian kaolin sample as a low-cost adsorbent was studied using a pseudo-second order model.
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Application of multivariate statistical methods and inverse geochemical modeling for characterization of groundwater — A case study: Ain Azel plain (Algeria)
TL;DR: In this paper, multivariate statistical methods and inverse geochemical modeling were jointly used to define the variation and the genetic origin of chemical parameters of groundwater in the Ain Azel plain, Algeria.
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Adsorption of Pb(II) from aqueous solutions using activated carbon developed from Apricot stone
TL;DR: In this paper, low-cost activated carbon was prepared from Apricot stone material by chemical activation with sulphuric acid for the adsorption of Pb(II) from dilute aqueous solution.
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A multivariate Statistical Analysis of Groundwater Chemistry Data
TL;DR: In this paper, the authors applied Q-mode hierarchical cluster (HCA) and principal component analysis (PCA) to groundwater hydrochemical data from the three times in 2004: June, September, and December, along the Ain Azel aquifer, Algeria, to extract principal factors corresponding to the different sources of variance in the hydrochemistry.
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Ultrasound assisted extraction of phenolic compounds from P. lentiscus L. leaves: Comparative study of artificial neural network (ANN) versus degree of experiment for prediction ability of phenolic compounds recovery
Farid Dahmoune,Farid Dahmoune,Hocine Remini,Sofiane Dairi,Omar Aoun,Kamal Moussi,Nadia Bouaoudia-Madi,Nawel Adjeroud,Nabil Kadri,Khalef Lefsih,Lhadi Boughani,Lhadi Boughani,Lotfi Mouni,Balunkeswar Nayak,Khodir Madani +14 more
TL;DR: In this article, the authors applied the central composite design (CCD) and artificial neural networks (ANNs) for the study of the operating parameters of ultrasound assisted extraction (UAE) in the recovery of phenolic compounds from P lentiscus leaves.