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Open AccessFeature PaperArticle

Use of Radial Basis Function Network to Predict Optimum Calcium and Magnesium Levels in Seawater and Application of Pretreated Seawater by Biomineralization as Crucial Tools to Improve Copper Tailings Flocculation

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Departamento de Ingeniería Química y Procesos de Minerales, Universidad de Antofagasta, Av. Universidad de Antofagasta, 02800 Antofagasta, Chile
2
Departamento de Biotecnología, Facultad de Ciencias del Mar y Recursos Biológicos (FACIMAR), Universidad de Antofagasta, Av. Universidad de Antofagasta, 02800 Antofagasta, Chile
3
Telematic University Pegaso, Piazza Trieste e Trento 48, 80132 Naples, Italy
*
Authors to whom correspondence should be addressed.
Minerals 2020, 10(8), 676; https://doi.org/10.3390/min10080676
Received: 29 May 2020 / Revised: 16 July 2020 / Accepted: 22 July 2020 / Published: 30 July 2020
(This article belongs to the Special Issue Understanding Bacterial Mineralization)
The combined use of the Radial Basis Function Network (RBFN) model with pretreated seawater by biomineralization (BSw) was investigated as an approach to improve copper tailings flocculation for mining purposes. The RBFN was used to set the optimal ranges of Ca2+ and Mg2+ concentration at different Ph in artificial seawater to optimize the performance of the mine tailings sedimentation process. The RBFN was developed by considering Ca2+ and Mg2+ concentration as well as pH as input variables, and mine tailings settling rate (Sr) and residual water turbidity (T) as output variables. The optimal ranges of Ca2+ and Mg2+ concentration were found, respectively: (i) 169–338 and 0–130 mg·L−1 at pH 9.3; (ii) 0–21 and 400–741 mg·L–1 at pH 10.5; (iii) 377–418 and 703–849 mg·L−1 at pH 11.5. The settling performance predicted by the RBFN was compared with that measured in raw seawater (Sw), chemically pretreated seawater (CHSw), BSw, and tap water (Tw). The results highlighted that the RBFN model is greatly useful to predict the settling performance in CHSw. On the other hand, the highest Sr values (i.e., 5.4, 5.7, and 5.4 m·h–1) were reached independently of pH when BSw was used as a separation medium for the sedimentation process. View Full-Text
Keywords: calcium; magnesium; Radial Basis Function Network (RBFN); settling rate; turbidity; biomineralization; mine tailings; water quality calcium; magnesium; Radial Basis Function Network (RBFN); settling rate; turbidity; biomineralization; mine tailings; water quality
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MDPI and ACS Style

Villca, G.; Arias, D.; Jeldres, R.; Pánico, A.; Rivas, M.; Cisternas, L.A. Use of Radial Basis Function Network to Predict Optimum Calcium and Magnesium Levels in Seawater and Application of Pretreated Seawater by Biomineralization as Crucial Tools to Improve Copper Tailings Flocculation. Minerals 2020, 10, 676. https://doi.org/10.3390/min10080676

AMA Style

Villca G, Arias D, Jeldres R, Pánico A, Rivas M, Cisternas LA. Use of Radial Basis Function Network to Predict Optimum Calcium and Magnesium Levels in Seawater and Application of Pretreated Seawater by Biomineralization as Crucial Tools to Improve Copper Tailings Flocculation. Minerals. 2020; 10(8):676. https://doi.org/10.3390/min10080676

Chicago/Turabian Style

Villca, Grecia; Arias, Dayana; Jeldres, Ricardo; Pánico, Antonio; Rivas, Mariella; Cisternas, Luis A. 2020. "Use of Radial Basis Function Network to Predict Optimum Calcium and Magnesium Levels in Seawater and Application of Pretreated Seawater by Biomineralization as Crucial Tools to Improve Copper Tailings Flocculation" Minerals 10, no. 8: 676. https://doi.org/10.3390/min10080676

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