451
Views
9
CrossRef citations to date
0
Altmetric
Original Articles

Effect of Operational Conditions on Separation of Lithium from Geothermal Water by λ-MnO2 Using Ion Exchange–Membrane Filtration Hybrid Process

, , , , , & show all
Pages 499-512 | Published online: 08 Oct 2018
 

ABSTRACT

A hybrid system coupling ion exchange and ultrafiltration (UF) was employed to separate lithium from lithium-spiked geothermal water. The effect of process parameters such as adsorbent type, adsorbent dosage, permeate flow rate, and replacement speeds of fresh and saturated adsorbents have been evaluated to determine the efficiency of the hybrid system. According to the results obtained using λ-MnO2 derived from spinel-type lithium manganese dioxide, the optimal operating conditions to separate lithium from geothermal water were found with powdery λ-MnO2 with an adsorbent concentration of 1.5 g adsorbent/L solution, replacement rates of fresh and saturated adsorbents of 6.0 mL/min, and a permeate flow rate of 5.0 mL/min. The ion exchange–UF hybrid system providing an advantage to work with very fine particles easily can be considered as a favorable process for the separation of lithium from geothermal water.

Acknowledgments

We are grateful to Izmir Geothermal Co. for geothermal water samples. We thank M.Akçay, S.Bunani and E.Altıok for the kind help in lithium analyses by AAS.

Additional information

Funding

This study was financially supported by a grant so-called TUBITAK–JSPS bilateral project (Project number: 214M360).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 876.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.