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Bioleaching of critical minerals from marine sediments by indigenous microbial communities: Experimental and predictive analysis
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology.ORCID iD: 0000-0001-8022-6322
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Industrial Biotechnology, Industrial Biotechnology.ORCID iD: 0009-0006-7841-4627
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemical Engineering, Resource recovery.ORCID iD: 0000-0001-7614-8448
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Chemistry, Applied Physical Chemistry.ORCID iD: 0009-0000-7483-0734
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2026 (English)In: Chemical Engineering Journal, ISSN 1385-8947, E-ISSN 1873-3212, Vol. 536, article id 176047Article in journal (Refereed) Published
Abstract [en]

Marine sediments represent a valuable source for critical minerals that prompts growing research interest in their potential for sustainable resource recovery. This study investigated the impact of bioleaching microorganisms, evaluating three different microbial inocula: sediment indigenous Fe-oxidizing bacteria, sediment indigenous Fe- and S-oxidizing bacteria, and Acidhiobacillus ferrooxidans. Key operational parameters including initial pH (2.0–7.0), energy source (Fe and S), and total solids content (5–10%) were also tested to optimize bioleaching efficiency. The use of Fe- and S-oxidizing bacteria enriched from the marine sediment resulted in the highest bioleaching potential for all target critical minerals. Highest Al leaching (806 mg/L) was obtained an initial pH of 2.0 and TS of 10%, in the presence of added Fe and S, while highest K leaching (169 mg/L) was achieved under the same initial pH and TS, but in the absence of Fe and S. Conversely, Mg leaching was highest as 506 mg/L at an initial pH 2.0 and TS of 10% with the addition of Fe and S. Alicyclobacillaceae was one of the key dominant microorganisms in the microbial community during the bioleaching process. On the other hand, Sulfurifustis played a key role in the early shifts in the microbial community. Additionally, Least Square Boosting (LSBoost), Random Forest Regression (RF), and Linear Regression (LR) were evaluated for predicting critical mineral release, with LSBoost achieving highest R2 values.

Place, publisher, year, edition, pages
Elsevier BV , 2026. Vol. 536, article id 176047
Keywords [en]
Critical minerals, Iron‑sulfur oxidizing bacteria, Machine learning, Marine sediment, PHREEQC
National Category
Microbiology Metallurgy and Metallic Materials Mineral and Mine Engineering Bioenergy
Identifiers
URN: urn:nbn:se:kth:diva-380510DOI: 10.1016/j.cej.2026.176047ISI: 001748624200001Scopus ID: 2-s2.0-105035673819OAI: oai:DiVA.org:kth-380510DiVA, id: diva2:2057112
Note

QC 20260504

Available from: 2026-05-04 Created: 2026-05-04 Last updated: 2026-05-04Bibliographically approved

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Kendir Cakmak, EceOtterheim, LinnéaMarques Penha, FredericoChen, ChenCuartero, MariaCetecioglu, Zeynep

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Kendir Cakmak, EceOtterheim, LinnéaMarques Penha, FredericoChen, ChenCuartero, MariaCetecioglu, Zeynep
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Industrial BiotechnologyIndustrial BiotechnologyResource recoveryApplied Physical Chemistry
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Chemical Engineering Journal
MicrobiologyMetallurgy and Metallic MaterialsMineral and Mine EngineeringBioenergy

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