journal article·2025-11

Microbial mineralization of struvite by using talc and its implications for phosphorus recovery

Xingtong Chen, Tianlei Zhao, Bing Li, Yihe Qin, Xiaoman Li, Run Yuan, Jingjing Chen, Han Li, Haiming Huang

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Abstract

Microbial mineralization of struvite is an ideal route to recover nitrogen and phosphorus from wastewater, but expensive magnesium sources limit its application. In this context, Shewanella oneidensis MR-1 was chosen as a model microorganism to investigate the feasibility of using inexpensive and abundant talc as a magnesium source for the microbial mineralization of struvite. The results showed that talc was able to provide magnesium ions for strain MR-1 to induce struvite mineralization, producing prismatic struvite with a purity of up to 78.42 mass%. With increasing ball-milling times from 0 to 90 min, the struvite purity gradually increased from 15.08 mass% to 51.36 mass%, and Mg transformation efficiency of talc increased from 3.95 % to 20.68 %. These findings indicate that mechanical activation can significantly improve the reactivity of talc in the microbial mineralization process. With increasing talc additions from 0.2 g/L to 2.0 g/L, the struvite purity gradually decreased from 78.42 mass% to 41.68 mass%, and Mg transformation efficiency of talc ranged from 17.54 % to 28.02 %. These findings revealed that excess talc could not be effectively converted into struvite and that excess talc also reduced struvite purity. Dissolution experiments revealed that organic matter such as amino acids in the culture medium and ammonium ions produced by strain MR-1, promoted the dissolution of magnesium ions in talc. This study deepens the understanding of microbial-mineral interactions and provides an economically feasible pathway for the removal and recovery of organic nitrogen and organophosphorus in eutrophic waters.
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Research context

OpenAlex topics: Phosphorus and nutrient management · Esophageal and GI Pathology · Constructed Wetlands for Wastewater Treatment

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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