Exploring the uniformity of MICP solidified fine particle silt with different sample preparation methods

Abstract

Microbial induced calcium carbonate precipitation (MICP) technology is widely used for reinforcement in geotechnical engineering due to its low cost, simple process, strong applicability and lack of secondary pollution. However, the presence of clay particles in silt increases the compressibility and decreases the permeability of soil, complicating the even distribution of slurry into soil pores. Therefore, it is necessary to develop a treatment technology which is suitable for silty soil sites, achieving effective solidification using MICP. This study examines three treatment techniques, including grouting, immersing and mixing methods, to solidify silt material. The strength characteristics of the solidified soil were analyzed by using unconfined compression tests. Results show that the mixing method provides the highest strength, followed by the grouting method, with the immersion method yielding the lowest strength. The uniformity of the solidified samples was assessed by determining calcium carbonate content, X-ray diffraction tests, and mercury injection tests. The MICP samples made by using immersing and grouting methods exhibited inhomogeneity in both radial and longitudinal directions. For the immersing method, calcium carbonate content decreased, pore volume increased, and the degree of cementation worsened progressively from the outer layer to the inner layer. For grouting method, the same phenomenon occurs from the bottom (grouting point) to the top. In contrast, the MICP samples with mixing method showed good homogeneity in all spatial directions. This study provides guidance and optimization strategies for applying MICP technology in silty soil sites.

Keywords

MICP / Immersing / Grouting / Mixing / Uniformity

CRediT authorship contribution statement

Bo Kang: Writing - original draft, Supervision, Methodology, Funding acquisition, Conceptualization. Hao Wang: Visualization, Validation, Data curation. Fusheng Zha: Writing - review & editing, Supervision, Funding acquisition. Congmin Liu: Validation, Methodology, Data curation. Annan Zhou: Writing - review & editing, Supervision, Methodology. Rulong Ban: Visualization, Validation, Data curation.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research is supported by was supported by the National Natural Science Foundation of China (42472337), National Key Research and Development Program of China (grant number: 2023YFC3707900), National Natural Science Foundation of China (grant numbers: 42030710).

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