Insights into the influence of cell concentration in design and development of microbially induced calcium carbonate precipitation (MICP) process

Abstract

Microbially induced calcium carbonate precipitation (MICP) process utilising the biogeochemical reactions for low energy cementation has recently emerged as a potential technology for numerous engineering applications. The design and development of an efficient MICP process depends upon several physicochemical and biological variables; amongst which the initial bacterial cell concentration is a major factor. The goal of this study is to assess the impact of initial bacterial cell concentration on ureolysis and carbonate precipitation kinetics along with its influence on the calcium carbonate crystal properties; as all these factors determine the efficacy of this process for specific engineering applications. We have also investigated the role of subsequent cell recharge in calcium carbonate precipitation kinetics for the first time. Experimental results showed that the kinetics of ureolysis and calcium carbonate precipitation are well-fitted by an exponential logistic equation for cell concentrations between optical density range of 0.1 OD to 0.4 OD. This equation is highly applicable for designing the optimal processes for microbially cemented soil stabilization applications using native or augmented bacterial cultures. Multiple recharge kinetics study revealed that the addition of fresh bacterial cells is an essential step to keep the fast rate of precipitation, as desirable in certain applications. Our results of calcium carbonate crystal morphology and mineralogy via scanning electron micrography, energy dispersive X-ray spectroscopy and X-ray diffraction analysis exhibited a notable impact of cell number and extracellular urease concentration on the properties of carbonate crystals. Lower cell numbers led to formation of larger crystals compared to high cell numbers and these crystals transform from vaterite phase to the calcite phase over time. This study has demonstrated the significance of kinetic models for designing large-scale MICP applications.