Performance of biological methods on self-healing and mechanical properties of concrete using S. pasteurii.

Biological methods (adding bacteria to the concrete mixtures) among the most recently investigated procedures increase the durability of concrete and repair concrete cracks. In the present study, different biological methods were used to heal the cracks of concrete and the most suitable method was subsequently introduced as the main aim of the research. For this purpose, the culture medium, various sources of calcium salts as bacterial nutrients, and the effect of air-entrained agent on the healing process were studied. The results showed that the use of bacterial nutrient inside the concrete mixes has an affirmative impact on the mechanical properties and self-healing characteristics of concretes. Simultaneous use of Sporosarcina pasteurii bacteria and calcium nitrate-urea or calcium chloride-urea as a bacterial nutrient in the concrete mixture increased the 28 days compressive strength of concretes by 23.4% and 7.5%, respectively. The utilization of bacterial cells, nutrients, and culture in the concrete mixture provided the ability to heal wide cracks where the healing time was significantly reduced (about 8 days). On the other hand, separation of the bacterial culture medium slightly reduced the self-healing performance of the concretes.

Urease production using corn steep liquor as a low-cost nutrient source by Sporosarcina pasteurii: biocementation and process optimization via artificial intelligence approaches.

To commercialize the biocementation through microbial induced carbonate precipitation (MICP), the current study aimed at replacing the costly standard nutrient medium with corn steep liquor (CSL), an inexpensive bio-industrial by-product, on the production of urease enzyme by Sporosarcina pasteurii (PTC 1845). Multiple linear regression (MLR) in linear and quadratic forms, adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) were used for modeling of process based on the experimental data for improving the urease activity (UA). In these models, CSL concentration, urea concentration, nickel supplementation, and incubation time as independent variables and UA as target function were considered. The results of modeling showed that the GP model had the best performance to predict the extent of urease, compared to other ones. The GP model had higher R2 as well as lower RSME in comparison with the models derived from ANFIS and MLR. Under the optimum conditions optimized by GP method, the maximum UA value of 3.6 Mm min-1 was also obtained for 5%v/v CSL concentration, 4.5 g L-1 urea concentration, 0 µM nickel supplementation, and 60 h incubation time. A good agreement between the outputs of GP model for the optimal UA and experimental result was obtained. Finally, a series of laboratory experiments were undertaken to evaluate the influence of biological cementation on the strengthening behavior of treated soil. The maximum shear stress improvement between bio-treated and untreated samples was 292% under normal stress of 55.5 kN as a result of an increase in interparticle cohesion parameters.