Abstract

Influence of Bacillus Subtilis (B. Subtilis) bacteria on the strength characteristics of 100% recycled concrete aggregate (RCA), incorporating silica fume (SF) as a substitution of cement, has been investigated in this study. Two groups of mixes (A for w/c=0.3 and B for w/c=0.35) were prepared using two different cement contents in each (400 and 450 kg/m3). The cement was partially substituted by weight with 5%, 7.5%, and 10% SF, with a constant concentration of bacterial culture (105 cfu/ml). All specimens were tested after a curing period of 7, 28, and 90days. The best results were observed by replacing cement with 7.5% SF via all mixes, with the best mix being A/2. At 90 days, the compressive strength (CS) of concrete in mix A/2 increased from 29.62 to 33.64 MPa for 5% SF, from 29.62 to 37.3 MPa for 7.5% SF and from 29.62 to 34.04 MPa for 10% SF with the addition of B. Subtilis bacteria. Similarly, for splitting tensile strength (STS) at 90days, the strength increased from 2.73 to 3.24 MPa for 5% SF, from 2.73 to 3.35 MPa for 7.5% SF, from 2.73 to 3.26 MPa for 10% SF. Calcite precipitation upon addition of B. Subtilis bacteria is considered the reason for the improved CS and STS of concrete, and SEM and EDS analysis confirmed this. Thereby, the formation of new C-S-H products and CaCO3 crystals in voids made the concrete denser. Incorporation of B. subtilis led to a 12 ± 1.5% increase in CaCO3 formation in concrete’s mortar after 7days of curing compared to specimens without bacteria. Moreover, the effect of atomic Ca/Si and Al + Fe)/Ca ratios was studied, and the results showed that the highest CS and STS were associated with the values Ca/Si = 0.17 and Al + Fe)/C = 2.95. Meanwhile, it is noteworthy that according to the Indian specifications (IS-10262–2009), based on the strength of the concrete, the findings of this work fulfill the requirements of lean, ordinary grade, and standard grade concrete. An economic study of all mixes has also been carried out. Additionally, using response surface methodology, a regression equation was developed to accurately predict the CS and STS and validate the data in this experimental work with a minimum range of error.

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