Optimization of bio-cement production from cement kiln dust using microalgae

Abstract

The main aim of this study was to maximize bio-cement (CaCO₃) production through a waste feedstock of cement kiln dust (CKD) as a source of calcium by deployment of microalgae sp. Chlorella kessleri. The effect of process parameters such as temperature, pH and time-intervals of microalgae cultivation, were set as criteria that ultimately subscribe to a process of optimization. In this regard, a single factor experiments integrated with response surface methodology (RSM) via central composite design (CCD) was considered. A quadratic model was developed to predict the maximum CaCO₃ yield. A ceiling of 25.18 g CaCO₃ yield was obtained at an optimal set of 23 °C, pH of 10.63 and day-9 of microalgae culture. Under these optimized conditions, maximum 96% calcium was extracted from CKD. FTIR, XRD and EDS analyses were conducted to characterize the CaCO₃ precipitates. Compressive modes of mechanical testing seemed to hold conventional cement complimented by CaCO₃ co-presence markedly superior to mere cement performance as far as compressive strength is concerned. The latter criterion exhibited further increase in correspondence with rise in cement to bio-cement ratio. This investigative endeavour at hand offers a simple pivotal platform on the basis of which a scale-up of microalgae-infested bio-cement production might be facilitated in conjunction with the added benefit of alleviation in environmental pollution through cement waste utilization.

Keywords: Bio-cement; CaCO3 precipitation; Microalgae; Optimization; Waste management.

Graphical abstract

Fig. 1

Schematic diagram of the experimental setup used to: a) cultivate Chlorella kessleri and b) produce bio-cement.

Fig. 2

The CaCO₃ precipitation with different temperature, pH and microalgae growth period. The initial pH for reaction mixture is (a) 7, (b) 9 and (c) 10, respectively.

Fig. 3

Parity plot for bio-cement production.

Fig. 4

Main effect (a) and interaction (b) plots for bio-cement yield.

Fig. 5

Response optimizer plot for bio-cement yield. Here, d and D are individual and overall desirability functions of the response, respectively (ideal value of d or D = 1). Hi, Lo and Cur are high, low and current factors level (coded values) settings, respectively.

Fig. 6

FTIR analysis of produced precipitates.

Fig. 7

XRD pattern of (a) CKD sample (b) precipitate produced using microalgae.

Fig. 8

EDX pattern of precipitate produced using microalgae.