Experimental Investigations and Prediction of Thermal Behaviour of Ferrosialate-Based Geopolymer Mortars


This paper studies the thermal behaviour of ferrosialate geopolymer mortars. This is done by monitoring various factors influencing the strength gain/loss, weight loss, enthalpy changes, physical and chemical transformations in the ferrosialate geopolymer structure using TG/DT analysis. This study proposed a novel predictive equation for estimating this parameter with the help of gene expression programming (GEP). Fly ash is used as a raw feed for sialate geopolymer, and red mud along with fly ash is used for ferrosialate geopolymer. Till 200 °C, oven-cured samples showed maximum strength results. Whereas in later stages, i.e. after exposure to 400 °C, ambient cured samples surpassed the former by 4.14%. Development of broad amorphous hump in the XRD patterns, presence of thicker geopolymer structure in the SEM images for 400 °C samples, an exothermic peak in the DTA curves at 400 °C and increment in the compressive strength up to 400 °C exposure, all pointing to a conclusion that elevated temperature-favoured ferrosialate geopolymer formation till 400 °C. After exposure to 800 °C, maximum strength loss of 68.57% and 30.3% is observed for sialate and ferrosialate samples dehydroxylation, recrystallization, and melting of unreacted particles are the reasons for diminishing the strength at elevated temperatures. An equation using GEP model (r2 = 0.913) having nine genes is proposed that can predict the residual compressive strength of ferrosialate geopolymer mortars. Though this model is for ferrosialate geopolymer, a similar technique can be easily adapted to other types of geopolymers.

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Thermogravimetric analysis


Differential thermal analysis


28-day ambient curing


72-h oven curing


Gene expression programming


Scanning electron microscope


X-ray diffraction










Red mud


Indian standards


Molarity of NaOH solution


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Authors would like to thank School of Bioscience and Engineering, VIT Vellore for giving access to SEM facility. Authors would also like to thank Hindalco, Belgaum for providing red mud.

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Correspondence to S. Karthiyaini.

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Appendix 1

See Table 6.

Table 6 Functions used in the programming

Appendix 2

See Table 7.

Table 7 Values of constants in expression trees

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Yeddula, B.S.R., Karthiyaini, S. Experimental Investigations and Prediction of Thermal Behaviour of Ferrosialate-Based Geopolymer Mortars. Arab J Sci Eng (2020).

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  • Ferrosialate
  • Prediction
  • Geopolymer
  • Red mud
  • Thermal behaviour
  • TGA