Influence of Na2SiO3/NaOH Ratio on Calcined Magnesium Silicate Based Geopolymer—Experimental and Predictive Study

R. Premkumar , Babu Chokkalingam Ramesh , P. L. Meyyappan , M. Shanmugasundaram

Journal of Wuhan University of Technology Materials Science Edition ›› 2023, Vol. 38 ›› Issue (5) : 1077 -1085.

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Journal of Wuhan University of Technology Materials Science Edition ›› 2023, Vol. 38 ›› Issue (5) : 1077 -1085. DOI: 10.1007/s11595-023-2796-z
Cementitious Materials

Influence of Na2SiO3/NaOH Ratio on Calcined Magnesium Silicate Based Geopolymer—Experimental and Predictive Study

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Abstract

This study aims to investigate the behavior of alkali activated mortar, which is made of naturally available magnesium silicate as source material. For magnesium silicate, ultrafine natural steatite powder (UFNSP) is used as the primary source of binder, and the activation is initiated through the alkali liquid which is proportioned in various combinations of silicate to hydroxide ratio (Na2SiO3/NaOH) ratio, and this ratio in this study varies from 1 to 3. The UFNSP is calcined at two different temperatures, 700 and 1 000 °C. The mortar mix is proportioned as 1:3 between powder and the fine aggregate, and the mortar is prepared with hydroxide molarity (M) of 10 M. The mortar is cured for 48 hours at 60 °C and the compressive strength was studied. All the mix were studied for its microstructural behavior along with compressive strength. The mix proportion of the mortar, and the results obtained through microstructural characterization were combinedly formed as input for artificial neural network(ANN) predictive modelling. The model is designed to predict the compressive strength, which is trained through Bayesian regularization algorithm with varying hidden neurons of 7 to 10. This experimental and predictive study shows that the strength is influenced by both Na2SiO3/NaOH ratio and calcination process. And the ANN is influenced by mainly calcination temperature and uncorrelation occurs in selected samples of 1 000 °C calcined UFNSP mix.

Keywords

magnesium silicate / silicate / alkali activation / geopolymer / UFNSP / prediction

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R. Premkumar, Babu Chokkalingam Ramesh, P. L. Meyyappan, M. Shanmugasundaram. Influence of Na2SiO3/NaOH Ratio on Calcined Magnesium Silicate Based Geopolymer—Experimental and Predictive Study. Journal of Wuhan University of Technology Materials Science Edition, 2023, 38(5): 1077-1085 DOI:10.1007/s11595-023-2796-z

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References

[1]

Komnitsas K, Zaharaki D. Geopolymerisation: A Review and Prospects for the Minerals Industry[J]. Miner. Eng., 2007, 20: 1261-1277.

[2]

Kinnunen P, Ismailov A, Solismaa S, et al. Recycling Mine Tailings in Chemically Bonded Ceramics - A Review[J]. J. Clean Prod., 2018, 174: 634-649.

[3]

Davidovits J. Geopolymers[J]. J. Theral. Analy., 1991, 37(8): 1 633

[4]

Duxson P, Fernández-Jiménez A, Provis JL, et al. Geopolymer Technology: The Current State of the Art[J]. J. Mater. Sci., 2006, 42(9): 2917-2933.

[5]

Yip CK, Lukey GC, Provis JL, et al. Effect of Calcium Silicate Sources on Geopolymerisation[J]. Cem. Con. Res., 2008, 38(4): 554-564.

[6]

Xu H, Van Deventer JSJ. The Geopolymerisation of Alumino-Silicate Minerals[J]. Inter. J. Min. Proc., 2000, 59: 247-266.

[7]

Hemalatha T, Ramaswamy A. A Review on Fly ash Characteristics–Towards Promoting High Volume Utilization in Developing Sustainable Concrete[J]. J. Clea. Prod., 2017, 147: 546-559.

[8]

Novais RM, Carvalheiras J, Seabra MP, et al. Effective Mechanical Reinforcement of Inorganic Polymers using Glass Fibre Waste[J]. J. Clea. Prod., 2017, 166: 343-349.

[9]

Nguyen KT, Nguyen QD, Le TA, et al. Analyzing the Compressive Strength of Green Fly Ash Based Geopolymer Concrete using Experiment and Machine Learning Approaches[J]. Constr. Build. Mater., 2020, 247: 1-11.

[10]

Tzanakos K, Mimilidou A, Anastasiadou K, et al. Solidification/Stabilization of Ash from Medical Waste Incineration into Geopolymers[J]. Waste Manag., 2014, 34: 1823-1828.

[11]

Sudalaimani K, Shanmugasundaram M. Influence of Ultrafine Natural Steatite Powder on Setting Time and Strength Development of Cement[J]. Adv. Mater. Sci. Eng., 2014: 1–8

[12]

Kumar P, Sudalaimani K, Shanmugasundaram M. An Investigation on Self-Compacting Concrete using Ultrafine Natural Steatite Powder as Replacement to Cement[J]. Adv. Mater. Sci. Eng., 2017: 1–8

[13]

Shanmugasundaram M, Sudalaimani K. An Investigation on High Performance Concrete with Ultra Fine Natural Steatite Powder[J]. Int. J. Info. (Japan)., 2014, 17(6): 2267-2277.

[14]

Shanmugasundaram M, Karthiyaini S, Sudalaimani K. Influence of Ultrafine Natural Steatite Powder on Strength and Permeability of High Performance Concrete[J]. Inter. J. App. Eng. Res., 2015, 10(18): 38967-38971.

[15]

Premkumar R, Ramesh BC, Athira VS, et al. Influence of Ultra-fine Steatite Powder on the Properties of Alkali-activated Concrete[J]. Proc. Inst. Civ. Eng. - Eng. Sus., 2023, 176(1): 17-27.

[16]

Cota FP, Alves RAA, Panzera TH, et al. Physical Properties and Microstructure of Ceramic-Polymer Composites for Restoration Works[J]. Mater. Sci. Eng. A, 2012, 531: 28-34.

[17]

Panzera THTH, Strecker K, Miranda J d S, et al. Cement - Steatite Composites Reinforced with Carbon Fibres: An Alternative for Restoration of Brazilian Historical Buildings[J]. Mater. Res., 2011, 14(1): 118-123.

[18]

Sugila Devi G, Sudalaimani K. Investigation on Calcined Magnesium-Based Mineral Powder and Its Behavior as Alternative Binder[J]. Adv. Mater. Sci. Eng., 2020: 1–7

[19]

Karthiyaini S, Rohan Kumar G, Shanmugasundaram M. Solidification of Bio-medical Waste Incinerated Bottom ash along with Steatite Powder as Sustainable Geopolymer[J]. Eco. Env. Conser., 2019, 25(1): 443-449.

[20]

Gaddam R, Shanmuga S. An Investigation on Mechanical Strength of Alkali Activated Ultra Fine Natural Steatite Powder based Geopolymer Mortar[J]. Technol. SK-Int. J. Civ. Eng., 2018, 9(2): 516-521.

[21]

Liu Y, Chen B. Research on The Preparation and Properties of a Novel Grouting Material based on Magnesium Phosphate Cement[J]. Constr. Build. Mater., 2019, 214: 516-526.

[22]

Xu X, Lin X, Pan X, et al. Influence of Silica Fume on the Setting Time and Mechanical Properties of a New Magnesium Phosphate Cement[J]. Constr. Build. Mater., 2020, 235: 117 544.

[23]

Terzić A, Obradović N, Stojanović J, et al. Influence of Different Bonding and Fluxing Agents on the Sintering Behavior and Dielectric Properties of Steatite Ceramic Materials[J]. Ceramics Inter., 2017, 43(16): 13264-13275.

[24]

Mielcarek W, Nowak-Woźny D, Prociów K. Correlation between MgSiO3 Phases and Mechanical Durability of Steatite Ceramics[J]. J. Euro. Ceramic Soc., 2004, 24(15–16): 3817-3821.

[25]

Zajac M, Durdzinski P, Stabler C, et al. Influence of Calcium and Magnesium Carbonates on Hydration Kinetics, Hydrate Assemblage and Microstructural Development of Metakaolin Containing Composite Cements[J]. Cem. Con. Res., 2018, 106: 91-102.

[26]

Liu Y, Chen B, Qin Z, et al. Experimental Research on Properties and Microstructures of Magnesium-Iron Phosphate Cement[J]. Constr. Build. Mater, 2020, 257(9): 1-13.

[27]

Karthiyaini S, Senthamaraikannan K, Priyadarshini J, et al. Prediction of Mechanical Strength of Fiber Admixed Concrete using Multiple Regression Analysis and Artificial Neural Network[J]. Adv. Mater. Sci. Eng., 2019: 1–7

[28]

Akkurt S, Ozdemir S, Tayfur G, et al. The use of GA-ANNs in the Modelling of Compressive Strength of Cement Mortar[J]. Cem. Con. Res., 2003, 33: 973-979.

[29]

Yuan Z, Wang LN, Ji X. Prediction of Concrete Compressive Strength: Research on Hybrid Models Genetic Based Algorithms and ANFIS[J]. Adv. Eng. Soft., 2014, 67: 156-163.

[30]

Siddique R, Aggarwal P, Aggarwal Y. Prediction of Compressive Strength of Self-Compacting Concrete Containing Bottom Ash Using Artificial Neural Networks[J]. Adv. Eng. Soft., 2011, 42(10): 780-786.

[31]

Suprakash AS, Karthiyaini S, Shanmugasundaram M. Future and Scope for Development of Calcium and Silica Rich Supplementary Blends on Properties of Self-Compacting Concrete[J]. J. Mater. Res. Tech., 2021, 15: 5662-5681.

[32]

Suprakash AS, Karthiyaini S. A Study on the Effect of Low Calcium Ultra-Fine Fly Ash as a Partial Sustainable Supplementary Material to Cement in Self-compacting Concrete[J]. J. Wuhan Univ. Technol.-Mat. Sci. Edit., 2023, 38: 330-341.

[33]

Sudalaimani K, Shanmugasundaram M. Influence of Ultrafine Natural Steatite Powder on Setting Time and Strength Development of Cement[J]. Adv. Mater. Sci. Eng., 2014: 1–4

[34]

Yeddula BSR, Karthiyaini S. Experimental Investigations and GEP Modelling of Compressive Strength of Ferrosialate based Geopolymer Mortars[J]. Constr. Build. Mater., 2020, 236: 1-15.

[35]

Mo BH, Zhu H, Cui XM, et al. Effect of Curing Temperature on Geopolymerization of Metakaolin-based Geopolymers[J]. Appl. Clay. Sci., 2014, 99: 144-148.

[36]

Luukkonen T, Abdollahnejad Z, Yliniemi J, et al. Alkali-Activated Soapstone Waste - Mechanical Properties, Durability, and Economic Prospects[J]. Sustain. Mater. Tech., 2019, 22: 1-8.

[37]

Khan MZN, Hao Y, Hao H, et al. Mechanical Properties of Ambient Cured High Strength Hybrid Steel and Synthetic Fibers Reinforced Geopolymer Composites[J]. Cem. Con. Comp., 2018, 85: 133-152.

[38]

Zhao J, Wang D, Wang X, et al. Ultrafine Grinding of Fly Ash with Grinding Aids: Impact on Particle Characteristics of Ultrafine Fly Ash and Properties of Blended Cement Containing Ultrafine Fly Ash[J]. Constr. Build. Mater., 2015, 78: 250-259.

[39]

Karthiyaini S. Physicochemical Properties of Alkali Activated Fly Ash Based Geopolymer Concrete: A Review[J]. Int. J. Earth Sci. Eng., 2016, 9(6): 2419-2426.

[40]

Yeddula BSR, Karthiyaini S. Experimental Investigations and Prediction of Thermal Behaviour of Ferrosialate-Based Geopolymer Mortars[J]. Arabian J. Sci. Eng., 2020, 45: 3937-3958.

[41]

Chang W, Zheng W. Estimation of Compressive Strength of Stirrup-Confined Circular Columns Using Artificial Neural Networks[J]. Struc. Con., 2019, 20(9): 1328-1339.

[42]

Deshpande N, Londhe S, Kulkarni S. Modeling Compressive Strength of Recycled Aggregate Concrete by Artificial Neural Network, Model Tree and Non-Linear Regression[J]. Inter. J. Sust. Built. Env., 2014, 3: 187-198.

[43]

Naderpour H, Rafiean AH, Fakharian P. Compressive Strength Prediction of Environmentally Friendly Concrete using Artificial Neural Networks[J]. J. Build. Eng., 2018, 16: 213-219.

[44]

Suprakash AS, Karthiyaini S, Shanmugasundaram M. A Study on Compressive Strength of Ultrafine Graded Fly Ash Replaced Concrete and Machine Learning Approaches in Its Strength Prediction[J]. Struc. Con., 2022, 23(6): 3849-3863.

[45]

Chithra S, Kumar SRRS, Chinnaraju K, et al. A Comparative Study on the Compressive Strength Prediction Models for High Performance Concrete Containing Nano Silica and Copper Slag using Regression Analysis and Artificial Neural Networks[J]. Constr. Build. Mater., 2016, 114: 528-535.

[46]

Priyadarshini J, Karthiyaini S, Suprakash AS, et al. A Deep Learning-Image based Approach for Detecting Cracks in Buildings[J]. Trait. Signal., 2022, 39(4): 1429-1434.

[47]

Zain MFM, Abd SM. Multiple Regression Model for Compressive Strength Prediction of High Performance Concrete[J]. J. Appl. Sci., 2009, 9: 155-160.

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