THE CORRELATION OF MICROSTRUCTURE, AND MECHANICAL PROPERTIES OF NOVEL Fe3O4-(AuTe2) –REINFORCED ALUMINIUM MATRIX COMPOSITE PRODUCED VIA RECRYSTALLIZATION ROUTE
DOI:
https://doi.org/10.33003/fjs-2022-0606-1130Keywords:
Microstructure, solar thermal, corrosion behavior, hardness, recrystallizationAbstract
Aluminum Metal Matrix Composites (AMMC) have been becoming suitable materials for many devices in the application of various fields such as medical equipment, aircraft, electrical motors, overhead transmission lines, construction, etc. Aluminum was reinforced with the Fe3O4-(AuTe2) through the recrystallization process, hence, AMMC was successfully developed. The aim was to characterize the microstructure and phase patterns of the developed AMMC and compare it with conventional Aluminum as well as its thermos-mechanical characteristics. Physical, mechanical, and morphological properties of the composite and regular Al were examined. Based on the outcomes, the microstructural examination of the composite showed that the Al matrix had a sizable distribution of reinforcement components. Additionally shown was the creation of new phases, which significantly improved the strength and corrosion resistance of the composite. The influence of the reinforcement materials was found to have greatly enhanced the hardness tests. From 60 HRB for ordinary Al to 92.3 for AMMC, the hardness rose. Hence, after corrosion tests in an acidic solution (5% H2SO4 + H2O) hardness also increased from 41.1 HRB of the conventional Al to 52.8 HRB of the AMMC. Therefore, Corrosion resistance is improved by adding this reinforcement (Al- Fe3O4-(AuTe2) to the composite (lower corrosion rate). We then chose Al-5Fe3O4-10(AuTe2) as an optimal composite after comparing all the samples.
References
Ashish, K., and Gaurav, K., (2018). A mix design procedure of self-compacting, international research journal of engineering and technology, ISSN: 2395-0072, volume-5 issue-2, February.
Bashar, S.M. Sani, H. Mohamed, M. and Liew, M.S. (2019). Optimization and characterization of castin-situ alkali-activated pastes by response surface methodology. https://doi.org/10.1016/j.conbuildmat.2019.07.267.
British Standards Institution. B.S 1881, Part 116, (1985). Method for Determination of Compressive Strength of Concrete Cubes.
Busic, R.; Bensic, M.; Milicevi´c, I.; Strukar, K. (2020). Prediction models for the mechanical properties of self-compacting concrete with recycled rubber and silica fume. Materials 13, 1821.
Gao, Y. Xu, J. Luo, X. Zhu, J. and Nie, L. (2016). “Experiment research on mix design and early mechanical performance of alkali-activated slag using response surface methodology (RSM),” Ceram. Int., vol. 42, no. 10, pp. 11666–11673, doi: 10.1016/j.ceramint.2016.04.076.
Haruna, S.; Mohammed, B.; Wahab, M.; Haruna, A. (2020). Compressive Strength and Workability of High Calcium One-Part Alkali Activated Mortars Using Response Surface Methodology. In IOP Conference Series: Earth and Environmental Science; IOP Publishing: Bristol, UK, 2020.
Karim MR, Hossain MM, Elahi MMA, Zain MFM. (2020). Effects of source materials, fineness and curing methods on the strength development of alkali-activated binder. J Build Eng. 29:101147.
Kumator, J. T. Yusuf, D. A. Stephen, P. E., Adamu, L. (2023). Modelling the Permeation Properties of Self-compacting Concrete Incorporating Sporosarcina Pasteurii. Journal of Civil Engineering and Materials Application. doi: 10.22034/jcema.2023.406578.1113.
Mohammed, B.S.; Xian, L.W.; Haruna, S.; Liew, M.; Abdulkadir, I.; Zawawi, N.A.W.A. (2021). Deformation Properties of Rubberized Engineered Cementitious Composites Using Response Surface Methodology. Iran. J. Sci. Technol. Trans. Civ. Eng. 45, 729–740.
Murad, N.Y., Imam, R., Abu Hajar, H., Habeh, D., Hammad, A. and Shawash, Z. (2020), "Predictive compressive strength models for green concrete", International Journal of Structural Integrity. Vol. 11 No. 2, pp. 169-184. https://doi.org/10.1108/IJSI-05-2019-0044.
Nada, A., and Amar, Y.A., (2018). Effect of internal curing on the performance of self-compacting concrete by using sustainable material, matec web of conferences 162, doi.org/10.1051/matecconf/2018/6202017.
Ogork E. O, Uche O.A.U and Elinwa A., (2014). Strength Prediction Models of Groundnut Husk Ash (GHA) Concrete'‘, American Journal of Civil Structural Engineering, 1(4): p. 104-110.
Okorie, A.U., Sylvia, E. K., Musa, A., Yasser, E. I., Hani, A., & Imhade, P. O., (2022). Modelling and Optimizing the Durability Performance of Self-Consolidating Concrete Incorporating Crumb Rubber and Calcium Carbide Residue Using Response Surface Methodology. https://doi.org/10.3390/ buildings12040398.
Shaikh, A.S., Lahare, P.S., Nagpure, V.B., Ghorpde, S.S., (2017). Curing of Concrete. International Research Journal of Engineering and Technology, Volume: 04 Issue: 03
Sunday, I. (2022). A Developed Predictive Model for Simulating the Effects of Ferrous Ion on the Compressive Strength of Oil Well Integrated Cement Sheath Systems, Using Box–Behnken Design of Experiments. International Journal of Innovative Scientific & Engineering Technologies Research 10(1):9-34.
Tufail, S., Riggs, H., Tariq, M., Sarwat, A.I., (2023). “Advancements and Challenges in Machine Learning: A Comprehensive Review of Models, Libraries, Applications, and Algorithms”, Electronics, v.12, n. 8, pp. 1789. doi: https://doi.org/10.3390/electronics12081789.
James, T., Malachi, A., E.W. Gadzama, V. Anametemfiok. (2011). Effect of Curing Methods on Compressive Strength of Concrete.Nigerian Journal of Technology Vol. 30, No. 3.
Vivian, W.Y. T., Anthony, B., Khoa, N. L., Luis, C.F. D., Ana, C.J. E. (2022). A prediction model for compressive strength of CO2 concrete using regression analysis and artificial neural networks, Construction and Building Materials Volume 324, https://doi.org/10.1016/j.conbuildmat.2022.126689
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