@article{scholars14655,
           pages = {2209--2224},
         journal = {Journal of Thermal Analysis and Calorimetry},
       publisher = {Springer Science and Business Media B.V.},
            year = {2021},
           title = {Artificial intelligence model and correlation for characterization and viscosity measurements of mono \& hybrid nanofluids concerned graphene oxide/silica},
             doi = {10.1007/s10973-021-10687-5},
            note = {cited By 0},
          volume = {145},
          number = {4},
          author = {Ahmad, M. N. and Mahmood, A. K. and Hashim, K. F. and Mustakim, F. B. and Selamat, A. and Bajuri, M. Y. and Arshad, N. I.},
            issn = {13886150},
        abstract = {Graphene oxide/silica composite{\^a}??s rheological behavior was studied in this investigation. This composite was made to reduce the cost of industrial usages. The volume fractions investigated from 0.1 to 1.0 (GO 30{\^a}??SiO2 70), the shear rates investigated from 12.23 to 122.3{\^A} s{\^a}??1, and the temperatures investigated from 25 to 50{\^A} {\^A}oC. To study the characterization of each solid and the composite, the XRD and the FESEM tests were done. The results of the viscosity investigation revealed the non-Newtonian behavior. After that, a numerical study was done to present a correlation and train an artificial neural network model. These numerical studies were done for both 12.23 and 122.3{\^A} s{\^a}??1 shear rates. The novel equation tolerances were 1.932 and 1.338 for 12.23 and 122.3{\^A} s{\^a}??1 shear rates, while for the artificial neural network model, the tolerances were 1.46196 and 1.25386 for 12.23 and 122.3{\^A} s{\^a}??1 shear rates. This means, after the model was trained, the deviation decreased around {\^a}??0.46999 and {\^a}??0.08467 for 12.23 and 122.3{\^A} s{\^a}??1 shear rates. This nanofluid can be employed in industrial systems. {\^A}{\copyright} 2021, Akad{\~A}{\copyright}miai Kiad{\~A}3, Budapest, Hungary.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103359687&doi=10.1007\%2fs10973-021-10687-5&partnerID=40&md5=17fb7e95ca1161c71b8eacbb6ca72b8c},
        keywords = {Fits and tolerances; Graphene; Non Newtonian flow; Shear deformation; Silica; Viscosity; Viscosity measurement, Artificial neural network modeling; Industrial systems; Nanofluids; Non-Newtonian behaviors; Novel equation; Rheological behaviors, Neural networks}
}