Self-ignited synthesis of nanocomposite powders induced by Spex mills; modeling and optimizing. Issue 2 (March 2015)

• Record Type: Journal Article
• Authors: Ebrahimi-Kahrizsangi, Reza; Abdellahi, Majid; Bahmanpour, Maryam
• Is Part Of: Ceramics international. Volume 41:Issue 2(2015)Part B
• Page Start: 3137
• Page End: 3151
• Publication Date: 2015-03
• Subjects: A. Milling -- Spex mills -- Ignition time -- Nanocomposites; Ceramics -- Periodicals; Céramique industrielle -- Périodiques; Ceramics; Periodicals; Electronic journals; 666
• DOI: 10.1016/j.ceramint.2014.10.158
• Languages: English
• ISSNs: 0272-8842

Abstract

Abstract: Spex mills are among the most important tools for synthesizing nanocomposite powders. However, review of the literature reveals that due to their complex geometry, an accurate simulation of these tools has not been accomplished yet. The SPEX mills are considered to be of higher energy than the other mills; hence they have an obvious potential to produce combustion reactions and consequently rapid synthesis of nanocomposites. In the present work, a novel modeling is performed on the Spex mills and the self-ignited reactions are simulated. The proposed modelling correlates the milling parameters with the ignition time using a mathematical formula. The mathematical formula ensures that if the milling parameters are known, the ignition time in combustion reactions is predictable. An optimization process is then conducted to optimize the milling and reaction parameters in order to minimize the ignition time predicted by the mathematical formula. The results show that the combination of modeling and optimization processes leads to the prediction and minimization of ignition time, which in turn brings about significant benefits including saving the energy and time consumed as well as reducing the costs of producing nanocomposite powders. At the end, a few case studies were performed for evaluating the results obtained by the modeling and optimizing algorithms. The result showed a good agreement between the experimental data and the simulated ones.