Optimization of process parameters to maximize hardness of metal/ceramic nanocomposites produced by high energy ball milling
Source abstract
Abstract
Abstract In our previous work [Abdellahi, J. Mater. Res. 28 (2013) 3270], a novel method was used to predict the hardness of Aluminum matrix nano-composites synthesized by high energy ball milling. In the mentioned work, however, systems under study were very limited, the squared regression of training and testing sets was not significant and optimizing was not performed on the milling parameters so that we finally had not an optimal system with a maximum value of hardness. In this work, for the first time, all mentioned shortcomings were addressed and resolved and as a new work the process parameters, namely, amount of reinforcement, amount of process control agent, type of mill, type of vial, type of ball, vial spinning rate, ball to powder weight ratio, type of process control agent, type of atmosphere, milling time, sintering time, sintering temperature and compact pressure were optimized to maximize the hardness of metal/ceramic nanocomposites produced by high energy ball milling. To evaluate the efficiency of the proposed optimization, a system based on the optimized parameters was established (system 2) and the obtained results were compared with those in system that was established based on the parameters used by Akbarpour et al. (system 1). The results showed two things: first, the use of system 2 brings a maximum value of hardness for the produced nanocomposites and second, the optimized system is really consistent with what actually happens in practice.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Aluminum Alloys Composites Properties · Advanced ceramic materials synthesis · Advanced materials and composites
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (42)
Show source-provided references
1. Rapid synthesis of MoSi2–Si3N4 nanocomposite via reaction milling of Si and Mo powder mixture10.1007/s12613-013-0841-1 ↗
2. Events and reaction mechanisms during synthesis of Al2O3–TiB2 nanocomposite via high energy ball milling10.1007/s11705-013-1325-6 ↗
3. Influence of B source materials on the synthesis of TiB2–Al2O3 nanocomposite powders by mechanical alloying10.1007/s12613-013-0857-6 ↗
4. Corrosion of aluminum and its alloys
5. Gene expression programming: a new adaptive algorithm for solving problems
6. The best conditions for minimizing the synthesis time of nanocomposites during high energy ball milling10.1016/j.ceramint.2014.02.049 ↗
7. M. Abdellahi, J. Heidari, M. Bahmanpour, A new predictive model to the bond strength of FRP-to-concrete composite joints, Struct. Concr. 10.1002/suco.201300093, in press.10.1002/suco.201300093 ↗
8. A new predictive model for calculating the hardness of metal matrix nanocomposites produced by mechanical alloying10.1557/jmr.2013.326 ↗
9. M. Abdellahi, M. Bahmanpour, M. Bahmanpour, Laminating; the best way to improve Charpy impact energy of nanocomposites, Ceram. Int. 10.1016/j.ceramint.2014.07.041, in press10.1016/j.ceramint.2014.07.041 ↗
10. Artificial bee colony algorithm solution for optimal reactive power flow10.1016/j.asoc.2012.01.006 ↗
11. On the performance of artificial bee colony (ABC) algorithm10.1016/j.asoc.2007.05.007 ↗
12. The use of artificial bee colony algorithm to speed up the nanopowders synthesis during high energy ball milling10.1016/j.powtec.2014.05.014 ↗
13. Technology for minimizing the synthesis time of nanostructured powders in planetary mills10.1590/S1516-14392014005000023 ↗
14. Minimizing the synthesis time of nanostructured powders in planetary mills using biogeography-based optimization (BBO) algorithm
15. Properties of mechanically milled and spark plasma sintered Al–AlB2 and Al–MgB2 nano-composite materials10.1016/j.msea.2007.02.130 ↗
16. Nanocomposites and an extremely hard nanocrystalline intermetallic of Al–Fe alloys prepared by mechanical alloying10.1016/j.msea.2009.12.044 ↗
17. Evolutions during synthesis of Al–AlN-nanostructured composite powder by mechanical alloying10.1016/j.jallcom.2007.07.054 ↗
18. Sintering behavior of Al–AlN-nanostructured composite powder synthesized by highenergy ball milling10.1016/j.jallcom.2008.05.069 ↗
19. Al–(L12)Al3Ti nanocomposites prepared by mechanical alloying: synthesis and mechanical properties10.1016/j.jallcom.2009.10.274 ↗
20. Production and characterization of in situ Al4C3reinforced aluminum-based composite produced by mechanical alloying technique10.1016/S0261-3069(03)00163-8 ↗
21. Effect of carbon nanotube (CNT) content on the mechanical properties of CNT-reinforced aluminum composites10.1016/j.compscitech.2010.05.004 ↗
22. Synthesis of Al3BC from mechanically milled and spark plasma sintered Al–MgB2composite materials10.1016/j.jallcom.2007.03.027 ↗
23. Novel Al-matrix nanocomposites reinforced with muffflti-walled carbon nanotubes10.1016/j.jallcom.2006.10.146 ↗
24. Mechanical solid state mixing for synthesizing of SiCp/Al nanocomposites10.1016/S0925-8388(98)00658-6 ↗
25. Investigation of planetary milling for nano-silicon carbide reinforced aluminium metal matrix composites10.1016/j.jallcom.2009.09.128 ↗
26. Synthesis, structure, and sinterability of 6061 AA100x–xwt.% TiO2 composites prepared by high-energy ball milling10.1016/j.jallcom.2009.11.051 ↗
27. Effect of strengthening mechanisms on cold workability and instantaneous strain hardening behavior during grain refinement of AA 6061–10wt% TiO2 composite prepared by mechanical alloying10.1016/j.jallcom.2010.07.168 ↗
28. Sintering of copper–alumina composites through blending and mechanical alloying powder metallurgy routes10.1016/0261-3069(95)00006-K ↗
29. Effects of copper and Al2O3particles on characteristics of Cu–Al2O3composites10.1016/j.matdes.2009.10.037 ↗
30. Hardening in copper-based nanocomposites
31. Effects of milling time on hardness and electrical conductivity of in situ Cu–NbC composite produced by mechanical alloying10.1016/j.jallcom.2008.09.018 ↗
32. Microstructure and properties of copper composite containing in situ NbC reinforcement: effects of milling speed10.1016/j.jallcom.2009.09.083 ↗
33. Production of copper–niobium carbide nanocomposite powders via mechanical alloying10.1016/j.msea.2005.03.090 ↗
34. Effect of specimen size and shape on compressive strength of concrete containing fly ash: Application of genetic programming for design10.1016/j.matdes.2013.10.073 ↗
35. Prediction of shear strength of FRP-reinforced concrete beams without stirrups based on genetic programming10.1016/j.advengsoft.2011.02.002 ↗
36. survey of application: genomics and genetic programming, a new frontier10.1016/j.ygeno.2012.05.014 ↗
37. Empirical modeling of splitting tensile strength from cylinder compressive strength of concrete by genetic programming
38. Application of artificial bee colony-based optimization for fault section estimation in power systems10.1016/j.ijepes.2012.07.012 ↗
39. A modified Artificial Bee Colony algorithm for real-parameter optimization10.1016/j.ins.2010.07.015 ↗
40. Collective decision-making in honey bee foraging dynamics
41. Parametric optimization of some non-traditional machining processes using artificial bee colony algorithm10.1016/j.engappai.2011.03.009 ↗
42. Microstructure and compressibility of SiC nanoparticles reinforced Cu nanocomposite powders processed by high energy mechanical milling10.1016/j.ceramint.2013.06.091 ↗