Contents lists available at ScienceDirect Materials Science & Engineering A journal homepage: www.elsevier.com/locate/msea Three-dimensional processing maps and microstructural evolution of a CNT- reinforced Al-Cu-Mg nanocomposite F. Mokdad a , D.L. Chen a, ⁎ , Z.Y. Liu b , D.R. Ni b , B.L. Xiao b , Z.Y. Ma b, ⁎ a Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, Canada M5B 2K3 b Shenyang National Laboratory for Materials Science, Institute of Metal Research, Chinese Academy of Sciences, 72 Wenhua Road, Shenyang 110016, China ARTICLE INFO Keywords: Carbon nanotube Aluminum matrix nanocomposite Efficiency Instability Dynamic recrystallization ABSTRACT The determination of the optimum processing window of a material at elevated temperatures is essential for metal forming. Such an “ideal” processing window could be characterized by the workability parameters of power dissipation efficiency, Ziegler's instability criteria, and the presence of favorable microstructures. The purpose of the present study is to develop three-dimensional (3D) processing maps of a 2.0 wt% carbon nanotube (CNT) reinforced 2024Al nanocomposite and to manifest continuous changes of power dissipation efficiency and flow instability domains involving key processing parameters of temperature, strain rate, and strain via iso- thermal compressive tests. The optimal hot working parameters of the 2024Al base alloy and the 2.0 wt% CNT/ 2024Al nanocomposite were identified to be at higher temperatures and lower strain rates, with a moderately smaller processing window for the nanocomposite due to the strengthening effect of CNTs and microstructural complexities. Instability occurred at higher strain rates and lower temperatures for both base alloy and nano- composite. In the stable domain dynamic recrystallization was observed to occur, and the fraction of re- crystallized grains increased with increasing deformation temperature, along with the presence of more random textures. 1. Introduction Carbon nanostructures, such as carbon nanotubes (CNTs), have been considered as effective reinforcements for metal matrix compo- sites (MMCs) and have been the center of interest for several studies in the literature [1–4]. In addition to their lightweighting attribute, CNTs possess remarkable properties including ultra-high specific strength and stiffness [5–8]. To manufacture high-performance CNT-reinforced alu- minum matrix composites (AMCs), it is necessary to establish a proper processing window via constructing material processing maps and identifying desirable microstructures. Some previous studies focused on the hot deformation behavior of lightweight alloys to control their forming process and obtain desired microstructures and mechanical properties. For instance, Gao et al. [9] studied the hot deformation behavior of a TA15 titanium alloy and observed the microstructural changes, where continuous dynamic recrystallization (CDRX) occurred. Similarly, Wang et al. [10] studied the main softening mechanisms of a 6061Al/B 4 C composite via hot compression testing, and also observed the happening of dynamic recrystallization (DRX). Processing maps are of special importance since they represent a powerful tool for identifying the optimal processing parameters during manufacturing of materials at elevated temperatures. The design of new alloys relies heavily on hot working, and the relevant microstructural features are strongly influenced by thermo-mechanical processing parameters such as temperature, strain rate and strain during hot de- formation [11,12]. Hence, through the development of processing maps, prevalent deformation mechanisms and microstructural features could be determined in different conditions. In this context, constitutive equations and processing maps were developed and presented in the literature for various alloys and composites such as Mg alloys [13–15], Al alloys [11,16–20], Cu alloys [21], high entropy alloys (HEAs) [12], Ni-based superalloys [22], Al6063/0.75Al 2 O 3 /0.75Y 2 O 3 nanocompo- site [23], 20 vol% S i C P /2024Al nanocomposite [24], and B 4 C particu- late-reinforced Al composite [18]. In addition to the conventional two- dimensional (2D) processing maps, some attempts were also made at a three-dimensional (3D) analysis of the safe (i.e., stable) processing window [17,25,26]. The advantage of 3D processing maps relative to the conventional 2D processing maps lies in the possibility of visualizing the “con- tinuous” changes of power dissipation with respect to the processing parameters at the same time, rather than having to look at each pro- cessing map separately which might lead to a “discontinuity” in the http://dx.doi.org/10.1016/j.msea.2017.07.028 Received 7 April 2017; Received in revised form 3 July 2017; Accepted 12 July 2017 ⁎ Corresponding authors. E-mail addresses: dchen@ryerson.ca (D.L. Chen), zyma@imr.ac.cn (Z.Y. Ma). Materials Science & Engineering A 702 (2017) 425–437 Available online 13 July 2017 0921-5093/ © 2017 Elsevier B.V. All rights reserved.