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High-strength aluminum alloys are important for lightweighting vehicles and are extensively used in aircraft and, increasingly, in automobiles. The highest-strength aluminum alloys require a series of high-temperature “bakes” (120° to 200°C) to form a high number density of nanoparticles by solid-state precipitation. We found that a controlled, room-temperature cyclic deformation is sufficient to continuously inject vacancies into the material and to mediate the dynamic precipitation of a very fine (1- to 2-nanometer) distribution of solute clusters. This results in better material strength and elongation properties relative to traditional thermal treatments, despite a much shorter processing time. The microstructures formed are much more uniform than those characteristic of traditional thermal treatments and do not exhibit precipitate-free zones. These alloys are therefore likely to be more resistant to damage.

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A lightweight (5.06 g.cm-3) AlTiVCr compositionally complex alloy consisting of four elements is presented. Interest in the system is due to its microstructural uniformity and the use of commodity elements. The focus of the present work was to highlight the systematic microstructural and chemical characterizationand the information gained by application of various physical and modeling techniques in concertin the context of complete characterization of compositionally complex alloys. Herein, analysis of as-cast AlTiVCr was investigated via conventional and scanning transmission electron microscopy, revealing a simple, single-phase microstructure. Characterization was supported by atom probe tomography and X-ray diffraction, whilst first-principles calculations based on density functional theory (DFT) were employed to calculate the thermodynamic and structural properties of the AlTiVCr alloy. The study was able to reveal the unique atomic locations in the alloy, whilst revealing that the B2 phase has a lower formation enthalpy (-9.30 kJ/mol atom) and is more stable than the disordered BCC phase (-1.25 kJ/mol atom) at low temperatures. The study herein provides insight into the combined analysis methods as relevant to the study of compositionally complex and high entropy alloys, indicating means of unambiguous characterization employing generalized multicomponent short range order analysis.

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Atom probe tomography (APT) represents a significant step toward atomic resolution microscopy, analytically imaging individual atoms with highly accurate, though imperfect, chemical identity and three-dimensional (3D) positional information. Here, a technique to retrieve crystallographic information from raw APT data and restore the lattice-specific atomic configuration of the original specimen is presented. This lattice rectification technique has been applied to a pure metal, W, and then to the analysis of a multicomponent Al alloy. Significantly, the atoms are located to their true lattice sites not by an averaging, but by triangulation of each particular atom detected in the 3D atom-by-atom reconstruction. Lattice rectification of raw APT reconstruction provides unprecedented detail as to the fundamental solute hierarchy of the solid solution. Atomic clustering has been recognized as important in affecting alloy behavior, such as for the Al-1.1 Cu-1.7 Mg (at. %) investigated here, which exhibits a remarkable rapid hardening reaction during the early stages of aging, linked to clustering of solutes. The technique has enabled lattice-site and species-specific radial distribution functions, nearest-neighbor analyses, and short-range order parameters, and we demonstrate a characterization of solute-clustering with unmatched sensitivity and precision.

Progress in the reconstruction for atom probe tomography has been limited since the first implementation of the protocol proposed by Bas et al. in 1995. This approach and those subsequently developed assume that the geometric parameters used to build the three-dimensional atom map are constant over the course of an analysis. Here, we test this assumption within the analyses of low-alloyed materials. By building upon methods recently proposed to measure the tomographic reconstruction parameters, we demonstrate that this assumption can introduce significant limitations in the accuracy of the analysis. Moreover, we propose a strategy to alleviate this problem through the implementation of a new reconstruction algorithm that dynamically accommodates variations in the tomographic reconstruction parameters.