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Creators/Authors contains: "Homer, Eric R."

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  1. ; ; ( , Acta Materialia)
    One of the major challenges towards understanding and further utilizing the properties and functional behaviors of grain boundaries (GB) is the complexity of general GBs with mixed tilt and twist character. Here, we report the correlations between mixed GBs and their tilt and twist components in terms of structure, energy and stress field by computationally examining 7440 silicon GBs. Such correlations indicate that low angle mixed GBs are formed through the reconstruction mechanisms between their superposed tilt and twist components, which are revealed as the energetically favorable dissociation, motion and reaction of dislocations and stacking faults. In addition, various complex disconnection network structures are discovered near the conventional twin and structural unit GBs, implying the role of disconnection superposition in forming high angle mixed GBs. By unveiling the energetic correlation, an extended Read-Shockley model that predicts the general trends of GB energy is proposed and confirmed in various GB structures across different lattices. Finally, this work is validated in comparison with experimental observations and first-principles calculations. 
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    Free, publicly-accessible full text available October 1, 2025
  2. ; ; ; ( , Acta Materialia)
    Solute segregation in materials with grain boundaries (GBs) has emerged as a popular method to thermodynamically stabilize nanocrystalline structures. However, the impact of varied GB crystallographic character on solute segregation has never been thoroughly examined. This work examines Co solute segregation in a dataset of 7272 Al bicrystal GBs that span the 5D space of GB crystallographic character. Considerable attention is paid to verification of the calculations in the diverse and large set of GBs. In addition, the results of this work are favorably validated against similar bicrystal and polycrystal simulations. As with other work, we show that Co atoms exhibit strong segregation to sites in Al GBs and that segregation correlates strongly with GB energy and GB excess volume. Segregation varies smoothly in the 5D crystallographic space but has a complex landscape without an obvious functional form. 
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    Free, publicly-accessible full text available October 3, 2025
  3. ; ; ( , Computational Materials Science)
    Free, publicly-accessible full text available September 1, 2025
  4. ; ; ; ; ( , Acta Materialia)
    Free, publicly-accessible full text available August 1, 2025
  5. ; ; ; ; ; ; ; ( , Acta Materialia)
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  6. ; ; ; ; ; ; ; ; ; ; et al ( , Modelling and Simulation in Materials Science and Engineering)
    Abstract

    SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic evolution during processing. The modular nature of the code allows new models and diagnostic computations to be added without modification to its core functionality, including its parallel algorithms. A variety of models for microstructural evolution (grain growth), solid-state diffusion, thin film deposition, and additive manufacturing (AM) processes are included in the code. SPPARKS can also be used to implement grid-based algorithms such as phase field or cellular automata models, to run either in tandem with a Monte Carlo method or independently. For very large systems such as AM applications, the Stitch I/O library is included, which enables only a small portion of a huge system to be resident in memory. In this paper we describe SPPARKS and its parallel algorithms and performance, explain how new Monte Carlo models can be added, and highlight a variety of applications which have been developed within the code.

     
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  7. ; ; ; ; ; ( , Acta Materialia)
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  8. ; ; ; ; ; ; ; ( , Scientific Data)
    Abstract

    Researchers continue to explore and develop aluminum alloys with new compositions and improved performance characteristics. An understanding of the current design space can help accelerate the discovery of new alloys. We present two datasets: 1) chemical composition, and 2) mechanical properties for predominantly wrought aluminum alloys. The first dataset contains 14,884 entries on aluminum alloy compositions extracted from academic literature and US patents using text processing techniques, including 550 wrought aluminum alloys which are already registered with the Aluminum Association. The second dataset contains 1,278 entries on mechanical properties for aluminum alloys, where each entry is associated with a particular wrought series designation, extracted from tables in academic literature.

     
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  9. ; ; ; ; ; ( , Journal of Microscopy)
    Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (body centred cubic and body centred tetragonal, with small tetragonality) phases in steels using standard EBSD software. One method to tackle the problem of phase distinction is to measure the tetragonality of the phases, which can be done using simulated patterns and cross‐correlation techniques to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so‐called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both kinetically simulated and dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point‐by‐point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image‐quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate ∼0.2% error in carbon content estimation. Such an error makes the technique unsuitable for estimation of total carbon content of most commercial steels, which often have carbon levels below 0.1%. However, even in the DP steel for this study (0.1 wt.% carbon) it can be used to map carbon in regions with higher accumulation (such as in martensite with nonhomogeneous carbon content).

    Lay Description

    Electron Backscatter Diffraction (EBSD) is a widely used approach for characterising the microstructure of various materials. However, it is difficult to accurately distinguish similar (BCC and BCT) phases in steels using standard EBSD software due to the small difference in crystal structure. One method to tackle the problem of phase distinction is to measure the tetragonality, or apparent ‘strain’ in the crystal lattice, of the phases. This can be done by comparing experimental EBSD patterns with simulated patterns via cross‐correlation techniques, to detect distortion away from a perfectly cubic crystal lattice. However, small errors in the determination of microscope geometry (the so‐called pattern or projection centre) can cause significant errors in tetragonality measurement and lead to erroneous results. This paper utilises a new approach for accurate pattern centre determination via a strain minimisation routine across a large number of grains in dual phase steels. Tetragonality maps are then produced and used to identify phase and estimate local carbon content. The technique is implemented using both simple kinetically simulated and more complex dynamically simulated patterns to determine their relative accuracy. Tetragonality maps, and subsequent phase maps, based on dynamically simulated patterns in a point‐by‐point and grain average comparison are found to consistently produce more precise and accurate results, with close to 90% accuracy for grain phase identification, when compared with an image‐quality identification method. The error in tetragonality measurements appears to be of the order of 1%, thus producing a commensurate error in carbon content estimation. Such an error makes an estimate of total carbon content particularly unsuitable for low carbon steels; although maps of local carbon content may still be revealing.

    Application of the method developed in this paper will lead to better understanding of the complex microstructures of steels, and the potential to design microstructures that deliver higher strength and ductility for common applications, such as vehicle components.

     
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  10. ; ; ; ; ; ; ; ( , Acta Materialia)
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