Aug 23 2017
From the beginning of the Enlightenment-era of Physics and Chemistry, Researchers have endeavored to record the properties of materials under disparate conditions. Such explorations have made huge contributions to the discipline of Materials Science and have assisted in developing aircraft and spacecraft, revolutionizing healthcare and developing industrial processes for synthesizing products such as cosmetics, adhesives, jet fuel, fertilizers and so on.
3D microstructure containing multiple solidification velocity changes. On the right, an exemption of intermetallic phases that shows the adjustments of the rods in the microstructure, such as the splitting, merging and overgrowing at different velocities. The gray planes indicate the height of the velocity change. CREDIT: High Performance Computing and Data Science Group, Karlsruhe Institute of Technology and Karlsruhe University of Applied Sciences.
Yet, even though Scientists try to develop highly complex materials to satisfy largely intricate industrial requirements (e.g. enhanced material resiliency to suit high-temperature processes, or compression processes for developing materials for flight), the potential of experimentally revealing and discerning the characteristics of materials has become highly expensive with respect to money, resources, time and energy required.
A group of Scientists headed by Professor Dr Britta Nestler from the Karlsruhe Institute of Technology and the Karlsruhe University of Applied Sciences has worked on advanced material design by adopting computation to model new material characteristics. The principal focus of the group is on materials for which experiments do not hold good in acceptably characterizing and manipulating the origin of their characteristics, or in cases where these experiments might be highly time-consuming to be efficiently carried out in a systematic way.
Nestler—who recently won the 2017 Gottfried Wilhelm Leibniz Prize from the German Research Foundation—and her colleagues used High Performance Computing Center Stuttgart’s (HLRS’s) Cray XC40 Hazel Hen supercomputer to achieve a major breakthrough in their multiscale and multiphysics modeling and simulation attempts.
The Karlsruhe team developed the parallel simulation software Pace3D, that is, Parallel Algorithms of Crystal Evolution in 3D, and has been a long-time user of HLRS resources, earlier analyzing material pattern formations, for example, multiphase directional solidification. The Researchers’ main aim is the computational investigation of the impact of fluctuating melting conditions on the characteristics of materials and on microstructure quantities.
In a paper recently reported in the journal Acta Materialia, the research team has provided complete information on the 3D simulations of an aluminum-silver-copper (Al-Ag-Cu) alloy upon being solidified and has compared microstructure properties with experimental photographs. As a first, the team has adopted a theory and experiment combination to make tailored velocity fluctuations for designing the microstructure and, consequently, material characteristics. The Researchers used Al-Ag-Cu because of the plentiful experimental data at disposal for comparing their simulation outcomes. The technique proves to be optimal for carrying out larger simulations of highly complex materials.
With the knowledge we’ve gained from our recent computing runs, we have a framework to go to technically relevant systems that often have experimental difficulties. We decided to investigate the Al-Cu-Ag microstructure pattern to show the validity of the model and the possibilities to compare it with a wide range of experimental data.
Johannes Hötzer, Lead Author of the study
Solidification speed changes
Materials Researchers have constantly tried to gain an in-depth knowledge of the limits of materials, such as the hottest temperature at which a mixture can function, the highest pressure it is able to withstand, and so on. One topic that draws considerable interest is the knowledge of the characteristics of eutectic materials comprising two (binary eutectic) or three (ternary eutectic) different solid phases in a microstructure arrangement that culminates in the lowest possible melting temperature. The latest focus of the team headed by Nestler is on ternary eutectics including three alloy components.
By adopting Hazel Hen, the Researchers simulated the way specific process conditions (e.g. processing temperature or solidification velocity) have an impact on the microstructure of a eutectic material. In order to deduce the correlations, the Researchers require large-scale 3D computations for simulating a representative sample of microstructural patterns. For instance, before carrying out their recent simulations, the Researchers proposed that when Al-Ag-Cu changes from liquid to solid, the solidification transition speed has a significant role in the manner in which the pattern of a microstructure splits and merges, and the way the width and length of the formed fibers have an impact on the strength of the material at higher temperatures.
Yet, the team had only 2D experimental data, which hindered their efforts in unequivocally proving or disproving their postulation. Computational Scientists and Experimentalists ought to observe the process in three-dimensional scale. They can achieve this with the assistance of a supercomputer.
The Researchers developed a multiphysics software package Pace3D for including a broad array of material models and executed a highly optimized model by working in cooperation with the Fredrich Alexander University Erlangen-Nuremberg, by using the University’s computational framework waLBerla (widely applicable Lattice Boltzmann from Erlangen).
The code disintegrates huge 3D simulations into approximately 10,000 computerized cubes, and then solves a range of physics equations within each cell for millions of time steps, where each step ranges from 0.1 to 1.0 ms. In order to detect the fluctuations in velocity, the Researchers ran multiple simulations sets with fluctuations in solidification velocity. Each simulation will take nearly 1 day on roughly 10,000 of Hazel Hen’s CPU cores.
Experimentalists were astonished to observe the results. With the help of their 2D experiments, the Researchers presupposed that the eutectic microstructures were formed within a very short time period in a predominantly uniform and straight manner. Yet, the simulation unearthed various rearrangement processes at the time of solidification and demonstrated that microstructure patterns get altered very gradually and on longer length scales than thought to be. These outcomes were then reasserted by synchrotron tomography—an imaging method that enables scientists to analyze material characteristics on a basic level.
Tailored Microstructures
The precise simulation outcomes achieved by the Researchers characterizes a proof of concept for its potential to simulate the formation of microstructure in a highly complex and absolutely industrially appropriate materials using a broad array of physical and material conditions.
Due to the fact that experiments constantly become highly complicated—the Karlsruhe specialists in computational materials modeling have extensively cooperated with Experimentalists performing zero-gravity material design studies on the International Space Station—computations will continue to have a major role. Nestler said that experiments such as those performed on the ISS were highly significant and also costly and time-consuming to conduct. Supercomputing techniques assist Scientists in getting closer to synthesizing customized materials with particular characteristics for specific applications, in addition to reducing the cost.
Computing also enables scientists to perform many permutations of the same simulations with very mean differences, which will otherwise mandate numerous discrete experiments.
In our simulations, we can vary physical and processing conditions, such as the solidification velocity, which have an influence on microstructure. By controlling this parameters, we end up getting a well-designed, tailored microstructure.
Professor Dr Britta Nestler, the Karlsruhe Institute of Technology and the Karlsruhe University of Applied Sciences
According to Nestler, in-depth knowledge on how to minutely vary temperature and speed profiles while producing complex materials will enable carrying out large-scale parallel computations that assist Materials Scientists in developing an exceptionally well-adapted material for a particular task. These materials can be applied in air and aerospace technologies, and also in industrial processes in which materials are exposed to extreme pressures or temperatures.
For instance, the Researchers performed simulations of a nickel, aluminum and chromium-34 alloy and were able to demonstrate the manner in which the alignment of the microstructure is enhanced by creating controlled process conditions, culminating in higher creep resistance, that is, the material is not deformed upon exposure to temperature-based or mechanical stress.
Our main goal is to design particular microstructures for multi-component alloys, for cellular or particle based systems that are based on its application. The application defines what new materials should look like or should be able to sustain, and we can now design, in a controlled manner, the particular microstructure that is needed.
Professor Dr Britta Nestler, the Karlsruhe Institute of Technology and the Karlsruhe University of Applied Sciences