Successful initiatives to improve the computational materials design and development process.
QuesTek has been at the forefront of several successful initiatives to develop methodologies for integrating computational tools into the materials design process. These methodologies allow us to significantly reduce the cost and time to develop and design novel materials, and to achieve better performance based on a deeper understanding of the underlying microstructures and properties.
The unique aspect of ICME is the use and integration of artificial intelligence, computational tools and physics-based models at different time- and length-scales to predict the microstructure or property evolution of a material for engineering purposes, for example to improve an industrial process.
When implemented correctly, ICME allows for prediction of material structure evolution occurring at a wide spectrum of length scales, resulting in accurate predictions of material behaviour as a function of e.g. time and temperature. To maximize the benefits of ICME it is critical to understand the strengths and limitations of the wide range of available tools, databases and information that constitute the Materials Genome.
QuesTek has always been on the forefront of ICME development and implementation. In the 2013 ICME study Implementing ICME in the Aerospace, Automotive, and Maritime Industries, QuesTek’s FerriumTM S53TM was used as a main example of successful implementation and application of ICME. Despite the wide-spread use of ICME-inspired models and tools, QuesTek has a unique approach to materials design from concept to qualification using systems engineering, ICME-based tools and Materials Genome databases.
The Materials Genome refers to the fundamental databases and information that govern material properties and behaviour.
The understanding and mathematical parametrization of underlying physical phenomena enables consistent modelling and prediction of material behaviour, reducing the need for extensive empirical investigation of each new material.
QuesTek has long experience in evaluating, expanding and modifying Materials Genome databases and related tools for applicability to novel and innovative material classes. This allows for faster and more robust adaption of cutting-edge scientific discoveries into commercial applications.
The AIM methodology reduces the risks related to the introduction of new materials by predicting the process-related variations in performance.
Introduction of new materials into engineered products can involve numerous steps and production runs in order to qualify the material and develop statistical confidence in the properties used by component designers. Any failures to accurately and repeatedly achieve material properties at full-scale production levels can be costly and time-consuming. The AIM methodology minimizes these risks and costs by combining physics-based material models with statistical analysis. QuesTek was a leading contributor to the AIM program, an initiative that created a materials development methodology which enables concurrent design of materials and components.
The AIM methodology is integrated into QuesTek’s design framework. This allows us to establish material requirements by coupling materials and component design, provide information to product designers at earlier stages in the development cycle, control the performance, reproducibility and cost of materials, as well as reduce risks for insertion of new materials while decreasing costly and time-consuming data generation.