Through the stone, bronze, and iron ages the discovery of new materials has chronicled human history. The coming of each age was sparked by a chance discovery of a new material. Despite the central importance of materials in enabling new technologies, even today the only way to develop new materials is through experiment driven trial and error. We have developed the first tool [Patent GB1302743.8], MAGE, Materials Automated Generation and Exploration: computationally designs materials with specified physical properties. We have proven its accuracy by predicting five new alloys [Patent GB1307533.8, Patent GB1307535.3, Rolls-Royce Group plc invention submissions NC12261, NC13006 & Acta Materialia, 61, 3378 (2013)] that were subsequently experimentally verified. MAGE can help not only materials scientists, but moreover design engineers. At present engineers must design new objects and products around the shortcomings of pre-existing but non-ideal materials. The capability to develop materials computationally would allow engineers to instantly optimize bespoke materials for their application, bringing materials into the heart of the design process.
The alloys developed include a new nickel-based alloy for turbine discs in jet engines, a novel alloy for lining the combustion chamber of a jet engine, and a molybdenum based forging alloy. Each alloy has eight individual physical properties that are predicted to match or exceed commercially available alternatives including fracture toughness, oxidation resistance, yield strength, creep resistance and processibility. These properties are calculated using a variety of techniques including ab initio calculations, physically based models, and interpolation of existing experimental data. Several properties for each alloy have subsequently been experimentally verified so the alloys are now undergoing compliance testing by Rolls Royce plc.
In the future we plan to further incorporate first principles methods into MAGE. Working with Samsung Electronics Co Ltd through a Global Research Outreach Grant we will first focus on designing new GaInN-based LEDs materials, exploiting Density Functional Theory to predict properties from first principles. This investigation should allow us to not only design potentially important semiconductor materials, but moreover act as a launch-pad to guide the future design of new materials from first principles.