Functional materials are essential to human welfare and to provide foundations for emerging industries. As an alternative route to experimental materials discovery, computational materials designs are playing an increasingly significant role in the whole discovery process. In this work, we use an in-house developed python utility: PAOFLOW, which generates finite basis Hamiltonians from the projection of first principles plane-wave pseudopotential wavefunctions on pseudo atomic orbitals(PAO) for post-process calculation on various properties such as the band structures, density of states, complex dielectric constants, diffusive and anomalous spin and charge transport coefficients. In particular, we calculated the dielectric function of Sr-, Pb-, and Bi-substituted BaSnO3 over wide concentration ranges. Together with some high-throughput experimental study, our result indicates the importance of considering the mixed-valence nature and clustering effects upon substitution of BaSnO3 with Pb and Bi. We also studied two prototype ferroelectric rashba semiconductors, GeTe and SnTe, and found the spin Hall conductivity(SHC) can be large either in ferroelectric or paraelectric structure phase. Upon doping, the polar displacements in GeTe can be sustained up to a critical hole concentration while the tiny distortions in SnTe vanish at a minimal level of doping. Moreover, we investigated the sensitivity of two dimensional group-IV monochalcogenides to external strain and doping, which reveal for the first time giant intrinsic SHC in these materials, providing a new route for the design of highly tunable spintronics devices based on two-dimensional materials.

The material development cycle is becoming too slow if compared with other technologies sectors like IT and electronics. The materials scientists’ community needs to bring materials science back to the core of human development. ICME (Integrated Computational Materials Engineer) is a new discipline that uses advanced computational tools to simulate material microstructures, processes and their links with the final properties. There is the need for a new way to design tailor-made materials with a faster and cheaper development cycle while creating products that meet “real-world” functionalities rather than vague set of specifications. Using the ICME approach, cutting edge computational thermodynamics models were employed in order to assist the microstructure characterization and refinement during the TIG welding of a functionally graded composite material with outstanding wear and corrosion resistance. The DICTRA diffusion model accurately predicted the carbon diffusion during sintering, Thermo-Calc and TC-PRISMA models described the thermodynamic and kinetics of harmful carbide precipitation, while COMSOL Multhiphysic furnished the temperature distribution profile at every timestep during TIG welding of the material. Bainite transformation and the influence of chromium and molybdenum was studied and modelled with MAP_STEEL software. The simulations were then compared with experimental observations and a very good agreement between computational works and experiments was found for both thermodynamic and kinetics predictions. The use of this new system proved to be a robust assistance to the classic development method and the material microstructures and processes were carefully adjusted in order to increase corrosion resistance and weldability. This new approach to material development can radically change the way we think and we make materials. The results suggest that the use of computational tools is a reality that can dramatically increase the efficiency of the material development.