Computational Nanoscience | Centre for Informatics

Computational Nanoscience

Research on nanomaterials has been attracting great attention because of the importance of these materials in daily life and for the development of future energy-efficient and environment-friendly designer materials. Properties of nanomaterial are often vastly different from those of the corresponding bulk material and therefore there are unprecedented opportunities to explore materials behaviour at the nanoscale. While historically materials development has been primarily from experiments, computational materials science has now emerged as the third branch of materials research and development, besides theory and experiment. Thanks to rapid advances in density functional theory and the exponential growth in available computing power, it is now possible to design materials at atomistic level with predictive capability and to fine tune properties relevant for specific applications. Optimization is the key for future development of an energy and materials efficient society and computer simulations are a very important tool for accelerated discovery and innovation of optimal designer materials. Materials genome initiative is a step in this direction.

Discerning and exploiting patterns in chemical data lies at the heart of any systematic program for materials design. Mining the growing mass of experimental data on nanomaterials using the tools of atomistic modeling, statistical learning, and pattern recognition is necessary to discover complex quantitative relationships between chemical structure and the properties of materials. Such statistical methods use an array of computed structural descriptors and/or process parameters to predict the value of an experimental quantity, or to complement and leverage from first-principles computations (such as those using ab initio quantum chemistry and density functional theory), enabling quantitative predictions on many more systems than would be practicable with first-principles computations alone. This vision for materials informatics is shared by the Materials Genome Initiative. Our focus is on study of nanostructures including 2D materials, development of models, simulation tools, and databases for predicting their properties and specific characteristics.

Primarily the following three major directions are currently pursued:

  • Inorganic nanomaterials - clusters, nanoparticles, nanowires, layered materials, & nanotubes (applications - devices, catalysis, environment, optical and magnetic), novel structures of boron
  • Materials for energy applications - solar cell materials, Li ion battery materials, solid state lighting materials, fuel cells, H2 storage, CO2 capture, thermoelectric materials
  • Materials for biological applications - drug delivery, sensors, imaging, drug design, nanomaterials in therapy such as using gold nanoparticles to cure cancer, multifunctional materials. This will involve research on a combination of inorganic -organic materials.