Aldo Romero

Research

Computational Material Science

The role of computers in our daily live has changed the way we do material science. The growth of computer power and the effort put into improving software and hardware have created a positive scene for using a good set of theories to describe, characterize and predict the properties of materials. Our department is participating in such endeavours and we are undertaking many different efforts to increase our understanding of materials. In particular, we have been involved in implementing and using Density Functional Theory (DFT), Time Dependent Density Functional Theory (TDDFT) and many particle approaches (GW or Bethe-Salpeter), which are the methods most often used to describe any material. Our experience goes from crystalline systems, amorphous and glasses to different types of nanostructures. Routinely, we perform computational materials characterizations, such as determining the electronic, optical, elastic, vibrational and magnetic properties, based on these theories.

More recently, we have devised projects in what is called “Computational High-Throughput.” This is basically the design of a material for a particular application, from scratch. We have been involved in one way or another in using or implementing the methods of Genetic Algorithms, Minima Hopping, Metadynamics, etc, creating tools that scientist can now use to design a particular material for a specific application. In particular, our groups have been involved in the development of codes such as Fireball as well as Abinit. We also keep strong collaborations with many groups around the world, in Germany, France, China, Spain, Switzerland, Italy, etc.