Computational discovery of new piezoelectric materials

The availability of new piezoelectric materials compatible with silicon chip integration for micro-electromechanical systems (MEMS) application is a highly attractive prospect. These new materials will help to bridge the gap between mechanical and electronic devices, making MEMS increasingly small and efficient. AlN is today’s industry’s standard and research is intensifying worldwide on AlN derivatives such as ScAlN. By alloying AlN with Sc, the crystal lattice is locally distorted due to the phase competition between the rock-salt ScN and wurtzite AlN structures, resulting in a progressive transition of AlN from wurtzite into a hexagonal-layered structure as the amount of Sc dopant atoms increases. This, in turn, induces an enhancement of the piezoelectric coefficients of ScAlN up to 50% Sc content (see figure).

Group-III nitrides

Group-III nitrides are material compounds of nitrogen (N) and the elements in the first column of the p-element block of the periodic table (technically, group IIIB): boron (B), aluminium (Al), gallium (Ga), indium (In) and thallium (Tl). The compounds AlN, GaN, InN and their alloys are technologically important semiconductors with multiple applications in optoelectronics, in particular incorporated in LEDs for light production. Much of my work during my PhD at the Tyndall National Institute focused on the study of some of the properties of these materials.

Digging into materials nanostructure through computational spectroscopy

Our two papers on understanding experimental X-ray spectra of materials utilizing simulated references just got accepted (and appeared as “just accepted” manuscripts) in Chemistry of Materials as Part I (more qualitative) & Part II (more quantitative). These papers are a collaboration of our group (Anja Aarva, who did most of the work, Tomi Laurila and …

The COMPEX project just started

The Academy of Finland funded COMPEX project (Towards accurate computational experimentation: machine-learning-driven simulation of nanocarbon synthesis) started on September 1st, 2019. This project will focus on developing atomistic simulation tools based on machine learning interatomic potentials to carry out large scale molecular dynamics and long-time-scale dynamics simulations to elucidate the growth mechanisms in carbon nanomaterials …

The way funding agencies allocate money is damaging scientific research [part 1 – prelude]

It’s not difficult to become disillusioned with academia after unsuccessfully spending a couple (and many more!) of years struggling to secure research funds from competitive grant calls. Many (good) scientists who become frustrated by the large amounts of time wasted and the extreme unfairness of the process end up leaving academia and research all together. …