Description and lab research areas
Our lab is computational; we use the toolkit available for quantum chemists to study exciting phenomena far away at the interstellar medium. The presence and formation of a large variety of organic molecules in the ISM are evident from both astronomical data of absorption and emission bands at different regions of the spectrum. However, it is not clear how molecules are formed in the ISM’s low temperature and density environments. Specifically, polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the ISM. Understanding the mechanism of formation of complex molecules such as PAHs and nitrogen-based PAHs (PANH) in the ISM is a long-standing challenge attracting growing attention in recent decades. We study different path for organic molecules formed in the ISM. The dynamic evolution of molecular systems can be calculated using Ab-Initio Molecular dynamics. Such calculation can give very accurate results; however, performing an ab-initio calculation in every time step of the molecular dynamics can be time-consuming. We are thus using Machine Learning (ML) algorithms, specifically artificial neural networks, to construct potential energy surfaces. Potentially, after the potential energy surfaces are built, they will enable us to perform simulations on a longer time scale and larger systems. Additionally, as many important reactions in the ISM resulting from a dynamic on an excited electronic state, we develop new methods that will enable us to investigate the propagation in time on an excited electronic state of large molecules.
Our lab has openings for postdoctoral positions for several ongoing projects. Candidates should have a PhD in chemistry, physics, or an equivalent discipline, with a strong background and previous experience in computational science.