I completed my Ph.D. in 2022, focusing on the theoretical and computational investigation of chemical reactions, energy transfer, spectroscopy, and the dynamics of polyatomic molecules. My research involves high-level ab initio electronic structure calculations using methods such as multireference configuration interaction (MRCI), perturbation theory (MPn and CASPT2), and coupled cluster (CC) techniques. I primarily employ the MOLPRO and ORCA software packages for these calculations. The resulting data are used to construct accurate potential energy surfaces (PES), which serve as a foundation for exploring a wide range of physical and chemical phenomena, including plasma processes, molecular spectroscopy, chemical reactivity, and rovibrational energy transfer.
To simulate molecular dynamics, I employ the quasi-classical trajectory (QCT) method, a well-established technique since the foundational work of Karplus et al. In addition to traditional PES approaches, I have explored the use of machine learning, applying artificial neural networks (ANNs) to model potential energy curves for diatomic systems using the open-source FANN (Fast Artificial Neural Network) library.
Currently, my research focuses on the study of organic and inorganic sulfur-bearing species, which have significant applications in pharmaceuticals, biomolecular chemistry, and astrochemistry. I am also actively engaged in the theoretical investigation of two-dimensional (2D) materials.
