We are interested in the application and development of computational chemistry methods to solve challenging problems from biology and materials science. Some of these phenomena cannot be studied using traditional methods because they involve the interaction between different electronic states. The development of methods to understand this kind of processes is one of the purposes of our group. Rachel is part of the team of developers of the Newton-X program, which is a general platform to perform non-adiabatic dynamics simulations based on the surface hoping approximation.
Main Research Topics:
1.) Chemical reactions in the ground and excited states
Computational chemistry has emerged as a very useful tool to understand complex phenomena. The computational modelling of reaction mechanisms provides valuable information of the energy barriers, solvent effects and substituent effects. We are particularly interested in the reactivity of radicals in the ground and excited states.
2.) Non-adiabatic dynamics and photo-phenomena in gas and condensed phase
Most photochemical applications involve solid-state or large extended molecules, however at this moment non-adiabatic dynamics simulations are limited to relatively small systems, thus to deal with challenging applications more efficient and suited methods must be developed. The excited states can be obtained with DFT, TDDFT, TDDFT tight-binding and Tamm-Dancoff (TDA) methods. Of particular interest is the implementation of the QM/MM and QM/QM models.
3.) Interpretation of time-resolved experiments
In pump-probe techniques, the system is excited to a specific electronic excited state (resonant experiments) and a time-dependent response function is monitored, thus providing valuable information on photochemical processes. Most simulations are based on static calculations of excited states using the Franck-Condon geometry; consequently the structural relaxation and the changes on the response functions during the processes are not taken into account. We aim to contribute to fill the gap between time-resolved experiments and theory providing general tools to generate a more effective simulation-experiment feedback.
4.) Molecular sensors and their light response
From pure basic research investigations to industrial applications, the use of light as sensing response is widespread. A number of “molecular sensors” are known that can be used to detect target molecules. The complexity of these molecular sensors varies from small discrete molecules to large biological systems but there are common principles in their functioning. The change of the light response of these molecules induced by binding with analytes or solvent molecules is frequently used as a detection method, some examples are the sensors employed in bioimaging techniques, the use of carbon nanotubes to detect small molecules and the host-guest interactions used in molecular recognition.