Periodic Reporting for period 3 - GEMS (General Embedding Models for Spectroscopy)
Período documentado: 2022-06-01 hasta 2023-11-30
Spectroscopy is a powerful analytical technique aimed at identifying molecular systems in a laboratory sample. Among the different spectroscopies, Raman scattering is particularly suitable for analytical detection, due to its sensitivity to molecular structure. Unfortunately, conventional Raman scattering suffers from a relatively low-in-intensity signal, which can however be hugely enhanced if the molecular probe is adsorbed on noble-metal nanosubstrates. The resulting technique, named Surface-Enhanced Raman Scattering (SERS), allows single-molecule detection with non-invasive approaches, and can be effectively exploited in many fields, including biosensing. The actual interpretation of SERS signals in terms of molecular patterns benefits from the coupling with theory and simulation. The goal of GEMS is to provide the scientific community with a user-friendly platform that can guide the interpretation of experimental results and predict molecular and supra-molecular signals that have never been measured.
We have started working on the project by first developing a theoretical model which is general enough to be able to describe metal nanoparticles and graphene at the same level of accuracy. The model has been tested on different experimentally studied systems, by showing an almost perfect reproduction of reference data. Thanks to these excellent results, we investigated whether the same approach can be successfully applied to the in-silico design of novel geometrical arrangements in graphene-based materials, to reach field enhancements comparable to those achieved by exploiting metal nanoparticles in SERS.
We have then started the calculation of molecular signals of molecular systems adsorbed on metal nanoparticle/graphene nanosubstrates, obtaining very promising results in terms of the accuracy of the approach to reproduce reference experimental data.
We have then started the calculation of molecular signals of molecular systems adsorbed on metal nanoparticle/graphene nanosubstrates, obtaining very promising results in terms of the accuracy of the approach to reproduce reference experimental data.