Summary
Viruses are nanoparticles with well-defined size, shape and elasticity in which acoustic waves are confined. This leads to the appearance of new vibration modes that correspond to the vibration of the virus particle as a whole object. The VIRUSong project aims at implementing and realizing a simple and radically new way to identify viral particles on the basis of these vibrations. Inelastic light scattering spectroscopy (Raman and Brillouin) is usually a tool of choice to measure these vibrations, but for viruses, the effective scattering cross section is small. To overcome this drawback, the VIRUSong project will mainly focus on a few viruses of different size and structure and two parallel strategies will be explored. (a) the coupling of viruses with nanoparticles of hard materials which are very simple nano resonators (NPRs). The project VIRUSong project aims at using them as antennas to collect and amplify the song of the virus particles (i.e. the vibrations of the virions). (b) the use of Stimulated low-frequency inelastic spectroscopy that will allow the label-free detection of any type of virus. To achieve these objectives, the project will analyze each selected familly of viruses to determine their composition, size, shape and mechanical properties. Finally, all this information will be correlated using artificial intelligence to identify a given virus based on its vibrational spectra. By pushing the current limits of stimulated inelastic light scattering spectroscopy, designing nanoparticle resonators (NPRs) and implementing efficient artificial intelligence models, this project aims to develop the proof of concept of a new technology capable of identifying viral particles by light in a few minutes, while achieving high selectivity (specific vibrational signature) and high sensitivity (down to the single viral particle).
Unfold all
/
Fold all
More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101099058 |
Start date: | 01-09-2023 |
End date: | 31-08-2027 |
Total budget - Public funding: | 5 473 554,00 Euro - 5 473 554,00 Euro |
Cordis data
Original description
Viruses are nanoparticles with well-defined size, shape and elasticity in which acoustic waves are confined. This leads to the appearance of new vibration modes that correspond to the vibration of the virus particle as a whole object. The VIRUSong project aims at implementing and realizing a simple and radically new way to identify viral particles on the basis of these vibrations. Inelastic light scattering spectroscopy (Raman and Brillouin) is usually a tool of choice to measure these vibrations, but for viruses, the effective scattering cross section is small. To overcome this drawback, the VIRUSong project will mainly focus on a few viruses of different size and structure and two parallel strategies will be explored. (a) the coupling of viruses with nanoparticles of hard materials which are very simple nano resonators (NPRs). The project VIRUSong project aims at using them as antennas to collect and amplify the song of the virus particles (i.e. the vibrations of the virions). (b) the use of Stimulated low-frequency inelastic spectroscopy that will allow the label-free detection of any type of virus. To achieve these objectives, the project will analyze each selected familly of viruses to determine their composition, size, shape and mechanical properties. Finally, all this information will be correlated using artificial intelligence to identify a given virus based on its vibrational spectra. By pushing the current limits of stimulated inelastic light scattering spectroscopy, designing nanoparticle resonators (NPRs) and implementing efficient artificial intelligence models, this project aims to develop the proof of concept of a new technology capable of identifying viral particles by light in a few minutes, while achieving high selectivity (specific vibrational signature) and high sensitivity (down to the single viral particle).Status
SIGNEDCall topic
HORIZON-EIC-2022-PATHFINDEROPEN-01-01Update Date
31-07-2023
Images
No images available.
Geographical location(s)