The constant demand for more powerful and energy-efficient electronic devices than existing ones is challenging scientists and companies to develop innovative solutions that can address such primary technological needs. Based on a recent scientific discovery made by our team we have developed a technology for superfast and extremely scalable logic and computing circuits with minimal energy losses, which has the potential to become the leading technology in the future world of largescale computing and telecommunication infrastructures.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
Displaying results 1 - 4 of 4
Mirrors for space applications, besides featuring suitable optical properties, should be light, resistant to mechanical stresses, and unsensitive to light-shadow thermal cycling. The standard optical materials easily fulfill optical and thermal requirements, but are fragile, and the mirrors must be thick (typically 1/6 of the diameter). For this reason they are heavy, and the only available solution is to lighten them, by removing material from the back side, still preserving the necessary mechanical robustness and optical quality.
The proposed technology deals with the development of active SERS (Surface Enhanced Raman Scattering) substrates ad hoc designed for diagnostics of cultural heritage. The substrates are prepared starting from common commercial 'polishing film' sheets (lapping optical fibers) showing an intrinsic roughness (48- 1000 nm) that favors the SERS effect. A pattern of silver or gold nanoparticles are deposited on these films through Pulsed Laser Deposition (PLD).
Recently, it has been demonstrated that Raman spectroscopy can play a fundamental role in assisting the work of the anatomopathologist by allowing classification of oncological samples with practically 100% accuracy in oncological diagnosis.