Summary
Light Emitting Diodes (LEDs) are present in displays of the great majority of devices we use every day, including smartphones, computers, TVs, etc. Unfortunately, they use toxic non-renewable rare-earth materials for their functioning. Fluorescent Proteins (FPs) have already proven to be an eco-friendly alternative, but their performance over time decreases as the intensity of the excitation source increases. This is because FPs have not been naturally or artificially evolved to function as color converters in electronic devices. Since it is not possible to artificially evolve proteins under LED operation conditions (stress), AnBioLED proposes to merge through machine learning evolutionary information (Ancestral Sequence Reconstruction) and computational protein design to identify key mutations in order to improve FPs photo and thermal stability. More importantly, AnBioLED will use experimental results under device operation conditions to reinforce the protein design strategy. The new ancestral FPs will merge the excellent photoluminescence properties of existing FPs with the robustness of their ancestors. AnBioLED novel approach will allow for the first time to optimize existing FPs for LEDs applications.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101064305 |
Start date: | 01-01-2023 |
End date: | 31-12-2024 |
Total budget - Public funding: | - 173 847,00 Euro |
Cordis data
Original description
Light Emitting Diodes (LEDs) are present in displays of the great majority of devices we use every day, including smartphones, computers, TVs, etc. Unfortunately, they use toxic non-renewable rare-earth materials for their functioning. Fluorescent Proteins (FPs) have already proven to be an eco-friendly alternative, but their performance over time decreases as the intensity of the excitation source increases. This is because FPs have not been naturally or artificially evolved to function as color converters in electronic devices. Since it is not possible to artificially evolve proteins under LED operation conditions (stress), AnBioLED proposes to merge through machine learning evolutionary information (Ancestral Sequence Reconstruction) and computational protein design to identify key mutations in order to improve FPs photo and thermal stability. More importantly, AnBioLED will use experimental results under device operation conditions to reinforce the protein design strategy. The new ancestral FPs will merge the excellent photoluminescence properties of existing FPs with the robustness of their ancestors. AnBioLED novel approach will allow for the first time to optimize existing FPs for LEDs applications.Status
SIGNEDCall topic
HORIZON-MSCA-2021-PF-01-01Update Date
09-02-2023
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