| Funding period: | Jan. 1, 2026 to Dec. 31, 2032 |
| Agency: | DFG |
| Funding scheme: | EXC |
Funding by the DFG via the “Responsible Electronics in the Climate Change Era – REC²” Cluster of Excellence (EXC 3035, Project-ID 533607596) is gratefully acknowledged.
Electronics offer numerous advantages for our lives, but at the cost of enormous resource and energy consumption and the generation of electronic waste.
The REC² cluster creates the scientific basis for the electronics of the future: new material platforms, component concepts and integrated systems with which responsible electronics can be realized in an ecologically, economically and socially sustainable way.
Prof. Cuniberti is associated PI in this Cluster of Excellence.
Aptamer-Functionalized Silicon Nanonet-Based Field-Effect-Transistors Combined with Machine Learning for Real-Time Detection of 17β-Estradiol
Advancing density functional tight-binding method for large organic molecules through equivariant neural networks
| Funding period: | Jan. 1, 2026 to Dec. 31, 2032 |
| Agency: | DFG |
| Funding scheme: | EXC |
Funding by the DFG via the “Responsible Electronics in the Climate Change Era – REC²” Cluster of Excellence (EXC 3035, Project-ID 533607596) is gratefully acknowledged.
Electronics offer numerous advantages for our lives, but at the cost of enormous resource and energy consumption and the generation of electronic waste.
The REC² cluster creates the scientific basis for the electronics of the future: new material platforms, component concepts and integrated systems with which responsible electronics can be realized in an ecologically, economically and socially sustainable way.
Prof. Cuniberti is associated PI in this Cluster of Excellence.
Aptamer-Functionalized Silicon Nanonet-Based Field-Effect-Transistors Combined with Machine Learning for Real-Time Detection of 17β-Estradiol
Advancing density functional tight-binding method for large organic molecules through equivariant neural networks
