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Sparse deep neural networks for modeling aluminum electrolysis dynamics

Deep neural networks have become very popular in modeling complex nonlinear processes due to their extraordinary ability to fit arbitrary nonlinear functions from data with minimal expert intervention. However, they are almost always overparameterized and challenging to interpret due to their...

Authors
Erlend Torje Berg Lundby
Adil Rasheed
Jan Tommy Gravdahl
Ivar Johan Halvorsen
Year
2023
Type
Academic article
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Publication

CO2 sorption and diffusion in fluorinated polymers for carbon capture and transport application

Fluorinated polymers play a significant role in the Carbon Capture and Storage (CCS) value chain, which is considered as the most viable solution to limit the CO2 emission in the atmosphere, with the potential to be applied at short-medium times. Indeed, among the various classes of polymers...

Authors
Virginia Signorini
Marco Giacinti Baschetti
Luca Ansaloni
Thijs Peters
Ben Alcock
Matteo Minelli
Year
2022
Type
Conference lecture