Nature

Graph neural network-based cell switching for energy optimization in ultra-dense heterogeneous networks

The development of ultra-dense heterogeneous networks (HetNets) will cause a significant rise in energy consumption with large-scale base station (BS) deployments, requiring cellular networks to be ...
Nature

Fast evaluation of the adsorption energy of organic molecules on metals via graph neural networks

Modeling in heterogeneous catalysis requires the extensive evaluation of the energy of molecules adsorbed on surfaces. This is done via density functional theory but for large organic molecules it ...
EurekAlert!

GAME-Net: a graph neural network for fast evaluation of the adsorption energy in heterogeneous catalysis

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...
The Conversation

This widely used chart makes the clean energy switch seem much harder than it actually is

If you follow news about climate change, you’ve probably seen the term “primary energy”. This phrase refers to the raw energy in fuels and natural resources – the energy content of oil in a barrel, ...