174 citations · 212 across the 9 of their papers we have counts for
4 papers · 1 filter
Simulating diffusion properties of solid-state electrolytes via a neural network potential: Performance and training scheme
Aris Marcolongo, Tobias Binninger, Federico Zipoli +1
The recently published DeePMD model (https://github.com/deepmodeling/deepmd-kit), based on a deep neural network architecture, brings the hope of solving the time-scale issue which…
Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy
Philippe Schwaller, Riccardo Petraglia, Valerio Zullo +6
We present an extension of our Molecular Transformer architecture combined with a hyper-graph exploration strategy for automatic retrosynthesis route planning without human interve…
An Information Extraction and Knowledge Graph Platform for Accelerating Biochemical Discoveries
Matteo Manica, Christoph Auer, Valery Weber +9
Information extraction and data mining in biochemical literature is a daunting task that demands resource-intensive computation and appropriate means to scale knowledge ingestion.…
Comparison of computational methods for the electrochemical stability window of solid-state electrolyte materials
Tobias Binninger, Aris Marcolongo, Matthieu Mottet +2
Superior stability and safety are key promises attributed to all-solid-state batteries (ASSBs) containing solid-state electrolyte (SSE) compared to their conventional counterparts…