Probing carbon capture, atom-by-atom with machine-learning model

A team of scientists at Lawrence Livermore National Laboratory (LLNL) has developed a machine-learning model to gain an atomic-level understanding of CO2 capture in amine-based sorbents. This innovative approach promises ...

Graph learning modules enhance drug-target interaction predictions

The identification of drug-target Interactions (DTIs) represents a pivotal link in the process of drug development and design. It plays a crucial role in narrowing the screening range of candidate drug molecules, thereby ...

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