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-learning (ML)- driven and physics-based computational workflows to screen large molecular libraries, predict key electrochemical and physicochemical properties, and deliver ranked shortlists of high[1
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, that e.g., allow to predict relevant dynamics for plasma control, or allow a full simulation of a discharge by using an integrated approach with suitable fidelity, are not mature yet. In very recent years
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