The To show the effect of the integration of a physics-assisted approach within our hybrid DL-DEM framework, we can start by computing the Radial Distribution Function (RDF), which is a typical observable to characterize the dried electrode microstructure in the simulations carried out with this level of particle description. We evaluate the RDFs in the 4 Test cases, according to equation 5, 𝑋 [12] = Test I, 𝑋 [13] = Test II, 𝑋 [14] = Test III and 𝑋 [15] = Test IV. In Figure we show the DEM target RDF versus the prediction of our PAML model (𝑛 𝐷𝐸𝑀 = 0, 5000, 7000, 10000) at the end of the drying process (21 TF) for the Test I case. Similarly, as in the other Test samples (II, III and IV) showed in Figure , we observe that the not inclusion of DEM steps (𝑛 𝐷𝐸𝑀 = 0), i.e. the purely data-driven DL model, does not capture well the interactions to allow a reasonable prediction of the RDF. In general, as 𝑛 𝐷𝐸𝑀 increases, the RDF predictions converge to the DEM one.