For the perspective of exporting this approach into the digitalization of the recycling process, it is expected that this hybrid methodology proves useful as well. PBMs are expected to be a key component to create large datasets and thus accelerate the quality control workflows by coupling them with data driven techniques. It is envisioned that to accelerate development, a modeling workflow could consist of first, performing enough experimental characterizations to parametrize and validate an electrochemical PBM. After that, the obtained data would be fed into a ML capable of extrapolating meaningful results for different conditions and use cases. Going further, this coupled approach could also be implemented in conjunction with powerful cloud computing power and Internet of Things technologies (IoT) with the purpose of creating a sophisticated virtual twin experience of the recycling process line.