Framework to embed machine learning algorithms in P-graph: Communication from the chemical process perspectives

P-graph is a popularly used framework for process network synthesis (PNS) and network topological optimization. This short communication introduces a Python interface for P-graph to serve as a linkage to modern programming ecosystems. This allows for a wider application of the fast and efficient P-graph solver, to provide structural and topological enumeration in numerous fields. The proposed framework allows for more integrative usage in Artificial Intelligence (AI), machine learning, process system engineering, chemical engineering and chemometrics. Large and repetitive topologies can also be automated using the new programming interface, saving time and effort in modelling. This short communication serves as a demonstration of the newly developed open-sourced P-graph interface. (c) 2022 The Authors. Published by Elsevier Ltd on behalf of Institution of Chemical Engineers. This is an open access article under the CC BY license (http://creative-commons.org/licenses/by/4.0/).