A Solvent Selection Framework for Porous Organic Polymers

Selecting suitable solvents to control the morphology and properties of novel functional materials remains a significant challenge, especially when there is limited or no prior knowledge of the material and its solubility. In this work, we present a solvent selection toolkit for functional porous organic polymers. We have developed the <i>MLoc</i> algorithm for the fast determination of Hansen solubility parameters (HSPs) for novel materials. This approach requires ultraviolet and visible (UV/vis) absorbance data, measured for a number of candidate solvents using a standard laboratory setup. Based on these measurements, <i>MLoc</i> determines the HSPs for novel porous organic materials using a centroid-location algorithm based on Hansen distance. The results of this algorithm can guide the fine-tuning of both morphology and carbon-capture performance of target polymers, which we illustrate in a case study. In this example, performing the polymer synthesis in solvents with HSPs most similar to the porous material has led to CO₂ uptake improved by 220% compared to a reported analogue (from 2.16 to 6.95 wt %). Using <i>MLoc</i>, we have also compiled a HSP database for 17 porous organic polymers, enhanced with data for over 80 reactions, sampling different conditions, which we present as a resource for future data-driven research in this area.