Gradient nanoporous phenolics as substrates for high-flux nanofiltration membranes by layer-by-layer assembly of polyelectrolytes

Machine learning for layer-by-layer nanofiltration membrane performance prediction and polymer candidate exploration

In this study, machine learning-based models were established for layer-by-layer (LBL) nanofiltration (NF) membrane performance prediction and polymer candidate exploration. Four different models, i.e., linear, random forest (RF), boosted tree (BT), and eXtreme Gradient Boosting (XGBoost), were formed, and membrane performance prediction was determined in terms of membrane permeability and selectivity. The XGBoost exhibited optimal prediction accuracy for membrane permeability (coefficient of determination (R2): 0.99) and membrane selectivity (R2: 0.80). The Shapley Additive exPlanation (SHAP) method was utilized to evaluate the effects of different LBL NF membrane fabrication conditions on membrane performances. The SHAP method was also used to identify the relationships between polymer structure and membrane performance. Polymers were represented by Morgan fingerprint, which is an effective description approach for developing modeling. Based on the SHAP value results, two reference Morgan fingerprints were constructed containing atomic groups with positive contributions to membrane permeability and selectivity. According to the reference Morgan fingerprint, 204 potential polymers were explored from the largest polymer database (PoLyInfo). By calculating the similarities between each potential polymer and both reference Morgan fingerprints, 23 polymer candidates were selected and could be further used for LBL NF membrane fabrication with the potential for providing good membrane performance. Overall, this work provided new ways both for LBL NF membrane performance prediction and high-performance polymer candidate exploration. The source code for the models and algorithms used in this study is publicly available to facilitate replication and further research. https://github.com/wangliwfsd/LLNMPP/.

Polyelectrolyte Multilayers: An Overview on Fabrication, Properties, and Biomedical and Environmental Applications

Polyelectrolyte multilayers are versatile materials that are used in a large number of domains, including biomedical and environmental applications. The fabrication of polyelectrolyte multilayers using the layer-by-layer technique is one of the simplest methods to obtain composite functional materials. The properties of the final material can be easily tuned by changing the deposition conditions and the used building blocks. This review presents the main characteristics of polyelectrolyte multilayers, the fabrication methods currently used, and the factors influencing the layer-by-layer assembly of polyelectrolytes. The last section of this paper presents some of the most important applications of polyelectrolyte multilayers, with a special focus on biomedical and environmental applications.