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Quantitative Structure–Property Relationship Model for Predicting the Propagation Rate Coefficient in Free-Radical Polymerization

Yajuan Shi, Mengxian Yu, Jie Liu, Fangyou Yan, Zheng‐Hong Luo, Yin‐Ning Zhou

2022Macromolecules27 citationsDOI

Abstract

In this work, a generalized quantitative structure–property relationship (QSPR) model is developed for predicting kp by using norm index (NI)-based descriptors, which is the so-called kp (T, NI)-QSPR model. The as-developed model enables the use of one unified formula to calculate kp values for a wide range of monomers, including linear and branched (meth)acrylates, nitrogen-containing methacrylates, hydroxyl-containing (meth)acrylates, and so forth. Importantly, the model exhibits excellent performance when compared with the benchmark kp values from the literature, and model validation proves the reasonable goodness-of-fit, robustness, predictivity, and reliability of the as-developed model. Meanwhile, the Arrhenius parameters show a clear kinetic behavior, indicating that acrylates have smaller fit, robustness, predictivity, and reliability of the as-developed model. Meanwhile, the Arrhenius parameters show a clear kinetic behavior, indicating that acrylates have smaller Ea values than methacrylates, which render higher kp values and activities in free-radical polymerization for acrylates. Notably, the model allows the prediction of kp values of monomer mixtures and new monomers. In view of the satisfactory accuracy in determining kp values, it is expected that our proposed method will contribute to the determination of kinetic parameters beyond propagation kinetics for a wide monomer range, and the obtained Arrhenius parameters can further improve the fundamental understanding of radical polymerization kinetics.

Topics & Concepts

Arrhenius equationMonomerRadical polymerizationPolymerizationThermodynamicsRobustness (evolution)ChemistryQuantitative structure–activity relationshipMethacrylateKineticsKinetic energyMaterials sciencePolymer chemistryActivation energyPhysical chemistryPolymerOrganic chemistryPhysicsStereochemistryBiochemistryQuantum mechanicsGeneAdvanced Polymer Synthesis and CharacterizationPhotopolymerization techniques and applicationsMachine Learning in Materials Science
Quantitative Structure–Property Relationship Model for Predicting the Propagation Rate Coefficient in Free-Radical Polymerization | Litcius