Self-Initiated Butyl Acrylate Polymerizations in Bulk and in Solution Monitored By In-Line Techniques

First principles assessment of solvent induced cage effects on intramolecular hydrogen transfer in the free radical polymerization of acrylates

We investigate the rate constant of poly-butyl acrylate backbiting between 310 and 510 K using semi-empirical metadynamics in the gas phase, bulk and solution. The simulations in the condensed phase are performed through a hybrid quantum mechanics/molecular mechanics approach. The free energy landscape associated with the reactive events under vacuum and in the condensed phase is used to correct harmonic transition state theory (TST) rate constants. The Arrhenius parameters so determined are introduced in a semi-detailed mechanistic kinetic mechanism of butyl acrylate polymerization in bulk and in solution, allowing it to test how the butyl acrylate polymerization rate is affected by solvent-induced cage effects on backbiting. The results show that the backbiting rate constant is higher in the condensed phase than in the gas phase. In addition, a twofold increase is observed in xylene compared to the bulk. These results differ significantly from previous theoretical calculations, especially at high temperatures, aligning better with experimental rate measurements. The semi-detailed model, incorporating our calculated rate coefficients, is validated against monomer concentration profiles from bulk and solution polymerizations in various reactor configurations, demonstrating good agreement with experimental data. This study paves the way for developing detailed kinetic models in the condensed phase using a priori kinetic parameters derived from molecular simulations, thus widening their range of applicability beyond the one experimentally accessible.

AI-Based Forecasting of Polymer Properties for High-Temperature Butyl Acrylate Polymerizations

High-temperature polymerizations involving self-initiation of the monomer are attractive because of high reaction rate, comparable lower viscosities, and no need for an additional initiator. However, the polymers obtained show a more complex microstructure, e.g., with specific branching levels or significant amounts of macromonomer. Simulations of the polymerization processes are powerful tools to gain a deeper understanding of the processes and the elemental reactions at the molecular level. However, simulations can be computationally demanding, requiring significant time and memory resources. Therefore, this study aims at applying AI-based forecasting of tailored polymer properties and using a kinetic Monte Carlo simulator for the generation of training and test data. The applied machine learning (ML) models (random forest and kernel density (KD) regression) predict monomer concentration, macromonomer content, and full molar mass distributions as a function of time, as well as the average branching level with an excellent performance (R 2 (coefficient of determination) > 0.99, MAE (mean absolute error) < 1% for kernel density regression). This study explores the number of training data needed for reliable and accurate predictions in ML models. Explainability methods reveal that the importance of input variables in ML models aligns with expert knowledge.

Effect of Novel Compound Redox Initiators on Polymerization Mechanism and Mechanical Properties of Acrylic Resin

Aiming at the problems of long reaction time and the risk of explosion polymerization of acrylate resin, a small amount of ferrocene (Fc) is added to the existing dibenzoyl peroxide (BPO)/N,N-dimethylaniline (DMA) initiators, and the compound redox initiators (BPO/DMA/ (Fc)) are proposed for acrylate resin polymerization at room temperature. The effect of the content of Fc in the resin on the reaction efficiency and the molding quality of products is researched, and the initiation mechanism of the compound redox initiators is analyzed. It is found that with the addition of Fc, the reaction time of the resin can be shortened by 68% at maximum, the heat release temperature of the resin can be reduced by 40% at maximum, the molecular weight of the reaction products can be increased by 74% at maximum, the tensile and bending properties of the resin castings are increased by 23% and 35% at maximum, respectively, and the bending strength and bending modulus are increased by 57% and 27% at maximum, respectively. The compound redox initiators proposed in this paper can improve the molding efficiency and quality of the product, lay a foundation for the application of acrylic resin in the field of pultrusion molding, perfusion molding, and other in situ molding of thermoplastic composites.

Polymerizable 2-Propionic-3-methylmaleic Anhydrides as a Macromolecular Carrier Platform for pH-Responsive Immunodrug Delivery

The design of functional polymers coupled with stimuli-triggered drug release mechanisms is a promising achievement to overcome various biological barriers. pH trigger methods yield significant potential for controlled targeting and release of therapeutics due to their simplicity and relevance, especially upon cell internalization. Here, we introduce reactive polymers that conjugate primary or secondary amines and release potential drugs under acidic conditions. For that purpose, we introduced methacrylamide-based monomers with pendant 2-propionic-3-methylmaleic anhydride groups. Such groups allow the conjugation of primary and secondary amines but are resistant to radical polymerization conditions. We, therefore, polymerized 2-propionic-3-methylmaleic anhydride amide-based methacrylates via reversible addition-fragmentation chain transfer (RAFT) polymerization. Their amine-reactive anhydrides could sequentially be derivatized by primary or secondary amines into hydrophilic polymers. Acidic pH-triggered drug release from the polymeric systems was fine-tuned by comparing different amines. Thereby, the conjugation of primary amines led to the formation of irreversible imide bonds in dimethyl sulfoxide, while secondary amines could quantitatively be released upon acidification. In vitro, this installed pH-responsiveness can contribute to an effective release of conjugated immune stimulatory drugs under endosomal pH conditions. Interestingly, the amine-modified polymers generally showed no toxicity and a high cellular uptake. Furthermore, secondary amine-modified immune stimulatory drugs conjugated to the polymers yielded better receptor activity and immune cell maturation than their primary amine derivatives due to their pH-sensitive drug release mechanism. Consequently, 2-propionic-3-methylmaleic anhydride-based polymers can be considered as a versatile platform for pH-triggered delivery of various (immuno)drugs, thus enabling new strategies in macromolecule-assisted immunotherapy.

Advances in continuous polymer analysis in flow with application towards biopolymers

Biopolymers, polymers derived from renewable biomass sources, have gained increasing attention in recent years due to their potential to replace traditional petroleum-based polymers in a range of applications. Among the many advantages of biopolymers can be included their biocompatibility, excellent mechanical properties, and availability from renewable feedstock. However, the development of biopolymers has been limited by a lack of understanding of their properties and processing behaviours. Continuous analysis techniques have the potential to hasten progress in this area by providing real-time insights into the properties and processing of biopolymers. Significant research in polymer chemistry has focused on petroleum-derived polymers and has thus provided a wealth of synthetic and analytical methodologies which may be applied to the biopolymer field. Of particular note is the application of flow technology in polymer science and its implications for accelerating progress towards more sustainable and environmentally friendly alternatives to traditional petroleum-based polymers. In this mini review we have outlined several of the most prominent use cases for biopolymers along with the current state-of-the art in continuous analysis of polymers in flow, including defining and differentiating atline, inline, online and offline analysis. We have found several examples for continuous flow analysis which have direct application to the biopolymer field, and we demonstrate an atline continuous polymer analysis method using size exclusion chromatography.

Graphical abstract

Coupling Kinetic Modelling with SAOS and LAOS Rheology of Poly(n-Butyl Acrylate)

A kinetic model based on fundamentals of radical polymerization and literature known rate parameters for the polymerization of n-butyl acrylate is validated against molecular analysis and rheological data. The model is used to predict conversion, molar mass distribution, and branching densities in form of short and long chain branching. Rheological measurements of synthesized model polymers are evaluated along the Carreau-Yasuda and Van Gurp-Palmen presentations, allowing to detect small differences in the degree of long chain branching. Contributions of anharmonics to viscoelastic response in large amplitude oscillations are small and differences between the products are dominated by the differences in molar mass.