Elucidation of Structure–Reactivity Trends in Free Radical Copolymerization Reactivity Ratios Using Data Science Methods

Problems in the current experimental determination of radical reactivity ratios (i.e., 's values') in free-radical copolymerization and the resulting limited physical meaning of these reactivity ratios are highlighted in the present work. It is exemplified that the radical reactivity ratios obtained via fitting of average propagation rate coefficients are very sensitive to small uncertainties in monomer reactivity ratios and homopropagation rate coefficients. Furthermore, the failure to select an appropriate modelling method, and to design experiments so as to satisfy its assumptions, may lead to incorrect parameter estimates. These problems result in large uncertainties in the measured values of the radical reactivity ratios, which in turn lead to large uncertainties in calculated ratios of propagating radical concentrations. This suggests that experimental determinations of the relative radical concentrations may lead to complimentary means for obtaining information on radical reactivity ratios, and possible ways of obtaining this information through catalytic chain transfer experiments are discussed.

On the determination of monomer reactivities in copolymerization

The copolymerization reactivity ratios for 2-ethoxyethyl methacrylate (EOEMA) with dodecyl methacrylate (DDMA) or styrene (ST) were estimated. Polymerization was performed by using tert-butyl peroxy-2-ethylhexanoate (0.01 mol dm−3) as initiator, isothermally (70 °C) to low conversions (< 10 wt.%) in a wide range of copolymer compositions (every 10 mol-% steps). For the DDMA/EOEMA copolymerization both monomers prefer to react with EOEMA: r (DDMA) = 0.82 and r (EOEMA) = 1.26 with r (DDMA) × r (EOEMA) = 1, which results in the random copolymerization. For the ST/EOEMA copolymerization reactivity ratios are r (ST) = 0.59 and r (EOEMA) = 0.49 indicating a higher reactivity with opposite monomer, while the alternation tendency is not highly pronounced. The probabilities for formations of dyad and triad monomer sequences in dependence on monomer compositions were calculated from the obtained reactivity ratios. With the share increase of ST or DDMA in copolymers surface properties changed from hydrophilic to hydrophobic. Glass transition temperature of copolymer increased with the increase of ST and decrease of DDMA. The molar mass distribution and thermal degradation of synthesized copolymers were also determined and discussed. The reactivity ratios enable optimization of copolymer properties for a given application as polyelectrolytes, drug delivery systems and multifunctional additives for improvement of rheological properties of lubricating oils.

Copolymers of poly( n-alkyl acrylates): synthesis, characterization, and monomer reactivity ratios

It is shown that it is possible to predict the reactivity ratios for the copolymerization of a given monomer pair if each monomer has been separately copolymerized with a third monomer, and the product of the reactivity ratios of one of these separate copolymerizations is equal to unity. This latter condition is frequently met in ionic copolymerizations and is sometimes true in free radical copolymerizations. Literature data for five trios of monomer are examined to show the validity of the predictions.

Copolymers of acrylamide ( AM ) and acrylic acid ( AA) were prepared by precipitation polymerization method at 65 °C in the ethyl acetate as solvent. Copolymer composition was determined by elemental analysis. Monomer reactivity ratios were determined in low conversions. Mayo-Lewis, Finemann-Ross, Inverted Finemann-Ross, Ezrielev-Brokhina-Roskin, Kelen-Tudos, Extended Kelen-Tudos and Mao-Huglin methods, as linear methods, and Tidwell-Mortimer, as nonlinear method, were applied to calculate rAM and rAA r reactivity ratios. Monomer reactivity ratios of AM and AA were obtained 0.46 and 0.28, respectively. Comparing of reactivity ratios of AM and AA in this work by other solvents showed that hydrogen bonding and ionic strength are important parameters that can affect the reactivity ratios of monomers. Moreover, microstructure of copolymers was determined using reactivity ratios and conditional probability based on the kinetic model for free-radical polymerization.

Sequence control is critical for tuning polymer properties in high-end applications, where reactivity ratios serve as key parameters for analyzing and regulating sequences. Nevertheless, traditional determination methods exhibit low experimental efficiency and are typically confined to two-component copolymerization. Here, we develop a machine learning platform, which leverages a novel design of "reactivity ratio fingerprints" (rFPs) to determine reactivity ratios in binary and ternary copolymerizations. Deep learning models trained on millions of rFPs enable highly efficient (millisecond-level) determination from sparse experimental data (random monomer structures, arbitrary reaction design). This approach demonstrates outstanding versatility to analyze reactivity ratios under diverse conditions (e.g., temperature, solvent). Notably, rFP-guided reaction design promotes on-demand sequence tailoring, compatible with a wide range of binary and ternary monomer combinations. Kinetic investigations and glass transition characterizations support the formation of varied sequence structures, facilitating the identification of binary and ternary azeotropic copolymerizations. This work not only unveils an attractive strategy for determining reactivity ratios but also offers a generalizable framework for sequencing complicated chain structures toward property engineering.

An understanding of the monomer reactivity ratios is extremely useful for tailoring copolymers with desired compositions for a diversity of end-use applications. In situ ATR-FTIR was employed to monitor the initial formation of copolymers of ethylene and vinyl acetate (VAc) during polymerization in the “green” solvent supercritical carbon dioxide (scCO2). To obtain the copolymer composition, a calibration curve of the absorbance ratio 1737/2929 cm−1 versus vinyl acetate content of poly(ethylene-co-vinyl acetate) (PEVA) was established, covering the range of 5−98 wt %. The reactivity ratios for copolymerization of ethylene and VAc in scCO2 were determined using both the Kelen−Tudos and the nonlinear least-squares (NLLS) methods. Off-line 1H NMR analysis was also utilized for obtaining the copolymer composition, by which the determined reactivity ratios were compared with the ones obtained using in situ FTIR. The effect of reaction temperature and pressure on reactivity ratios was examined at 50 and 72 °C and at 13.8 and 27.6 MPa, with the lower temperature and higher pressure conditions increasing the reactivity ratios slightly. In situ FTIR was found to be able to accurately measure the reactivity ratios, and both the Kelen−Tudos and NNLS methods gave similar results. The obtained reactivity ratios will promote the application of the green solvent scCO2 in the production of the widely commercialized copolymer PEVA.

Controlled activity polymers. X synthetically tailored monomers and copolymers with hydrolytically-labile pendent esters of allelopathic phenols

Copolymerization of benzyl methacrylate (BMA) with maleic anhydride (MA), initiated by 2,2′‐azoisobutyronitrile at 70°C in chloroform or acetonitrile, were investigated. The complex formation between the two monomers in chloroform was studied by 1H NMR spectroscopy. The stability constant of the complex was found to be 0,25 l.mol−1. The following copolymerization reactivity ratios were found: in chloroform: rBMA = 0,188 ± 0,035 and rMA = 0,003 ± 0,005, in acetonitrile: rBMA = 0,116 ± 0,093 and rMA = 0,231 ± 0,027. By 1H NMR investigations it could be shown that the results correlate with the changes of the reactivity ratios depending on the solvent used.

On the preparation of acrylic acid/vinyl acetate copolymers with constant composition — 1. Copolymerization reactivity ratios

ObjectiveThe purpose of this research is to identify how data science is applied in suicide prevention literature, describe the current landscape of this literature and highlight areas where data science...

Copolymers of furfuryl acrylate (A) with 2-hydroxyethyl methacrylate (H) were prepared by free radical copolymerization in DMF solution at 50°C, using 2,2'-azobisisobutyronitrile (AIBN) as initiator. The reactivity ratios of both monomers were calculated according to the general copolymerization equation using the Fineman-Röss and Kelen-Tüdos 1inearization methods, as well as the Tidwell-Mortimer non linear least-squares treatment and the Monte Carlo random method. The reactivity ratios obtained were rA = 0.93 and rH = 1.42. Similar results were obtained by both, the Monte Carlo and the non-linear least squares methods. The microstructure of copolymer chains based on the first order Markov statistics is described.

The determination of reactivity ratios is simplified by using an excess of one monomer (M1) at a time large enough that the copolymers will have a very small content of the other monomer (M2). In this case chain propagation takes place almost exclusively by addition to polymer radicals with a terminal M1‐unit (P) and monomer consumption by propagation of P may be neglected. One reactivity ratio (r1) is obtained from monomer conversions by means of a simple integrated equation which is valid up to high conversions. A calculation is proposed in order to account for the neglected propagation via P. The other reactivity ratio (r2) is obtained from copolymerizations with excess M2.As the new method uses an integrated form of the MAYO equation it permits the determination of monomer conversions directly by gas chromatography of unreacted monomers. Thus, if desired, analysis of copolymers can be avoided. The gas chromatographic method has been tested with the radical copolymerization of styrene and methyl methacrylate.In ternary and quaternary copolymerizations the new method offers particular advantages.

This paper proposes a new method for calculating the monomer reactivity ratios for binary copolymerization based on the terminal model. The original optimization method involves a numerical integration algorithm and an optimization algorithm based on k-nearest neighbour non-parametric regression. The calculation method has been tested on simulated and experimental data sets, at low (<10%), medium (10–35%) and high conversions (>40%), yielding reactivity ratios in a good agreement with the usual methods such as intersection, Fineman–Ross, reverse Fineman–Ross, Kelen–Tüdös, extended Kelen–Tüdös and the error in variable method. The experimental data sets used in this comparative analysis are copolymerization of 2-(N-phthalimido) ethyl acrylate with 1-vinyl-2-pyrolidone for low conversion, copolymerization of isoprene with glycidyl methacrylate for medium conversion and copolymerization of N-isopropylacrylamide with N,N-dimethylacrylamide for high conversion. Also, the possibility to estimate experimental errors from a single experimental data set formed by n experimental data is shown.