Radical Polymerization Of Styrene Research Articles

Functionalized Polyisobutylene and Polyisobutylene‐Based Block Copolymers by Mechanistic Transformation from Cationic to Radical Process

AbstractThe strategy for the preparation of polyisobutylene‐based block copolymers via mechanistic transformation from cationic to radical polymerization is reported. This strategy involves the synthesis of 2‐bromo‐2‐methylpropanoyl‐terminated difunctional polyisobutylene macroinitiator (BiBB‐PIB‐BiBB) via consecutive cationic polymerization, in situ preparation of hydroxyl‐terminated polyisobutylene and its acylation by 2‐bromo‐2‐methylpropanoyl bromide. The Mn2(CO)10−triggered photo‐induced radical polymerization of styrene in bulk using this macroinitiator leads to the formation of multiblock copolymer, while predominantly triblock copolymer is generated during the polymerization of methyl methacrylate. The possibility to functionalize the polyisobutylene by pyrene via photo‐induced radical addition of 1‐bromomethyl pyrene in the presence of Mn2(CO)10 is also demonstrated in this work.

Increased stability of polymer dispersions obtained by heterophase radical polymerization of styrene and MMA in the presence of water-insoluble organosilicon macromeres

It is shown that during the copolymerization of methyl methacrylate with the surfactant comonomer α,ω-dipropylmethacrylatep olidimethylsiloxane with the number of repeating dimethylsiloxane units n = 20 (DPMPDMS), strong interfacial adsorption layers are formed on the surface of polymer–monomer particles formed from microdrops, ensuring the stability of particles to various types of influences.

Effect of Molecular Architecture of Surface-Active Organosilicon Macromers on Their Colloidal Properties in Relation to Heterophasic Radical Polymerization of Styrene and Methyl Methacrylate

The effects of the molecular architecture of water-insoluble organosilicon polymerizable surfactant macromers (SAMs) on their colloidal-chemical characteristics and on their efficiency in heterophase radical polymerization of styrene and methyl methacrylate were studied. It was shown that despite considerable differences in the structure of three synthesized oligomers (linear α,ω-dipropylmethacrylatepolydimethylsiloxane with a number of repeated siloxane units n = 20—l-SAM; branched γ-methacryloxypropyl containing dimethylsiloxane oligomer—b-SAM; and “spherical” oligo-(γ-methacryloxypropyl)silsesquioxane—s-SAM), the colloidal-chemical characteristics (interfacial tension, layer thickness, adsorption, etc.) were rather similar. In particular, they all form “thick” multimolecular adsorption layers on the toluene–water interphase. All three SAMs were shown to act as effective colloidal stabilizers in heterophase radical polymerization of styrene and methyl methacrylate, which resulted in one-step preparation of large (0.5–1.5 µm) polymer particles with narrow particle size distribution. The obtained results are consistent with the published data on the use of water-insoluble polymerizable oligomers of various chemical structures on the heterophase radical polymerization. The use of these colloidal stabilizers may be considered as an effective way to obtain stable suspensions with large particles and narrow particle size distribution.

Transfer Learning of Full Molecular Weight Distributions via High-Throughput Computer-Controlled Polymerization.

The skew and shape of the molecular weight distribution (MWD) of polymers have a significant impact on polymer physical properties. Standard summary metrics statistically derived from the MWD only provide an incomplete picture of the polymer MWD. Machine learning (ML) methods coupled with high-throughput experimentation (HTE) could potentially allow for the prediction of the entire polymer MWD without information loss. In our work, we demonstrate a computer-controlled HTE platform that is able to run up to 8 unique variable conditions in parallel for the free radical polymerization of styrene. The segmented-flow HTE system was equipped with an inline Raman spectrometer and offline size exclusion chromatography (SEC) to obtain time-dependent conversion and MWD, respectively. Using ML forward models, we first predict monomer conversion, intrinsically learning varying polymerization kinetics that change for each experimental condition. In addition, we predict entire MWDs including the skew and shape as well as SHAP analysis to interpret the dependence on reagent concentrations and reaction time. We then used a transfer learning approach to use the data from our high-throughput flow reactor to predict batch polymerization MWDs with only three additional data points. Overall, we demonstrate that the combination of HTE and ML provides a high level of predictive accuracy in determining polymerization outcomes. Transfer learning can allow exploration outside existing parameter spaces efficiently, providing polymer chemists with the ability to target the synthesis of polymers with desired properties.

Dl-Methionine-Mediated Reversible Deactivation Radical Polymerization of Styrene and Methyl Methacrylate.

Reversible deactivation radical polymerization (RDRP) is a facile and highly efficient technique for the synthesis of well-defined polymer with precise structure. dl-Methionine (Met) as a RDRP control agent is described and assessed for RDRP of styrene (St) and methyl methacrylate (MMA) with AIBN as radical initiator at 75°C, which enables excellent control of this polymerization. The addition of dl-Methionine significantly decreased the dispersity (Đ) of the polymers for both monomers and first-order linear kinetic plots of polymethyl methacrylate (PMMA) are observed in DMSO. Considering the heat resistance of dl-Methionine, kinetic studies indicate that polymerization develops at a faster rate at higher reaction temperature (100°C) with the same dl-Methionine content. Well-defined polymethyl methacrylate-block-polystyrene (PMMA-block-PSt) is successfully achieved by the chain extension reaction that demonstrates the high end fidelities of this polymerization approach. The system allows the use of dl-Methionine, a rich source and easily synthesized agent, to mediate RDRP strategy.

Synthesis and electrical characterization of poly[(linoleic acid)‐g‐(styrene)‐g‐(ε‐caprolactone)] graft copolymers as gate insulator for OFET devices

AbstractThis study reports a one‐pot process used to synthesize poly[(linoleic acid)‐g‐(styrene)‐g‐(ε‐caprolactone)] (PLina‐g‐PSt‐g‐PCL) graft copolymers. The process was carried out by combining the atom transfer radical polymerization of styrene with the ring‐opening polymerization of ε‐caprolactone from polymeric linoleic acid having hydroxyl groups and bromine groups in the main chain. The characterization of the products was achieved using proton nuclear magnetic resonance, size‐exclusion chromatography, Fourier transform infrared spectroscopy, thermogravimetric analysis, and differential scanning calorimetry techniques. Subsequently, an organic field effect transistor (OFET) was fabricated with PLina‐g‐PSt‐g‐PCL graft copolymers as the insulator layer. Poly(3‐hexylthiophene) (P3HT) was used as the active layer and prepatterned OFET substrates were used as the welding/discharge electrodes. To measure capacitance, an ITO/P3HT/PLina‐g‐PSt‐g‐PCL/Al structure was prepared using the same method. To obtain output and transfer current–voltage characteristics, electrical characterizations of OFET devices were conducted in darkness and an atmosphere of air. From a capacitance–frequency plot, the key characteristics of the devices, including the threshold voltage (VTh), field effect mobility, and current on/off ratio (Ion/off), were derived. The fundamental electrical parameters in the fabricated OFET devices based on styrene concentration were thoroughly examined. It was observed that the produced PLina‐g‐PSt‐g‐PCL OFETs display positive device characteristics such as low VTh, exceptional mobility, and Ion/off values. © 2023 The Authors. Polymer International published by John Wiley & Sons Ltd on behalf of Society of Industrial Chemistry.

Stochastic Modelling and Simulation of Free Radical Polymerization of Styrene in Microchannels using a Hybrid Gillespie Algorithm

Most recently, the production of polystyrene by Free Radical Polymerization (FRP) via microchannels has been a subject of core interest due to the efficiency of a micro-or milli-reactor brings. In addition, especially in pilot experimentations, a micro or milli-reactor has been known widely to be efficient in monitoring the microstructural end-use features or properties of the polymer as the chain propagates and ultimately terminates. However, the limitations posed by using micro or milli-reactors in process intensification such as clogging of pores can be a bottleneck when tracking the common phenomena associated with FRP such as cage, gel, and glass effects. In this work, the simulation of the synthesis of polystyrene in FRP via microchannels is computed using a robust and time-efficient hybrid Gillespie Algorithm (GA) or Hybrid Stochastic Simulation Algorithm (HSSA). The obtained results of the end-use properties of polystyrene such as Monomer conversion, Polydispersity Index, Number-Average Molar Mass and Weight Average Molar Mass were compared to experimental data. The simulation results agree well with the experimental results reported in this work. Hence, stochastic simulations prove to be an effective tool in making decisions in the context of process intensification of chain growth polymerization reactions even at a large scale.

Correntropy based Elman neural network for dynamic data reconciliation with gross errors

BackgroundMeasurement information in chemical processes is inevitably corrupted. Dynamic data reconciliation is an effective method to improve the quality of noisy measurement data. However, except for random errors, possibly gross errors are usually present in the measurement data, which may result in the deterioration and even failure of process control and optimization. MethodsConsidering the problem that dynamic mathematical models of some complex and unknown processes are difficult or impossible to be obtained, this paper combines the neural network with the correntropy estimator to design a robust dynamic data reconciliation scheme for unknown dynamic systems corrupted by both random and gross errors. The correntropy estimator is taken as a new objective function to form the robust Elman neural network (ENN). Furthermore, the processes of weight learning and parameter optimization are designed and described in detail based on the correntropy estimator. FindingsThe performance of the proposed robust ENN is demonstrated through its application on the free radical polymerization of styrene. With mixed gross errors, the mean squared error decreases more than 14-fold and falls below one ten-thousandth. Comparisons with other approaches show that the proposed method can effectively suppress the influence of gross errors and greatly improve the dynamic behavior of systems.

2,4,5,6-Substituted 4,5-dihydro-1,2,4,5-tetrazin-3(2H)-ones as non-classical initiators of controlled radical polymerization of styrene

2,4,5,6-Substituted 4,5-dihydro-1,2,4,5-tetrazin-3(2H)-ones as non-classical initiators of controlled radical polymerization of styrene

Synthesis and sorption properties of organo-mineral sorbents based on poly(styrene-b-4-vinylpyridine) copolymer

New organo-mineral composites SiO2/poly(styrene-b-4-vinylpyridine) were obtained by adsorption of block- copolymers poly(styrene-b-4-vinylpyridine) with molar ratios of styrene (St) and 4-vinylpyridie (4-VP) St:4-VP = 1:4 and St:4-VP = 1:5 from THF solution onto silica gel surface. Block-copolymers were synthesized by controlled radical polymerization of styrene with RAFT agent and further copolymerization with 4-vinylpyridine. Also blok-copolymer with thiol end-group was obtained and has been employed for preparation of the composite. Composition of the block-copolymers and surface morphology of composites obtained were determined using 1H NMR and FT-IR spectroscopy, differential scanning calorimetry, thermogravimetric analysis and scanning electron microscopy. It was established that sorption capacity of the organo-mineral composites toward Pb(ІІ), Fe(ІІІ) and Cu(ІІ) ions is in 2–4 times higher in comparison with parent silica gel.

Photo-induced atom transfer radical polymerization of styrene using a highly active claw-type Schiff-base ligand

The use of a tripodal Schiff base, tris[N-(2-(4-(dimethylamino)pyridylmethyl)-2-iminoethyl]amine (PyNMe23Tren), as a highly active claw-type ligand for photo-induced atom transfer radical polymerization (Photo-ATRP) is reported. CuBr2 / PyNMe23Tren is employed as the catalyst for Photo-ATRP of styrene (St) under the irradiation of visible or ultraviolet light. Well-defined polystyrene (PSt) could be synthesized with high chain-end functionality confirmed by in situ chain extension and PSt-Br macroinitiator for the secondary polymerization of St. Through switching the light “on” and “off”, temporal control of Photo-ATRP was successfully demonstrated. After the polymerization, the reaction system appeared stratification and the upper layer PSt could be facilely separated from the system.

Unscented Kalman Filter-Based Robust State and Parameter Estimation for Free Radical Polymerization of Styrene with Variable Parameters.

The free radical polymerization of styrene (FRPS) is a complex process system with uncertain parameters in its mechanistic model. When the reaction conditions are switched, or the reaction process generates faults, the parameters will change. Therefore, state and parameter estimation (SPE) becomes an important part of the process monitoring and process control for free radical polymerization of styrene. The unscented Kalman filter (UKF) is widely used for nonlinear process systems, but it rarely considers the problem of model parameter uncertainty. UKF can be used for SPE, called UKF-based SPE (UKF-SPE), where the parameters are usually estimated simultaneously as an extension of the state space. However, when the parameters change with system switching, the traditional UKF-SPE cannot detect and track the parameter changes in time, and inaccurate parameters generate modeling errors. To deal with the problem, a UKF-based robust SPE method (UKF-RSPE) for the free radical polymerization of styrene with variable parameters is proposed, introducing a parameter testing criterion based on hypothesis testing and moving windows to directly detect whether the parameters have changed. Based on the detection results, a gradient descent method with adaptive learning rate is used to iteratively update the parameters to speed up the tracking of the parameters and to obtain more accurate parameters and states. Finally, the proposed UKF-based robust SPE is applied to free radical polymerization of styrene in a jacketed continuous stirred tank reactor. The experimental results verify the effectiveness and robustness of the method, which can track the parameters faster and obtain more accurate states.

Gel-Permeation Chromatography as a Tool for the Real-Time-Estimation of the Chain length Distribution in a Polymerization Reactor

Abstract The knowledge of the chain length distribution (CLD) during the operation in a polymerization reactor is necessary in order to control polymer quality. Model-based measurement methods (Kalman filter) provide the possibility of reconstructing on-line not directly accessible process states from easily available measurements. However, the presence of model inaccuracies or disturbances influencing primarily the CLD demand additional measurement information about CLD. An extended Kalman filter composed of two decoupled filters and considering Gel-Permeation chromatographic, (GPC), measurements for the continuous estimation of the CLD in the case of free radical polymerization of styrene is discussed. Although the existence of a time delay, due to the GPC analysis, the consideration of this measurement in the filter algorithm produces the local observability of the states characterizing the CLD, allows continuous access to the CLD and its characteristic values and provides a periodical adaption of the CLD to the reality.

Synthesis, characterization, and performance evaluation of novel terpolymers as pour point depressors and paraffin inhibitors for Egyptian waxy crude oil

Recently, researchers have shown an increased interest in wax precipitation prevention techniques. Herein, novel reactive terpolymer was synthesized by free radical polymerization of styrene, dodecyl acrylate, and maleic anhydride monomers. After that, esterification and imidation modifications for the synthesized terpolymer were performed. The pristine and modified terpolymers various characteristics were investigated by FTIR, 1H-NMR, GPC, and TGA techniques. The performance of the synthesized modified terpolymers as pour point depressors and paraffin inhibitors for the Egyptian waxy crude oil were evaluated. Additionally, the influence of their addition on the wax crystals modification was examined by polarizing optical microscopy. The results show that all the synthesized additives exhibited an efficient depressive effect on the waxy crude oil (i.e., low pour point depressant and high paraffin inhibition). Styrene dodecyl acrylate maleic anhydride imide (IDA) exhibited the best performance at optimum dosage of 200 ppm as it depresses the pour point by 17 °C from the blank and achieved a paraffin inhibition of 95%. So, the synthesized terpolymers can be considered as promising and applicable additives for depressing the pour point and inhibiting the paraffinic precipitates for the waxy crude oils.

P-Quinones in the radical polymerization of styrene

p-Quinones in the radical polymerization of styrene

EFFECT OF ACETYL ACETONE ON RADICAL POLYMERIZATION OF VINYL MONOMERS INITIATED BY BENZOYL PEROXIDE

The radical polymerization of styrene and methyl methacrylate (MMA) initiated by benzoyl peroxide (BР) with the addition of 10, 20, 50, and 80% of acetylacetone (AA) mixed with a monomer was studied. It was found that the rate of the polymerization process increases in the presence of a certain amount of AA in the system (³ 50% of the monomer). This is due to the fact that AA accelerates the decomposition of BP, while removing it from the system in the form of non-radical products, and the initiating function is performed by acetylacetonate radicals, which are formed upon interaction with BP. The incorporation of acac fragments into the polymer chain has been proved by IR and 1H NMR spectroscopy. It was found that these groups in the composition of the polymer interact with the p-system of benzene rings of polystyrene. The second reason for the accelerating action is the formation of complexes between the monomer and AA, in which the additive has an acceptor effect, leading to the facilitation of the breaking of double bonds in the monomer. It was shown that MMA has a stronger effect on AA polymerization, because forms stronger complexes with the enol form of AA, which requires a longer time for the radical to leave the complex. In this regard, during its polymerization, induction periods are observed, the duration of which is directly proportional to the concentration of AA in a mixture with MMA. It was revealed that another feature of the effect of AA on radical polymerization is its participation in chain transfer reactions, which does not decrease the rate of the process, but only leads to a decrease in the molecular weight of the products. This makes it an effective regulator of polymer molecular weights. The paper proposes a scheme for the polymerization of vinyl monomers, initiated by BP with the addition of AA.

A kinetic modeling framework for the peroxide-initiated radical polymerization of styrene in the presence of rubber particles from recycled tires

A novel modeling framework is presented for the peroxide-initiated radical polymerization of styrene, in the presence of ground-tire rubber particles. The model takes into account the previously observed effects of the rubber particles, and their highly-reactive additives, on the course of the polymerization. To this end, a generalized kinetic mechanism is proposed, on the basis of a typical styrene homopolymerization scheme, including also a series of additional chemical reactions that are implemented to describe the deviation of the system from the respective homopolymerization case when ground-tire rubber is present in the mixture. This deviation is mainly manifested through an accelerated peroxide decomposition and significant retardation and inhibition of the reaction and displays a non-linear dependence on the contents of rubber particles and initiator. The proposed model succeeds in predicting this behavior under different reaction conditions, while its generality makes it suitable for implementation in other similar grafting polymerization systems.

One-pot exfoliation and surface functionalization of MoS2: A potential nanofiller to overcome the brittleness of polystyrene (PS)

In this communication, we describe a simple one-pot approach to exfoliate and functionalize MoS2 (f-MoS2) via liquid-phase exfoliation (LPE) starting from bulk MoS2 dispersed in styrene/N-methyl pyrrolidone (NMP) solution using azobisisobutyronitrile (AIBN) as a radical initiator. The colloidal stability of f-MoS2 is achieved due to an in situ radical polymerization of styrene and functionalization on the edge sites of MoS2. Thermogravimetric analysis (TGA) showed the presence of 8.23 wt% of functionalized MoS2. The f-MoS2 was then incorporated in polystyrene (PS) matrix at different loadings (15 wt%, 30 wt% and 60 wt%) by a solution-based process using toluene as solvent. The f-MoS2/PS nanocomposites exhibited a good polymer/nanofiller interfacial interaction and promoted significant thermal stabilization in PS increasing, in our best case, the T-5% and T-50% temperatures by 91 °C and 15 °C, respectively, compared to neat PS. When increasing the f-MoS2 loading, we also noticed a dramatic decrease on the glass transition temperature (Tg) of the f-MoS2/PS nanocomposites, which has a direct correlation on its mechanical properties. As f-MoS2 loading increases the Young's modulus decreases, compared to neat PS. However, at 60 wt% f-MoS2 loading, the nanocomposite showed basically the same Young's modulus of neat PS and the strain at break increased more than a 150%, which indicates a significant load transfer between the polymer-nanofiller interface. Therefore, the f-MoS2 is a potential candidate to overcome the brittleness of PS. In addition, this simple one-pot approach opens pathways for new developments of functionalized MoS2.

Atom Transfer Radical Polymerization of Styrene and Acrylates: Effects of Catalyst, Ligand, Solvent, and Initiator

Well-defined polystyrenes were successfully prepared by the CuX/(dN)bpy or CuX/ PMDETA catalyzed atom transfer radical polymerization of styrene using 1-phenylethyl bromide (1-PEBr) or benzyl bromide (BnBr) as initiators. We found that the CuX/PMDETA catalyzed ATRP of styrene proceeded faster than CuX/(dN)bpy catalyzed counterpart in bulk, diphenyl ether (DPE) and anisole. Using CuX/(dN)bpy catalyst, well-defined polystyrenes were obtained with good chain-end functionalities and low polydispersity (Mw/Mn <1.5) compared to CuX/PMDETA catalyst. The CuBr/PMDETA catalyzed ATRP of n-butyl acrylate (nBA), n-butyl methacrylate (nBMA), and tert-butyl methacrylate (tBMA) were also proceeded in a controlled manner. The molecular structure and molecular weight of polymers were determined by proton nuclear magnetic resonance (1H NMR) spectroscopy and size exclusion chromatography (SEC), respectively.

Model development and control of an auto-refrigerated polystyrene polymerization reactor

Dynamic model development and control of an existing operating industrial continuous bulk free radical styrene polymerization process are carried out to evaluate the performance of auto-refrigerated CSTRs (continuous stirred tank reactors). One of the most difficult tasks in polymerization processes is to control the high viscosity reactor contents and heat removal. In this study, temperature control of an auto-refrigerated CSTR is carried out using an alternative control scheme which makes use of a vacuum system connected to the condenser and has not been addressed in the literature (i.e. to the best of our knowledge). The developed model is then verified using some experimental data of the real operating plant. To show the heat removal potential of this control scheme, a common control strategy used in some previous studies is also simulated. Simulation results show a faster dynamics and superior performance of the first control scheme which is already implemented in our operating plant. Besides, a nonlinear model predictive control (NMPC) is developed for the polymerization process under study to provide a better temperature control while satisfying the input/output and the heat exchanger capacity constraints on the heat removal. Then, a comparison has been also made with the conventional proportional-integral (PI) controller utilizing some common tuning rules. Some robustness and stability analyses of the control schemes investigated are also provided through some simulations. Simulation results clearly show the superiority of the NMPC strategy from all aspects.