pH-detachable polymer brushes formed using titanium−diol coordination chemistry and living radical polymerization (RAFT)

pH-detachable poly(styrene) brushes formed on indium−tin oxide (ITO) glass substrates using metal complex chemistry and reversible addition−fragmentation chain transfer (RAFT) polymerization was described. These pH-detachable polymeric brushes were generated using both “graft-from” and “graft-to” methodologies. The methodologies involved either the surface self-assembly of catechol-functional RAFT agents (graft-from) or catechol-terminal polymer chains (graft-to) onto the ITO substrate via titanium−diol coordination. The stepwise functionalization of the ITO glass surfaces was characterized successfully using X-ray photoelectron spectroscopy (XPS) and contact angle measurement. Poly(styrene) brushes generated using the “graft-from” method were denser than those generated using the “graft-to” method, as exemplified by atom force microscopy (AFM) and quantified using cyclic voltammetry. Poly(styrene) brushes assembled using both methods could be detached easily by manipulating the pH of the brush environment. Cyclic voltammetry was utilized to calculate precisely the surface coverage of the RAFT functionality and polymeric brush density.

Performance analysis of two advanced controllers for polystyrene polymerization in batch reactor

The performance of two advanced model based non-linear controllers is analyzed for the optimal setpoint tracking of free radical polymerization of styrene in batch reactors. Artificial neural network-based model predictive controller (NN-MPC) and generic model controller (GMC) are both applied for controlling the system. The recently developed hybrid model [1] as well as available literature models are utilized in the control study. The optimal minimum temperature profiles are determined based on Hamiltonian maximum principle. Different types of disturbances are artificially generated to examine the stability and robustness of the controllers. The experimental studies reveal that the performance of NN-MPC is superior over that of GMC.

Prediction interval-based modelling of polymerization reactor: a new modelling strategy for chemical reactors

Precise and reliable modelling of polymerization reactor is challenging due to its complex reaction mechanism and non-linear nature. Researchers often make several assumptions when deriving theories and developing models for polymerization reactor. Therefore, traditional available models suffer from high prediction error. In contrast, data-driven modelling techniques provide a powerful framework to describe the dynamic behaviour of polymerization reactor. However, the traditional NN prediction performance is significantly dropped in the presence of polymerization process disturbances. Besides, uncertainty effects caused by disturbances present in reactor operation can be properly quantified through construction of prediction intervals (PIs) for model outputs. In this study, we propose and apply a PI-based neural network (PI-NN) model for the free radical polymerization system. This strategy avoids assumptions made in traditional modelling techniques for polymerization reactor system. Lower upper bound estimation (LUBE) method is used to develop PI-NN model for uncertainty quantification. To further improve the quality of model, a new method is proposed for aggregation of upper and lower bounds of PIs obtained from individual PI-NN models. Simulation results reveal that combined PI-NN performance is superior to those individual PI-NN models in terms of PI quality. Besides, constructed PIs are able to properly quantify effects of uncertainties in reactor operation, where these can be later used as part of the control process. © 2014 Taiwan Institute of Chemical Engineers.

Performance analysis of three advanced controllers for polymerization batch reactor: an experimental investigation

The performances of three advanced non-linear controllers are analyzed for the optimal set point tracking of styrene free radical polymerization (FRP) in batch reactors. The three controllers are the artificial neural network-based MPC (NN-MPC), the artificial fuzzy logic controller (FLC) as well as the generic model controller (GMC). A recently developed hybrid model (Hosen et al., 2011a. Asia-Pac. J. Chem. Eng. 6(2), 274) is utilized in the control study to design and tune the proposed controllers. The optimal minimum temperature profiles are determined using the Hamiltonian maximum principle. Different types of disturbances are introduced and applied to examine the stability of controller performance. The experimental studies revealed that the performance of the NN-MPC is superior to that of FLC and GMC. © 2013 The Institution of Chemical Engineers.

Direct observation of the intergallery expansion of polystyrene–montmorillonite nanocomposites

The intergallery expansion development of a series of differently modified montmorillonite polystyrene nanocomposites was directly observed with time-resolved in situ small-angle X-ray scattering (SAXS) using synchrotron radiation. The results indicated that the interlayer expansion varied depending on the clay modification and the chemical compatibility of the clay modifiers with the styrene monomer. The influence of the differently modified clays on the free radical polymerization was also investigated, particularly the effect on the conversion of styrene and molecular weight evolution of the polymer. On the basis of the kinetic study of the polymerization of styrene in the presence of varied modified clay particles, the intergallery expansion mechanism was postulated and discussed for different composite morphologies. Such studies provide an important guideline for the design of clay modifiers and development of clay–polymer nanocomposites.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.

Synthesis and mechanistic insights of macromolecular assemblies from ABA triblock copolymer blends

Macromolecular assembly of block copolymers into numerous nanostructures resembles self-organization of proteins and cellular components found in nature. In order to mimic nature’s assemblies either to cure a disease or construct functional devices, the organization principles underpinning the emergence of complex shapes need to be understood. In the same vein, this study aimed at understanding morphology evolution in a triblock copolymer blend in aqueous solution. An ABA type amphiphilic triblock copolymer (polystyrene-b-polyethylene oxide-b-polystyrene, PS-b-PEO-b-PS) was synthesized at different compositions via atom transfer radical polymerization (ATRP) and self-assembly behavior of a binary mixture in aqueous solution was studied. Block copolymers that form worms and vesicles in its pristine state was shown to form complex morphologies such as fused rings, “jellyfish”, toroid vesicles, large compound vesicles and large lamellae after blending. The tendency of vesicle-forming block copolymer to form bilayers may be responsible for triggering complex morphologies when mixed with a worm or micelle-forming polymer. In other words, the interplay between curvature effects produced by two distinct polymers with different hydrophobic block lengths results in complex morphologies due to chain segregation within the nanostructure.

A novel water-soluble hydrophobically associating polyacrylamide based on oleic imidazoline and sulfonate for enhanced oil recovery

3-(2-(2-Heptadec-8-enyl-4,5-dihydro-imidazol-1-yl)ethylcarbamoyl)acrylic acid (NIMA), 3-(diallyl-amino)-2-hydroxypropyl sulfonate (NDS), acrylamide (AM) and acrylic acid (AA) were successfully utilized to prepare novel acrylamide-based copolymers (named AM/AA/NIMA and AM/AA/NDS/NIMA) which were functionalized by a combination of imidazoline derivative and/or sulfonate via redox free-radical polymerization. The two copolymers were characterized by infrared (IR) spectroscopy, 1H nuclear magnetic resonance (1H NMR), viscosimetry, pyrene fluorescence probe, thermogravimetry (TG) and differential thermogravimetry (DTG). As expected, the polymers exhibited excellent thickening property, shear stability (viscosity retention rate 5.02% and 7.65% at 1000 s-1) and salt-tolerance (10:000 mg L-1 NaCl: viscosity retention rate up to 17.1% and 10.2%) in comparison with similar concentration partially hydrolyzed polyacrylamide (HPAM). The temperature resistance of the AM/AA/NDS/NIMA solution was also remarkably improved and the viscosity retention rate reached 54.8% under 110 °C. According to the core flooding tests, oil recovery could be enhanced by up to 15.46% by 2000 mg L-1 of the AM/AA/NDS/NIMA brine solution at 80 °C.

Synthesis of Sodium Poly[4-styrenesulfonyl(trifluoromethylsulfonyl)imide]-co-ethylacrylate] Solid Polymer Electrolytes

Sodium-based batteries are being considered to replace Li-based batteries for the fabrication of large-scale energy storage devices. One of the main obstacles is the lack of safe and conductive solid Na-ion electrolytes. A Na-ion polymer based on the (4-styrenesulfonyl(trifluromethylsulfonyl) imide anion, Na[STFSI], has been prepared by a radical polymerization process and its conductive properties determined. In addition, a number of multi-component polymers were synthetized by co-reaction of two monomers: Na[STFSI] and ethyl acrylate (EA) at different ratios. The structural and phase characterizations of the polymers were probed by various techniques (DSC, TGA, NMR, GPC, Raman, FTIR and Impedance spectroscopy). Comparative studies with blends of the homopolymers Na[PSTFSI] and poly(ethylacrylate) (PEA) have also been performed. The polymers are all thermally stable up to 300°C and the ionic conductivity of EA copolymers and EA blends are about 1-3 orders of magnitude higher than that of Na[PSTFSI]. The highest conductivity measured at 100°C was found for Na[PSTFSI-blend-5EA] at 7.9 × 10^-9 S cm^-1, despite being well below its Tg. Vibrational spectroscopy indicates interaction between Na⁺ and the EA carbonyl groups, with a concomitant decrease in the sulfonyl interaction, facilitating Na⁺ motion, as well as lowering Tg.

Nano-capsules of amphiphilic poly (ethylene glycol)-block-poly (bisphenol A carbonate) copolymers via thermodynamic entrapment

The synthesis of amphiphilic poly(ethylene glycol)-block-poly(bisphenol A carbonate) (PEG-b-PC) block copolymer is presented here using a simple bio-chemistry coupling reaction between poly(bisphenol A carbonate) (PC) with a monomethylether poly(ethylene glycol) (mPEG-OH) block, mediated by dicyclohexylcarbodiimide/4-dimethylaminopyridine. This method inherently allows great flexibility in the choice of starting materials as well as easy product purification only requiring phase separation and water washing. Collective data from Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (NMR) and modulated dynamic scanning calorimetry (MDSC) confirmed the successful attachment of the poly(ethylene glycol) (mPEG-OH) and poly(bisphenol A carbonate) (PC) blocks. The preparation of nano-capsules was carried out by sudden addition of water to PEG-b-PC copolymers dispersed in THF, resulting in the controlled precipitation (i.e. thermodynamic entrapment) of the copolymer. Nano-capsules as small as 85 nm ± 30 nm were produced using this simple and fast methodology. We also demonstrate that encapsulating a water-insoluble bisphenol A diglycidyl ether (DGEBA) epoxy resin is possible highlighting the potential use of these capsules as a chemical delivery system.

The quest for single-enantiomer outcomes in free-radical chemistry

A significant challenge facing free-radical chemists is in the area of stereocontrol, specifically the ability to control the direction of reagent attack at a prochiral radical. While significant inroads have been made in the area of diastereoselective radical chemistry, less successful have been attempts to provide truly enantioselective processes. This article highlights recent efforts in the area of enantioselective free-radical reduction chemistry and describes how single-enantiomer outcomes are possible when simple enantiopure stannanes are used in conjunction with large, sterically-demanding Lewis acids. Selectivities in excess of 90% are now possible, with one example in excess of 99.5% ee provided.

Single enatiomer free-radical chemistry - Lewis acid-mediated reductions of racemic halides using chiral non-racemic stannanes

Additions of one to two equivalents of Lewis acids that include magnesium salts to free-radical reduction reactions involving ester functionalized radicals and (1R,2S,5R)-menthyldiphenyltin hydride 4, bis((1R,2S,5R)-menthyl)phenyltin hydride 5, tris((1R,2S,5R)-menthyl)tin hydride 6, bis((1R,2S,5R)-menthyl)-[8-(N,N-dimethylamino)naphthyl]tin hydride 12, bis((1R,2S,5R)-menthyl)-[1-((S)-N,N-dimethylaminoethyl)phenyl]tin hydride 13 or 3α-dimethylstannyl-5α-cholestane 14 result in remarkable enantioselectivities. Examples include (S)-naproxen ethyl ester 16, produced in 74% yield and greater than 99% ee at −78°C from the bromide and 5 in the presence of MgBr₂, and ethyl (R)-N-trifluoroacetyl-_D-phenylglycinate 18, obtained in 78% yield and 99% ee under identical conditions. Kinetic and computational studies provide insight into the origins of these observations.