Enrique Luis Lima

In‐line evaluation of average particle size in styrene suspension polymerizations using near‐infrared spectroscopy

The main objective of this article is evaluating the influence of average polystyrene particle size upon the near-infrared (NIR) spectra collected during suspension polymerization experiments and observing whether NIR spectroscopy may be used for in-line monitoring and control of average particle size. It is shown that NIR spectra are sensitive to changes of the average particle size, and that standard empirical models (PLS—partial least squares—and NN—neural networks) may be built to correlate average particle size and light absorbance at certain wavelengths fairly well. Finally, it is shown that these models allow the in-line evaluation of average particle size in styrene suspension polymerizations with NIR spectroscopy.

Dynamic optimization of semicontinuous emulsion copolymerization reactions: composition and molecular weight distribution

Abstract Iterative dynamic programming (IDP) is used to compute optimal monomer and chain transfer agent feed profiles to produce polymer with specified copolymer composition and molecular weight distribution. The approach used allows the implementation of constrained optimization procedures for systems described by complex mathematical models, as those needed for proper description of emulsion copolymerization reactors, especially when the computation of the whole molecular weight distribution is desired. The proposed approach is applied to the semicontinuous methyl methacrylate (MMA)/butyl acrylate (BuA) emulsion copolymerization in stirred tank reactors, using dodecanethiol as chain transfer agent (CTA). It is shown that this technique allows the effective computation of feed policies for the production of copolymers with constant composition and well-defined molecular weight distributions.

Control and design of average particle size in styrene suspension polymerizations using NIRS

In a previous paper, Santos et al. (J Appl Polym Sci 1998, 20, 1737) showed that NIRS may be used efficiently for in-line evaluation of average particle sizes in styrene suspension polymerizations if proper calibration is carried out with the help of both multivariate techniques and nonlinear models. In the present work, the technique presented by Santos et al. was used for in-line evaluation and for control and design of average particle sizes during styrene suspension polymerizations carried out in the batch mode. The effects of agitation speed and stabilizer concentration on the particle-size Distribution (PSD) were investigated. It is shown here that this technique allows the successful design and real-time control of particle sizes in lab-scale styrene suspension polymerization reactors.

Dynamic optimization of non-linear emulsion copolymerization systems: Open-loop control of composition and molecular weight distribution

Time optimal monomer and chain-transfer agent feed profiles were computed and implemented experimentally for the simultaneous control of copolymer composition and molecular weight distribution in non-linear emulsion copolymerization systems. Iterative dynamic programming was used for the off-line calculation of the optimal feed policies. This approach can deal with constrained optimization of systems described by complex mathematical models, as those needed for the emulsion copolymerization kinetics, especially when the computation of the whole molecular weight distribution is included. The proposed approach was applied to the semibatch methylmethacrylate (MMA)/n-butylacrylate (n-BA) emulsion copolymerization, using n-dodecanethiol as chain-transfer agent, and allowed the production of copolymers with constant composition and with well-defined molecular weight distributions.

Model structure determination in neural network models

Feedforward neural networks (FNN) have been used intensively for the identification and control of chemical engineering processes. However, there is no efficient model structure determination methodology for a particular mapping application. This has resulted in a tendency to use networks that are much larger than required. In this paper a new procedure for model structure determination in feedforward neural networks is proposed. This procedure is based on network pruning using the orthogonal least-squares technique to determine insignificant or redundant synaptic weights, biases, hidden nodes and network inputs. The advantages of this approach are discussed and illustrated using simulated and experimental data. The results show that the orthogonal least-squares technique is quite efficient in determining the significant elements on the neural network models. The results also show the importance of pruning procedures to identify parsimonious FNN models.

In-line monitoring of weight average molecular weight in solution polymerizations using intrinsic viscosity measurements

Abstract The main objective of this work is developing a simple viscometrical method for in-line monitoring and control of weight average molecular weight ( M w ) in solution polymerizations. The method is based on the evaluation of the approximate intrinsic viscosity of the polymer solution, at each sampling time, using a single measurement of the flow time of a diluted polymer solution through a capillary tube. Experiments were carried out for peroxide initiated styrene solution polymerization reactions in a tubular reactor. Results obtained for approximate intrinsic viscosities are in agreement with the intrinsic viscosity values published in the literature and allow fast and fair in-line values for M w .

Uma Revisão Sobre os Processos de Polimerização em Suspensão

Several processes can be employed for manufacturing polymer materials. Each process presents some intrinsic features that lead to production of resins with peculiar properties, which define the end-use application of the final polymeric material. Suspension polymerization processes are extensively used because of their many advantages, such as the easy separation of the polymer particles, easy removal of the heat of reaction, easy temperature control and low levels of impurities and additives in the final polymer material. For this reason, suspension polymerization processes are suitable to produce polymer resins for biotechnological and medical applications. The main objective of this work is to discuss the fundamental aspects of suspension polymerization processes, focusing upon the effects of the main process variables on the performance of suspension polymerizations. Additionally, it is shown that near infrared spectroscopy (NIRS) can be useful for monitoring and real time control of suspension processes, allowing for production of polymer beads with controlled morphology.

Modeling and control of tubular solution polymerization reactors

A detailed mathematical model was developed to describe the operation of free-radical solution styrene tubular polymerization reactors. Experiments were carried out and good agreement between steady-state model and experimental results was reached. It was also shown that the detailed model might be successfully replaced by a much simpler model, which may be implemented on-line for control purposes. Additional dynamic experimental results showed that jacket temperature perturbations may lead to oscillatory dynamic responses and that internal velocity profiles can be very distorted even at low polymer concentrations. A model predictive control, with a hybrid neural network internal model, was then implemented both theoretically and experimentally, allowing the successful control of monomer conversion.

Molecular weight distribution in composition controlled emulsion copolymerization

The effect of different strategies for copolymer composition control on the molecular weight distribution (MWD) and gel fraction in the emulsion copolymerization of methyl methacrylate and butyl acrylate was investigated. Starved and semistarved processes for copolymer composition control were both considered. For gel-forming systems it was found that the starved process gave more gel and lower molecular weights than the semistarved process. The feasibility of simultaneous control of the copolymer composition and the MWD was assessed.

Dynamic optimization of semicontinuous emulsion copolymerization reactions: Composition and molecular weight distribution

Iterative dynamic programming is used to compute optimal monomer and CTA feed profiles to produce polymer with pre-specified copolymer composition and MWD. This approach can deal with constrained optimizations of systems described by complex mathematical models, as those needed for the emulsion copolymerization kinetics, especially when the computation of the whole MWD is included. The proposed approach is applied to the semicontinuous MMA/BuA emulsion copolymerization, using dodecanethiol as CTA, allowing the effective computation of feed policies for the production of constant composition copolymer with well-defined MWDs.