1442 results about "Polymerization reactor" patented technology

The invention relates to processes and plants for continuous solution polymerization. Such plant and processes include a pressure source, a polymerization reactor, downstream of said pressure source, pressure let-down device, downstream of said polymerization reactor, and a separator, downstream of said pressure let-down device, wherein said pressure source is sufficient to provide pressure to said reaction mixture during operation of said process plant to produce a single-phase liquid reaction mixture in said reactor and a two-phase liquid-liquid reaction mixture in said separator in the absence of an additional pressure source between said reactor and said separator.

A method of starting up a gas phase polymerization reactor, comprising controlling an amount of hydrocarbon absorbed in a polymer seedbed during startup to avoid formation of agglomerates or sheeting on an interior wall of the reactor. A system for of starting up a gas phase polymerization reactor, comprising a controller coupled to the polymerization reactor and controlling an amount of hydrocarbon absorbed in a polymer seedbed during startup to avoid formation of agglomerates or sheeting on an interior wall of the reactor.

A composite material, contains a polymer, a polymerizer, a corresponding catalyst for the polymerizer, and a plurality of capsules. The polymerizer is in the capsules. The composite material is self-healing.

The present invention concerns a high melt strength propylene polymer or copolymer suitable for manufacturing foams and thermoformed product exhibiting a melt strength of at least 3 g and comprising a high molar mass portion and a low or medium molar mass portion. The polymers are produced by subjecting propylene and optionally other olefins to polymerization in a plurality of polymerization reactors connected in series, employing different amounts of hydrogen as a molar mass modifier in at least two of the reactors, and carrying out the polymerization reaction in the presence of a catalyst system capable of catalyzing the formation of a high molar mass polymerization product having a MFR2 of less than 0.1 g / 10 min and a low or medium molar mass polymerization product having a MFR2 of more than 0.5 g / 10 min.

The invention provides for polymerization catalyst compositions, and for methods for introducing the catalyst compositions into a polymerization reactor. More particularly, the method combines a catalyst component containing slurry and a catalyst component containing solution to form the completed catalyst composition for introduction into the polymerization reactor. The invention is also directed to methods of preparing the catalyst component slurry, the catalyst component solution and the catalyst compositions, to methods of controlling the properties of polymer products utilizing the catalyst compositions, and to polymers produced therefrom.

A method is described for improving the prediction accuracy and generalization performance of artificial neural network models in presence of input-output example data containing instrumental noise and / or measurement errors, the presence of noise and / or errors in the input-output example data used for training the network models create difficulties in learning accurately the nonlinear relationships existing between the inputs and the outputs, to effectively learn the noisy relationships, the methodology envisages creation of a large-sized noise-superimposed sample input-output dataset using computer simulations, here, a specific amount of Gaussian noise is added to each input / output variable in the example set and the enlarged sample data set created thereby is used as the training set for constructing the artificial neural network model, the amount of noise to be added is specific to an input / output variable and its optimal value is determined using a stochastic search and optimization technique, namely, genetic algorithms, the network trained on the noise-superimposed enlarged training set shows significant improvements in its prediction accuracy and generalization performance, the invented methodology is illustrated by its successful application to the example data comprising instrumental errors and / or measurement noise from an industrial polymerization reactor and a continuous stirred tank reactor (CSTR).