Application of Genetic Algorithm in Simultaneous Deconvolution: Case Studies of Ethylene/1‐Butene Copolymers with Direct and Inverse MW/CC Relationships

Abstract

For multiple-site-type catalytic system, simultaneous deconvolution of molecular weight distribution and chemical composition distribution can be used to determine the number of site types and chain microstructures of polymers produced on each site type. In the conventional deconvolution with generalized reduced gradient (GRG) nonlinear algorithm, appropriate initial guesses are often required. In the case that the relationship between molecular weight and comonomer content (MW/CC) is not known, inadequate initial guesses can lead to inaccurate parameter estimation. In this work, genetic algorithm is considered as an alternative optimization tool during simultaneous deconvolution with the advantage that it can reach the global solution without relying on the adequate initial guesses. The proposed approach is validated with simulated data of model ethylene/1-butene copolymers with inverse and direct MW/CC relationships and benchmarked with the conventional GRG technique.

Application of Multipopulation Genetic Algorithm in Industrial Special Clothing Design

“…In 1996, the sales volume of industrial protective clothing in Europe was US $3.13 billion, and it was expected to reach US $3.77 billion by 2003. In 1995, the consumption of synthetic fiber used in industrial clothing in Japan reached 3.5% 43.44 million tons, accounting for about 3% of its total synthetic fiber output [4]. In general, the industrial clothing market will have a large growth, and special industrial clothing will become the highest growth point in the market [5].…”

Polyolefin microstructural deconvolution methods: The good, the bad, and the ugly

“…Chayrattanoroj and Anantawaraskul [ 129 ] extended this joint deconvolution approach for digital multiple‐site‐type copolymers made in dual reactors in series (bimodal polyethylenes). Finally, Khayanying and Anantawaraskul [ 130 ] used a genetic algorithm to improve the convergence properties of their joint MWD × CCD deconvolution method.…”

Modeling Propylene Polymerization in a Two‐Reactor System: Model Development and Parameter Estimation

“…Table 7 summarizes two additional model parameters (k p,j [C 0,j ][M] and k d,j ) for each site type estimated from polymer yield data by minimizing Equation (22). The mass fractions of polymers produced on each site type (m j ) were estimated using the simultaneous MWD deconvolution results shown in Table 4.…”

“…Microstructural distribution deconvolution is a technique that can be used to identify the minimum number of site types and determine the mass fractions and microstructures of polymer populations produced on each site type from the overall microstructural distribution. [10][11][12][13][14][15][16][17][18][19][20][21][22] Deconvolution methods based on MWD measured with gel permeation chromatography (GPC) have been widely successful in many applications. [23][24][25][26][27][28][29][30][31][32][33] Typically, this method assumes that the MWD of polyolefin populations produced on each site type follows Flory's most probable distribution (MPD), as demanded from the mechanism of olefin polymerization with coordination catalysts.…”