Linear segmented polyurethanes. II. A mathematical model for the prepolymerization stage

Polo, Mara Lis; Pesoa, Juan Ignacio; Nicolau, Verónica V.; Spontón, Marisa Elisabet; Estenoz, Diana Alejandra; Meira, G. R.

doi:10.1002/app.46946

Cited by 5 publications

(23 citation statements)

References 55 publications

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“…2 Table 5 presents: (a) the global recipe given as weight ( g) of initial reagents, moles (n) of initial reactive groups, and global split of reagents r' (= n 0 − OH =n 0 − NCO ); and (b) the recipes into each reaction phase, given by their splits (r' 1 and r' 2 ). 2 The final measurements and simulation results are in Table 5 and in Figure 2. Table 5, lower section, compare the measurements and model predictions of the average molar masses at (t end = 30 min).…”

Section: Prepolymerization Of Expmentioning

confidence: 99%

“…The prepolymerization rate constant was readjusted into: (k 1 = 0.00265 L mol −1 s −1 ). 2 In addition to our previous models, 1,2 many other mathematical models have been published on the synthesis of linear polyurethanes. [3][4][5][6][7][8][9][10][11][12][13][14][15][16] These articles have been classified in different ways.…”

Section: Introductionmentioning

confidence: 95%

“…This article presents a mathematical model for the synthesis of linear polyurethanes that extends our two previous models. 1,2 In the first part of this sequel, 1 five polymerizations were carried out at 60 C, with the aim of producing several high molar mass thermoplastic elastomers. The reactions involved methylene diphenyl diisocyanate (MDI), two poly(tetramethylene oxide) (PTMO) macrodiols of different molar mass distributions (MMDs), and 1,4-butanediol (BD) as chain extender.…”

Section: Introductionmentioning

confidence: 99%

“…[3][4][5][6][7][8][9][10][11][12][13][14][15][16] These articles have been classified in different ways. 2 For example, the models in References 3-9 simulate the synthesis of oligomers, while those in References 10-16 simulate the synthesis of high polymers. Also, the models in References 3,4,9-16 are algebraic and stochastic (and therefore rate constant independent), while those in References 5-8 are dynamic and deterministic, thus requiring a rate constant.…”

Section: Introductionmentioning

confidence: 99%

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Linear segmented polyurethanes. III. Mathematical model for a two‐steps polymerization

Polo

Spontón

Huespe

et al. 2020

J of Applied Polymer Sci

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In the first article of this sequel (J. Appl. Polym. Sci., 2018, 135, 45747), an experimental and theoretical investigation was developed on the two-steps synthesis of linear segmented thermoplastic polyurethanes. The reactions were carried out at 60 C, with methylene diphenyl diisocyanate (MDI), two poly(tetramethylene oxide) macrodiols, and 1,4-butanediol (BD) as chain extender. In our second article (J. Appl. Polym. Sci., 2019, 136, 46946), a mathematical model for the prepolymerization was developed, that involved integrating a differential equation for each generated polymer species. The present article extends such model, and predicts the molecular structure along the finishing stage. In each stage, the new model first solves the molar balances at polymer topologies level (i.e.,: Disregarding the molar mass distribution [MMD] of the reacted macrodiol chains), and then calculates the MMD of the evolving polymer and its main subsets through an algebraic convolution procedure. The model reproduces the prepolymerization predictions of our previous article, but is three orders of magnitude faster. In the finishing stage, up to 156,000 polymer topologies and 4.53 × 10 8 polymer species were calculated; and the rate constant was readjusted to (k 2 = 0.00129 L mol −1 s −1), in order to fit the measured MMDs.

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Section: Prepolymerization Of Expmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Linear segmented polyurethanes. III. Mathematical model for a two‐steps polymerization

Polo

Spontón

Huespe

et al. 2020

J of Applied Polymer Sci

Self Cite

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“…highlighted the use of Computer Aided Process Engineering (CAPE) methods and tools for systematic analysis of chemical product–process development. A good number of papers have also been published on modeling and simulation of polymerization reactions . However, the application of DEA, a mathematical approach, and Shannon's Entropy for synthesis of polysaccharide based graft copolymers has not been reported yet in literature.…”

Section: Introductionmentioning

confidence: 99%

Quantification of Optimal Reaction Parameters for the Synthesis of a Polysaccharide‐Based Graft Copolymers Using Combined Shannon's Entropy and Data Envelopment Analysis

2019

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The traditional process of synthesis of desired materials involves a trial and error approach, which consumes considerable time and resources. Therefore, it is necessary to implement computer-aided optimizing techniques for the precise synthesis of desired material. This paper presents a novel modeling approach for precise synthesis of graft copolymers of poly(acrylic acid) and Tamarind seed polysaccharide (xyloglucan). Different sets of variables generated through experimental study have been analyzed for the quantification of optimal reaction variables and parameters using combined Shannon's entropy and data envelopment analysis (DEA). Experimental data from the grafting reaction such as concentration of acrylic acid, temperature, and time are used to validate the model and a good agreement between model predictions and experimental data is observed. The proposed innovative green approach for designing the precise synthesis of xyloglucan based graft copolymers may help in identifying the optimal conditions for polymerization reaction to reach targeted materials more efficiently.

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Data Envelopment Analysis and Decision Maker Models: An Innovative Approach for Optimization of Reaction Variables of Graft Copolymerization of Poly(butyl acrylate) to Tamarind Seed Xyloglucan

Yadav

Malhotra

Mishra

2020

Macro Theory & Simulations

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This article presents a novel methodology using a combination of nonparametric frontier analysis models, data envelopment analysis (DEA), and decision maker (DM) model to optimize real-time reaction variables, that is, concentration of butyl acrylate, time duration of the reaction, and temperature for precision synthesis of poly(butyl acrylate) (PBA) and xyloglucan (tamarind seed polysaccharide) graft copolymers.The copolymer samples (units) obtained by a different set of reaction variables and conditions are ranked using DEA to identify the efficient units. An appropriate minimum weight restriction is imposed by the DM on the chosen inputs and output by linear programming models that are designed in such a way that each DEA efficient unit can get "maximin" weight. The model predictions for reaction parameters and experimental data obtained are found to be very close to each other.

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Linear segmented polyurethanes. II. A mathematical model for the prepolymerization stage

Cited by 5 publications

References 55 publications

Linear segmented polyurethanes. III. Mathematical model for a two‐steps polymerization

Linear segmented polyurethanes. III. Mathematical model for a two‐steps polymerization

Quantification of Optimal Reaction Parameters for the Synthesis of a Polysaccharide‐Based Graft Copolymers Using Combined Shannon's Entropy and Data Envelopment Analysis

Data Envelopment Analysis and Decision Maker Models: An Innovative Approach for Optimization of Reaction Variables of Graft Copolymerization of Poly(butyl acrylate) to Tamarind Seed Xyloglucan

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