Special Issue "Computational Methods for Polymers"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Chemical Systems".

Deadline for manuscript submissions: 30 June 2019

Special Issue Editor

Guest Editor
Prof. Dr. Masoud Soroush

Department of Chemical and Biological Engineering, Drexel University, Philadelphia, PA 19104, USA
Website | E-Mail
Interests: process systems engineering; polymer reaction engineering; electronic-level modeling of reactions; polymer membranes; renewable power generation and storage systems

Special Issue Information

Dear Colleagues,

Advances in computational methods in the past decade have permitted the efficient reliable conduction of many complex tasks computationally (in silico). High-fidelity, multiscale, first priciples and entirely data-based mathematical models have been the backbone of the computational methods. The methods have allowed for the in-silico discovery of new materials, identification of new reaction pathways, determination and evaluation of optimal product synthesis steps, experimentation, and design of novel processes with improved energy efficiency and sustiability. They have also contributed to improving the real-time control and monitoring of processes. Polymers and polymer processes have also benfitted from these methods.

This Special Issue seeks papers that apply a computational method to a polymer, a polymer process and/or a polymerization reaction. Its scope includes modeling (from the electronic scale to the macroscopic scale), model-based product design, estimation, machine learning, data analytics, control, monitoring, optimization, numerical simulation, fault detection and identification, risk assessment, safety analysis, and model-based process design. Of particular interest are manuscripts that integrate experimental and computational studies.

Prof. Dr. Masoud Soroush
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1100 CHF (Swiss Francs). Please note that for papers submitted after 30 June 2019 an APC of 1200 CHF applies. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Computational methods
  • Polymers
  • Multiscale modeling
  • Estimation
  • Control
  • Optimization
  • Detection and diagnosis
  • Optimal control
  • Inference
  • Machine learning
  • Data analytics

Published Papers (4 papers)

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Research

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Open AccessFeature PaperArticle
Data-Driven Estimation of Significant Kinetic Parameters Applied to the Synthesis of Polyolefins
Processes 2019, 7(5), 309; https://doi.org/10.3390/pr7050309
Received: 23 April 2019 / Revised: 14 May 2019 / Accepted: 16 May 2019 / Published: 22 May 2019
PDF Full-text (2076 KB)
Abstract
A data-driven strategy for the online estimation of important kinetic parameters was assessed for the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst at different diene concentrations and reaction temperatures. An initial global sensitivity analysis selected the significant kinetic parameters of the [...] Read more.
A data-driven strategy for the online estimation of important kinetic parameters was assessed for the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst at different diene concentrations and reaction temperatures. An initial global sensitivity analysis selected the significant kinetic parameters of the system. The retrospective cost model refinement (RCMR) algorithm was adapted and implemented to estimate the significant kinetic parameters of the model in real time. After verifying stability and robustness, experimental data validated the algorithm performance. Results demonstrate the estimated kinetic parameters converge close to theoretical values without requiring prior knowledge of the polymerization model and the original kinetic values. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
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Graphical abstract

Open AccessFeature PaperArticle
Universal Relationships in Hyperbranched Polymer Architecture for Batch and Continuous Step Growth Polymerization of AB2-Type Monomers
Processes 2019, 7(4), 220; https://doi.org/10.3390/pr7040220
Received: 21 March 2019 / Revised: 13 April 2019 / Accepted: 16 April 2019 / Published: 17 April 2019
PDF Full-text (23166 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Design and control of hyperbranched (HB) polymer architecture by way of reactor operation is key to a successful production of higher-valued HB polymers, and it is essential in order to clarify the fundamental structural characteristics formed in representative types of reactors. In this [...] Read more.
Design and control of hyperbranched (HB) polymer architecture by way of reactor operation is key to a successful production of higher-valued HB polymers, and it is essential in order to clarify the fundamental structural characteristics formed in representative types of reactors. In this article, the irreversible step growth polymerization of AB2 type monomer is investigated by a Monte Carlo simulation method, and the calculation was conducted for a batch and a continuous stirred-tank reactor (CSTR). In a CSTR, a highly branched core region consisting of units with large residence times is formed to give much more compact architecture, compared to batch polymerization. The universal relationships, unchanged by the conversion levels and/or the reactivity ratio, are found for the mean-square radius of gyration Rg2, and the maximum span length LMS. For batch polymerization, the g-ratio of Rg2 of the HB molecule to that for a linear molecule conforms to that for the random branched polymers represented by the Zimm-Stockmayer equation. A single linear equation represents the relationship between Rg2 and LMS, both for batch and CSTR. Appropriate process control in combination with the chemical control of the reactivity of the second B-group promises to produce tailor-made HB polymer architecture. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
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Graphical abstract

Open AccessArticle
Categorization of Failures in Polymer Rapid Tools Used for Injection Molding
Processes 2019, 7(1), 17; https://doi.org/10.3390/pr7010017
Received: 17 December 2018 / Revised: 22 December 2018 / Accepted: 25 December 2018 / Published: 2 January 2019
PDF Full-text (4885 KB) | HTML Full-text | XML Full-text
Abstract
Background—Polymer rapid tooling (PRT) inserts for injection molding (IM) are a cost-effective method for prototyping and low-volume manufacturing. However, PRT inserts lack the robustness of steel inserts, leading to progressive deterioration and failure. This causes quality issues and reduced part numbers. Approach—Case studies [...] Read more.
Background—Polymer rapid tooling (PRT) inserts for injection molding (IM) are a cost-effective method for prototyping and low-volume manufacturing. However, PRT inserts lack the robustness of steel inserts, leading to progressive deterioration and failure. This causes quality issues and reduced part numbers. Approach—Case studies were performed on PRT inserts, and different failures were observed over the life of the tool. Parts molded from the tool were examined to further understand the failures, and root causes were identified. Findings—Critical parameters affecting the tool life, and the effect of these parameters on different areas of tool are identified. A categorization of the different failure modes and the underlying mechanisms are presented. The main failure modes are: surface deterioration; surface scalding; avulsion; shear failure; bending failure; edge failure. The failure modes influence each other, and they may be connected in cascade sequences. Originality—The original contributions of this work are the identification of the failure modes and their relationships with the root causes. Suggestions are given for prolonging tool life via design practices and molding parameters. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
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Review

Jump to: Research

Open AccessFeature PaperReview
Advances in Mathematical Modeling of Gas-Phase Olefin Polymerization
Processes 2019, 7(2), 67; https://doi.org/10.3390/pr7020067
Received: 31 December 2018 / Revised: 25 January 2019 / Accepted: 26 January 2019 / Published: 30 January 2019
Cited by 1 | PDF Full-text (772 KB) | HTML Full-text | XML Full-text
Abstract
Mathematical modeling of olefin polymerization processes has advanced significantly, driven by factors such as the need for higher-quality end products and more environmentally-friendly processes. The modeling studies have had a wide scope, from reactant and catalyst characterization and polymer synthesis to model validation [...] Read more.
Mathematical modeling of olefin polymerization processes has advanced significantly, driven by factors such as the need for higher-quality end products and more environmentally-friendly processes. The modeling studies have had a wide scope, from reactant and catalyst characterization and polymer synthesis to model validation with plant data. This article reviews mathematical models developed for olefin polymerization processes. Coordination and free-radical mechanisms occurring in different types of reactors, such as fluidized bed reactor (FBR), horizontal-stirred-bed reactor (HSBR), vertical-stirred-bed reactor (VSBR), and tubular reactor are reviewed. A guideline for the development of mathematical models of gas-phase olefin polymerization processes is presented. Full article
(This article belongs to the Special Issue Computational Methods for Polymers)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Name: Professor Alex Penlidis
Affiliation: Department of Chemical Engineering, University of Waterloo

2. Name: Professor Fouad Teymour
Affiliation: Chemical Engineering, Illinois Institute of Technology

3. Name: Professor Prashant Mhaskar
Affiliation: Chemical Engineering, McMaster University

4. Name: Professor  Fernando Lima
Affiliation: Chemical and Biomedical Engineering, West Virginia University, USA
Title:
SimCentral Simulation and Model Predictive Control of a Polymer-based Membrane Reactor System for Water-gas Shift Reaction Applications

5. Name: Professor Timothy Mckenna
Affiliation: Centre National de Recherche Scientifique, Lyon, France

6. Name: Professor Hidetaka TOBITA
Affiliation: Department of Materials Science and Engineering, University of Fukui, Japan
Title:
Effect of Reactor Types on the Hyperbranched Polymer Architecture

7. Name: Professor Jose A. Romagnoli
Affiliation: Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States

8. Name: Professor Christian Elm
Affiliation: Dipartimento di Scienze Chimiche, Università di Napoli Federico II, , 80126 Napoli, Italy

9. Name: Professor Ahmad Rahimpour
Affiliation: Babol Noshirvani University of Technology

10. Name: Alexander Penlidis
Affiliation: Department of Chemical Engineering, University of Waterloo

11. Name: Shaghayegh Hamzehlou
Affiliation:
Universidad del País Vasco

 

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