Development of Molecular Weight Distribution in ATRP with Radical Termination

Mastan, Erlita; Zhou, Da-Peng; Zhu, Shiping

doi:10.1002/mats.201300166

Cited by 16 publications

(21 citation statements)

References 59 publications

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“…Considering the chain termination reaction, M n decreases from 40 904 to 40 060, whereas PDI increases from 1.025 to 1.047. Similar simulation results are also reported by Mastan et al 28; accumulation of oligomers in the system may be a possible reason for these results. In addition, the dead polymer is mainly generated close to the reactor wall and far from the reactor inlet (see Fig.…”

Section: Resultssupporting

confidence: 91%

Computational Fluid Dynamics Simulation of Multiscale Mixing in Anionic Polymerization Tubular Reactors

2016

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The molecular properties of polymers are greatly influenced by operation parameters during polymerization in reactors. Since operation parameter distributions in reactors also result in molecular property distributions, polymerization bridges the gap between molecular properties and operation parameters. The combination of the computational fluid dynamics technology with the method of moments to form a uniquely coupled model was used to describe multiscale mixing fields in the reactor. The coupled model was validated by open experimental data, and the effects of polymerization kinetics on macroscopic and microscopic fields were investigated numerically. Also, the coupled model was applied to numerically predict the impacts of some key operation conditions on the main macroscopic flow field parameters and polymer molecular properties.

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Section: Resultssupporting

confidence: 91%

Computational Fluid Dynamics Simulation of Multiscale Mixing in Anionic Polymerization Tubular Reactors

2016

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“…If needed, inversion method can be applied to construct the full CLD based on the premise that the distribution type is known. Furthermore, Mastan et al recently proposed a novel method for the description of full molar mass distribution of polymer synthesized by ATRP . The novelty of that work lies in analogously relating the activation–deactivation cycles in ATRP to a series of CSTRs.…”

Section: Methods Of Momentsmentioning

confidence: 99%

“…In this work, diffusional limitations on termination were ignored for simplicity. Subsequently, a modified model for monomer conversion dependent PDI and a new polydispersity expression including effects of the monomer conversion, monomer addition per activation/deactivation cycle, and amount of dead chains were introduced for ATRP systems . Saldívar‐Guerra et al showed that direct integration of the equation can be used to predict the CLD for NMP and RAFT polymerization systems …”

Section: Methods Of Momentsmentioning

confidence: 99%

State‐of‐the‐Art and Progress in Method of Moments for the Model‐Based Reversible‐Deactivation Radical Polymerization

Zhou

Luo

2016

Macro Reaction Engineering

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polymerization (FRP). However, because of the slow initiation, rapid propagation, and termination involving many different chain lengths, FRP is difficult to control over the polymer architectures and the minimum dispersity of the molar mass distribution is 2. [4,5] What's exciting is that controlled radical polymerization (also termed as reversible-deactivation radical polymerization (RDRP)) was discovered about two decades ago. [6,7] In most of RDRP systems, the initiation or degeneratively exchange is fast, propagation is relatively slow, and termination is suppressed per present chain, referring to the dominance of dormant chains in the final mixture. As a result, polymerization proceeds in a controlled manner, allowing one to prepare various well-defined block copolymers, stars, bottlebrushes, and hybrid materials. [6] Therefore, RDRP has attracted increasing interest from both academic and industrial fields. [8][9][10] Facing the increasing demand on high qualified and tailor-made polymeric materials, despite the technological promise, there are only limited products and investigations based on RDRP techniques at industrial scale. This can be attributed to the limited commercial RDRP agents Reversible-deactivation radical polymerization (RDRP) techniques have received lots of interest for the past 20 years, not only owing to their simple, mild reaction conditions and broad applicability, but also their accessibility to produce polymeric materials with well-defined structures. Modeling is widely applied to optimize the polymerization conditions and processes. In addition, there are numerous literatures on the kinetic and reactor models for RDRP processes, which show the accessibility on polymerization kinetics insight, process optimization, and controlling over chain microstructure with predetermined molecular weight and low dispersity, copolymer composition distribution, and sequence distribution. This review highlights the facility of the method of moments in the modeling field and presents a summary of the present state-of-the-art and future perspectives focusing on the model-based RDRP processes based on the method of moments. Summary on the current status and challenges is discussed briefly.in large quantities at reasonable costs and the extra cost of the polymer purification processes. [10] From the view point of chemical engineering, the productivity and quality of the polymer products, as well as the polymer chain composition and chain topology, are largely influenced by the engineering problems, such as micromixing, residence time distribution of reactor, mass and heat transfers. It normally takes a long time to obtain an optimized operation condition and products only through practices. The ongoing paradigm of polymerization processes begins to shift from process design and operation by experiments and empirical methods to one by the combination of experiments and mathematical models. [11,12] In order to speed up the industrialization of RDRP techniques, the polymerization engineers can take advant...

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“…The polymer MWD can be better understood and controlled by using mathematical models that describe its evolution during the synthesis reaction. Previous mathematical modeling of ATRP has been done by a number of research groups, but most of that research focused on previous versions of ATRP, especially early works trying to better understand the kinetics and mechanism of these processes. In contrast, a few have been done on the modeling of ICAR and ARGET systems, which have greater industrial potential.…”

Section: Introductionmentioning

confidence: 99%

Mathematical modeling of the full molecular weight distribution in ATRP techniques

et al. 2016

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In this work the molecular weight distribution (MWD) of several atom transfer radical polymerization (ATRP) techniques has been derived and solved using the Reduced Stiffness by Quasi Steady State Approximation (RSQSSA) methodology. The Quasi Steady State Approximation has been validated on the living radicals for normal, Simultaneous Reversible and Normal Initiation and Activators Regenerated by Electron Transfer (ARGET), and it is shown that the information lost due to its application is negligible. According to these results, RSQSSA shows the best performance in terms of wall-clock time and required memory in comparison to implicit techniques and Predici. In the case of the ARGET technique, the model predictions show good agreement with experimental data. Finally, an analysis on the impact of the slow and fast activation of the initiator on the MWD using ARGET has been carried out, indicating that the optimal initiator to control the MWD should exhibit activation-deactivation rates very similar to those of the polymeric equilibrium.

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Development of Molecular Weight Distribution in ATRP with Radical Termination

Cited by 16 publications

References 59 publications

Computational Fluid Dynamics Simulation of Multiscale Mixing in Anionic Polymerization Tubular Reactors

Computational Fluid Dynamics Simulation of Multiscale Mixing in Anionic Polymerization Tubular Reactors

State‐of‐the‐Art and Progress in Method of Moments for the Model‐Based Reversible‐Deactivation Radical Polymerization

Mathematical modeling of the full molecular weight distribution in ATRP techniques

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