scholarly journals The Chain Length Distribution of an Ideal Reversible Deactivation Radical Polymerization

Polymers ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 887 ◽  
Author(s):  
Simon Harrisson
Keyword(s):  
Radical Polymerization ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Chain Transfer ◽  
Negative Binomial ◽  
Length Distribution ◽  
Degree Of Polymerization ◽  
Chain Length Distribution ◽  
Reversible Deactivation ◽  
Reversible Deactivation Radical Polymerization

The chain length distribution (CLD) of a reversible deactivation radical polymerization at full conversion is shown to be a negative binomial distribution with parameters that are simple functions of the number-average degree of polymerization and either the chain transfer constant (in the case of polymerizations that incorporate a reversible chain transfer step) or the concentrations of dormant polymer chains and deactivating agent and the rate constants of propagation and deactivation (other types of RDRP). Expressions for the CLD at intermediate conversions are also derived, and shown to be consistent with known expressions for the number-average degree of polymerization and dispersity. It is further demonstrated that these CLDs are well-approximated by negative binomial distributions with appropriate choice of parameters. The negative binomial distribution is thus a useful model for CLDs of reversible deactivation radical polymerizations.

scholarly journals The Competition of Termination and Shielding to Evaluate the Success of Surface-Initiated Reversible Deactivation Radical Polymerization

Polymers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1409
Author(s):  
Francisco J. Arraez ◽  
Paul H. M. Van Steenberge ◽  
Dagmar R. D’hooge
Keyword(s):  
Radical Polymerization ◽  
Kinetic Monte Carlo ◽  
Length Distribution ◽  
Layer Growth ◽  
Height Distribution ◽  
Structure Property ◽  
Chain Length Distribution ◽  
Reversible Deactivation ◽  
Reversible Deactivation Radical Polymerization ◽  
Tethered Chains

One of the challenges for brush synthesis for advanced bioinspired applications using surface-initiated reversible deactivation radical polymerization (SI-RDRP) is the understanding of the relevance of confinement on the reaction probabilities and specifically the role of termination reactions. The present work puts forward a new matrix-based kinetic Monte Carlo platform with an implicit reaction scheme capable of evaluating the growth pattern of individual free and tethered chains in three-dimensional format during SI-RDRP. For illustration purposes, emphasis is on normal SI-atom transfer radical polymerization, introducing concepts such as the apparent livingness and the molecular height distribution (MHD). The former is determined based on the combination of the disturbing impact of termination (related to conventional livingness) and shielding of deactivated species (additional correction due to hindrance), and the latter allows structure-property relationships to be identified, starting at the molecular level in view of future brush characterization. It is shown that under well-defined SI-RDRP conditions the contribution of (shorter) hindered dormant chains is relevant and more pronounced for higher average initiator coverages, despite the fraction of dead chains being less. A dominance of surface-solution termination is also put forward, considering two extreme diffusion modes, i.e., translational and segmental. With the translational mode termination is largely suppressed and the living limit is mimicked, whereas with the segmental mode termination occurs more and the termination front moves upward alongside the polymer layer growth. In any case, bimodalities are established for the tethered chains both on the level of the chain length distribution and the MHD.

scholarly journals Fundamentals of reversible addition–fragmentation chain transfer (RAFT)

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Catherine L. Moad ◽  
Graeme Moad
Keyword(s):  
Radical Polymerization ◽  
Chain Length ◽  
Molar Mass ◽  
Chain Transfer ◽  
Raft Polymerization ◽  
Length Distribution ◽  
Chain Length Distribution ◽  
Reversible Addition ◽  
Raft Agent ◽  
End Group

Abstract Radical polymerization is transformed into what is known as reversible addition–fragmentation chain transfer (RAFT) polymerization by the addition of a RAFT agent. RAFT polymerization enables the preparation of polymers with predictable molar mass, narrow chain length distribution, high end-group integrity and provides the ability to construct macromolecules with the intricate architectures and composition demanded by modern applications in medicine, electronics and nanotechnology. This paper provides a background to understanding the mechanism of RAFT polymerization and how this technique has evolved.

scholarly journals Living Radical Polymerization by the RAFT Process - A Second Update

2009 ◽  
Vol 62 (11) ◽  
pp. 1402 ◽  
Author(s):  
Graeme Moad ◽  
Ezio Rizzardo ◽  
San H. Thang
Keyword(s):  
Radical Polymerization ◽  
Chain Transfer ◽  
Raft Polymerization ◽  
Diverse Range ◽  
Reversible Addition ◽  
Reversible Deactivation ◽  
Modified Surfaces ◽  
Diagnostic Applications ◽  
Reversible Deactivation Radical Polymerization ◽  
End Group

This paper provides a second update to the review of reversible deactivation radical polymerization achieved with thiocarbonylthio compounds (ZC(=S)SR) by a mechanism of reversible addition–fragmentation chain transfer (RAFT) that was published in June 2005 (Aust. J. Chem. 2005, 58, 379–410). The first update was published in November 2006 (Aust. J. Chem. 2006, 59, 669–692). This review cites over 500 papers that appeared during the period mid-2006 to mid-2009 covering various aspects of RAFT polymerization ranging from reagent synthesis and properties, kinetics and mechanism of polymerization, novel polymer syntheses and a diverse range of applications. Significant developments have occurred, particularly in the areas of novel RAFT agents, techniques for end-group removal and transformation, the production of micro/nanoparticles and modified surfaces, and biopolymer conjugates both for therapeutic and diagnostic applications.

scholarly journals Living Radical Polymerization by the RAFT Process – A Third Update

2012 ◽  
Vol 65 (8) ◽  
pp. 985 ◽  
Author(s):  
Graeme Moad ◽  
Ezio Rizzardo ◽  
San H. Thang
Keyword(s):  
Radical Polymerization ◽  
Chain Transfer ◽  
Raft Polymerization ◽  
Diverse Range ◽  
Reversible Addition ◽  
Reversible Deactivation ◽  
Modified Surfaces ◽  
Diagnostic Applications ◽  
Reversible Deactivation Radical Polymerization ◽  
End Group

This paper provides a third update to the review of reversible deactivation radical polymerization (RDRP) achieved with thiocarbonylthio compounds (ZC(=S)SR) by a mechanism of reversible addition-fragmentation chain transfer (RAFT) that was published in June 2005 (Aust. J. Chem. 2005, 58, 379). The first update was published in November 2006 (Aust. J. Chem. 2006, 59, 669) and the second in December 2009 (Aust. J. Chem. 2009, 62, 1402). This review cites over 700 publications that appeared during the period mid 2009 to early 2012 covering various aspects of RAFT polymerization which include reagent synthesis and properties, kinetics and mechanism of polymerization, novel polymer syntheses, and a diverse range of applications. This period has witnessed further significant developments, particularly in the areas of novel RAFT agents, techniques for end-group transformation, the production of micro/nanoparticles and modified surfaces, and biopolymer conjugates both for therapeutic and diagnostic applications.

Niche Sharing in Intertidal Mollusks and Decapods in Rocky Shore of Easter Island

2019 ◽  
Vol 53 (5) ◽  
pp. 417-422
Author(s):  
P. De los Ríos ◽  
E. Ibáñez Arancibia
Keyword(s):  
Spatial Distribution ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Rocky Shore ◽  
Negative Binomial ◽  
Null Model ◽  
Easter Island ◽  
Published Data ◽  
Distribution Analysis ◽  
Field Works

Abstract The coastal marine ecosystems in Easter Island have been poorly studied, and the main studies were isolated species records based on scientific expeditions. The aim of the present study is to apply a spatial distribution analysis and niche sharing null model in published data on intertidal marine gastropods and decapods in rocky shore in Easter Island based in field works in 2010, and published information from CIMAR cruiser in 2004. The field data revealed the presence of decapods Planes minutus (Linnaeus, 1758) and Leptograpsus variegatus (Fabricius, 1793), whereas it was observed the gastropods Nodilittorina pyramidalis pascua Rosewater, 1970 and Nerita morio (G. B. Sowerby I., 1833). The available information revealed the presence of more species in data collected in 2004 in comparison to data collected in 2010, with one species markedly dominant in comparison to the other species. The spatial distribution of species reported in field works revealed that P. minutus and N. morio have aggregated pattern and negative binomial distribution, L. variegatus had uniform pattern with binomial distribution, and finally N. pyramidalis pascua, in spite of aggregated distribution pattern, had not negative binomial distribution. Finally, the results of null model revealed that the species reported did not share ecological niche due to competition absence. The results would agree with other similar information about littoral and sub-littoral fauna for Easter Island.

ANALISIS RISIKO OPERASIONAL MENGGUNAKAN PENDEKATAN DISTRIBUSI KERUGIAN DENGAN METODE AGREGAT

2011 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Y. ARBI ◽  
R. BUDIARTI ◽  
I G. P. PURNABA
Keyword(s):  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Financial Institution ◽  
Expected Value ◽  
Insurance Companies ◽  
Limited Data ◽  
Loss Distribution Approach ◽  
Potential Loss ◽  
The Impact

Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes or external problems. Insurance companies as financial institution that also faced at risk. Recording of operating losses in insurance companies, were not properly conducted so that the impact on the limited data for operational losses. In this work, the data of operational loss observed from the payment of the claim. In general, the number of insurance claims can be modelled using the Poisson distribution, where the expected value of the claims is similar with variance, while the negative binomial distribution, the expected value was bound to be less than the variance.Analysis tools are used in the measurement of the potential loss is the loss distribution approach with the aggregate method. In the aggregate method, loss data grouped in a frequency distribution and severity distribution. After doing 10.000 times simulation are resulted total loss of claim value, which is total from individual claim every simulation. Then from the result was set the value of potential loss (OpVar) at a certain level confidence.

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