Protein‐like behavior of multiblock copolymer chains in a selective solvent by a variety of lattice and off‐lattice Monte Carlo simulations

Lewandowski, Krzysztof; Knychała, P.; Banaszak, M.

doi:10.1002/pssb.200880252

Cited by 17 publications

(31 citation statements)

References 28 publications

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“…Negative ǫ ij 's indicate that there is an attraction between monomers, and the presence of the solvent is taken into account in an implicit manner [22]. By controlling the relative strength of this attraction, via T * , we effectively vary solvent quality, from good to bad, which causes a collapse of the polymer chain, from a swollen state to a globular state [23][24][25]. The swollen and collapsed states are separated by the Θ solvent state, where the chain is Gaussian.…”

Section: B Polymer Modelmentioning

confidence: 99%

Intraglobular structures in multiblock copolymer chains from a Monte Carlo simulation

Lewandowski

Banaszak

2011

Phys. Rev. E

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Multiblock copolymer chains in implicit nonselective solvents are studied by Monte Carlo method which employs a parallel tempering algorithm. Chains consisting of 120 A and 120 B monomers, arranged in three distinct microarchitectures: (10−10) 12 , (6−6) 20 , and (3−3) 40 , collapse to globular states upon cooling, as expected. By varying both the reduced temperature T * and compatibility between monomers ω, numerous intra-globular structures are obtained: diclusters (handshake, spiral, torus with a core, etc.), triclusters, and n-clusters with n > 3 (lamellar and other), which are reminiscent of the block copolymer nanophases for spherically confined geometries. Phase diagrams for various chains in the (T * , ω)-space are mapped. The structure factor S(k), for a selected microarchitecture and ω, is calculated. Since S(k) can be measured in scattering experiments, it can be used to relate simulation results to an experiment. Self-assembly in those systems is interpreted in term of competition between minimization of the interfacial area separating different types of monomers and minimization of contacts between chain and solvent. Finally, the relevance of this model to the protein folding is addressed. * mbanasz@amu.edu.pl; http://www.simgroup.amu.edu.pl

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Section: B Polymer Modelmentioning

confidence: 99%

Intraglobular structures in multiblock copolymer chains from a Monte Carlo simulation

Lewandowski

Banaszak

2011

Phys. Rev. E

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“…For each polymer length we perform many simulations with different number of replicas. For N = 25 we use M = 6, 8, 10, 12, 14, 16, 20, 24, 28, 32, 40, 50, 60, 70, 80 and 94; for N = 50 we use M = 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78, 86 and 94; for N = 75 we use M = 10, 12,14,16, 18, 20, 22, 26, 28, 30, 38, 46, 54, 62, 70, 78, 86 and 94. All systems are simulated in temperature range * 1 1 T = to * 15.…”

Section: A Simulationmentioning

confidence: 99%

“…Elementary moves consist of pivot, kink and slithering-snake moves. Detailed description of this model can be found in references [13,14] …”

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confidence: 99%

Parallel-Tempering Monte-Carlo Simulation with Feedback-Optimized Algorithm Applied to a Coil-to-Globule Transition of a Lattice Homopolymer

Lewandowski¹,

Knychała²,

Banaszak³

2010

CMST

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Abstract:We present a study of the parallel tempering (replica exchange) Monte Carlo method, with special focus on the feedbackoptimized parallel tempering algorithm, used for generating an optimal set of simulation temperatures. This method is applied to a lattice simulation of a homopolymer chain undergoing a coil-to-globule transition upon cooling. We select the optimal number of replicas for different chain lengths, N = 25, 50 and 75, using replica's round-trip time in temperature space, in order to determine energy, specific heat, and squared end-to-end distance of the homopolymer chain for the selected temperatures. We also evaluate relative merits of this optimization method. Key words: Monte Carlo, parallel tempering, replica exchange, feedback-optimized, polymer, single chain CMST 16(1) 29-35 (201029-35 ( ) DOI:10.12921/cmst.2010 K. Lewandowski, P. Knychała, M. Banaszak 30and exchange interval, S. It is known that quality of the PT method strongly depends on those parameters, and if they are not chosen correctly, simulation can give the same results as without the PT. It is not clear how many replicas are optimal, and it is hard to establish the appropriate criteria for this choice. One approach is to consider some thermodynamic quantity (for example the specific heat, C v ) and to test it how much CPU-time is needed to obtain correct result, or run many simulations with the same number of MCS (or total MCS of all replicas), and to test measurement accuracy for this quantity. In another approach, one can find the optimum * T set that gives the shortest round-trip times of replicas in temperature space.Feedback-optimized PT (FOPT) algorithm, which we use in this work, is designed to find temperature sets that maximize the current of replicas from the lowest temperature to the highest one (details in reference [7] The FOPT uses ( )f T histogram to optimize temperature set in order to minimize round-trip times.In this work, we use round-trip time to find optimal parameters set. We test systems of different sizes, N, and with different number of replicas, M, to find the optimum parameter set. We do not vary the exchange interval, S, which is set to 200 MCS. In the future, we intend to test the S effect on the PT simulation results.It is worth to notice, that there are also other methods for generating optimal temperature sets [8][9][10]. One of them, is proposed by Sabe et al. [9], and is based mainly on the work of Kofke [11] and Kone and Kofke [12], in which the optimal temperature sets are found by using the condition of constant entropy increase for the adjacent replicas. According to our knowledge, the round-trip time of replicas with the FOPT, which we present in this work, is used as a criterion for finding optimal number of replicas in the PT simulations for the first time. II. MODELThe simulation is performed on the face centered cubic (FCC) lattice with coordination number z = 12 and the bond length 2 l a = where a is the FCC lattice constant. Chain bond are not allowed to be stretched or br...

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“…Towards this end, computer simulations have recently made substantial strides 4,19,20,21,22,23,24,25,26,27,28,29,30,31 focusing on solutions of linear multiblock copolymers of the (A n B n ) m type, where n is the degree of polymerization of each block and m is the number of blocks. Systematic explorations within the large parameter space established quantitative relations on how copolymer architecture and intermolecular interactions determine the macroscopic phase behavior and the related chain conformations changes.…”

Section: Introductionmentioning

confidence: 99%

“…Rackaitis, et al 32 Lewandowski, et al in a series of papers 19,20,21 performed off-lattice Monte Carlo simulations on a single multiblock copolymer chain using different architectures in nonselective solvents. His main findings for small m-values reported a two-stage transition upon solvent quality decrease, with swollen/solvated coils collapsing first towards a pearl-necklace microstructure and, upon worsening of the solvent quality, towards a single-globule microstructure.…”

Section: Introductionmentioning

confidence: 99%

Collapse transitions in thermosensitive multi-block copolymers: A Monte Carlo study

Rissanou

Tzeli

Anastasiadis

et al. 2014

The Journal of Chemical Physics

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Protein‐like behavior of multiblock copolymer chains in a selective solvent by a variety of lattice and off‐lattice Monte Carlo simulations

Cited by 17 publications

References 28 publications

Intraglobular structures in multiblock copolymer chains from a Monte Carlo simulation

Intraglobular structures in multiblock copolymer chains from a Monte Carlo simulation

Parallel-Tempering Monte-Carlo Simulation with Feedback-Optimized Algorithm Applied to a Coil-to-Globule Transition of a Lattice Homopolymer

Collapse transitions in thermosensitive multi-block copolymers: A Monte Carlo study

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