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1.
J Chem Phys ; 158(9): 094905, 2023 Mar 07.
Article in English | MEDLINE | ID: mdl-36889964

ABSTRACT

We present a computer simulation study of the aggregation and ordering of short alkane chains using a united atom model description. Our simulation approach allows us to determine the density of states of our systems and, from those, their thermodynamics for all temperatures. All systems show a first order aggregation transition followed by a low-temperature ordering transition. For a few chain aggregates of intermediate lengths (up to N = 40), we show that these ordering transitions resemble the quaternary structure formation in peptides. In an earlier publication, we have already shown that single alkane chains fold into low-temperature structures, best described as secondary and tertiary structure formation, thus completing this analogy here. The aggregation transition in the thermodynamic limit can be extrapolated in pressure to the ambient pressure for which it agrees well with experimentally known boiling points of short alkanes. Similarly, the chain length dependence of the crystallization transition agrees with known experimental results for alkanes. For small aggregates, for which volume and surface effects are not yet well separated, our method allows us to identify the crystallization in the core of the aggregate and at its surface, individually.

2.
Polymers (Basel) ; 11(5)2019 Apr 30.
Article in English | MEDLINE | ID: mdl-31052227

ABSTRACT

The combination of flexibility and semiflexibility in a single molecule is a powerful design principle both in nature and in materials science. We present results on the conformational behavior of a single multiblock-copolymer chain, consisting of equal amounts of Flexible (F) and Semiflexible (S) blocks with different affinity to an implicit solvent. We consider a manifold of macrostates defined by two terms in the total energy: intermonomer interaction energy and stiffness energy. To obtain diagrams of states (pseudo-phase diagrams), we performed flat-histogram Monte Carlo simulations using the Stochastic Approximation Monte Carlo algorithm (SAMC). We have accumulated two-Dimensional Density of States (2D DoS) functions (defined on the 2D manifold of macrostates) for a SF-multiblock-copolymer chain of length N = 64 with block lengths b = 4, 8, 16, and 32 in two different selective solvents. In an analysis of the canonical ensemble, we calculated the heat capacity and determined its maxima and the most probable morphologies in different regions of the state diagrams. These are rich in various, non-trivial morphologies, which are formed without any specific interactions, and depend on the block length and the type of solvent selectivity (preferring S or F blocks, respectively). We compared the diagrams with those for the non-selective solvent and reveal essential changes in some cases. Additionally, we implemented microcanonical analysis in the "conformational" microcanonical ( N V U , where U is the potential energy) and the true microcanonical ( N V E , where E is the total energy) ensembles with the aim to reveal and classify pseudo-phase transitions, occurring under the change of temperature.

3.
Polymers (Basel) ; 9(2)2017 Jan 25.
Article in English | MEDLINE | ID: mdl-30970714

ABSTRACT

Local stiffness of polymer chains is instrumental in all structure formation processes of polymers, from crystallization of synthetic polymers to protein folding and DNA compactification. We present Stochastic Approximation Monte Carlo simulations-a type of flat-histogram Monte Carlo method-determining the density of states of a model class of single semi-flexible polymer chains, and, from this, their complete thermodynamic behavior. The chains possess a rich pseudo phase diagram as a function of stiffness and temperature, displaying non-trivial ground-state morphologies. This pseudo phase diagram also depends on chain length. Differences to existing pseudo phase diagrams of semi-flexible chains in the literature emphasize the fact that the mechanism of stiffness creation matters.

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