Evidence of random copolymer adsorption at fluctuating selective interfaces from Monte-Carlo simulation studies

Dynamic transformation of bio-inspired single-chain nanoparticles at interfaces

The interfacial behavior of macromolecules dictates their intermolecular interactions, which can impact the processing and application of polymers for pharmaceutical and synthetic use. Using molecular dynamics simulations, we observe the evolution of a random heteropolymer in the presence of liquid-liquid interfaces. The system of interest forms single-chain nanoparticles through hydrophobic collapse in water, lacking permanent crosslinks and making their morphology mutable in new environments. Complex amphiphilic polymers are shown to be capable of stabilizing high interfacial tension water-hexane interfaces, often unfolding to maximize surface coverage. Despite drastic changes to polymer conformation, monomer presence in the water phase is generally maintained and most changes are due to increased hydrophobic solvent exposure toward the oil phase. These results are then compared to the behavior at the water-graphene interface, where the macromolecules adsorb but do not remodel. The polymer's behavior is shown to depend significantly on both its own amphiphilic character and the deformability of the interface.

Effects of concentration and chain length of the sequence copolymer on interfacial properties of homopolymers/sequence copolymers ternary blends: A DPD simulation study

The effect of the concentration and chain length of the copolymer AB with sequence length τ = 8 on the interfacial properties of the ternary mixtures A₁₀/AB/B₁₀ are investigated by the dissipative particle dynamics (DPD) simulations. It is found that: i) As the copolymer concentration varies from 0.05 to 0.15, increasing the copolymer enrichment at the center of the interface enlarges the interface width ω and reduces the interfacial tension. However, as the concentration of the sequence copolymers further increases to 0.2, because the interface has formed micelles and the micellization could lower the efficiency of copolymers as a compatibilizer, the interfacial tension exhibits a slightly increase; ii) elevating the copolymer chain length, the copolymer volumes vary from a cylinder shape to a pancake shape. The blends of the copolymer with chain length N_cp = 24 exhibit a wider interfacial width w and a lower interfacial tension γ, which indicates that the sequenced copolymer N_cp = 24 exhibits a better performance as the compatibilizers. This study illustrates the correlations between the reduction in interfacial tension produced by the sequence copolymers and their molecular parameters, which guide a rational design of an efficient compatibilizer.

Decoding Interaction Patterns from the Chemical Sequence of Polymers Using Neural Networks

The relation between chemical sequences and the properties of polymers is considered using artificial neural networks with a low-dimensional bottleneck layer of neurons. These encoder-decoder architectures may compress the input information into a meaningful set of physical variables that describe the correlation between distinct types of data. In this work, neural networks were trained to translate a sequence of hydrophilic and hydrophobic segments into the effective free energy landscape of a copolymer interacting with a lipid membrane. The training data were obtained by the sampling of coarse-grained polymer conformations in a given membrane density field. Neural networks that were split into separate channels have learned to decompose the free energy into independent components that are explainable by known concepts from polymer physics. The semantic information in the hidden layers was employed to predict polymer translocation events through a membrane for a more detailed dynamic model via a transfer learning procedure. The search for minimal translocation times in the compressed chemical space underlined that nontrivial sequence motifs may lead to optimal properties.

Hyperscaling relationship between the interfacial tension of liquids and their correlation length near the critical point

Interfaces involving coexisting phases in condensed matter are essential in many phenomena: wetting, nucleation, morphology, phase separation kinetics, membranes, phase coexistence in nanomaterials, etc. The majority of analytical theories available use concepts derived from mean field artifacts which do not describe adequately these systems. Satisfactory numerical simulation of interfaces at the atomistic to mesoscopic scale is still a challenge. In the present work, the interfacial tension between mixtures of organic solvents and water is obtained from mesoscopic computer simulations. The temperature dependence of the interfacial tension is found to obey a scaling law with an average critical exponent μ = 1.23. Additionally, we calculate the evolution of the correlation length, defined as the thickness of the interface between the immiscible fluids, as a function of temperature and find that it obeys also a scaling law with an average critical exponent being ν = 0.67. Finally, we show that the comparison of μ and ν for these binary mixtures constitutes the first test of Widom's hyperscaling relationship between these exponents in 3d, expressed as μ = ν (d - 1). Based on these values and those for the 3d Ising model it is argued that both systems belong to the same universality class, which opens up the way for the calculation of new scaling exponents.