Sequence transferable coarse-grained model of amphiphilic copolymers

Thermal Conductivity of Polymers: A Simple Matter Where Complexity Matters

Thermal conductivity coefficient κ measures the ability of a material to conduct a heat current. In particular, κ is an important property that often dictates the usefulness of a material over a wide range of environmental conditions. For example, while a low κ is desirable for the thermoelectric applications, a large κ is needed when a material is used under the high temperature conditions. These materials range from common crystals to commodity amorphous polymers. The latter is of particular importance because of their use in designing light weight high performance functional materials. In this context, however, one of the major limitations of the amorphous polymers is their low κ, reaching a maximum value of ≈0.4 W/Km that is 2-3 orders of magnitude smaller than the standard crystals. Moreover, when energy is predominantly transferred through the bonded connections, κ ⩾ 100 W/Km. Recently, extensive efforts have been devoted to attain a tunability in κ via macromolecular engineering. In this work, an overview of the recent results on the κ behavior in polymers and polymeric solids is presented. In particular, computational and theoretical results are discussed within the context of complimentary experiments. Future directions are also highlighted.

A Simple Generic Model of Elastin-Like Polypeptides with Proline Isomerization

A generic model of elastin-like polypeptides (ELP) is derived that includes proline isomerization (ProI). As a case study, conformational transition of a -[valine-proline-glycine-valine-glycine]- sequence is investigated in aqueous ethanol mixtures. While the non-bonded interactions are based on the Lennard-Jones (LJ) parameters, the effect of ProI is incorporated by tuning the intramolecular 3- and 4-body interactions known from the underlying all-atom simulations into the generic model. One of the key advantages of such a minimalistic model is that it readily decouples the effects of geometry and the monomer-solvent interactions due to the presence of ProI, thus gives a clearer microscopic picture that is otherwise rather nontrivial within the all-atom setups. These results are consistent with the available all-atom and experimental data. The model derived here may pave the way to investigate large scale self-assembly of ELPs or biomimetic polymers in general.

Smart Polymers for Soft Materials: From Solution Processing to Organic Solids

Polymeric materials are ubiquitous in our everyday life, where they find a broad range of uses-spanning across common household items to advanced materials for modern technologies. In the context of the latter, so called "smart polymers" have received a lot of attention. These systems are soluble in water below their lower critical solution temperature Tℓ and often exhibit counterintuitive solvation behavior in mixed solvents. A polymer is known as smart-responsive when a slight change in external stimuli can significantly change its structure, functionm and stability. The interplay of different interactions, especially hydrogen bonds, can also be used for the design of lightweight high-performance organic solids with tunable properties. Here, a general scheme for establishing a structure-property relationship is a challenge using the conventional simulation techniques and also in standard experiments. From the theoretical side, a broad range of all-atom, multiscale, generic, and analytical techniques have been developed linking monomer level interaction details with macroscopic material properties. In this review, we briefly summarize the recent developments in the field of smart polymers, together with complementary experiments. For this purpose, we will specifically discuss the following: (1) the solution processing of responsive polymers and (2) their use in organic solids, with a goal to provide a microscopic understanding that may be used as a guiding tool for future experiments and/or simulations regarding designing advanced functional materials.

Polymer cyclization for the emergence of hierarchical nanostructures

The creation of synthetic polymer nanoobjects with well-defined hierarchical structures is important for a wide range of applications such as nanomaterial synthesis, catalysis, and therapeutics. Inspired by the programmability and precise three-dimensional architectures of biomolecules, here we demonstrate the strategy of fabricating controlled hierarchical structures through self-assembly of folded synthetic polymers. Linear poly(2-hydroxyethyl methacrylate) of different lengths are folded into cyclic polymers and their self-assembly into hierarchical structures is elucidated by various experimental techniques and molecular dynamics simulations. Based on their structural similarity, macrocyclic brush polymers with amphiphilic block side chains are synthesized, which can self-assemble into wormlike and higher-ordered structures. Our work points out the vital role of polymer folding in macromolecular self-assembly and establishes a versatile approach for constructing biomimetic hierarchical assemblies.

Synthetic polymer nano-objects with well-defined hierarchical structures are important for a wide range of applications such as nanomaterial synthesis, catalysis, and therapeutics. Here the authors demonstrate the strategy of fabricating controlled hierarchical structures through self-assembly of folded synthetic polymers.

Coarse grained simulation of the aggregation and structure control of polyethylene nanocrystals

Polyethylene (PE) telechelics with carboxylate functional groups at both ends have been shown to assemble into hexagonal nanocrystal platelets with a height defined by their chain length in basic CsOH-solution. In this coarse grained (CG) simulation study we show how properties of the functional groups alter the aggregation and crystallization behavior of those telechelics. Systematic variation of the parameters of the CG model showed that important factors which control nanoparticle stability and structure are the PE chain length and the hydrophilicity and the steric demand of the head groups. To characterize the aggregation process we analyzed the number and size of the obtained aggregates as well as intramolecular order and intermolecular alignment of the polymer chains. By comparison of CG and atomistic simulation data, it could be shown that atomistic simulations representing different chemical systems can be emulated with specific, different CG parameter sets. Thus, the results from the (generic) CG simulation models can be used to explain the effect of different head groups and different counterions on the aggregation of PE telechelics and the order of the obtained nanocrystals.

Development of Coarse-Grained Models for Poly(4-vinylphenol) and Poly(2-vinylpyridine): Polymer Chemistries with Hydrogen Bonding

In this paper, we identify the modifications needed in a recently developed generic coarse-grained (CG) model that captured directional interactions in polymers to specifically represent two exemplary hydrogen bonding polymer chemistries-poly(4-vinylphenol) and poly(2-vinylpyridine). We use atomistically observed monomer-level structures (e.g., bond, angle and torsion distribution) and chain structures (e.g., end-to-end distance distribution and persistence length) of poly(4-vinylphenol) and poly(2-vinylpyridine) in an explicitly represented good solvent (tetrahydrofuran) to identify the appropriate modifications in the generic CG model in implicit solvent. For both chemistries, the modified CG model is developed based on atomistic simulations of a single 24-mer chain. This modified CG model is then used to simulate longer (36-mer) and shorter (18-mer and 12-mer) chain lengths and compared against the corresponding atomistic simulation results. We find that with one to two simple modifications (e.g., incorporating intra-chain attraction, torsional constraint) to the generic CG model, we are able to reproduce atomistically observed bond, angle and torsion distributions, persistence length, and end-to-end distance distribution for chain lengths ranging from 12 to 36 monomers. We also show that this modified CG model, meant to reproduce atomistic structure, does not reproduce atomistically observed chain relaxation and hydrogen bond dynamics, as expected. Simulations with the modified CG model have significantly faster chain relaxation than atomistic simulations and slower decorrelation of formed hydrogen bonds than in atomistic simulations, with no apparent dependence on chain length.

Why Do Elastin-Like Polypeptides Possibly Have Different Solvation Behaviors in Water-Ethanol and Water-Urea Mixtures?

The solvent quality determines the collapsed or the expanded state of a polymer. For example, a polymer dissolved in a poor solvent collapses, whereas in a good solvent it opens up. While this standard understanding is generally valid, there are examples when a polymer collapses even in a mixture of two good solvents. This phenomenon, commonly known as co-non-solvency, is usually associated with a wide range of synthetic (smart) polymers. Moreover, recent experiments have shown that some biopolymers, such as elastin-like polypeptides (ELPs) that exhibit lower critical solution behavior T l in pure water, show co-non-solvency behavior in aqueous ethanol mixtures. In this study, we investigate the phase behavior of elastin-like polypeptides (ELPs) in aqueous binary mixtures using molecular dynamics simulations of all-atom and complementary explicit solvent generic models. The model is parameterized by mapping the solvation free energy obtained from the all-atom simulations onto the generic interaction parameters. For this purpose, we derive segment-based (monomer level) generic parameters for four different peptides, namely proline (P), valine (V), glycine (G), and alanine (A), where the first three constitute the basic building blocks of ELPs. Here, we compare the conformational behavior of two ELP sequences, namely -(VPGGG)- and -(VPGVG)-, in aqueous ethanol and -urea mixtures. Consistent with recent experiments, we find that ELPs show co-non-solvency in aqueous ethanol mixtures. Ethanol molecules have preferential binding with all ELP residues, with an interaction contrast of 6-8 k B T, and thus driving the coil-to-globule transition. On the contrary, ELP conformations show a weak variation in aqueous urea mixtures. Our simulations suggest that the glycine residues dictate the overall behavior of ELPs in aqueous urea, where urea molecules have a rather weak preferential binding with glycine as observed from the all atom simulations, i.e., less than k B T. This weak interaction dilutes the overall effect of other neighboring residues and thus ELPs exhibit a different conformational behavior in aqueous urea in comparison to aqueous ethanol mixtures. While the validation of the latter findings will require a more detailed experimental investigation, the results presented here may provide a new twist to the present understanding of cosolvent interactions with peptides and proteins.

Machine-Learning Enabled New Insights into the Coil-to-Globule Transition of Thermosensitive Polymers Using a Coarse-Grained Model

We present a computational framework that integrates coarse-grained (CG) molecular dynamics (MD) simulations and a data-driven machine-learning (ML) method to gain insights into the conformations of polymers in solutions. We employ this framework to study conformational transition of a model thermosensitive polymer, poly( N-isopropylacrylamide) (PNIPAM). Here, we have developed the first of its kind, a temperature-independent CG model of PNIPAM that can accurately predict its experimental lower critical solution temperature (LCST) while retaining the tacticity in the presence of an explicit water model. The CG model was extensively validated by performing CG MD simulations with different initial conformations, varying the radius of gyration of chain, the chain length, and the angle between the adjacent monomers of the initial configuration of PNIPAM (total simulation time = 90 μs). Moreover, for the first time, we utilize the nonmetric multidimensional scaling (NMDS) method, a data-driven ML approach, to gain further insights into the mechanisms and pathways of this coil-to-globule transition by analyzing CG MD simulation trajectories. NMDS analysis provides entirely new insights and shows multiple metastable states of PNIPAM during its coil-to-globule transition above the LCST.

Molecular dynamics study of the LCST transition in aqueous poly(N-n-propylacrylamide)

The breadth of technological applications of smart polymers relies on the possibility of tuning their molecular structure to respond to external stimuli. In this context, N-substituted acrylamide-based polymers are widely studied thermoresponsive polymers. Poly(N-n-propylacrylamide) (PNnPAm), which is a structural isomer of the poly(N-isopropylacrylamide) (PNIPAm) exhibits however, a lower phase transition in aqueous solution. In this work, we use all-atom molecular dynamics simulations of PNnPAm in aqueous solutions to study, from a microscopic point-of-view, the influence of chain size and concentration on the LCST of PNnPAm. Our analysis shows that the collapse of a single oligomer of PNnPAm upon heating is dependent on the chain length and corresponds to a complex interplay between hydration and intermolecular interactions. Analysis of systems with multiple chains shows an aggregation of PNnPAm chains above the LCST.

Main-chain polyacetal conjugates with HIF-1 inhibitors: temperature-responsive, pH-degradable drug delivery vehicles

Main-chain polymer-drug conjugates are prepared from polyacetals (PA) and three hydrophobic diol-based HIF-1 inhibitors. The new conjugates are temperature-responsive with lower critical solution temperature (LCST) behavior and are intrinsically pH-degradable. While soluble in plasma at room temperature, they lose solubility above a target temperature that can be adjusted to virtually any temperature of physicological interest, providing mechanisms for site-specific delivery by active thermal targeting or temperature-induced gelation. The reverse phase transition temperature can be precisely tuned by proper choice of four structural variables that characterize the amphiphilic diol and divinyl ether monomers used in the synthesis, or by adjusting the content of drug incorporated within the polymer. These main-chain PA-drug conjugates also allow for site-specific controlled release as they degrade in acidic microenvironments such as tumors. The degradation rates increase with decreasing pH, degradation products are neutral, and pristine drug is released, without any remnants of the conjugation chemistry.