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To rationally design supramolecular polymers capable of self-healing or reconfiguring their structure in a dynamically controlled way, it is imperative to gain access into the intrinsic dynamics of the supramolecular polymer (dynamic exchange of monomers) while maintaining a high-resolution description of the monomer structure. But this is prohibitively difficult at experimental level. Here we show atomistic, coarse-grained modelling combined with advanced simulation approaches to characterize the molecular mechanisms and relative kinetics of monomer exchange in structural variants of a synthetic supramolecular polymer in different conditions. We can capture differences in supramolecular dynamics consistent with the experimental observations, revealing that monomer exchange in and out the fibres originates from the defects present in their supramolecular structure. At the same time, the submolecular resolution of this approach offers a molecular-level insight into the dynamics of these bioinspired materials, and a flexible tool to obtain structure-dynamics relationships for a variety of polymeric assemblies. Accessing the dynamics of soft self-assembled materials at high resolution is very difficult. Here the authors show atomistic and coarse-grained modelling combined with enhanced sampling to characterize the molecular mechanisms and kinetics of monomer exchange in synthetic supramolecular polymers.

Multi-component systems often display convoluted behavior, pathway complexity and coupled equilibria. In recent years, several ways to control complex systems by manipulating the subtle balances of interaction energies between the individual components have been explored and thereby shifting the equilibrium between different aggregate states. Here we show the enantioselective chain-capping and dilution-induced supramolecular polymerization with a Zn 2+ -porphyrin-based supramolecular system when going from long, highly cooperative supramolecular polymers to short, disordered aggregates by adding a monotopic Mn 3+ -porphyrin monomer. When mixing the zinc and manganese centered monomers, the Mn 3+ -porphyrins act as chain-cappers for Zn 2+ -porphyrin supramolecular polymers, effectively hindering growth of the copolymer and reducing the length. Upon dilution, the interaction between chain-capper and monomers weakens as the equilibria shift and long supramolecular polymers form again. This dynamic modulation of aggregate morphology and length is achieved through enantioselectivity in the aggregation pathways and concentration-sensitive equilibria. All-atom and coarse-grained molecular simulations provide further insights into the mixing of the species and their exchange dynamics. Our combined experimental and theoretical approach allows for precise control of molecular self-assembly and chiral discrimination in complex systems. Controlling multicomponent systems is difficult due to convoluted behavior, pathway complexity, and coupled equilibria. Here the authors showed modulation of aggregate morphology in a zinc porphyrin-based supramolecular system via judicious capping with a manganese porphyrin monomer, in which the monomer’s chirality can influence the supramolecular behavior.

Mechanical interlocking of molecules (catenation) is a nontrivial challenge in modern synthetic chemistry and materials science 1 , 2 . One strategy to achieve catenation is the design of pre-annular molecules that are capable of both efficient cyclization and of pre-organizing another precursor to engage in subsequent interlocking 3 – 9 . This task is particularly difficult when the annular target is composed of a large ensemble of molecules, that is, when it is a supramolecular assembly. However, the construction of such unprecedented assemblies would enable the visualization of nontrivial nanotopologies through microscopy techniques, which would not only satisfy academic curiosity but also pave the way to the development of materials with nanotopology-derived properties. Here we report the synthesis of such a nanotopology using fibrous supramolecular assemblies with intrinsic curvature. Using a solvent-mixing strategy, we kinetically organized a molecule that can elongate into toroids with a radius of about 13 nanometres. Atomic force microscopy on the resulting nanoscale toroids revealed a high percentage of catenation, which is sufficient to yield ‘nanolympiadane’ 10 , a nanoscale catenane composed of five interlocked toroids. Spectroscopic and theoretical studies suggested that this unusually high degree of catenation stems from the secondary nucleation of the precursor molecules around the toroids. By modifying the self-assembly protocol to promote ring closure and secondary nucleation, a maximum catenation number of 22 was confirmed by atomic force microscopy. Nanoscale toroids with a high percentage of poly-catenation and radii of up to about 13 nm are kinetically organized using fibrous supramolecular assemblies with intrinsic curvature and a solvent-mixing strategy.

Supramolecular polymers are composed of monomers that self-assemble non-covalently generating distributions of fibres in continuous exchange-and-communication with each other and the surroundings. Intriguing collective properties may emerge in such molecular-scale complex systems, following mechanisms often difficult to ascertain. Here we show how non-trivial collective behaviours may emerge in dynamical supramolecular polymer systems already at low-complexity levels. We combine minimalistic models, simulations, and advanced statistical analyses investigating how cooperative and non-cooperative supramolecular polymer systems respond to a specific stimulus: i.e., the addition of molecular sequestrators perturbing their equilibrium. Our data show how, while in a non-cooperative system all assemblies populating the system suffer uniformly the perturbation, in a cooperative system the larger/stronger assemblies survive at the expense of the smaller/weaker entities. Collective behaviours typical of larger-scale and more complex (social, economic, etc.) systems may thus emerge even in relatively simple self-assembling systems from the internal (microscopic) dynamic heterogeneity of their ensembles. Supramolecular polymers possess features typical of complex systems, but the mechanisms that lead to the emergence of collective properties inside them are often difficult to ascertain. Here the authors show how nontrivial collective behaviors, typical of higher-scale, more complex systems, may emerge in dynamical supramolecular polymer systems already at low-complexity levels, from the internal dynamical diversity characterizing their ensembles.

Supramolecular polymers are composed of monomers that self-assemble non-covalently, generating distributions of monodimensional fibres in continuous communication with each other and with the surrounding solution. Fibres, exchanging molecular species, and external environment constitute a sole complex system, which intrinsic dynamics is hard to elucidate. Here we report coarse-grained molecular simulations that allow studying supramolecular polymers at the thermodynamic equilibrium, explicitly showing the complex nature of these systems, which are composed of exquisitely dynamic molecular entities. Detailed studies of molecular exchange provide insights into key factors controlling how assemblies communicate with each other, defining the equilibrium dynamics of the system. Using minimalistic and finer chemically relevant molecular models, we observe that a rich concerted complexity is intrinsic in such self-assembling systems. This offers a new dynamic and probabilistic (rather than structural) picture of supramolecular polymer systems, where the travelling molecular species continuously shape the assemblies that statistically emerge at the equilibrium. The dynamic structure of supramolecular polymers is challenging to determine both in experiments and in simulations. Here the authors use coarse-grained molecular models to provide a comprehensive analysis of the molecular communication in these complex molecular systems.

The development of powerful methods for living covalent polymerization has been a key driver of progress in organic materials science. While there have been remarkable reports on living supramolecular polymerization recently, the scope of monomers is still narrow and a simple solution to the problem is elusive. Here we report a minimalistic molecular platform for living supramolecular polymerization that is based on the unique structure of all-cis 1,2,3,4,5,6-hexafluorocyclohexane, the most polar aliphatic compound reported to date. We use this large dipole moment (6.2 Debye) not only to thermodynamically drive the self-assembly of supramolecular polymers, but also to generate kinetically trapped monomeric states. Upon addition of well-defined seeds, we observed that the dormant monomers engage in a kinetically controlled supramolecular polymerization. The obtained nanofibers have an unusual double helical structure and their length can be controlled by the ratio between seeds and monomers. The successful preparation of supramolecular block copolymers demonstrates the versatility of the approach. Living supramolecular polymerization can produce precise covalent polymers, but the scope of monomers is still narrow. Here the authors show a molecular platform for living supramolecular polymerization that is based on the unique structure of all-cis 1,2,3,4,5,6- 22 hexafluorocyclohexane, the most polar aliphatic compound reported to date.

Dendrimers are well-defined macromolecules whose highly branched structure is reminiscent of many natural structures, such as trees, dendritic cells, neurons or the networks of kidneys and lungs. Nature has privileged such branched structures for increasing the efficiency of exchanges with the external medium; thus, the whole structure is of pivotal importance for these natural networks. On the contrary, it is generally believed that the properties of dendrimers are essentially related to their terminal groups, and that the internal structure plays the minor role of an ‘innocent’ scaffold. Here we show that such an assertion is misleading, using convergent information from biological data (human monocytes activation) and all-atom molecular dynamics simulations on seven families of dendrimers (13 compounds) that we have synthesized, possessing identical terminal groups, but different internal structures. This work demonstrates that the scaffold of nanodrugs strongly influences their properties, somewhat reminiscent of the backbone of proteins. The biological properties of dendrimers are thought to be largely dependent on the chemical nature of their surface. Here, the authors show that the internal scaffold of dendritic nanodrugs strongly influences their bioactivity, based on convergent information from biology and computation results.

Chemists have created molecular machines and switches with specific mechanical responses that were typically demonstrated in solution, where mechanically relevant motion is dissipated in the Brownian storm. The next challenge consists of designing specific mechanisms through which the action of individual molecules is transmitted to a supramolecular architecture, with a sense of directionality. Cellular microtubules are capable of meeting such a challenge. While their capacity to generate pushing forces by ratcheting growth is well known, conversely these versatile machines can also pull microscopic objects apart through a burst of their rigid tubular structure. One essential feature of this disassembling mechanism is the accumulation of strain in the tubules, which develops when tubulin dimers change shape, triggered by a hydrolysis event. We envision a strategy toward supramolecular machines generating directional pulling forces by harnessing the mechanically purposeful motion of molecular switches in supramolecular tubules. Here, we report on wholly synthetic, water-soluble, and chiral tubules that incorporate photoswitchable building blocks in their supramolecular architecture. Under illumination, these tubules display a nonlinear operation mode, by which light is transformed into units of strain by the shape changes of individual switches, until a threshold is reached and the tubules unleash the strain energy. The operation of this wholly synthetic and stripped-down system compares to the conformational wave by which cellular microtubules disassemble. Additionally, atomistic simulations provide molecular insight into how strain accumulates to induce destabilization. Our findings pave the way toward supramolecular machines that would photogenerate pulling forces, at the nanoscale and beyond.

Sentiment lexicon is a reliable resource in computing sentiment classification. However, a general purpose lexicon alone is not sufficient, since text sentiment classification is perceived as a context-dependent task in the literature. On the contrary, we observe that many people tend to imitate others while writing reviews. As such, the subject of all the public opinion towards an entity ends up as an imbalanced corpus. In this paper, we intend to induce a context-based lexicon as a resource to explore imbalanced text sentiment classification. This method addresses the above mentioned two critical problems in text sentiment classification. First, it identifies subjective words relative to the context and computes the weight scores for subjective terms and full review. Also, in recent years, the application of RNNs to a variety of problems has been incredible, especially in natural language processing tasks. Thus, we take the advantages of the context-based lexicon as well as a bidirectional LSTM to handle text sentiment classification. Second, it deals imbalanced data by deploying a text based oversampling method for creating new synthetic text samples. The reason behind using a text based oversampling method is to make use of semantics of the information while creating new text samples. Experimental results prove that leveraging sentiment lexicon relative to the context and application of Bidiricetional LSTM with text based oversampling is useful in imbalanced text sentiment classification and in achieving state-of-the-art results over deep neural learning model baselines.

Bio-based polyurethane (PU) coatings were prepared from novel branched isostearic acid (ISA) and long chains dimer fatty acid. Fatty amide was synthesized by the amidation of ISA with diethanolamine and the required hydroxyl functionality was developed via condensation polymerization with dimer fatty acid to produce polyesteramide polyol. The structure of the synthesized ISA based fatty amide (ISAFA) and polyesteramide polyol (ISAPEP) were identified using Fourier-transform infrared spectroscopy (FT-IR) and proton nuclear magnetic resonance (1HNMR). The number average molecular weight of prepared polyesteramide polyol was assessed by gel permeation chromatography (GPC), while the rheological behavior was examined by the rheometer. Polyurethane metal coatings were developed from polyesteramide polyol, which crosslinks with hexamethylene diisocyanate (PU-H) and toluene diisocyanate (PU-T) and studied the influence of isocyanate structure on final PU coatings. A comparison in the crosslinks density of PU films was investigated by the gel content method. Differential scanning calorimetry (DSC) and thermo gravimetric analysis (TGA) were performed to evaluate the glass transition temperature (Tg) and thermal stability of the PU coatings. The surface roughness of prepared PU coatings was examined by Atomic force microscopy (AFM). The PU coated metal panels and films were examined for swelling resistance, hydrophobicity, mechanical, and coating properties. Results confirmed that bio-based long chain fatty acids provided hydrophobicity, flexibility and impact resistance to final PU coatings. It also noted that PU-T coating resulted in increasing thermal, mechanical, and coating properties compared to PU-H coating and this resulted from the structure of TDI, which contribute to higher crosslink density (i.e. presence of aromatic ring).