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Dialysis diffusion kinetics are performed via in situ NMR spectroscopy for numerous different raw polymeric solutions to result in a general guideline for polymer purification using dialysis.

This study presents interpenetrating metallopolymer networks (IPNs) based on the orthogonality of two different metal complexes. The synthesized IPNs exhibit excellent shape-memory and self-healing abilities.

The halogen bond is a special non-covalent interaction, which can represent a powerful tool in supramolecular chemistry. Although the halogen bond offers several advantages compared to the related hydrogen bond, it is currently still underrepresented in polymer science. The structural related hydrogen bonding assumes a leading position in polymer materials containing supramolecular interactions, clearly indicating the high potential of using halogen bonding for the design of polymeric materials. The current developments regarding halogen bonding containing polymers include self-assembly, photo-responsive materials, self-healing materials and others. These aspects are highlighted in the present perspective. Furthermore, a perspective on the future of this rising young research field is provided., The incorporation of halogen bonding into polymer architectures is a new approach for the design of functional materials. This perspective emphasizes the current development in the field of halogen bonding featuring polymer materials.

This work presents the synthesis and characterization of easily tuneable shape-memory metallopolymers. Furthermore, the structural design enables excellent rewriting properties. For this purpose, two different polymers were synthesized using either 2-ethyl hexyl- or butyl methacrylate monomers featuring both histidine and terpyridine ligands in their side chains. The addition of metal salt resulted in the selective formation of stable complexes with the terpyridine ligands (NiCl2 or FeSO4) and addition of a second metal ion led to labile ones with the histidine ligands (Zn(TFMS)2 or NiCl2). As a consequence, a dual supramolecular crosslinked metallopolymer network was formed, which was confirmed using Raman spectroscopy. Due to the use of different metal salts, it is possible to tune the stability of both complexes independently and, thus, the switching and rewriting temperature of the shape-memory polymer. Fixity and recovery rates up to 99% were obtained by this approach. Furthermore, thermo mechanical analyses revealed the rewriting possibility without reducing the shape-memory abilities.

Fluorescence upconversion by triplet-triplet annihilation is demonstrated for a fully polymer-integrated material, i.e. in the limit of restricted diffusion. Organic sensitizer and acceptor are covalently attached to a poly(methacrylate) backbone, yielding a metal-free macromolecular all-in-one system for fluorescence upconversion. Due to the spatial confinement of the optically active molecular components, i.e. annihilator and sensitizer, UC by TTA in the constrained polymer system in solution is achieved at exceptionally low averaged annihilator concentrations. However, the UC quantum yield in the investigated systems is found to be low, highlighting that only chromophores in specific local surroundings yield upconversion in the limit of restricted diffusion. A photophysical model is proposed taking the heterogeneous local environment within the polymers into account.

Particle sizes represent one of the key factors influencing the usability and specific targeting of nanoparticles in medical applications such as vectors for drug or gene therapy. A multi‐layered graph convolutional network combined with a fully connected neuronal network is presented for the prediction of the size of nanoparticles based only on the polymer structure, the degree of polymerization, and the formulation parameters. The model is capable of predicting particle sizes obtained by nanoprecipitation of different poly(methacrylates). This includes polymers the network has not been trained with, indicating the high potential for generalizability of the model. By utilizing this model, a significant amount of time and resources can be saved in formulation optimization without extensive primary testing of material properties., Utilizing a combination of different model structures and machine learning techniques, a model that is able to predict the size of polymeric nanoparticles based solemnly on the structure and preparation parameters is presented. The prediction achieves results with errors

The self-healing behavior of two supramolecular polymers based on π–π-interactions featuring different polymer backbones is presented. For this purpose, these polymers were synthesized utilizing a polycondensation of a perylene tetracarboxylic dianhydride with polyether-based diamines and the resulting materials were investigated using various analytical techniques. Thus, the molecular structure of the polymers could be correlated with the ability for self-healing. Moreover, the mechanical behavior was studied using rheology. The activation of the supramolecular interactions results in a breaking of these noncovalent bonds, which was investigated using IR spectroscopy, leading to a sufficient increase in mobility and, finally, a healing of the mechanical damage. This scratch-healing behavior was also quantified in detail using an indenter.

The mechanical addressability of specific chemical bonds holds a high potential for the improvement of polymeric materials. While in many cases, mechanical forces applied to polymers lead to bond scissoring and materials failure, including mechanophores into the polymer structure can lead to stimuli-responsive materials reacting to an applied force in a predefined manner. In this contribution, the mechanical addressability of bis-terpyridine metal complexes embedded into a polymer structure is investigated. The activation of the transition metal complexes in the metallopolymer is monitored by adding a fluorescent sensor molecule to the metallopolymer solution during ultrasonication. Upon sonication, the activation of the complexes leads to fluorescence-quenching of the sensor. The dependency of the metal ion and the type of polymer as well as their molar mass is investigated in detail, showing that this concept could possibly be used in further application of stimuli-responsive or self-healing materials.

Tailor-made metallopolymers have the ability to heal surface cracks during thermal treatment. In order to evaluate the self-healing properties in a detailed fashion, a defined way to induce scratches in combination with a quantitative analysis is required. Thus, the previously described qualitative statements of healable metallopolymers are quantified and examined in more detail in the present study. For this purpose, the scratch profiles, introduced by laser ablation or by a scalpel treatment, are measured and the residual scratch area is displayed as a function of the healing time. This quantification is the basis for future healing experiments using the volume for the determination of the healing efficiency. Furthermore, it is also presented that the healing of defects occurs even if the material has been ablated by using the intensity focused energy of a fs-laser. A comparison of the healing efficiencies is performed and the analysis offers insights into the underlying healing process. Furthermore, the reproducibility of the defect formation is very uniform and the depth can easily be tuned by changing the settings. Consequently, laser ablation is shown to be an ideal tool to induce scratches into a material in order to evaluate the subsequent healing behavior in a quantitative fashion.

This article presents novel biobased ionomers featuring self-healing abilities. These smart materials are synthesized from itaconic acid derivates. Large quantities of itaconic acid can be produced from diverse biomass like corn, rice, and others. This study presents a comprehensive investigation of their thermal and mechanical properties via differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and FT-Raman and FT-IR measurements as well as dynamic mechanic analysis. Within all these measurements, different kinds of structure-property relationships could be derived from these measurements. For example, the proportion of ionic groups enormously influences the self-healing efficiency. The investigation of the self-healing abilities reveals healing efficiencies up to 99% in 2 h at 90 °C for the itaconic acid based ionomer with the lowest ionic content.

In this work, we present a new strategy to engineer novel self-healing ionomers, namely, zwitterionic polymers, and a comprehensive analysis of their mechanical, viscoelastic, and scratch-healing properties. This new method enables reproducible damage of the polymer surfaces, calculation of the scratch volume through tactile profile scans, and quantification of the self-healing efficiency. Based on the results of the scratch tests and complementary rheology, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and hardness tests, new trends, and structure–property relationships can be identified. A novel soft material that can heal itself has been engineered by researchers in Germany. Polymeric molecules are formed by long chains of atoms. Some polymers can reform when broken, giving them the intrinsic ability to repair scratches or tears. These self-healing properties are useful for applications in long-lasting biomedical implants, for example. Martin D. Hager and colleagues from the Friedrich Schiller University Jena synthesized and characterized a novel type of self-healing materials using a so-called zwitterionic polymer, a polymer which includes both positive and negative charges in the side-chains. Using a simple new method to create their material, the team investigated its hardness, its viscoelastic properties and quantified how efficiently it healed scratches of different sizes. This novel approach to scratch-healing tests, which utilizes the scratch volume, is both reproducible and quantifiable and could be extended to other materials. New self-healing zwitterionic polymer networks are prepared and the healing efficiency is quantified by 3D plotting, as well as volume calculation of the damaged surface after tactile profile scans. The results are complemented by comprehensive investigations of the mechanical, viscoelastic, and thermal properties in order to identify structure-property relationships.

Self-healing polymers look back on almost 40 years of history. Beginning in the early 1980s, many different examples were studied—for instance, the self-healing polymers based on microcapsules in 2001. These materials were able to close cracks, to heal damage, and to restore their (mechanical) properties almost like the big role model: nature. The chapter will provide a general discussion of the basic principles of self-healing polymers and will elucidate the underlying healing mechanisms. Thus it will go beyond a pure description of several aspects of self-healing polymers, and it will contain information on how a polymer must be designed to show self-healing. Within this context, a view on the mechanism of extrinsic and intrinsic self-healing polymers will be presented.

Shape memory polymers represent an interesting class of stimuli-responsive polymers. With their ability to memorize and recover their original shape, they could be useful in almost every area of our daily life. We herein present the synthesis of shape-memory metallopolymers in which the switching unit is designed by using bis(pyridine&ndash, triazole) metal complexes. The polymer networks were synthesized via free radical polymerization of methyl-, ethyl- or butyl-methacrylate, tri(ethylene glycol) dimethacrylate and a methacrylate moiety of the triazole&ndash, pyridine ligand. By the addition of zinc(II) or cobalt(II) acetate it was possible to achieve metallopolymer networks featuring shape-memory abilities. The successful formation of the metal-ligand complex was proven by Fourier transform infrared (FT-IR) spectroscopy and by 1H NMR spectroscopy. Furthermore, the shape-recovery behavior was studied in detailed fashion and even triple-shape memory behavior could be revealed.

For the first time, reversible covalent urethane units are used for the design of new self-healing polymers. For this purpose, an electron-poor diol was synthesized and utilized as crosslinker to create a dynamic polymer network. Therefore, the diol, butyl methacrylate as well as 2-isocyanato ethyl methacrylate are intermixed and photo-polymerized in a bone-shaped PTFE mold. The resulting test specimens are characterized by DSC, TGA and DMTA and the self-healing behavior is studied using tensile tests. Thereby, healing efficiencies of up to 85% could be reached while the material exhibits good mechanical properties with high E-moduli. Additionally, the self-healing mechanism, which is based on exchange reactions of the reversible urethane moieties, is investigated by Raman as well as temperature dependent IR measurements.

Within the current study, a novel approach for the detailed determination of the scratch healing efficiency in mussel-inspired polymer films is presented. For this purpose, a sensor molecule was incorporated into a self-healing polymer network based on reversible zinc-histidine interactions. The fluorescence of the sensor molecule was monitored enabling a detailed depth- and time-resolved determination of the healing efficiency by means of confocal laser scanning microscopy (CLSM). Finally, this concept represents an efficient and detailed approach for the determination of the scratch self-healing efficiency in polymer films and can also be applied for other scratch self-healing systems, which are based on reversible dynamic bonds.

An experimental method for determining solid/liquid interfacial energies of alloys is presented. Spherical intermetallic particles of Al2Cu with diameters down to 50 nm were generated as ”divorced eutectic” in an initially homogeneous solid solution of 4 wt% Cu in Al by short-term annealing (t

In this work we present the first incorporation of bis-bidentate halogen bond linkers into an organic healing ionomer system resulting in the formation of crosslinked supramolecular networks. The obtained supramolecular coatings feature an excellent healing ability as well as an enhanced mechanical performance.

The embedding of molecular reactive species such as catalysts into polymers opens up new avenues for advanced composite design for energy technologies and beyond. Herein, two new approaches for the connection of molecular molybdenum sulfide clusters and synthetic polymers are presented. The approach one is based on the utilization of a molecular molybdenum sulfide cluster as a potential chain transfer agent in a free radical polymerization process. The second one is a postpolymerization functionalization of a thiol end‐functionalized polymer with a thiomolybdate cluster. Detailed characterization using Raman spectroscopy reveals the successful functionalization in the latter approach, whereas in the other one, a noncovalent interaction is suggested. Furthermore, visible light‐driven hydrogen evolution demonstrates that the molecular molybdenum sulfide cluster retains its catalytic activity after the combination with polymers.

The incorporation of metal complexes into polymers leads to functional materials; whereas, the properties of polymers – easy processability, light weight or the adjustable molar mass – and those of metal complexes – optical properties, catalytic activity or biomedical potential – can be combined. Through the years, various different applications have been developed, depending on the needs of current techniques and society. Thus, advanced applications enabled by metallopolymers, include areas: like self-assembly, stimuli-responsive behavior, catalysis, optics, self-healing, shape-memory as well as biomedicine and further potential applications can be expected. This review will summarize and discuss these applications as well as how the interactions of metal complexes and polymers enable them.

The scratch healing behavior of different polymers based on reversible interactions was investigated. For this purpose, scratches were induced via femtosecond laser ablation and were analyzed using laser-scanning microscopy. The healing process was monitored over time and the residual scratch volume was studied. Thus, healing kinetics of different self-healing polymers were obtained revealing a new three step-healing process. An initial time is required in order to start the crack closure behavior. Afterwards, a fast healing behavior followed by a final slow healing period could be observed. Consequently, this study discloses significant insights into the time-dependent healing behavior of polymeric materials.

The main aim of this work is to study the respective contribution of the hard and soft blocks of a metal-ligand containing block copolymer to the self-healing behavior. To this aim, different block copolymers containing terpyridine were synthesized using reversible addition-fragmentation chain transfer (RAFT) polymerization. These block copolymers consisted of polystyrene as the hard block, n-butyl acrylate (BA) as soft block and terpyridine units as the ligand moiety placed at different locations in the soft block. These block copolymers were complexed with manganese(II) chloride to introduce transient crosslinks and, thus, self-healing behavior. Homopolymers with the hard and soft block only were also synthesized and tested. A quasi-irreversible crosslinking, i.e. by using nickel(II) nitrate, was performed in order to study the dynamics of the permanently (strongly) crosslinked network. Rheological master curves were generated enabling the determination of the terminal flow in these networks and the reversibility of the supramolecular interactions. Additionally, the macroscopic scratch healing behavior and the molecular mobility of the polymer chains in these supramolecular networks were investigated. A kinetic study of the scratch healing was performed to determine the similarities in temperature dependence for rheological relaxations and macroscopic scratch healing. In our previous work, we have explored the effect of strength of the reversible metal-ligand interaction and the effect of changing the ratio of hard to soft block. This work goes further in separating the individual contributions of the hard and soft blocks as well as the reversible interactions and to reveal their relative importance in the complex phenomenon of scratch healing.

Biology offers a valuable inspiration toward the development of self-healing engineering composites and polymers. In particular, chemical level design principles extracted from proteinaceous biopolymers, especially the mussel byssus, provide inspiration for design of autonomous and intrinsic healing in synthetic polymers. The mussel byssus is an acellular tissue comprised of extremely tough protein-based fibers, produced by mussels to secure attachment on rocky surfaces. Threads exhibit self-healing response following an apparent plastic yield event, recovering initial material properties in a time-dependent fashion. Recent biochemical analysis of the structure⁻function relationships defining this response reveal a key role of sacrificial cross-links based on metal coordination bonds between Zn2+ ions and histidine amino acid residues. Inspired by this example, many research groups have developed self-healing polymeric materials based on histidine (imidazole)⁻metal chemistry. In this review, we provide a detailed overview of the current understanding of the self-healing mechanism in byssal threads, and an overview of the current state of the art in histidine- and imidazole-based synthetic polymers.