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Institute
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Enzyme degradable polymersomes from chitosan-g-[poly-l-lysine-block-epsilon-caprolactone] copolymer
(2020)
The scope of this study includes the synthesis of chitosan-g-[peptide-poly-epsilon-caprolactone] and its self-assembly into polymeric vesicles employing the solvent shift method. In this way, well-defined core-shell structures suitable for encapsulation of drugs are generated. The hydrophobic polycaprolactone side-chain and the hydrophilic chitosan backbone are linked via an enzyme-cleavable peptide. The synthetic route involves the functionalization of chitosan with maleimide groups and the preparation of polycaprolactone with alkyne end-groups. A peptide functionalized with a thiol group on one side and an azide group on the other side is prepared. Thiol-ene click-chemistry and azide-alkyne Huisgen cycloaddition are then used to link the chitosan and poly-epsilon-caprolactone chains, respectively, with this peptide. For a preliminary study, poly-l-lysin is a readily available and cleavable peptide that is introduced to investigate the feasibility of the system. The size and shape of the polymersomes are studied by dynamic light scattering and cryo-scanning electron microscopy. Furthermore, degradability is studied by incubating the polymersomes with two enzymes, trypsin and chitosanase. A dispersion of polymersomes is used to coat titanium plates and to further test the stability against enzymatic degradation.
This opinion article describes recent approaches to use the "biorefinery" concept to lower the carbon footprint of typical mass polymers, by replacing parts of the fossil monomers with similar or even the same monomer made from regrowing dendritic biomass. Herein, the new and green catalytic synthetic routes are for lactic acid (LA), isosorbide (IS), 2,5-furandicarboxylic acid (FDCA), and p-xylene (pXL). Furthermore, the synthesis of two unconventional lignocellulosic biomass derivable monomers, i.e., alpha-methylene-gamma-valerolactone (MeGVL) and levoglucosenol (LG), are presented. All those have the potential to enter in a cost-effective way, also the mass market and thereby recover lost areas for polymer materials. The differences of catalytic unit operations of the biorefinery are also discussed and the challenges that must be addressed along the synthesis path of each monomers.
A method for the fabrication of well-defined metallic nanostructures is presented here in a simple and straightforward fashion. As an alternative to lithographic techniques, this routine employs microcontact printing utilizing wrinkled stamps, which are prepared from polydimethylsiloxane (PDMS), and includes the formation of hydrophobic stripe patterns on a substrate via the transfer of oligomeric PDMS. Subsequent backfilling of the interspaces between these stripes with a hydroxyl-functional poly(2-vinyl pyridine) then provides the basic pattern for the deposition of citrate-stabilized gold nanoparticles promoted by electrostatic interaction. The resulting metallic nanostripes can be further customized by peeling off particles in a second microcontact printing step, which employs poly(ethylene imine) surface-decorated wrinkled stamps, to form nanolattices. Due to the independent adjustability of the period dimensions of the wrinkled stamps and stamp orientation with respect to the substrate, particle arrays on the (sub)micro-scale with various kinds of geometries are accessible in a straightforward fashion. This work provides an alternative, cost-effective, and scalable surface-patterning technique to fabricate nanolattice structures applicable to multiple types of functional nanoparticles. Being a top-down method, this process could be readily implemented into, e.g., the fabrication of optical and sensing devices on a large scale.
We search for homovalent alternatives for A, B, and X-ions in ABX(3) type inorganic halide perovskites suitable for tandem solar cell applications. We replace the conventional A-site organic cation CH3NH3, by 3 inorganic cations, Cs, K, and Rb, and the B site consists of metals; Cd, Hg, Ge, Pb, and Sn This work is built on our previous high throughput screening of hybrid perovskite materials (Kar et al 2018 J. Chem. Phys. 149, 214701). By performing a systematic screening study using Density Functional Theory (DFT) methods, we found 11 suitable candidates; 2 Cs-based, 3 K-based and 6 Rb-based that are suitable for tandem solar cell applications.
Stem cells are capable of sensing and processing environmental inputs, converting this information to output a specific cell lineage through signaling cascades. Despite the combinatorial nature of mechanical, thermal, and biochemical signals, these stimuli have typically been decoupled and applied independently, requiring continuous regulation by controlling units. We employ a programmable polymer actuator sheet to autonomously synchronize thermal and mechanical signals applied to mesenchymal stem cells (MSC5). Using a grid on its underside, the shape change of polymer sheet, as well as cell morphology, calcium (Ca2+) influx, and focal adhesion assembly, could be visualized and quantified. This paper gives compelling evidence that the temperature sensing and mechanosensing of MSC5 are interconnected via intracellular Ca2+. Up-regulated Ca2+ levels lead to a remarkable alteration of histone H3K9 acetylation and activation of osteogenic related genes. The interplay of physical, thermal, and biochemical signaling was utilized to accelerate the cell differentiation toward osteogenic lineage. The approach of programmable bioinstructivity provides a fundamental principle for functional biomaterials exhibiting multifaceted stimuli on differentiation programs. Technological impact is expected in the tissue engineering of periosteum for treating bone defects.
Stem cells are capable of sensing and processing environmental inputs, converting this information to output a specific cell lineage through signaling cascades. Despite the combinatorial nature of mechanical, thermal, and biochemical signals, these stimuli have typically been decoupled and applied independently, requiring continuous regulation by controlling units. We employ a programmable polymer actuator sheet to autonomously synchronize thermal and mechanical signals applied to mesenchymal stem cells (MSC5). Using a grid on its underside, the shape change of polymer sheet, as well as cell morphology, calcium (Ca2+) influx, and focal adhesion assembly, could be visualized and quantified. This paper gives compelling evidence that the temperature sensing and mechanosensing of MSC5 are interconnected via intracellular Ca2+. Up-regulated Ca2+ levels lead to a remarkable alteration of histone H3K9 acetylation and activation of osteogenic related genes. The interplay of physical, thermal, and biochemical signaling was utilized to accelerate the cell differentiation toward osteogenic lineage. The approach of programmable bioinstructivity provides a fundamental principle for functional biomaterials exhibiting multifaceted stimuli on differentiation programs. Technological impact is expected in the tissue engineering of periosteum for treating bone defects.
Supramolecular polymers or fibers are non-covalent assemblies of unimeric building blocks connected by secondary interactions such as hydrogen bonds or pi-pi interactions. Such structures hold enormous potential in the development of future materials, as their non-covalent nature makes them highly modular and adaptive. Within this review we aim to provide a broad overview over the area of linear supramolecular polymers including the different mechanisms of their polymerization as well as methods essential for their characterization. The different non-covalent interactions able to form supramolecular polymers are discussed, and key examples for each species are shown. Particular emphasis is laid on the development of living supramolecular polymerization able to produce fibers with a controlled length and low length dispersity, and even enable the production of supramolecular block copolymers. Another important and very recent field is the development of out-of-equilibrium supramolecular polymers, where the polymerization process can be temporally controlled enabling access to highly adaptive materials.
This paper discusses the full structural solution of the hybrid perovskite formamidinium lead tribromide (FAPbBr(3)) and its temperature-dependent phase transitions in the range from 3 K to 300 K using neutron powder diffraction and synchrotron X-ray diffraction. Special emphasis is put on the influence of deuteration on formamidinium, its position in the unit cell and disordering in comparison to fully hydrogenated FAPbBr(3). The temperature-dependent measurements show that deuteration critically influences the crystal structures, i.e. results in partially-ordered temperature-dependent structural modifications in which two symmetry-independent molecule positions with additional dislocation of the molecular centre atom and molecular angle inclinations are present.
Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm.