| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Müller, Martin
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (38/38 displayed)
- 2024Overview: Machine Learning for Segmentation and Classification of Complex Steel Microstructures
- 2024Efficient Phase Segmentation of Light-Optical Microscopy Images of Highly Complex Microstructures Using a Correlative Approach in Combination with Deep Learning Techniques
- 2023Reproducible Quantification of the Microstructure of Complex Quenched and Quenched and Tempered Steels Using Modern Methods of Machine Learning
- 2023Influence of the Sequence Motive Repeating Number on Protein Folding in Spider Silk Protein Filmscitations
- 2023Klassifizierung komplexer Gefüge mit maschinellem Lernen am Beispiel bainitischer Stähle
- 2022Addressing materials’ microstructure diversity using transfer learningcitations
- 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopycitations
- 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy
- 2022Addressing materials' microstructure diversity using transfer learningcitations
- 2021High Hydrogen Mobility in an Amide–Borohydride Compound Studied by Quasielastic Neutron Scatteringcitations
- 2021A Complementary and Revised View on the N-Acylation of Chitosan with Hexanoyl Chloride
- 2021Effectiveness and Utility of Virtual Reality Simulation as an Educational Tool for Safe Performance of COVID-19 Diagnostics: Prospective, Randomized Pilot Trialcitations
- 2021Microstructural Classification of Bainitic Subclasses in Low-Carbon Multi-Phase Steels Using Machine Learning Techniques
- 2021A deep learning approach for complex microstructure inferencecitations
- 2021A dangerously underrated entity? Non-specific complaints at emergency department presentation are associated with utilisation of less diagnostic resourcescitations
- 2021Deformation Behavior of Cross-Linked Supercrystalline Nanocompositescitations
- 2020Classification of Bainitic Structures Using Textural Parameters and Machine Learning Techniques
- 2020Towards Quantitative Interpretation of Fourier-Transform Photocurrent Spectroscopy on Thin-Film Solar Cellscitations
- 2020Catechol Containing Polyelectrolyte Complex Nanoparticles as Local Drug Delivery System for Bortezomib at Bone Substitute Materialscitations
- 2019Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticles
- 2019Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticlescitations
- 2019Iron oxide-based nanostructured ceramics with tailored magnetic and mechanical properties: Development of mechanically robust, bulk superparamagnetic materials
- 2019Iron oxide-based nanostructured ceramics with tailored magnetic and mechanical properties: development of mechanically robust, bulk superparamagnetic materialscitations
- 2019Modulating the Mechanical Properties of Supercrystalline Nanocomposite Materials via Solvent–Ligand Interactionscitations
- 2018Bioinspired thermoresponsive nanoscaled coatings: Tailor-made polymer brushes with bioconjugated arginine-glycine-aspartic acid-peptidescitations
- 2018Phase Transformations in the Brazing Joint during Transient Liquid Phase Bonding of a γ-TiAl Alloy Studied with In Situ High-Energy X-Ray Diffractioncitations
- 2017Local flow stresses in interpenetrating-phase composites based on nanoporous gold — In situ diffractioncitations
- 2016Local flow stresses in interpenetrating-phase composites based on nanoporous gold — in situ diffraction
- 2016In-situ Observation of Cross-Sectional Microstructural Changes and Stress Distributions in Fracturing TiN Thin Film during Nanoindentationcitations
- 2016Phase Transformation and Residual Stress in a Laser Beam Spot-Welded TiAl-Based Alloycitations
- 2016High-temperature stable Zirconia particles doped with Yttrium, Lanthanum, and Gadoliniumcitations
- 2016In Situ Synchrotron Radiation Diffraction of The Solidificationof Mg-Dy(-Zr) Alloys
- 2015Synthesis and thermal stability of zirconia and yttria-stabilized zirconia microspheres
- 2014Nanocomposite coatings with stimuli-responsive catalytic activitycitations
- 2010Studying the influence of chemical structure on the surface properties of polymer filmscitations
- 2009Charging and structure of zwitterionic supported bilayer lipid membranes studied by streaming current measurements, fluorescence microscopy, and attenuated total reflection Fourier transform infrared spectroscopycitations
- 2001Origin and effect of fiber attack for the processing of C/SiC
- 2001Improving damage tolerance of C/SiC
Places of action
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article
Bioinspired thermoresponsive nanoscaled coatings: Tailor-made polymer brushes with bioconjugated arginine-glycine-aspartic acid-peptides
Abstract
<jats:p>The development of bioengineered surface coatings with stimuli-responsive properties is beneficial for a number of biomedical applications. Environmentally responsive and switchable polymer brush systems have a great potential to create such smart biointerfaces. This study focuses on the bioconjugation of cell-instructive peptides, containing the arginine-glycine-aspartic acid tripeptide sequence (RGD motif), onto well-defined polymer brush films. Herein, the highly tailored end-grafted homo polymer brushes are either composed of the polyelectrolyte poly(acrylic) acid (PAA), providing the reactive carboxyl functionalities, or of the temperature-responsive poly(N-isopropylacrylamide) (PNIPAAm). Of particular interest is the preparation of grafted-to binary brushes using both polymers and their subsequent conversion to RGD-biofunctionalized PNIPAAm-PAA binary brushes by a carbodiimide conjugation method. The bioconjugation process of two linear RGD-peptides Gly-Arg-Gly-Asp-Ser and Gly-Arg-Gly-Asp-Ser-Pro-Lys and one cyclic RGD-peptide cyclo(Arg-Gly-Asp-D-Tyr-Lys) is comparatively investigated by complementary analysis methods. Both techniques, in situ attenuated total reflectance Fourier transform infrared spectroscopy measurements and the in situ spectroscopic ellipsometric analysis, describe changes of the brush surface properties due to biofunctionalization. Besides, the bound RGD-peptide amount is quantitatively evaluated by ellipsometry in comparison to high performance liquid chromatography analysis data. Additionally, molecular dynamic simulations of the RGD-peptides themselves allow a better understanding of the bioconjugation process depending on the peptide properties. The significant influence on the bioconjugation result can be derived, on the one hand, of the polymer brush composition, especially from the PNIPAAm content, and, on the other hand, of the peptide dimension and its reactivity.</jats:p>