DC1: Daniel Pliego Sosa
Daniel comes from Mexico, he is a PhD student at Technische Universiteit Delft (TUD) in Netherlands.
Daniel’s project focuses on studying the selective migration and interfacial accumulation of certain polymers in aqueous multiphase systems developed using microfluidics. The selective crosslinking of the phases can be exploited to engineer complex microstructures that afford simultaneous control over the compartmentalization of 2D and 3D domains. A better understanding of the compartmentalization and spatial organization strategies of polymeric solutions is needed to improve the rational design of complex compartmentalized systems. Two distinct approaches are commonly employed to achieve polymeric spatial arrangement in solutions: 3D-bulk compartmentalization and 2D-interfacial organization. However, in most cases, these two forms of organization remain disconnected. Overall, this project shows promising implications for advancing compartmentalization strategies, enabling closer integration between bulk phases and interfaces akin to biological systems.
DC 2: Misthi Singh
Misthi comes from India, she is a PhD student at Universitat Jaume I de Castellón (UJI) in Spain.
Misthi focuses on utilizing low molecular weight supramolecular gelators to prepare hydrogels. Specifically, the aim is to craft assembles driven primarily by either enthalpy or entropy, highlighting their privotal roles as design parameters in the creation of multicomponent materials. The exploration of mixed low molecular weight gelator systems holds significant promise for the development of advanced materials with tunable properties. By combining gelators with different temperature sensitivities, multicomponent networks that respond to temperature changes in predictable and controllable ways can be created. This approach not only enhances the functionality of the resulting materials but also provides a deeper understanding of the principles governing multicomponent self-assembly. As these systems continue to be investigated, it is anticipated to discover new applications and advancing the field of supreamolecular chemistry.
DC3: Angelita Krama
Angelita comes from Brazil, she is employed by Henkel (HEN) in Germany, and is enrolled as PhD student at University of Stuttgart.
Angelita’s project consists in formulating dual networks and study their kinetics. On the one hand, low Molecular Weight Gelators (LMWGs) are molecules with a molecular mass of less than 1000 g/mol that are capable of non-covalent self-assembly into a 3D network of fibers, i.e. into a gel network. To form a gel, the gelator must have a – usually very low – solubility in the continuous phase. On the other hand, surfactants can reduce the interfacial tension by adsorption at the interface in heterogeneous systems. At certain concentrations, surfactants can form micelles with different shapes such as spheres, lamellae, rods and worm-like. The worm-like micelles have the ability to form a viscoelastic network with typical rheological behavior. Combining LMWGs and surfactants may thus lead to the formation of a dual network consisting of gel fibers and worm-like micelles. Ideally the gelator is newly developed / synthesized by project partners IA better understanding of the interactions between LMGWs and surfactants will help in developing new formulations with a wide range of applications in field such as beauty care and home care products.
DC4: Anna Papaioannou
Anna comes from Greece, she is a PhD student at Université de Bordeaux (UB) in France.
Anna aims at the characterization and the understanding of multi-component supramolecular gels for applications in home and personal care and regenerative therapies. Their properties can be determined by super resolution microscopy (SRM). SRM are state-of-the-art fluorescence microscopy techniques which are better resolved than standard optical microscopy and can be performed on native solvated materials. SRM exploits single molecule detection (SMD), which allows to localize individual fluorophores in millions of video frames. A Single Molecule Localization Microscopy image is then reconstructed, point by point, like an impressionist painting. The organization and the size of the material’s nanostructures, as well as some dynamic properties, can be thereby assessed with unprecedented precision.
DC5: Florian Trummer
Florian comes from Austria, he is a PhD student at University of Stuttgart (UST) in Germany.
Florian focuses on elucidating the structure and dynamics of hierarchically organized soft matter materials on various length scales by applying scattering techniques like neutron, X-Ray and light scattering as well as complementary microscopy techniques. Knowledge about the nanostructure of materials is a key element to understanding their properties and to facilitate the design of novel materials for use in, e.g, pharmaceutics, food industry and washing applications. Therefore, there is a close collaboration with fellow DCs to characterize their samples’ structures and to shed light on possible structure-property relationships.
DC6: Philomène Le Bastart de Villeneuve
Philomène comes from France, she is a PhD student at University of Stuttgart (UST) in Germany.
Philomène’s work focused on Gelled Complex Fluids, soft materials in which the microstructure of a complex fluid is combined with the mechanical stability of a gel. It makes them interesting candidates for (trans-)dermal drug delivery or tissue healing applications. In this research project, the focus will be on non-irritating, bio-compatible gels. To formulate these gels, binary systems consisting of water and sugar-based surfactants will be gelled with a biodegradable low molecular weight gelators (LMWGs). The latter self-assemble reversibly into fibres, which in turn, form a 3D gel network. The present work seeks to (a) adjust the rheological behaviour via the gelator concentration or via an alignment of fibres and (b) investigate the solubilisation of model drugs in micelles (Figure, left) or in lyotropic liquid crystals (Figure, right).
DC7: Karolina Gwizdala
Karolina comes from Poland, she is employed by Centro de Investigación Príncipe Felipe (CIPF) in Spain, and is enrolled as PhD student at Universitat Jaume I de Castellón.
Karolina aims to develop rationally designed multifunctional materials (MultiMats) to treat spinal cord injury (SCI) by combining neural progenitor cell (NPC) therapy with self-organizing oligo-/poly-peptides of varying architectures. The resultant materials will be investigated regarding their formulation into fibers by modulating amino acid content/nature, counterion use, and active substances, which aims to create a substrate conductive to MultiMat generation that also provides support for neuronal regeneration. MultiMat bioassessment will be performed to facilitate the maintenance, growth, and differentiation of NPCs into neurons, an essential step for SCI regeneration. Selected MultiMats will undergo in vivo/ex vivo evaluations in combination with NPCs using rat SCI models.
DC8: Martina La Manna
Martina comes from Italy, she is a PhD student at Universitat Jaume I de Castellón (UJI) in Spain.
Martina aims to prepare multicomponent materials (Multimats) by combining short peptide-based LMWGs and biopolymers, mainly polypeptides, to be applied at the interface of biological systems. Both components will be functionalized by targeting moieties or drugs to obtain high-performance materials. Multimats will undergo characterization via NMR, electron microscopy, and rheology, and their biocompatibility and biodegradability will be assessed. They will be used to grow and differentiate neural precursor cells for spinal cord injury treatment. Additionally, they will be studied as skin permeation enhancers of model drugs in organotypic skin models developed from humans and scaffolds for the controlled growth of melanoma 3D spheroid/organoid models.
DC9: Silvia Spagnoli
Silvia comes from Italy, she is a PhD student at Université de Bordeaux (France).
The research project focuses on the development of fluorophores for the study and characterization of multi-component soft materials. The objective is to establish and apply new imaging methods through super-resolution fluorescence microscopy techniques adapted to multiscale organized materials compatible with living cells. Such methods can be adapted to non-emissive nanofibers, tagging them with luminescent probes. Moreover, the synthesis and development of photoactive components is expected: these, when irradiated under microscopy, can either activate a different optical behavior or induce spatially controlled self-assembly. The studied materials will then be evaluated with the other network partner laboratories for potential application in the fields of Regenerative Therapies (nerve cells) or Topical Therapies (skin treatment).
DC10: Niccoló Cosottini
Niccoló comes from Italy, he is a PhD student at University of York (UK).
Supramolecular gels are ideal next generation materials for drug formulation and delivery. It is possible to achieve controlled drug formulation and release by controlling interactions between active pharmaceutical ingredients and the self-assembled gel network. Furthermore, gels offer a variety of advantages in terms of drug administration depending on the macroscopic properties of the material, for example opening up approaches such as transdermal, intransal and subcutaneous delivery. With these goals in mind, my research project consists of the study of supramolecular hydrogels based on 1,3:2,4-dibenzylidenesorbitol derivatives. By adjusting their size (macro, micro, and nano) and composition, it is possible to create systems with tunable properties, making them valuable in various fields such as medicine, material science, electronics, cosmetics, and the food industry. This work will involve collaboration between a variety of groups within the network, and should open up new possibilities for drug delivery using simple, commercially-viable, supramolecular gels.
DC11: Raj Kumar
Raj comes from India, he is a PhD student at the University of Strathclyde (UoS) in Scotland.
Raj’s research leverages AI models like graph neural networks and multi-objective optimization to design peptide-based hydrogels tailored for biopolymer entrapment. It employs multiscale molecular dynamics simulations combining coarse-grained and atomistic models, and explainable AI techniques to predict hydrogel properties, drug release profiles, and biopolymer encapsulation. This AI-driven approach, integrated with experimental validation, advances personalized hydrogels for drug delivery, tissue engineering, and biosensing applications. Supported by high-performance computing and interdisciplinary partnerships, the project combines cutting-edge AI, simulations, and experiments to develop tailored hydrogel systems