Microgel structure-driven linear and non-linear mechanical properties of self-assembled microgel films

Thermo-Sensitive Microgel/Poly(ether sulfone) Composited Ultrafiltration Membranes

Thermo-sensitive microgels known as PMO-MGs were synthesized via surfactant free emulsion polymerization, with poly(ethylene glycol) methacrylate (OEGMA₄₇₅) and 2-(2-methoxyethoxy) ethyl methacrylate (MEO₂MA) used as the monomers and N, N-methylene-bis-acrylamide used as the crosslinker. PMO-MGs are spherical in shape and have an average diameter of 323 ± 12 nm, as determined via transmission electron microscopy. PMO-MGs/poly (ether sulfone) (PES) composited ultrafiltration membranes were then successfully prepared via the non-solvent-induced phase separation (NIPS) method using a PMO-MG and PES mixed solution as the casting solution. The obtained membranes were systematically characterized via combined X-ray photoelectron spectroscopy, field-emission scanning electron microscopy, Fourier transform infrared spectroscopy and contact angle goniometer techniques. It was found that the presence of PMO-MGs significantly improved the surface hydrophilicity and antifouling performance of the obtained membranes and the PMO-MGs mainly located on the channel surface of the membranes. At 20 °C, the pure water flux increased from 217.6 L·m^-2·h^-1 for pure PES membrane (M00) to 369.7 L·m^-2·h^-1 for PMO-MGs/PES composited membrane (M20) fabricated using the casting solution with 20-weight by percentage microgels. The incorporation of PMO-MGs also gave the composited membranes a thermo-sensitive character. When the temperature increased from 20 to 45 °C, the pure water flux of M20 membrane was enhanced from 369.7 to 618.7 L·m^-2·h^-1.

Soft Self-Assembled Mechanoelectrical Transducer Films from Conductive Microgel Waterborne Dispersions

The present study aims in the developing of new soft transducers based on sophisticated stimuli-responsive microgels that exhibit spontaneous self-assembly forming cohesive films with conductive and mechanoelectrical properties. For that, oligo(ethylene glycol)-based stimuli-responsive microgels have been synthesized using bio-inspired catechol cross-linkers by one-step batch precipitation polymerization in aqueous media. Then, 3,4-ethylene dioxyyhiophene (EDOT) has been directly polymerized onto stimuli-responsive microgels using catechol groups as the unique dopant. PEDOT location is dependent on the cross-linking density of microgel particles and EDOT amount used. Moreover, the spontaneous cohesive film formation ability of the waterborne dispersion after evaporation at soft application temperature is demonstrated. The films obtained present conductivity and enhanced mechanoelectrical properties triggered by simple finger compression. Both properties are function of the cross-linking density of the microgel seed particles and PEDOT amount incorporated. In addition, to obtain maximum electrical potential generated and the possibility to amplify it, several films in series were demonstrated to be efficient. The present material can be a potential candidate for biomedical, cosmetic, and bioelectronic applications.

Convolutional neural network-based colloidal self-assembly state classification

Colloidal self-assembly is a viable solution to making advanced metamaterials. While the physicochemical properties of the particles affect the properties of the assembled structures, particle configuration is also a critical determinant factor. Colloidal self-assembly state classification is typically achieved with order parameters, which are aggregate variables normally defined with nontrivial exploration and validation. Here, we present an image-based framework to classify the state of a 2-D colloidal self-assembly system. The framework leverages deep learning algorithms with unsupervised learning for state classification and a supervised learning-based convolutional neural network for state prediction. The neural network models are developed using data from an experimentally validated Brownian dynamics simulation. Our results demonstrate that the proposed approach gives a satisfying performance, comparable and even outperforming the commonly used order parameters in distinguishing void defective states from ordered states. Given the data-based nature of the approach, we anticipate its general applicability and potential automatability to different and complex systems where image or particle coordination acquisition is feasible.

Spontaneously Self-Assembled Microgel Film as Co-Delivery System for Skincare Applications

Nowadays, the design of innovative delivery systems is driving new product developments in the field of skincare. In this regard, serving as potential candidates for on-demand drug delivery and fulfilling advanced mechanical and optical properties together with surface protection, spontaneously self-assembled microgel films can be proposed as ideal smart skincare systems. Currently, the high encapsulation of more than one drug simultaneously in a film is a very challenging task. Herein, different ratios (1:1, 3:1, 9:1) of different mixtures of hydrophilic/hydrophobic UVA/UVB-absorbers working together in synergy and used for skin protection were encapsulated efficiently into spontaneously self-assembled microgel films. In addition, in vitro release profiles show a controlled release of the different active molecules regulated by the pH and temperature of the medium. The analysis of the release mechanisms by the Peppas-Sahlin model indicated a superposition of diffusion-controlled and swelling-controlled releases. Finally, the distribution of active molecule mixtures into the film was studied by confocal Raman microscopy imaging corroborating the release profiles obtained.