A versatile direct optical characterization method for morphology changes and swelling kinetics of smart hydrogels

G. Mu, J. Koerner
Leibniz University Hannover,

Keywords: smart hydrogel, dynamic properties, optical characterization, swelling kinetics


Stimulus-responsive (i.e. smart) hydrogels offer a tremendous potential for applications in drug delivery, (biomedical) sensing or as tunable shape-changing materials. Their properties and response to a wide variety of physical and chemical stimuli, such as temperature, pH, magnetic fields or specific molecules can be tailored within a large range [1]. In order to develop new material compositions for specific use cases, samples need to be characterized with regard to the relevant properties. Especially for sensing applications, where the stimulus-dependent swelling change of the hydrogel is harnessed to quantify the stimulus, the swelling kinetics of the respective material needs to be studied to determine its suitability for the intended purpose. This entails time constants for (de)swelling, achievable volume change, anisotropy, hysteresis effects and time-dependent morphology. While many methods are available to determine the static material properties, such as inner structure, composition and steady-state volume, the characterization of the aforementioned dynamic properties remains a challenge and only very few methods are currently available [2]. We have developed a measurement concept that addresses this void through a simple yet effective and versatile approach: we employ a 3D-printed measurement chamber equipped with bottom and side observation windows. Side and bottom view images of a sample inside the chamber are obtained by microscope cameras. Automated image capture and analysis are carried out in user-defined regimes by a self-written Python program. Image analysis entails sophisticated algorithms to determine the sample area from which in turn sample volume can be obtained by combining the data from bottom and side view. Through post processing, time-dependent swelling curves and fully three-dimensional reconstructions showing the time-resolved morphological changes during (de)swelling can be derived as well as further secondary data (e.g. time constants, swelling degrees). We have extensively tested the setup with liquid- and temperature-based stimuli, for regular and irregular shaped samples down to micrometer dimensions and varying shades of color/transparency [2]. The latter is specifically challenging, as it required the development of sophisticated algorithms for automated area/edge detection [2]. Our approach is very versatile as the measurement setup is fully customizable (3D-printed chamber, commercially available parts) and can therefore be employed for a wide variety of stimuli and samples and neither sample sizes nor shapes are restricted. In contrast to many other characterization approaches, ours does not require any pretreatment or modification of the sample. The generated amount of data is kept low as only individual images are captured by user-defined parameters. Due to the subsequent fitting processes after image analysis, only a very small number of data points are required to still obtain conclusive secondary data like time constants and swelling degrees. The presented optical characterization method offers a powerful and affordable characterization setup for dynamic properties of smart hydrogels and polymers, which can be set up in any laboratory context. Source codes as well as design files for a fluidic chamber are freely available [2]. [1] S. Bashir et al., MDPI Polymers 12(11):2702, 2020 [2] K. Rückmann et al., Elsevier Polymer 246:124713, 2022