Claas Willem Visser

CO2 sorbents play a central role in many carbon capture technologies. Visual monitoring of the sorbent behavior during CO2 capture could provide direct feedback and enable the optimization of both the sorbent and the reactor, which remains largely unexplored. In this work, we develop a self-reporting CO2 sorbent, prove its quantitative indication of CO2 absorption and desorption, and apply this method to evaluate different methods of sorbent regeneration. A pH indicator, thymol blue (TB), was embedded into polyethyleneimine (PEI) hydrogel particles, revealing a clear color transition from blue to green, yellow, and orange during CO2 absorption. This optical response was quantified by extracting Hue, a color coordinate in the Hue, Saturation, Value (HSV) space, from the particle images. Time-resolved analysis of the CO2 absorption revealed that Hue closely follows the measured CO2 uptake. A previously developed diffusion-reaction model was employed to investigate the relationship between the optical response and the internal chemistry of the particles. The measured Hue evolution more closely follows the modeled protonation response averaged over a substantial fraction of the particle volume than that of the shallow near-surface regions, supporting its potential use as an optical indicator for CO2 uptake. The robustness of the optical response was further confirmed by evaluating particles with different water contents, and excellent reversibility of the optical response was demonstrated during steam regeneration. As a final step, microwave regeneration was optically evaluated via this method, and shown to be much faster but less complete than steam regeneration. These results demonstrate that PEI/TB hydrogel particles can provide a timely, direct, and convenient optical signal during CO2 absorption and regeneration, enabling pathways for optimization at particle and potentially reactor scales.

Foam-based pressure sensors are attractive for human motion tracking and health monitoring, as they integrate flexibility, compressibility, and sensitivity. However, their stiffness, geometry, and cellular architecture can hardly be independently controlled. Moreover, degradation upon cyclic use and multistep fabrication methods hamper their broad application. Here, we demonstrate single-step additive manufacturing of elastic polymer foams with programmable shapes and tunable stiffness. Using direct bubble writing (DBW), conductive foams are printed cell by cell. Silver nanoparticles are formed and embedded within the polymer matrix during the printing process, thereby eliminating the need for extensive postprocessing and degradation caused by the delamination of conductive layers. The conductivity (resistance) and sensitivity of the foams are measured as a function of the silver loading, revealing that the pressure sensitivity is weakly dependent on the silver content. The density of printed foams is controlled by adjusting the gas pressure applied during the printing process, resulting in elastic modulus from 11.4 ± 1.2 kPa to 22.0 ± 2.0 kPa. The sensitivity of the sensors ranges from 0.16 to 0.0014 kPa^-1 for pressures 1 kPa < P < 125 kPa, which is comparable to state-of-the-art foam-based pressure sensors. The sensors exhibit low hysteresis (below 10%) and stable cyclic performance up to 60% strain. We showcase their application potential in real-time detection of human motion (finger, hand, and foot). Altogether, direct bubble writing enables one-step, high-throughput manufacturing of pressure sensors with custom shape, stiffness, and conductivity.

Power minimisation of fluid transport in branched fluidic networks has become of paramount importance for microfluidics, additive manufacturing and hierarchical functional materials. For fully developed laminar flow of Newtonian fluids, Murray's theory provides a solution for the channel and network dimensions that minimise power consumption. However, design and optimisation of networks that transport complex fluids is still challenging. Here, we generalise Murray's theory towards fluid rheologies, including non-Newtonian (power-law) and yield-stress fluids (Bingham, Herschel–Bulkley, Casson). A straightforward graphical approach is presented that provides the optimal radii in a branching network, and the angles between these branches. The wall shear stress is found to be uniform over the entire network, and the velocity profile is self-similar. Furthermore, the effect of non-optimal channel radii on the power consumption of the network is investigated. Finally, examples illustrate how this approach applies to a wide variety of systems.

Microcapsules with a liquid core and a solid shell composed of hydrophobic nanoparticles are broadly applied in food, pharmaceutics, and biotechnologies. For example, Pickering emulsions, colloidosomes, or antibubbles (droplets surrounded by air layers in water) enable controlled release of active agents, biocompatibility, and contact‐less liquid transportation. However, producing controlled nanoparticle‐ or polymer‐laden hydrophobic shells at scale is highly challenging, since bulk methods are polydisperse and microfluidic chips are prone to clogging and slow. Here, clog‐free coating of an aqueous jet with silica nanoparticle suspensions with concentrations up to 10% (w/v), as well as high concentrations of polymers (30% (w/v) poly(lactic acid) (PLA)), is demonstrated, enabling continuous generation of microcapsules at flow rates up to 4 mL min⁻¹. Pickering emulsions are converted into capsules, providing hydrophobic shells consisting of nanoparticles for controlled release. As a highlight, the scalable fabrication of air‐coated capsules (antibubbles) in the sub‐millimeter range is demonstrated. The shell contains an air film that protects the liquid core for days yet enables ultrasound‐induced release within 3 min. By enabling rapid fabrication of controlled Pickering emulsions, colloidosomes, antibubbles, and biodegradable capsules, jetting through a liquid layer (JetALL) provides a versatile platform for advanced applications in food, pharmacy, and life science.

We present a new approach for the microrheological characterization of soft suspended bodies. We obtain results comparable to AFM based dynamic nanoindentation. We discuss viscoelastic and poroelastic contributions to material behavior.

Direct Bubble Writing is a recent technique to print shape-stable 3-dimensional foams from streams of liquid bubbles. These bubbles are ejected from a core-shell nozzle, deposited on the build platform placed at a distance of approximately 10 cm below the nozzle, and photo-polymerized in situ. The bubbles are ejected diagonally, with a vertical velocity component equal to the ejection velocity and a horizontal velocity component equal to the motion of the printhead. Owing to the horizontal velocity component, a discrepancy exists between the nozzle trajectory and the location of the printed strand. This discrepancy can be substantial, as for high printhead velocities (500 mm/s) an offset of 8 mm (in radius) was measured. Here, we model and measure the deviation in bubble deposition location as a function of printhead velocity. The model is experimentally validated by the printing of foam patterns including a straight line, a circle, and sharp corners. The deposition offset is compensated by tuning the print path, enabling the printing of a circular path to the design specifications and printing of sharp corners with improved accuracy. These results are an essential step towards the Direct Bubble Writing of 3-dimensional polymer foam parts with high dimensional accuracy.