The catalysis by metal nanoparticles is one of the fastest growing areas in nanoscience due to our society's exploding need for fuels, drugs, and environmental remediation. However, the optimal control of catalytic activity and selectivity remains one of the grand challenges in the 21st century. This project 'Nanoreactor' aimed to theoretically and numerically derive design rules for the optimization of nanoparticle catalysis by nanoreactors constituted of thermosensitive yolk-shell carrier systems. In the latter, the nanoparticle is stabilized in solution by an encapsulating, thermosensitive hydrogel shell. Responsive nanoreactors permit catalytic reaction to be switched and tuned, e.g. by the temperature or the pH. The novel hybrid character of these emerging 'nanoreactors' opens up unprecedented ways for the control of nanocatalysis due to new designable degrees of freedom. The complex mechanisms behind stimuli-responsive nanocatalysis were here addressed by a concerted, interdisciplinary modelling approach, based on multiscale computer simulations of solvated polymers and the statistical and continuum mechanics of soft matter structures and dynamics. We aimed to integrate the molecular solvation effects and our growing knowledge of hydrogel mechanics and thermodynamics into advanced reaction-diffusion equations for a quantitative rate prediction. One key objective was to derive predictive theories for reactant transport through the polymer shell, that is, the hydrogel permeability and include those in useful rate equations to describe the experiments. The expected results and design principles shall help experimentalists to synthesize tailor-made, superior nanocatalysts for the increasing demand of our society for energy materials, fine chemicals and enviromental remediation.
