Polymer brushes can absorb vapors from the surrounding atmosphere, which is relevant for many applications such as in sensing and separation technologies. In this article, we report on the absorption of binary mixtures of solvent vapors (A and B) with a thermodynamic mean-field model and with grand-canonical molecular dynamics simulations. Both methods show that the vapor with the strongest vapor–polymer interaction is favored and absorbs preferentially. In addition, the absorption of one vapor (A) influences the absorption of another (B). If the A–B interaction is stronger than the interaction between vapor B and the polymers, the presence of vapor A in the brush can aid the absorption of B: the vapors absorb collaboratively as friends. In contrast, if the A–polymer interaction is stronger than the B–polymer interaction and the brush has reached its maximum sorption capacity, the presence of A can reduce the absorption of B: the vapors absorb competitively as foes.

Vapors in the air around us can provide useful information about our environment, but we need sensitive vapor sensors to access this information, especially because those vapors are often present at very low concentrations. We report molecular dynamics simulations of a concept that can significantly increase the sensitivity of vapor sensors at low concentrations. By coating the sensor surfaces with end-anchored immiscible polymers, surface-bound polymer blends are formed that can concentrate vapors, reaching sorption enhancements of more than one order of magnitude, especially at low vapor concentrations.

Polymer brushes attract vapors that are good solvents for polymers. This is useful in sensing and other technologies that rely on concentrating vapors for optimal performance. It was recently shown that vapor sorption can be enhanced further by incorporating two incompatible types of polymers A and B in the brushes: additional vapor adsorbs at the high-energy polymer-polymer interface in these binary brushes. In this article, we present a model that describes this enhanced sorption in binary brushes of immiscible A-B polymers. To do so, we set up a free-energy model to predict the interfacial area between the different polymer phases in binary brushes. This description is combined with Gibbs adsorption isotherms to determine the adsorption at these interfaces. We validate our model with coarse-grained molecular dynamics simulations. Moreover, based on our results, we propose design parameters (A-B chain fraction, grafting density, vapor, and A-B interaction strength) for optimal vapor absorption in coatings composed of binary brushes.

Polymer brushes in gaseous environments absorb and adsorb vapors of favorable solvents, which makes them potentially relevant for sensing applications and separation technologies. Though significant amounts of vapor are sorbed...

Molecules can partition from a solution into a polymer coating, leading to a local enrichment. If one can control this enrichment via external stimuli, one can implement such coatings in novel separation technologies. Unfortunately, these coatings are often resource intensive as they require stimuli in the form changes of bulk solvent conditions such as acidity, temperature, or ionic strength. Electrically driven separation technology may provide an appealing alternative, as this will allow local, surface-bound stimuli instead of system-wide bulk stimuli to induce responsiveness. Therefore, we investigate via coarse grained molecular dynamics simulations the possibility of using coatings with charged moieties, specifically gradient polyelectrolyte brushes, to control the enrichment of the neutral target molecules near the surface with applied electric fields. We find that targets which interact more strongly with the brush show both more absorption and a larger modulation by electric fields. For the strongest interactions evaluated in this work, we obtained absorption changes of over 300 % between the collapsed and extended state of the coating.