Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models

Abstract A challenging topic in surface engineering is predicting the wetting properties of soft interfaces with different liquids. However, a robust computational protocol suitable for wettability molecular precision still lacking. In this article, we propose workflow based on dynamics simulations to predict polymer surfaces and test it against experimental contact angle several polar nonpolar liquids, namely water, formamide, toluene, hexane. The specific case study addressed here focuses poly(lactic- co -glycolic acid) (PLGA) flat surface, but proposed experimental-modeling may have broader fields application. structural PLGA slabs been modeled roughness determined microscopy measurements, while computed tensions angles were validated standardized characterization tests, reaching discrepancy less than 3% water. Overall, work represents initial step toward an integrated multiscale framework more complex interfaces, which will eventually take into account effect topology at higher scales synergically be employed techniques. Impact statement Controlling has important implications energy (e.g., self-cleaning solar panels), mechanical enhanced heat transfer), chemical fluids separation), biomedical implants biocompatibility) industries. Wetting arise from combination physical features surfaces, are inherently intertwined multiscale. Therefore, tailoring target functionalities time-intensive process, especially if relying trial-and-error approach only. This becomes even materials, since their configuration depends solid-liquid interactions level could not defined priori . improved accuracy atomistic models allows detailing how effective materials nanoscale features. validate new assessing prediction capabilities augmented by close comparison experiments. Since smooth copolymer considered, effort mainly wettability. perspective, silico coupled include microstructures, easing development multi-scale tunable Graphical abstract