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 predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular dynamics simulations to predict the wettability of polymer surfaces and test it against the experimental contact angle of several polar and nonpolar liquids, namely water, formamide, toluene, and hexane. The specific case study addressed here focuses on a poly(lactic-co-glycolic acid) (PLGA) flat surface, but the proposed experimental-modeling protocol may have broader fields of application. The structural properties of PLGA slabs have been modeled on the surface roughness determined with microscopy measurements, while the computed surface tensions and contact angles were validated against standardized characterization tests, reaching a discrepancy of less than 3% in the case of water. Overall, this work represents the initial step toward an integrated multiscale framework for predicting the wettability of more complex soft interfaces, which will eventually take into account the effect of surface topology at higher scales and synergically be employed with experimental characterization techniques. Impact statement: Controlling the wettability of surfaces has important implications for energy (e.g., self-cleaning solar panels), mechanical (e.g., enhanced heat transfer), chemical (e.g., fluids separation), and biomedical (e.g., implants biocompatibility) industries. Wetting properties arise from a combination of chemical and physical features of surfaces, which are inherently intertwined and multiscale. Therefore, tailoring wettability to target functionalities is a time-intensive process, especially if relying on a trial-and-error approach only. This becomes even more challenging with soft materials, since their surface configuration depends on the solid-liquid interactions at the molecular level and could not be defined a priori. The improved accuracy of atomistic models allows detailing how the effective properties of materials arise from their nanoscale features. In this article, we propose and validate a new molecular dynamics protocol for assessing the wettability of soft interfaces with polar and nonpolar liquids. The prediction capabilities of simulations are augmented by a close comparison with microscopy and contact angle experiments. Since smooth copolymer surfaces are considered, here the effort mainly focuses on the effect of chemical features on wettability. In perspective, the proposed atomistic in silico approach could be coupled with computational models at higher scales to include the effect of surface microstructures, eventually easing the development of multi-scale surfaces with tunable wettability. Graphical abstract: [Figure not available: see fulltext.] © 2022, The Author(s).

Bellussi, F.M., Roscioni, O.M., Rossi, E., Cardellini, A., Provenzano, M., Persichetti, L., et al. (2022). Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models. MRS BULLETIN, 48 [10.1557/s43577-022-00380-9].

Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models

Rossi, Edoardo;Persichetti, Luca;Sebastiani, Marco;Fasano, Matteo
2022

Abstract

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 predicting wettability with molecular precision is still lacking. In this article, we propose a workflow based on molecular dynamics simulations to predict the wettability of polymer surfaces and test it against the experimental contact angle of several polar and nonpolar liquids, namely water, formamide, toluene, and hexane. The specific case study addressed here focuses on a poly(lactic-co-glycolic acid) (PLGA) flat surface, but the proposed experimental-modeling protocol may have broader fields of application. The structural properties of PLGA slabs have been modeled on the surface roughness determined with microscopy measurements, while the computed surface tensions and contact angles were validated against standardized characterization tests, reaching a discrepancy of less than 3% in the case of water. Overall, this work represents the initial step toward an integrated multiscale framework for predicting the wettability of more complex soft interfaces, which will eventually take into account the effect of surface topology at higher scales and synergically be employed with experimental characterization techniques. Impact statement: Controlling the wettability of surfaces has important implications for energy (e.g., self-cleaning solar panels), mechanical (e.g., enhanced heat transfer), chemical (e.g., fluids separation), and biomedical (e.g., implants biocompatibility) industries. Wetting properties arise from a combination of chemical and physical features of surfaces, which are inherently intertwined and multiscale. Therefore, tailoring wettability to target functionalities is a time-intensive process, especially if relying on a trial-and-error approach only. This becomes even more challenging with soft materials, since their surface configuration depends on the solid-liquid interactions at the molecular level and could not be defined a priori. The improved accuracy of atomistic models allows detailing how the effective properties of materials arise from their nanoscale features. In this article, we propose and validate a new molecular dynamics protocol for assessing the wettability of soft interfaces with polar and nonpolar liquids. The prediction capabilities of simulations are augmented by a close comparison with microscopy and contact angle experiments. Since smooth copolymer surfaces are considered, here the effort mainly focuses on the effect of chemical features on wettability. In perspective, the proposed atomistic in silico approach could be coupled with computational models at higher scales to include the effect of surface microstructures, eventually easing the development of multi-scale surfaces with tunable wettability. Graphical abstract: [Figure not available: see fulltext.] © 2022, The Author(s).
Bellussi, F.M., Roscioni, O.M., Rossi, E., Cardellini, A., Provenzano, M., Persichetti, L., et al. (2022). Wettability of soft PLGA surfaces predicted by experimentally augmented atomistic models. MRS BULLETIN, 48 [10.1557/s43577-022-00380-9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/418009
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