Abstract

Many-body polarization and hydration forces can strongly affect the equilibrium structure and energetics of mixed phases. Accurately reproducing both forces presents a challenge to force field models because it requires balancing hydrogen bonding at short range with many-body orientational order and dispersive attraction at long range. This work reports the first comparison of experimental measurements of the pressure-area isotherm for hydroxypropylcellulose (HPC) against molecular dynamics results with four different force field models-united-atom, all-atom (OPLS and CHARMM), and Drude oscillator models. All force fields exhibit the experimentally determined, exponentially shaped repulsive force at short range. Above a critical temperature of about 40 °C and a lattice spacing of around 14 Å, HPC experiments show a reversible, heat-induced polymer aggregation into an ordered phase driven by loss of water. The nonpolarizable force fields do not display the critical point and instead show biphasic behavior at all temperatures tested. This indicates net attractive forces at intermediate lattice spacings. In contrast, the Drude polarizable force field shows positive osmotic pressure and a single, homogeneous phase over all temperatures and spacings tested. Analysis of structural data from our simulations provides several clues to help interpret these findings. Although all force fields show similar water-water hydrogen bond numbers in the mixed phase, the polarizable model predicts that water-HPC hydrogen bonds are much more favorable than HPC-HPC hydrogen bonds when polymers are dispersed. At high density, water is driven out and replaced by HPC-HPC hydrogen bonds. The polarizable force field shows that both effects have a stronger dependence on polymer density than any of the nonpolarizable models. Our observations support the conclusion that hydration forces are coupled to the polymer coordination number by local, structural waters and that long-range dispersive attraction is overestimated by pairwise additive models.

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