This paper presents a thermodynamically consistent model for the phase equilibrium of water/ caprolactam/nylon-6 mixtures, based on the POLYNRTL (polymer nonrandom two-liquid) activity-coefficient model. Our model predicts phase equilibrium for any binary or ternary mixture containing water, -caprolactam, and nylon-6 at industrially relevant temperatures and pressures with an average error of 1%. This paper also demonstrates its application to simulate a melt train and a bubble-gas kettle train for industrial production of nylon-6. Prior literature makes simplifying assumptions about liquid-phase (molten polymer) activities of water and -caprolactam; these assumptions are shown to be unrealistic.

We present a new mass-transfer model for simulating industrial nylon-6 polymerization trains. In this model, both diffusion and boiling (bubble nucleation) contribute to mass transfer. With this model, we are able to simulate widely differing production technologies using identical mass-transfer parameters, along with identical models for fundamentals such as phase equilibrium, physical properties, and polymerization kinetics. To illustrate, we simulate the direct-melt process and the bubble-gas kettle process. The direct-melt process builds up the polymer molecular weight and removes nearly all residual caprolactam monomer by employing, under vacuum, a wiped-wall evaporator and a rotating-disk finisher. The bubble-gas kettle process, on the other hand, injects inert gas bubbles through the melt at nearly atmospheric pressure to build up the polymer molecular weight but does not significantly reduce the caprolactam level because the diffusion coefficient is so low. We validate our process models using commercial train performance data at different production rates, including the first known validation of a dynamic rate-change simulation for industrial polycondensation trains. Model predictions quantitatively agree with product quality data such as formic acid viscosity (FAV), polymer end-group concentration, and water extractables. The prediction errors for the direct-melt process are 2.81%, −3.13%, and −3.06% for FAV, water extractables, and amine end groups, respectively. For the bubble-gas kettle process, the prediction errors are −17.2%, −17.0%, and −7.49% for extrusion FAV, washed-and-dried FAV, and water extractables, respectively. These errors are much lower than the ca. −50% errors obtained by existing advanced models for devolatilization.