(95c) Prediction of Nanofiltration Separation Performance for Multicomponent Aqueous Organic Acid Solutions

Nanofiltration membrane separation provides an energy-efficient and economically viable solution for the selective removal of organic acids from biomass fermentation broths. To advance process development in this area, rigorous and predictive thermodynamic models are essential for extrapolating beyond the costly and labor-intensive separation experiments traditionally required. This work introduces a robust thermodynamic modeling methodology that predicts solute rejection in multicomponent aqueous organic acid systems based on single-component rejection and permeate flux data.

Building on the classical solution-diffusion model, this advanced framework incorporates detailed aqueous-phase organic acid solution chemistry and non-ideal solution behavior. It accurately describes single-component systems and delivers precise predictions for binary and ternary separation performance across a range of conditions, including feed pH (~3–10), acid concentrations (0.2–0.6 mmol/L), applied pressures (3.44–27.57 bar), and a temperature of 298.15 K. With an average absolute relative deviation below 10%, the model provides critical insights into the process complexities and efficiencies possible in organic acid nanofiltration separations. This approach provides strong theoretical support for the design and optimization of economically viable, energy-efficient nanofiltration processes for organic acid recovery, with promising applications in industrial-scale biomass fermentation.