Authors:
Prof. Dr. Daisuke Minakata | Michigan Technological University | United States
Ryan Kibler | Michigan Technological University | United States
Muxue Zhang | Michigan Technological University | United States
Lauren Breitner | Trussell Technologies. Inc. | United States
Kerry Howe | University of New Mexico | United States
The presence of trace chemicals called chemicals of emerging concern (CECs) in effluents of wastewater present challenges to the practice of potable water reuse. Reverse Osmosis (RO) is an attractive and promising membrane-based treatment process that can be applied for the removal of CECs in wastewater reclamation processes. While RO rejects a wide variety of CECs with greater than 99% rejection efficiency, neutral compounds with a molecular weight less than 200 g/mol have poor rejection efficiencies. Given that hundreds of thousands of chemicals are in commercial use and production, experimental investigations of the rejection efficiencies of individual CECs are not practical. Consequently, a comprehensive model is needed to predict the rejection efficiencies of a wide variety of CECs.
Although several past experimental and theoretical studies attempted to understand the rejection mechanisms of organics through RO, complex heterogeneous RO membrane properties and the interacting thermodynamic and kinetic contributions to the rejection mechanism have limited the ability to quantitative predict those rejection efficiencies. Quantitative structure activity relationships (QSARs) are attractive approaches to the systematic prediction of the rejection efficiencies of organic compounds that contain diverse structures and a variety of physicochemical properties. Although QSARs have been developed for nano filtration membranes, those QSARs lack a mechanistic basis for rejection.
We developed a group contribution method (GCM) by fragmenting the structure of a given organic into groups. The parameters that represent the free energies of interaction between each fragmented part (both base structure and functional group) and RO membrane were determined by minimizing the objective function that calculates the normalized difference between the experimental and calculated mass transfer coefficients using genetic algorithms. The error goal (EG) was set to calculate the mass transfer coefficients in order to predict the corresponding rejection efficiencies within ±5% from experimental values.
Results
Among the 70 mass transfer coefficients determined by our bench-top experiments through 6 RO membranes, 54 compounds including 26 halo and oxygenated alkanes, 8 alkenes and 20 alkyl and halobenzenes were selected based on the applicable range of rejection efficiencies. Overall, 92% of best calibrated mass transfer coefficient values were within EG for TMG(D) membrane. Similarly, 85% of mass transfer coefficient values (n=53) for BW30XFRLE, 76% (n=54) for ESPA2-LD, 71% (n=48) for AG-LF, 100% (n=46) for SW30XHR, and 98% (n=46) for TM800M were obtained.
The free energy of interaction for each segmented group of a given compound indicates the structural contribution to the overall mass transfer coefficient. For alkanes, the free energies of interaction were determined based on minimum carbon-based structures with functional groups. For alkenes and aromatic compounds, the free energies of interaction were determined by a base carbon-carbon double bond or a benzene ring structure with the functional group(s). The different treatment of a base structure by the number and positions of functional groups successfully differentiated the effects of isomers. Finally, the free energy of interaction quantitatively represents the hydrophilic/hydrophobic effects of each functional group to the overall free energy of interaction.