Clean water availability is one of the sustainable development goals set by UN. Towards this goal, the treatment of aqueous solutions containing either metal cations or single/binary mixture of textile dyes, using Metal Organic Frameworks (MOFs) as adsorbents is carried out. Equilibrium, kinetics, and thermodynamic aspects of the adsorption are reported.
The original TMU-5 MOF used in the adsorption of cadmium cations exhibited water instability especially under acidic conditions. To ensure water stability of this MOF, the silica coated TMU-5 (SiO2@TMU-5) was synthesized. The coated MOF could effectively treat cadmium ion concentrations in the feed solution (2 – 20 mg/L) and operate close to natural pH condition of 6. This water-resistant MOF registered a high adsorption capacity of about 630 mg/g for cadmium cation and could be used through three adsorption-regeneration cycles. The physicochemical properties of the adsorbent were characterized. The coating of TMU-5 with silica layer led to increase in water stability but came at the cost of reduced adsorption capacity.
As the effluents may contain a wide variety of dyes, it becomes necessary to address their simultaneous or sequential removal at different process conditions using MOFs. While there were several studies for systematically investigating the adsorption of a single solute, such analyses were rather limited for mixture of solutes under different process conditions. Adsorption involving a mixture of two dyes with a single adsorbent as well as mixture of two dyes with a mixture of two adsorbents were analysed using the I-optimal experimental design approach. The water stable MIL-101(Cr) and MIL-101(Cr)-SO3H were chosen as adsorbents for treating Acid Orange 10 (anionic), Basic Yellow 2 (cationic) and Rhodamine B (zwitterionic) dyes. The two MOFs were labelled as MIL and MILS respectively. While MIL MOF could adsorb the anionic dye, the MILS MOF showed preference for cationic and zwitterionic dyes.
The adsorption of BY2 dye on MILS was not affected significantly by pH. Thermodynamic studies revealed the exothermic nature of the adsorption of BY2 dyes on MILS. The adsorption of AO10 on MIL was pH dependent. The adsorption mechanism was attributed to electrostatic interaction of AO10 with MIL. For BY2 and RhB adsorption, π-π interactions as well as electrostatic interactions with MILS were prominent. The characterization studies revealed that SO3H functionalization reduced the BET surface area but enhanced the MOF’s functionality.
Binary adsorption studies of the cationic BY2 and zwitterionic RhB on MILS were carried out. The steepest ascent to the global optimum conditions from arbitrary staring points were tracked in the process variable space for the 1:3, 1:1, and 3:1 binary dye feed ratios. It was found that more benign conditions such as lower temperature and near neutral pH conditions may be employed in the adsorption process with a small loss in performance. The elliptic multi-objective optimization algorithm was utilized to obtain a compromise solution when simultaneously optimizing total adsorption capacity and total percentage removal.
The efficacy of simultaneously treating a binary mixture of zwitterionic and anionic dyes viz. Rhodamine B and Acid Orange 10 dyes with a mixture of MIL and MILS adsorbents was studied. The optimal adsorption capacities were predicted to be 27.6, 20.4, 28.3 mg/g respectively for 1:3, 1:1, and 3:1 mass ratios of the dye mixtures. This was followed by the strategy of treating the same mixture of dyes using a sequential adsorption technique. The sequential adsorption method enhanced the adsorption capacity for the dyes when compared with the treatment involving a mixture of the two adsorbents. The total maximum adsorption capacity for stage I was predicted to be 30.3 mg/g while for stage II it was 62.8 mg/g.
Water stable MOF based adsorbents may be used for removal of metal cations and mixtures of different dyes. The optimum conditions to maximize percentage removals and adsorption capacities for the different classes of dyes have to be established from process modelling. Even sub-optimal conditions with benign operating conditions that may not compromise the objectives significantly may be identified using the improved ridge analysis method developed in this study.