The adsorptive removal of dyes from industrial wastewater using commercially available adsorbents is not significantly efficient. Metal–organic frameworks (MOFs) offer outstanding properties which can boost the separation performance over current commercial adsorbents and hence, these materials represent a milestone in improving treatment methods for dye removal from water. Accordingly, in this paper, the recent studies in the modification of MOF structures in dye removal from the aquatic environment have been discussed. This study aims to elaborate on the synthetic strategies applied to improve the adsorption efficiency and to discuss the major adsorption mechanisms as well as the most influential parameters in the adsorptive removal of dyes using MOFs. More particularly, the advanced separation performance of MOF-based adsorbents will be comprehensively explained. The introduction of various functional groups and nanomaterials, such as amine functional groups, magnetic nanoparticles, and carbon-based materials such as graphene oxide and CNT, onto the MOFs can alter the removal efficiency of MOF-based adsorbents through enhancing the water stability, dispersion in water, interactions between the MOF structure and the contaminant, and the adsorption capacity. Finally, we summarize the challenges experienced by MOF-based materials for dye removal from water and propose future research outlooks to be considered.

We studied the performance of fine-tuning open-source LLMs for a range of different chemical questions. We benchmark their performances against “traditional” machine learning models and find that, in most cases, the fine-tuning approach is superior.