Data-driven synthesis of electron-rich metal–organic frameworks for enhanced U(vi) removal

Abstract

To address the challenge of uranium (U)-containing wastewater pollution stemming from nuclear energy development, this study utilized a data-driven high-throughput screening method based on multiply–accumulate operation (MACCS) molecular fingerprints to pinpoint an electron-rich amino group modification strategy, and then a series of amine-modified UiO-66 (NH₂-UiO-66, ED-UiO-66, and DETA-UiO-66) samples with gradient increase in amino group density were successfully synthesized. By employing post-synthetic modification techniques to precisely graft ED and DETA onto the UiO-66 framework, we significantly enhanced the density of active sites while preserving crystal stability. In addition, adsorption investigation demonstrated a positive correlation between the number of amino groups and U(VI) capture capacity. Specifically, DETA-UiO-66, containing triamino groups, achieved a saturated adsorption capacity of 494.84 mg g⁻¹ at pH = 7, representing a 132% increase compared to the unmodified conventional UiO-66 (C-UiO-66). The adsorption process followed a pseudo-second-order kinetic model, indicating that chemical adsorption was the dominant mechanism. This conclusion was further corroborated by FTIR and XPS analyses, which revealed an amino-carboxyl synergistic effect, as well as density functional theory (DFT) calculations that elucidated the adsorption energy and sites. Moreover, the resulting amine-modified UiO-66 exhibited excellent regeneration performance, maintaining a good capacity retention rate after five reuse cycles. Collectively, these findings provide valuable theoretical insights and practical references for the design and utilization of high-efficiency U(VI) adsorbents.