Elucidating hydrogen bonding and synergistic adsorption mechanisms of morphine on deep eutectic solvent-functionalized biochar through machine learning and density functional theory.

Adsorbent materials effectively separated psychoactive substances from the ambient medium through adsorption, serving as a sustainable removal strategy. In this study, a novel magnetic biochar was developed using waste shrimp shells as the raw material, through hydrochloric acid activation, Fe doping, pyrolysis, and deep eutectic solvent (DES) functionalization. The prepared adsorbents (MSBC-PG, MSBC-PA, MSBC-LA) possessed a hierarchical pore structure and abundant oxygen-containing functional groups. Among them, MSBC-PG exhibited a BET surface area of 176.9 m2 g-1, a total pore volume of 0.25 cm3 g-1, and a maximum adsorption capacity for morphine of 1186.4 μg g-1. The adsorption behavior of morphine on the material was well-described by the Langmuir and pseudo-second-order kinetic models, confirming a spontaneous and endothermic process involving both chemical and physical adsorption. MSBC-PG maintained stable adsorption performance across a pH range of 4-10, exhibited minimal interference from humic acid and urea, and retained over 85 % efficiency after five regeneration cycles. Post-adsorption characterization, density functional theory (DFT) calculations, and SHAP analysis collectively revealed that the adsorption mechanism involved the synergistic effects of pore filling, hydrogen bonding, and π-π interactions, with oxygen-containing functional groups playing a decisive role. A machine learning model based on gradient boosting decision trees (R2 = 0.99) further identified oxygen content, initial concentration, and contact time as key factors governing the adsorption process. This study provided an effective strategy for designing sustainable shrimp shell-based adsorbents to remediate opioid-contaminated water bodies.