Mechanism of enhanced punicalagin adsorption by ultrasound-chitosan functionalized baobab green adsorbents

• Synergistic ultrasound and chitosan functionalization improved the performance of BFS adsorbents • Increased surface area and pore volume, enabling fast adsorption kinetics and mass transfer • Punicalagin adsorption capacity increased from 79 to 211.21 mg g⁻¹ after functionalization • Functionalized BFS adsorbents retained >85% adsorption efficiency after four reuse cycles • Hydrogen bonding and electrostatic interaction govern punicalagin binding mechanism Developing sustainable low-cost adsorbents with high polyphenol adsorption capacity is crucial for advancing green separation technologies. This study integrates experimental and computational techniques to elucidate the synergistic effects of ultrasonication (US) and chitosan (CS) functionalization on the adsorption performance of baobab fruit shell (BFS) green adsorbents for punicalagin adsorption. Characterization via BET, FTIR, XRD, and SEM-EDS analyzes confirmed that US-CS functionalization increased surface area, pore volume, and accessible functional groups. Modified BFS (MBFS) adsorbents treated under high-intensity short-time (HIST, 687.9 W cm −2 , 5 min) US treatment showed a three-fold increase in punicalagin adsorption capacity (211.21 mg g −1 ) and rapid adsorption equilibrium within 5 min. US generally intensified mass transfer during adsorption, as evidenced by the significant increase in external mass transfer coefficient from 1.21 × 10 −4 to 2.82 × 10 −4 ms −1 following HIST treatment. Based on XPS results, hydrogen bonding, hydrophobic, and electrostatic interactions are involved in punicalagin adsorption on MBFS. The pseudo-first-order kinetic and Langmuir isotherm models (R² > 0.99) best described the adsorption mechanism, confirming both physisorption and a propensity for monolayer adsorption on homogeneous surfaces. HIST treatment preserved structural integrity under transient mechanical stress, enabling MBFS to retain over 85% efficiency after four adsorption-desorption cycles. Machine learning models, particularly XGBoost (R² > 0.95; RMSE = 6.47), accurately predicted the punicalagin adsorption capacity and identified HIST and CS crosslinking as the key variables. Overall, US- and CS-functionalized BFS adsorbents show strong potential as a green and sustainable alternatives for polyphenol purification.