Microwave-assisted β-cyclodextrin modified calcium-rich biochar for tetracycline removal from wastewater: mechanistic, machine learning, density functional theory calculations and life cycle assessment

Abstract

The removal of antibiotics from water using sustainable and cost-effective methods remains an environmental challenge. In this study, cotton-stalk biochar (CBC) was used as a substrate and waste eggshells as a calcium source to prepare a β-cyclodextrin-functionalized adsorbent (Ca@CBC/β-CD) via microwave-assisted crosslinking. The obtained material was used for tetracycline (TC) removal from water. Experimental results showed that Ca@CBC/β-CD exhibited the best adsorption performance at approximately pH = 6, and the adsorption kinetics were well described by the pseudo-second-order model. The adsorption isotherm followed the Langmuir model, with the maximum adsorption capacity increasing from 142.36 mg g⁻¹ at 25 °C to 161.91 mg g⁻¹ at 45 °C. The adsorbent also showed good tolerance to common coexisting ions and retained about 84–86% of its initial capacity after five regeneration cycles. Spectroscopic characterization combined with density functional theory (DFT) calculations revealed that TC adsorption was governed by the synergistic contribution of Ca²⁺ inner-sphere complexation/surface bridging, β-CD host–guest inclusion, and multi-point hydrogen bonding. Among the tested machine-learning models, the gradient boosting decision tree showed the best predictive performance (test-set R² = 0.9914) and identified initial concentration, adsorbent dosage, and contact time as the key adsorption factors. Life-cycle assessment further indicated that the preparation stage generated 5.44 kg CO₂-eq per kg adsorbent, with electricity being the primary hotspot. Overall, Ca@CBC/β-CD represents an efficient, reusable, and relatively sustainable adsorbent for TC removal from water.

Graphic Abstract

Keywords

β-cyclodextrin / Biochar / Tetracycline / Machine learning / Adsorption / Life cycle assessment

Highlight

•	A new adsorbent from waste cotton stalks and eggshells captures antibiotics through pores and surface sites.
•	Tests and quantum-level calculations show efficient, reusable removal of antibiotics from water.
•	A machine learning model accurately predicted adsorption performance and highlighted the most important factors.
•	Life cycle assessment found electricity use is the main environmental hotspot in adsorbent production.

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Funding

Science and Technology Program Project of Alaer City (2025GX06)

Bingtuan Science and Technology Program(2021DB019)

President’s foundation of Tarim University(TDZKCX202404)

RIGHTS & PERMISSIONS

The Author(s)