Highly Efficient Adsorption of Norfloxacin by Low-Cost Biochar: Performance, Mechanisms, and Machine Learning-Assisted Understanding.
Miaomiao ZhangPengwei LiDong GuoZiheng ZhaoWeisheng FengZhijuan ZhangPublished in: ACS omega (2024)
This study employed potassium carbonate (K 2 CO 3 ) activation using ball milling in conjunction with pyrolysis to produce biochar from one traditional Chinese herbal medicine Atropa belladonna L. (ABL) residue. The resulting biochar KBC 800 was found to possess a high specific surface area ( S BET = 1638 m 2 /g) and pore volume (1.07 cm 3 /g), making it effective for removing norfloxacin (NOR) from wastewater. Batch adsorption tests confirmed its effectiveness in eliminating NOR, along with its excellent resistance to interference from impurity ions or antibiotics. Notably, the maximum experimental NOR adsorption capacity on KBC 800 was 666.2 mg/g at 328 K, surpassing those of other biochar materials reported. The spontaneous and endothermic adsorption of NOR on KBC 800 could be better suited to the Sips model. Additionally, KBC 800 adsorbs NOR mainly by pore filling, with electrostatic attraction, π-π EDA interactions, and hydrogen bonds also contributing significantly. The machine learning model revealed that NOR adsorption on the biochar was significantly affected by the initial concentration, followed by S BET and average pore size. Based on the random forest model, it is demonstrated that biochar is able to adsorb NOR effectively. It is noteworthy that the use of low-cost pharmaceutical wastes to produce adsorbents for emerging contaminants such as antibiotics could have greater potential for future practical applications under the ongoing dual carbon policy.
Keyphrases
- sewage sludge
- anaerobic digestion
- low cost
- heavy metals
- aqueous solution
- machine learning
- highly efficient
- municipal solid waste
- organic matter
- plant growth
- healthcare
- systematic review
- public health
- randomized controlled trial
- risk assessment
- artificial intelligence
- climate change
- big data
- current status
- quantum dots
- single cell
- drinking water