Citation: Zhihao Li, Zhiruo Zhou, Yuan Qin, Dan Huang, Meizhen Wang. Density functional theory assists in promoting advanced oxidation processes: Toward efficient antibiotic degradation in waters[J]. Chinese Chemical Letters, ;2026, 37(6): 112318. doi: 10.1016/j.cclet.2025.112318 shu

Density functional theory assists in promoting advanced oxidation processes: Toward efficient antibiotic degradation in waters

Zhihao Li ^a ,
Zhiruo Zhou ^{a, *,} ,
Yuan Qin ^b ,
Dan Huang ^a ,
Meizhen Wang ^{a, c, *,}

a.
Zhejiang Key Laboratory of Solid Waste Pollution Control and Resource Utilization, School of Environmental Science and Engineering, Zhejiang Gongshang University, Hangzhou 310018, China
b.
College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou 310018, China
c.
School of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China

zhouzhiruo@zjgsu.edu.cn

wmzyy@163.com

Received Date: 6 June 2025
Revised Date: 3 December 2025
Accepted Date: 23 December 2025
Available Online: 24 December 2025

Figures(6)

Antibiotic contamination in aquatic environments poses a serious threat to ecological safety and public health. However, traditional advanced oxidation processes (AOPs) face critical bottlenecks due to unclear microscopic reaction mechanisms, including ambiguous reactive species generation pathways and a lack of theoretical guidance for catalyst design. This review systematically elucidates the pivotal role of density functional theory (DFT) in antibiotic degradation via AOPs: (1) By accurately simulating catalyst electronic structures, adsorption energies, and reaction energy barriers, DFT reveals the evolution rules of active sites (e.g., multi-element doping reduces the O–O bond cleavage energy barrier by 36%), thereby optimizing reaction pathways across photocatalysis, electrochemical oxidation, and persulfate activation systems; (2) Combined with Fukui index and molecular orbital analyses, DFT enables precise identification of vulnerable sites in antibiotic molecules (e.g., C8/C13 of ofloxacin and O23/N15 of ciprofloxacin), and predicts the thermodynamics and kinetics of reactive species (e.g., ¹O₂, SO₄^•‒) formation; (3) Under a closed-loop "computational guidance — experimental validation" framework, DFT drives catalyst structure optimization and reaction pathway regulation, significantly enhancing AOP mineralization efficiency (e.g., 2.5-fold increase in tetracycline removal rate). Future directions should focus on integrating non-adiabatic molecular dynamics, machine learning-assisted screening, and toxicity prediction of degradation products to promote the intelligent design and green engineering of AOPs, thereby building an efficient and precise antibiotic pollution control system.
- Advanced oxidation processes (AOPs),
- Density functional theory (DFT),
- Catalyst design,
- Reaction mechanism elucidation
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沈阳化工大学材料科学与工程学院沈阳 110142