Integrating Biolayer Interferometry, Atomic Force Microscopy, and Density Functional Theory Calculation Studies on the Affinity between Humic Acid Fractions and Graphene Oxide.


Journal

Environmental science & technology
ISSN: 1520-5851
Titre abrégé: Environ Sci Technol
Pays: United States
ID NLM: 0213155

Informations de publication

Date de publication:
02 04 2019
Historique:
pubmed: 14 3 2019
medline: 19 9 2019
entrez: 14 3 2019
Statut: ppublish

Résumé

The interactions between nanoparticles and humic acid (HA) are critical to understanding the environmental risks and applications of nanoparticles. However, the interactions between HA fractions and graphene oxide (GO, a popular carbon nanosheet) at the molecular level remain largely unclear. Four HA fractions with molecular weights ranging from 4.6 to 23.8 kDa were separated, and the large HA fractions presented low oxygen contents and many aromatic structures. The binding constants of the large HA fractions on GO were 2.6- to 3551-fold higher than those of the small HA fractions, while the maximum adsorption capacities of the larger HA fractions onto GO were much higher. Atomic force microscopy (AFM) found that the small and large HA fractions were spread over the center and the edge of the GO nanosheets, respectively. Density functional theory (DFT) simulation and nuclear magnetic resonance spectroscopy confirmed the above phenomena (three adsorption patterns, "vs", "ps", and "pea") and revealed that HA bonded to the GO nanosheets mainly through van der Waals force and π-π interactions. The integrating analysis of binding affinity, AFM, and DFT provides new insights into the environmental behavior of GO and the applications of GO in pollutant removal under exposure from HA.

Identifiants

pubmed: 30865825
doi: 10.1021/acs.est.8b05232
doi:

Substances chimiques

Humic Substances 0
Oxides 0
Graphite 7782-42-5

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3773-3781

Auteurs

Qixing Zhou (Q)

Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering , Nankai University , Tianjin 300350 , China.

Shaohu Ouyang (S)

Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering , Nankai University , Tianjin 300350 , China.

Zhimin Ao (Z)

Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Institute of Environmental Health and Pollution Control, School of Environmental Science and Engineering , Guangdong University of Technology , Guangzhou , 510006 , China.

Jing Sun (J)

Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering , Nankai University , Tianjin 300350 , China.

Guanlan Liu (G)

Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Institute of Environmental Health and Pollution Control, School of Environmental Science and Engineering , Guangdong University of Technology , Guangzhou , 510006 , China.

Xiangang Hu (X)

Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education)/Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering , Nankai University , Tianjin 300350 , China.

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Classifications MeSH