Unveiling Adsorption Mechanisms of Organic Pollutants onto Carbon Nanomaterials by Density Functional Theory Computations and Linear Free Energy Relationship Modeling

Wang, Ya; Chen, Jingwen; Wei, Xiaoxuan; Maldonado, Arturo J. Hernandez; Chen, Zhongfang

doi:10.1021/acs.est.7b02707

Cited by 45 publications

(21 citation statements)

References 89 publications

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“…In line with the above described, in this work, the absorption capability of graphene oxide and chitosan toward two specifics emergent pollutants were studied by using the density functional theory (DFT) [ 47 ], which is broadly used to understand and predict the adsorption of a specific molecule over a polymeric structure [ 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ], proving suitable correlations with the experimental results.…”

Section: Introductionmentioning

confidence: 99%

Predicting the Adsorption of Amoxicillin and Ibuprofen on Chitosan and Graphene Oxide Materials: A Density Functional Theory Study

et al. 2021

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The occurrence, persistence, and accumulation of antibiotics and non-steroidal anti-inflammatory drugs (NSAIDs) represent a new environmental problem due to their harmful effects on human and aquatic life. A suitable absorbent for a particular type of pollutant does not necessarily absorb other types of compounds, so knowing the compatibility between a particular pollutant and a potential absorbent before experimentation seems to be fundamental. In this work, the molecular interactions between some pharmaceuticals (amoxicillin, ibuprofen, and tetracycline derivatives) with two potential absorbers, chitosan and graphene oxide models (pyrene, GO-1, and coronene, GO-2), were studied using the ωB97X-D/6-311G(2d,p) level of theory. The energetic interaction order found was amoxicillin/chitosan > amoxicillin/GO-1 > amoxicillin/GO-2 > ibuprofen/chitosan > ibuprofen/GO-2 > ibuprofen/GO-1, the negative sign for the interaction energy in all complex formations confirms good compatibility, while the size of Eint between 24–34 kcal/mol indicates physisorption processes. moreover, the free energies of complex formation were negative, confirming the spontaneity of the processes. The larger interaction of amoxicillin GOs, compared to ibuprofen GOs, is consistent with previously reported experimental results, demonstrating the exceptional predictability of these methods. The second-order perturbation theory analysis shows that the amoxicillin complexes are mainly driven by hydrogen bonds, while van der Waals interactions with chitosan and hydrophobic interactions with graphene oxides are modelled for the ibuprofen complexes. Energy decomposition analysis (EDA) shows that electrostatic energy is a major contributor to the stabilization energy in all cases. The results obtained in this work promote the use of graphene oxides and chitosan as potential adsorbents for the removal of these emerging pollutants from water.

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Section: Introductionmentioning

confidence: 99%

Predicting the Adsorption of Amoxicillin and Ibuprofen on Chitosan and Graphene Oxide Materials: A Density Functional Theory Study

et al. 2021

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“…Quantitative structure–property relationship (QSPR) models can just make up for these shortcomings. Mechanism-based QSPR models, such as polyparameter linear free energy relationship (pp-LFER) model, can not only provide predictive K d values efficiently, but also promote the adsorption mechanism analysis [16,17,18]. Currently, few K d predictive models for microplastics have been reported.…”

Section: Introductionmentioning

confidence: 99%

Developing Predictive Models for Carrying Ability of Micro-Plastics towards Organic Pollutants

Wei

Wang

et al. 2019

Molecules

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Microplastics, which have been frequently detected worldwide, are strong adsorbents for organic pollutants and may alter their environmental behavior and toxicity in the environment. To completely state the risk of microplastics and their coexisting organics, the adsorption behavior of microplastics is a critical issue that needs to be clarified. Thus, the microplastic/water partition coefficient (log Kd) of organics was investigated by in silico method here. Five log Kd predictive models were developed for the partition of organics in polyethylene/seawater, polyethylene/freshwater, polyethylene/pure water, polypropylene/seawater, and polystyrene/seawater. The statistical results indicate that the established models have good robustness and predictive ability. Analyzing the descriptors selected by different models finds that hydrophobic interaction is the main adsorption mechanism, and π−π interaction also plays a crucial role for the microplastics containing benzene rings. Hydrogen bond basicity and cavity formation energy of compounds can determine their partition tendency. The distinct crystallinity and aromaticity make different microplastics exhibit disparate adsorption carrying ability. Environmental medium with high salinity can enhance the adsorption of organics and microplastics by increasing their induced dipole effect. The models developed in this study can not only be used to estimate the log Kd values, but also provide some necessary mechanism information for the further risk studies of microplastics.

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“…CNTs have a large surface area and offer strong interactions between the CNT and small molecules; thus, the use of CNTs for adsorption‐based environmental remediation has been studied theoretically and experimentally . CNTs are an important carbon‐based adsorptive material with exceptional adsorption capabilities and high adsorption efficiency for various organic pollutants . CNTs are particularly promising as a benzene adsorbent for environmental protection/remediation .…”

Section: Introductionmentioning

confidence: 99%

Endohedral and exohedral complexes of 1‐benzene with carbon nanotubes and high‐density assembly of multiple benzenes inside of a carbon nanotube

Jiang

Wang

2019

Int J of Quantum Chemistry

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The 1‐benzene was put on the inside and surface of various armchair (n, n) (n = 6‐12, 14) and zigzag (n, 0) (n = 10‐17, 20) nanotubes of different diameters. The binding structure, binding energy, and effects on binding energy were analyzed. All interaction structures and the properties of the assembled complexes were investigated via density functional tight‐binding method. Furthermore, we put multiple benzene molecules (2‐18 benzenes) inside the armchair (10, 10), (9, 9), and (8, 8) carbon nanotubes (CNTs) and found that two types of structures were formed for the endohedral complexes of multiple benzenes‐spiral symmetrical polygon and criss‐crossed types, respectively. The detail of the binding energies and structure properties for (10, 10)/kBen (k = 1‐6, 18), (9, 9)/kBen (k = 4, 5, 15), and (8, 8)/kBen (k = 1‐8) were discussed. Furthermore, the HOMOs and LUMOs of the representative complexes were also studied to illustrate the interactions. This article offers a new assembly method to prepare a high density of benzenes inside of CNTs and offers a method for benzene adsorption by CNT.

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Unveiling Adsorption Mechanisms of Organic Pollutants onto Carbon Nanomaterials by Density Functional Theory Computations and Linear Free Energy Relationship Modeling

Cited by 45 publications

References 89 publications

Predicting the Adsorption of Amoxicillin and Ibuprofen on Chitosan and Graphene Oxide Materials: A Density Functional Theory Study

Predicting the Adsorption of Amoxicillin and Ibuprofen on Chitosan and Graphene Oxide Materials: A Density Functional Theory Study

Developing Predictive Models for Carrying Ability of Micro-Plastics towards Organic Pollutants

Endohedral and exohedral complexes of 1‐benzene with carbon nanotubes and high‐density assembly of multiple benzenes inside of a carbon nanotube

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