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石墨烯纳米片对有机污染物的浓度依赖吸附:量子力学模型。

Concentration-dependent adsorption of organic contaminants by graphene nanosheets: quantum-mechanical models.

机构信息

Quantum Chemistry Group, Department of Chemistry and Centre of Advanced Studies in Chemistry, Panjab University, Chandigarh, 160014, India.

出版信息

J Mol Model. 2021 Jan 25;27(2):48. doi: 10.1007/s00894-021-04686-4.

DOI:10.1007/s00894-021-04686-4
PMID:33496822
Abstract

Adsorption is the key process in the expression of environmentally relevant physicochemical and toxicological properties of carbon nanomaterials. However, the adsorption of organic contaminants on to nanomaterials is a highly complex phenomenon, owing to the heterogeneity of adsorption sites, for example, on graphene surface as well as due to multiple factors operative during the adsorption, particularly, at the quantum-mechanical level. For predicting the concentration-dependent adsorption coefficients of organic contaminants by carbon nanomaterials, one option has been to rely on the existing linear-solvation energy relationship (LSER) models. The present work on the adsorption of aromatic and aliphatic organic contaminants by graphene nanosheets reveals that the existing LSER models are prone to failure when tested for internal and external validation using an external prediction set of compounds unknown to the model. As an alternative to the LSERs, the present work reports pure quantum-mechanical models developed using computational only quantum-mechanical descriptors. The reliability of the quantum-mechanical models was tested using state-of-the-art validation procedures employing an external prediction set of compounds. The proposed quantum-mechanical models reveal mean polarizability, zero-point vibrational energy, and its electron-correlation contribution to be the key descriptors in the prediction of adsorption coefficients of organic contaminants by graphene nanosheets.

摘要

吸附是表达碳纳米材料与环境相关的物理化学和毒理学性质的关键过程。然而,由于吸附位点的非均一性,例如在石墨烯表面,以及由于吸附过程中多个因素的作用,特别是在量子力学水平上,有机污染物在纳米材料上的吸附是一个高度复杂的现象。为了预测碳纳米材料对有机污染物的浓度依赖性吸附系数,一种选择是依赖于现有的线性溶剂化能量关系(LSER)模型。本研究对石墨烯纳米片吸附芳香族和脂肪族有机污染物的研究表明,现有的 LSER 模型在使用模型未知的外部化合物预测集进行内部和外部验证时容易出现故障。作为 LSER 的替代方法,本研究报告了仅使用计算量子力学描述符开发的纯量子力学模型。使用外部化合物预测集,通过最先进的验证程序测试了量子力学模型的可靠性。所提出的量子力学模型表明,平均极化率、零点振动能及其电子相关贡献是预测石墨烯纳米片吸附系数的关键描述符。

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本文引用的文献

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Electrostatics and Polarization in σ- and π-Hole Noncovalent Interactions: An Overview.σ-和π-空穴非共价相互作用中的静电学与极化:综述
Chemphyschem. 2020 Apr 2;21(7):579-588. doi: 10.1002/cphc.201900968. Epub 2020 Jan 16.
2
Externally predictive quantum-mechanical models for the adsorption of aromatic organic compounds by graphene-oxide nanomaterials.用于预测芳香族有机化合物在氧化石墨烯纳米材料上吸附的外量子力学模型。
SAR QSAR Environ Res. 2019 Dec;30(12):847-863. doi: 10.1080/1062936X.2019.1666164. Epub 2019 Oct 2.
3
Quantum-mechanical LSERs for the concentration-dependent adsorption of aromatic organic compounds by activated carbon: Applications and comparison with carbon nanotubes.
量子力学 LSERs 在活性炭对芳香族有机化合物的浓度依赖吸附中的应用:与碳纳米管的比较。
SAR QSAR Environ Res. 2019 Feb;30(2):109-130. doi: 10.1080/1062936X.2019.1566173. Epub 2019 Feb 7.
4
Predictive models for adsorption of organic compounds by Graphene nanosheets: comparison with carbon nanotubes.预测模型对有机化合物的吸附作用的石墨烯纳米片:与碳纳米管。
Sci Total Environ. 2019 Mar 1;654:28-34. doi: 10.1016/j.scitotenv.2018.11.029. Epub 2018 Nov 6.
5
Concentration dependent adsorption of aromatic organic compounds by SWCNTs: Quantum-mechanical descriptors for nano-toxicological studies of biomolecules and agrochemicals.浓度依赖性芳香族有机化合物在单壁碳纳米管上的吸附:用于生物分子和农用化学品纳米毒理学研究的量子力学描述符。
J Mol Graph Model. 2018 Oct;85:232-241. doi: 10.1016/j.jmgm.2018.08.012. Epub 2018 Sep 8.
6
Adsorption mechanism of emerging and conventional phenolic compounds on graphene oxide nanoflakes in water.水中新兴和常规酚类化合物在氧化石墨烯纳米片上的吸附机制。
Sci Total Environ. 2018 Sep 1;635:629-638. doi: 10.1016/j.scitotenv.2018.03.389. Epub 2018 Apr 24.
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J Hazard Mater. 2018 Feb 5;343:200-207. doi: 10.1016/j.jhazmat.2017.09.032. Epub 2017 Sep 20.
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Chemosphere. 2017 Oct;185:826-832. doi: 10.1016/j.chemosphere.2017.07.062. Epub 2017 Jul 14.
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