Accurate model to predict the solubility of fullerene C<sub>60</sub> in organic solvents by using support vector regression

Cheng, Wen-De; Cai, Can

doi:10.1080/1536383x.2016.1252336

Cited by 9 publications

(3 citation statements)

References 34 publications

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“…This is why modeling of C60 solubility attracted so much attention and resulted in a variety of theoretical approaches, among which the best predications come so far from non-linear modeling via machine learning [18]. Other approaches taking advantage of quantitative structure-property relationships (QSPR) [19][20][21], the multiple linear regression (MLR) [19,22], partial least square regression (PLS) [23], support vector machines (SVMs) [22] and neural networks (NNs) [20] have been reported for predicting the solubility of C60 fullerenes in different organic solvents. Although these models offer quite an acceptable estimate suitable for screening of new solvents, they all rely on the sets of molecular descriptors characterizing solute-solvents properties.…”

Section: Introductionmentioning

confidence: 99%

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Cysewski

2019

Symmetry

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The default COSMO-RS (Conductor like Screening Model for Real Solvents) approach is incapable of accurate computation of C60 solubility in net solvents. Additionally, there is no adequate selection of single or multiple reference solvent, which can be applied to the whole population of 180 solvents for improving prediction of mole fraction at saturated conditions. This failure cannot be addressed to inaccurate data of the Buckminster fusion, although they pose a challenge for experimental measurement due to intense sublimation of C60 at elevated temperatures and the possibility of solvates precipitation. However, taking advantage of the richness of experimental data of fullerene solubility, it is possible to identify the source of errors expressed in terms of fluidization affinity. Classification of solvents according to the value of this fluidization term allowed for formulation of a consonance solvents approach, which enables accurate prediction of C60 solubility using the single reference solvent method.

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Section: Introductionmentioning

confidence: 99%

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Cysewski

2019

Symmetry

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“…Several studies,experimental as well as computational, are known in the literature to analyze the solubility of fullerenes, but mainly available for the solubility of C 60 fullerenes in diverse solvents . The in‐silico (computational) studies have an advantage over the in‐vivo and in‐vitro (experimental) studies as the former are cost effective, less laborious, and can be analyzed simultaneously for diverse solvents.…”

Section: Introductionmentioning

confidence: 99%

“…The in‐silico (computational) studies have an advantage over the in‐vivo and in‐vitro (experimental) studies as the former are cost effective, less laborious, and can be analyzed simultaneously for diverse solvents. These studies include several quantitative structure‐property relationship (QSPR) models based on linear as well non‐linear approaches, for example, using support vector machine (SVM), multi linear regression (MLR), partial least square regression (PLS), neutral networks (NNs), decision treeboost (DTB) methods etc . Recently, Gupta and Basant, using the DTB method, has also attempted to model the solubility of C 70 fullerenes.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Solubility of C₇₀ Fullerenes in Diverse Solvents: Role of Quantum‐mechanical Descriptors

Lata

Vikas

2019

Molecular Informatics

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This paper is dedicated to Prof. Paola Gramatica on the occasion of her retirement.Abstract: Solubility of fullerenes in diverse solvents is difficult to model owing to the involvement of inherent quantum-mechanical interactions. This work proposes pure quantum mechanical models for predicting the solubility of C 70 fullerenes. The models are developed using singlemolecule quantum mechanical properties of solvents,which includes electron-correlation based descriptors accounting for the instantaneous inter-electronic interactions responsible for the origin of these properties. The external predictivity of the models was validated using an external prediction set of compounds not exposed to the model during its development. The most influential factor affecting the solubility was found to be electron-correlation contribution to the energy of highest occupied molecular orbital of solvents, which in fact, has been analyzed to suppress the solubility of fullerenes. However, the polarizability of the solvents, particularly that due to the quantum-mechanical exchange interactions between the electrons, is observed to drive the solubility of C 70 fullerenes. The present work also found several other quantum mechanical properties affecting the solubility of fullerenes, which pay valuable insights towards the origin of the solubility of carbon-based nanomaterials.Keywords: modelling · solubility · fullerenes · quantum-mechanical methods Recently, Gupta and Basant, [25] using the DTB method, has also attempted to model the solubility of C 70 fullerenes. Very recently, Torpova and Torpov, [26] has proposed nano-QSPRs based on a quasi-simplified molecular input-line entry systems (SMILES) which is an expansion of the traditional SMILES but under varying conditions. The aim of the present work is to explore the correlations between the solubility of C 70 fullerenes in diverse solvents and the single-molecule quantum-mechanical properties of these solvents. For this, the quantitative models based on the quantum-mechanical descriptors are [a] S. Lata, Vikas

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Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents

Basant

2018

Chemosphere

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Accurate model to predict the solubility of fullerene C₆₀ in organic solvents by using support vector regression

Cited by 9 publications

References 34 publications

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Modeling the Solubility of C₇₀ Fullerenes in Diverse Solvents: Role of Quantum‐mechanical Descriptors

Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents

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Accurate model to predict the solubility of fullerene C60 in organic solvents by using support vector regression

Cited by 9 publications

References 34 publications

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Modeling the Solubility of C70 Fullerenes in Diverse Solvents: Role of Quantum‐mechanical Descriptors

Predictive modeling: Solubility of C60 and C70 fullerenes in diverse solvents

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Accurate model to predict the solubility of fullerene C₆₀ in organic solvents by using support vector regression

Modeling the Solubility of C₇₀ Fullerenes in Diverse Solvents: Role of Quantum‐mechanical Descriptors