Prediction of second-order rate constants of the sulfate radical anion with aromatic contaminants using the Monte Carlo technique

Lotfi, Shahram; Ahmadi, Shahin; Azimi, Ali; Kumar, Parvin

doi:10.1039/d3nj03696k

New J. Chem.

2023

DOI: 10.1039/d3nj03696k

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Prediction of second-order rate constants of the sulfate radical anion with aromatic contaminants using the Monte Carlo technique

Shahram Lotfi,

Shahin Ahmadi,

Ali Azimi

et al.

Abstract: It has been proved that the removal of aromatic contaminants from the environment with sulfate radical anion (SO4˙−)-based advanced oxidation technology is an effective method.

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2024

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Cited by 7 publications

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Prediction of second-order rate constants of the sulfate radical anion with aromatic contaminants using the Monte Carlo technique

Abstract: It has been proved that the removal of aromatic contaminants from the environment with sulfate radical anion (SO4˙−)-based advanced oxidation technology is an effective method.

Cited by 7 publications

References 66 publications

In silico development of novel angiotensin-converting-enzyme-I inhibitors by Monte Carlo optimization based QSAR modeling, molecular docking studies and ADMET predictions

In silico development of novel angiotensin-converting-enzyme-I inhibitors by Monte Carlo optimization based QSAR modeling, molecular docking studies and ADMET predictions

Optimization of Monte Carlo Method-Based QSPR modeling for lipophilicity in radiopharmaceuticals

The coefficient of conformism of a correlative prediction (CCCP): Building up reliable nano-QSPRs/QSARs for endpoints of nanoparticles in different experimental conditions encoded via quasi-SMILES

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