2023
DOI: 10.1021/acs.iecr.2c02333
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Elucidating the Sorption Mechanisms of Environmental Pollutants Using Molecular Simulation

Abstract: With the global expansion of industrial activities, the entry of various pollutants into the environment has remained a serious issue. One of the best ways to remove these pollutants is to use the adsorption method. Understanding adsorption mechanisms to improve and optimize adsorbents are pivotal for adsorbent development. In this study, the application of molecular simulation in developing various adsorbents has been reviewed. A variety of molecular simulation methods such as molecular dynamics (MD), density… Show more

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Cited by 20 publications
(14 citation statements)
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“…45 Focusing on PFAS, several interaction mechanisms are involved in contaminant adsorption on the adsorbent and the interface of the fluids; the most well-known are van der Waals forces, electrostatic interactions, and hydrogen bonding. 28 The classical MD simulations reveal the mechanisms underlying these processes. For that reason, classical MD gained attention in recent years among molecular researchers in this field 28 and has been shown to be affordable for systems containing the maximum number of 10 6 atoms and time duration of 1000 ns.…”
Section: Nanoscale Molecular Dynamicsmentioning
confidence: 99%
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“…45 Focusing on PFAS, several interaction mechanisms are involved in contaminant adsorption on the adsorbent and the interface of the fluids; the most well-known are van der Waals forces, electrostatic interactions, and hydrogen bonding. 28 The classical MD simulations reveal the mechanisms underlying these processes. For that reason, classical MD gained attention in recent years among molecular researchers in this field 28 and has been shown to be affordable for systems containing the maximum number of 10 6 atoms and time duration of 1000 ns.…”
Section: Nanoscale Molecular Dynamicsmentioning
confidence: 99%
“…The amphiphilic and oleophobic characteristics of PFAS make it difficult to accurately predict their sorption and transport in porous media based on surface and solution conditions. For example, when attempting to correlate PFAS sorption with the bulk properties of soil/sediment, such as an organic fraction, protein content, anion or cation exchange capacity, and mineral type, the covariation of these properties in the sorbent has been shown to lead to confounding results. , Additionally, the complexity of PFAS molecular interaction at fluid interfaces challenges experimentation, characterization, and the computational tools that might reveal molecular scale behaviors. , Efforts are needed for a fundamental understanding of interactions, surface chemical features, and fluid–fluid behaviors embedded within computational platforms required to assess feasible experimental designs and to assist with upscaling . Based on the fundamental understanding, quantitative models for PFAS dynamics are expected via correlating with specific soil properties, interfacial parameters, PFAS chemical structures, and solution chemistry.…”
Section: Challenges In Characterizing Pfas Dynamicsmentioning
confidence: 99%
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“…The π–π interaction mechanism is commonly used to explain the interaction between pollutants containing π-electrons (aromatic rings) and species with π-electrons . The beneficial contribution of π interaction can significantly improve the adsorption efficiency.…”
Section: Introductionmentioning
confidence: 99%
“…13,14 Due to these limitations, molecular docking techniques are often comple- mented with molecular dynamics simulations, which simulate the conformational adjustments and motions of molecular systems. 15 Molecular dynamics simulations can provide a more accurate representation of the flexibility of ligand−receptor interactions, improving the reliability of the predictions. 16,17 Nonetheless, molecular docking provides useful guidance for further experimental and computational analyses by generating initial hypotheses about ligand−receptor interactions and potential binding modes, serving as an efficient screening tool for large chemical libraries.…”
Section: ■ Introductionmentioning
confidence: 99%