Molecular simulation-based insights into dye pollutant adsorption: A perspective review

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorIslamic Azad University-
Autor(es): dc.contributorIran Polymer and Petrochemical Institute-
Autor(es): dc.contributorUniversity of Technology Sydney-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of KwaZulu-Natal-
Autor(es): dc.contributorAjman University-
Autor(es): dc.creatorSalahshoori, Iman-
Autor(es): dc.creatorWang, Qilin-
Autor(es): dc.creatorNobre, Marcos A.L.-
Autor(es): dc.creatorMohammadi, Amir H.-
Autor(es): dc.creatorDawi, Elmuez A.-
Autor(es): dc.creatorKhonakdar, Hossein Ali-
Data de aceite: dc.date.accessioned2025-08-21T22:25:47Z-
Data de disponibilização: dc.date.available2025-08-21T22:25:47Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-10-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.cis.2024.103281-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/300245-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/300245-
Descrição: dc.descriptionGrowing concerns about environmental pollution have highlighted the need for efficient and sustainable methods to remove dye contamination from various ecosystems. In this context, computational methods such as molecular dynamics (MD), Monte Carlo (MC) simulations, quantum mechanics (QM) calculations, and machine learning (ML) methods are powerful tools used to study and predict the adsorption processes of dyes on various adsorbents. These methods provide detailed insights into the molecular interactions and mechanisms involved, which can be crucial for designing efficient adsorption systems. MD simulations, detailing molecular arrangements, predict dyes' adsorption behaviour and interaction energies with adsorbents. They simulate the entire adsorption process, including surface diffusion, solvent layer penetration, and physisorption. QM calculations, especially density functional theory (DFT), determine molecular structures and reactivity descriptors, aiding in understanding adsorption mechanisms. They identify stable adsorption configurations and interactions like hydrogen bonding and electrostatic forces. MC simulations predict equilibrium properties and adsorption energies by sampling molecular configurations. ML methods have proven highly effective in predicting and optimizing dye adsorption processes. These models offer significant advantages over traditional methods, including higher accuracy and the ability to handle complex datasets. These methods optimize adsorption conditions, clarify adsorbent functionalization roles, and predict dye removal efficiency under various conditions. This research explores MD, MC, QM, and ML approaches to connect molecular interactions with macroscopic adsorption phenomena. Probing these techniques provides insights into the dynamics and energetics of dye pollutants on adsorption surfaces. The findings will aid in developing and optimizing new materials for dye removal. This review has significant implications for environmental remediation, offering a comprehensive understanding of adsorption at various scales. Merging microscopic data with macroscopic observations enhances knowledge of dye pollutant adsorption, laying the groundwork for efficient, sustainable removal technologies. Addressing the growing challenges of ecosystem protection, this study contributes to a cleaner, more sustainable future.-
Descrição: dc.descriptionAjman University-
Descrição: dc.descriptionDepartment of Chemical Engineering Science and Research Branch Islamic Azad University-
Descrição: dc.descriptionDepartment of Polymer Processing Iran Polymer and Petrochemical Institute, P.O. Box 14965-115-
Descrição: dc.descriptionSchool of Civil and Environmental Engineering University of Technology Sydney-
Descrição: dc.descriptionSão Paulo State University (Unesp) School of Technology and Sciences, SP-
Descrição: dc.descriptionDiscipline of Chemical Engineering School of Engineering University of KwaZulu-Natal, Howard College Campus, King George V Avenue-
Descrição: dc.descriptionCollege of Humanities and Sciences Department of Mathematics and Science Ajman University, P.O. Box 346, Ajman-
Descrição: dc.descriptionSão Paulo State University (Unesp) School of Technology and Sciences, SP-
Descrição: dc.descriptionAjman University: DRGS-2023-IRG-HBS-02-
Idioma: dc.languageen-
Relação: dc.relationAdvances in Colloid and Interface Science-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectAdsorption mechanisms-
Palavras-chave: dc.subjectComputational techniques-
Palavras-chave: dc.subjectDye pollutants removal-
Palavras-chave: dc.subjectEnvironmental pollution-
Palavras-chave: dc.subjectSustainable removal strategies-
Título: dc.titleMolecular simulation-based insights into dye pollutant adsorption: A perspective review-
Tipo de arquivo: dc.typevídeo-
Aparece nas coleções:Repositório Institucional - Unesp

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