Computational and Theoretical Advances in Nanomaterial Adsorption: Mechanisms, Modeling, and Environmental Applications

The growing intensity of environmental contamination has heightened the need for advanced and selective adsorption strategies. Nanomaterials have gained prominence as effective adsorbents owing to their large surface areas, adjustable surface functionalities, and distinctive interfacial characteristics. At the same time, computational and theoretical modeling has become a vital approach for uncovering adsorption mechanisms, forecasting adsorption efficiency, and supporting rational material design. This review provides a critical overview of recent progress in computational and theoretical studies of nanomaterial-based adsorption, focusing on interfacial adsorption mechanisms, modeling techniques across multiple length scales, and environmentally relevant applications. Major theoretical approaches, including density functional theory, molecular dynamics, Monte Carlo simulations, and integrated multiscale methods, are discussed in the context of adsorption isotherms, kinetics, and thermodynamic behavior. Additionally, the role of data-driven and machine-learning-assisted models in accelerating predictive screening of adsorbents is highlighted. Key challenges related to multiscale integration, computational efficiency, and system realism are identified, alongside emerging opportunities for developing sustainable and application-focused adsorption modeling frameworks