Comparison Between Molecular Dynamics Potentials for Simulation of Graphene-Based Nanomaterials for Biomedical Applications

分子动力学 纳米材料 石墨烯 纳米技术 材料科学 统计物理学 化学 化学物理 计算化学 物理
作者
Laurentius Ivan Ageng Marhaendra,Yudi Rosandi,Amirah Mohd Gazzali,Dhania Novitasari,Muchtaridi Muchtaridi
出处
期刊:Drug Development and Industrial Pharmacy [Taylor & Francis]
卷期号:: 1-16
标识
DOI:10.1080/03639045.2025.2457387
摘要

This article provides a substantial review of recent research and comparison on molecular dynamics potentials to determine which are most suitable for simulating the phenomena in graphene-based nanomaterials (GBNs). GBNs gain significant attention due to their remarkable properties and potential applications, notably in nanomedicine. However, the physical and chemical characteristics toward macromolecules that justify their nanomedical applications are not yet fully understood. The molecular interaction through molecular dynamic simulation offers the benefits for simulating inorganic molecules like GBNs, with necessary adjustments to account for physical and chemical interactions, or thermodynamic conditions. In this review, we explore various molecular dynamics potentials (force fields) used to simulate interactions and phenomena in graphene-based nanomaterials. Additionally, we offer a brief overview of the benefits and drawbacks of each force fields that available for analysis to assess which one is suitable to study the molecular interaction of graphene-based nanomaterials. We identify and compare various molecular dynamics potentials that available for analyzing GBNs, providing insights into their suitability for simulating specific phenomena in graphene-based nanomaterials. The specification of each force fields and its purpose can be used for further application of molecular dynamics simulation on GBNs. GBNs hold significant promise for applications like nanomedicine, but their physical and chemical properties must be thoroughly studied for safe clinical use. Molecular dynamics simulations, using either reactive or non-reactive MD potentials depending on the expected chemical changes, are essential for accurately modeling these properties, requiring careful selection based on the specific application.

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