Development of coarse-grained simulation methods for the study of soft matter systems

开发用于研究软物质系统的粗粒度模拟方法

• 批准号: 2115555
• 金额: --
• 依托单位: Durham University
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2115555
• 关键词: Development; coarse; grained; simulation; methods

Coarse-grained molecular models have become widely used for the simulation of soft matter systems. The simple idea behind coarse-grained modelling for a molecular system is to develop a model at a lower resolution than a conventional atomistic model, with the aim of still capturing the key chemistry and physics of the system. The coarse-grained model will allow for simulations of time and length scales that are far beyond what is possible with an atomistic model (typically 1000x-10000x). This allows systems to be studied that would be intractable for a conventional atomistic simulation. Examples include: self-assembly in solution, peptide folding and aggregation, self-assembly within lipid membranes, the formation of micelles, prediction of surfactant phase diagrams, elucidation of complex thermotropic liquid crystal phases, partitioning of molecules between different phases, and the study of complex polymer systems (to name but a few!). There are two key problems that affect most coarse-grained molecular modelling: the representability and transferability problems. The former is concerned with the ability of a coarse-grained model to represent physical properties at the thermodynamic state point at which it is parametrised, the latter is concerned with the ability of the same model to be predictive at different state points, i.e. under conditions where parametrisation data was not available. This project is concerned with the development of better coarse-grained models, which will improve both transferability and representability. The project aims to make a sea-change in terms of what is currently possible in the realm of coarse-grained molecular models. It seeks to develop new models that are more reliable and more transferable than current models and can be used with confidence to tackle a range of complex problems in soft matter chemistry.

粗粒分子模型已被广泛用于软物质系统的模拟。分子系统粗粒度建模背后的简单想法是开发一个分辨率低于传统原子模型的模型，目的是仍然捕获系统的关键化学和物理特性。粗粒度模型将允许模拟时间和长度尺度，这远远超出了原子模型（通常为1000 x-10000 x）的可能性。这使得系统的研究，将是一个传统的原子模拟棘手。示例包括：溶液中的自组装、肽折叠和聚集、脂质膜内的自组装、胶束的形成、表面活性剂相图的预测、复杂热致液晶相的阐明、分子在不同相之间的分配以及复杂聚合物系统的研究（仅举几例！）。影响大多数粗粒度分子建模的关键问题有两个：可表示性和可传递性问题。前者涉及粗粒度模型在其被参数化的热力学状态点处表示物理性质的能力，后者涉及相同模型在不同状态点处的预测能力，即在参数化数据不可用的条件下。这个项目关注的是更好的粗粒度模型的开发，这将提高可移植性和可表示性。该项目的目标是在粗粒度分子模型领域目前可能的情况下进行彻底的改变。它旨在开发比当前模型更可靠，更可转移的新模型，并可用于解决软物质化学中的一系列复杂问题。