Molecular Modelling based design of ligand shells to functionalize magnetic nanoparticles for the removal of heavy metal pollutants from water.

该项目旨在通过分子建模和模拟设计磁铁矿纳米颗粒的定制功能化，以结合重金属离子和相关的有机金属化合物。虽然在这个阶段反映了一个纯理论的项目，我们的目标是开发一个基于模型的搜索策略，以确定合适的成分和结构作为指导合成。通过与实验合作伙伴的合作，这将最终实现通过磁提取来净化水中的重金属。为了实现这一目标，我们建立在最近建立的概念，从水中去除石油污染，利用超顺磁性纳米粒子功能化的自组装单分子层（SAM）的n-烷基膦酸。虽然烃与这种自组装膜的烷基链的缔合是由简单的疏水分离机制驱动的，但需要精心选择的定制螯合残基的自组装膜来有效地结合和去除水中的重金属污染物。这需要深入了解分子识别和结构基序的调整-这两者都应该从分子模拟中实现。

This project aims at designing tailor-made functionalization of magnetite nanoparticles to bind heavy metal ions and related organometallic compounds by means of molecular modelling and simulation. While at this stage reflecting a pure theory project, we aim at developing a model-based search strategy for identifying suitable constituents and structures as guides to syntheses. In cooperation with experimental partners, this shall finally enable water cleaning from heavy metals by magnetic extraction. To achieve this, we build on a recently established concept for the removal of oil pollution from water that takes use of super-paramagnetic nanoparticles functionalized by self-assembled monolayers (SAMs) of n-alkyl phosphonic acids. While the association of hydrocarbons to the alkyl chains of such SAMs is driven by a simple hydrophobic segregation mechanism, well-chosen SAMs of tailor-made chelating residues are needed for efficiently binding and removing heavy metal pollutants from water. This calls for in-depth understanding of molecular recognition and the tuning of structural motifs – which shall both be achieved from molecular simulations.