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

本项目旨在通过分子建模和模拟的方法，设计量身定制的功能化磁铁矿纳米颗粒，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项目，但我们的目标是开发一个基于模型的搜索策略，以识别合适的成分和结构，作为合成的指导。在与实验伙伴的合作下，这将最终使通过磁萃取去除水中重金属成为可能。为了实现这一目标，我们建立了最近建立的去除水中油污的概念，该概念利用超顺磁性纳米颗粒，这些纳米颗粒由n-烷基膦酸自组装单层（sam）功能化。虽然碳氢化合物与此类SAMs的烷基链的结合是由简单的疏水分离机制驱动的，但为了有效地结合和去除水中的重金属污染物，需要精心选择具有定制螯合残基的SAMs。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.