The black box opened: Non-invasive observation of nanoparticle transport in rock pore systems

全世界约有20亿人使用地下水。因此，我们必须开发工具来保护这一宝贵的资源免受污染。这项工作的一个关键工具是为所关注的污染物建立一个可靠的迁移模型。没有这一点，我们就无法预测污染物在含水层中的移动，而这对于风险评估和补救战略的设计至关重要。人造纳米颗粒对这一资源构成了一种新的、知之甚少的威胁，越来越多的纳米颗粒被发现具有毒性。这是特别值得关注的，因为全球对纳米颗粒的需求由于其在广泛的商业应用中的使用而持续增长。问题是，大规模生产和使用制造的纳米颗粒将不可避免地导致释放到地下水中。此外，制造的纳米颗粒也被设计用于一系列有机和无机污染物的原位地下水修复。然而，这些纳米颗粒的有效输送需要能够预测它们在含水层和污染区域内的运动，然而，关键的是，由于当前运输模型的重大局限性，我们目前无法可靠地预测纳米颗粒的运输。到目前为止，大多数纳米颗粒传输模型已经开发使用的数据从列包含玻璃珠或砂，其中纳米颗粒被注入在一端和纳米颗粒的突破在另一端进行测量。就目前而言，基于这些数据的模型往往无法预测纳米颗粒的传输。这是因为我们必须使用穿透曲线来推断柱内发生的传输过程，而不是实际看到它们的作用。该专栏仍然是一个难以捉摸的黑匣子。要打开这个黑盒子，我们必须能够看到柱子的内部，并对其中纳米粒子的运动进行成像。 在这里，我们将使用磁共振成像（MRI）和磁化率测量（MSM）的新组合来实现这一目标。MRI以其在医院环境中的使用而闻名，在医院环境中，它以非侵入性的方式对患者进行体内成像，患者不会受到分析的伤害。同样的技术也可以用来在多孔介质柱内部成像。此外，当我们使用标记有顺磁性标签的纳米颗粒时，分子很容易通过MRI可见。这项技术已经应用于临床研究，例如，标记的纳米颗粒用于成像药物输送。通过使用MRI成像纳米颗粒运输，我们将能够创建纳米颗粒通过多孔介质迁移的高分辨率电影。有了这个大大增强的数据集，我们将开发出更强大的纳米颗粒传输模型。虽然MRI通过生成高空间和时间分辨率的传输数据集为我们提供了相当大的优势，但它在含有高浓度顺磁性杂质（如Fe或Mn）的岩石上并不起作用。对于这些岩石，我们将使用磁化率测量（MSM）。事实上，这是MSM的一个新应用，MSM传统上用于检查岩石中的孔隙度和磁组构的排列。这种技术并没有给我们提供MRI的详细空间分辨率，但它确实提供了关于纳米颗粒浓度和纳米颗粒羽流在多孔介质中迁移时的形状的基本数据。这些数据将使我们能够测试使用MRI数据集开发的增强模型是否适用于MRI不兼容的岩石。通过这种双管齐下的方法，我们能够在更广泛的岩石类型上测试我们的增强模型。在本研究结束时，我们的目标是提供更强大和可靠的纳米颗粒传输模型，这是纳米颗粒风险评估和修复应用中靶向纳米颗粒传输技术设计所迫切需要的。

Groundwater is used by approximately 2 billion people worldwide. It is thus imperative that we develop the tools to protect this valuable resource from pollutants. A key tool in this endeavour is a reliable transport model for the pollutant of concern. Without this, we cannot predict the movement of the pollutant through the aquifer, which is essential for risk assessment and the design of remediation strategies. Manufactured nanoparticles present a new and poorly understood threat to this resource, with increasing numbers of nanoparticles found to exhibit toxicity. This is of particular concern as the global demand for nanoparticles continues to grow due to their use in a wide range of commercial applications. Problematically, large scale production and use of manufactured nanoparticles will inevitably lead to release into groundwater. In addition, manufactured nanoparticles are also being designed for in situ groundwater remediation of a range of both organic and inorganic pollutants. Effective delivery of these nanoparticles, however, requires the ability to predict their movement within the aquifer and contaminated zone.Critically, however, we are at present unable to predict reliably nanoparticle transport due to significant limitations in current transport models. To date, most nanoparticle transport models have been developed using data from columns containing glass beads or sand, where nanoparticles are injected at one end and the breakthrough of nanoparticles at the other is measured. As it stands, models based on these data all too often fail to predict nanoparticle transport. This is because we must use the breakthrough curves to infer the transport processes which occur inside the column, rather than actually seeing them in action. The column remains an elusive black box. To open this black box, we must be able to look inside the column and image the movement of nanoparticles within. Here, we will achieve this using a novel combination of magnetic resonance imaging (MRI) and magnetic susceptibility measurements (MSM). MRI is most renowned for its use in hospital settings, where it is used to image inside patients in a non-invasive manner, the patient unharmed by analysis. This same technology can be used to image inside the columns of porous media. Moreover, when we use nanoparticles that are labelled with a paramagnetic tag, the molecule becomes easily visible with MRI. This technology is already applied in clinical research, where, for example, tagged nanoparticles are used to image drug delivery.By imaging nanoparticle transport with MRI, we will be able to create high resolution movies of nanoparticle migration through the porous media. With this dramatically enhanced dataset, we will develop far more robust models of nanoparticle transport. While MRI affords us considerable advantage by generating high spatial and temporal resolution transport datasets, it does not work so well on rocks which contain high concentrations of paramagnetic impurities, such as Fe or Mn. For these rocks, we will use magnetic susceptibility measurements (MSM). Indeed, this is a novel application of MSM, which is traditionally used to examine porosity and the alignment of magnetic fabric in rocks. This technique does not give us the detailed spatial resolution of MRI, but it does provide essential data on nanoparticle concentration and the shape of the nanoparticle plume as it migrates through the porous media. These data will enable us to test if the enhanced models developed using MRI datasets are applicable to MRI-incompatible rock. Using this 2-pronged approach we are able to test our enhanced models on a much wider range of rock types.By the end of this research, we aim to deliver far more robust and reliable nanoparticle transport models which are sorely needed for nanoparticle risk assessment and in the design of techniques for targeting nanoparticle delivery in remediation applications.