EAGER: Development of a Mechanistic Framework Correlating Quantum Dot Surface Chemistry and Subsurface Environmental Fate and Transport

[1505718] goldfarb, jillian。量子点（QD）表面涂层与生态表面之间的界面相互作用是这些材料的环境命运和运输的关键决定因素。然而，目前对这种相互作用发生的机制还没有基本的了解。因此，有必要使用一系列测试来检查和测试每种纳米材料，以预测其在地下的行为。这一建议将为理解量子点表面涂层及其亚表面反应之间的相互作用机制奠定基础。多元统计分析工具将用于分析数据，通过将量子点涂层的组成与影响纳米颗粒行为的环境因素联系起来，减少实验负担。通过为理解具有不同结构的量子点如何响应不同环境刺激奠定机制基础，该项目可能会将我们评估新兴纳米材料对环境影响的方法从测试-观察方法转变为预测-验证方法。长期目标是在计算和实验相结合的框架下评估人造纳米材料对环境的影响。这是一种与现有的彻底测试每一种新纳米材料的策略完全不同的方法，并且涉及到开发一种新的预测工具的创新方法。核/壳半导体量子点（QDs）是一种具有无限应用前景的非均质纳米材料，对人类健康和环境的潜在影响尚不清楚。随着量子点从专门的研究实验室转变为消费者和生物设备的组件，有必要了解它们如何在环境中相互作用、持续存在和降解。本研究的目的是建立一个实验框架，以从机制上理解量子点表面特征与地下环境的物理化学性质之间的关系，以及核/壳量子点的聚集、吸附和分配。这一目标将通过合成四种有机涂层组合（疏水相互作用或键合，与静电排斥或位阻配对）来实现。纳米粒子将被全面表征，以评估它们的尺寸，形态，单分散性，浓度，量子产率和光致发光，晶体结构，核壳原子的比例，以及涂层与颗粒的比例。为了发展这种机制的理解，将测量量子点与普通土壤胶体的团聚动力学，它们在辛醇和水之间的分配行为，以及它们在饱和多孔介质上的吸附，所有这些都是离子强度和pH的函数。使用多元统计分析的初始框架将能够建模和量化pH值与离子强度之间的关系，以及四种涂层可能性中的每种涂层的分配、团聚和吸附。

1505718Goldfarb, JillianThe interfacial interactions between quantum dots (QD) surface coatings and ecological surfaces are critical determinants of the environmental fate and transport of these materials. However, currently there is no foundational understanding of the mechanisms by which such interactions occur. Therefore it is necessary to examine and test every nanomaterial using a battery of tests to predict resulting subsurface behavior. This proposal will lay a foundation for a mechanistic understanding of the interplay between QD surface coatings and their subsurface reactions. Multivariate statistical analysis tools will be used to analyze data in a framework that reduces the experimental burden by correlating the composition of QD coatings with the environmental factors that influence nanoparticle behavior. By laying a mechanistic foundation for understanding of how QDs with varying structures respond to different environmental stimuli, the project may transform our approach to evaluating the environmental impacts of emerging nanomaterials from the test-and-observe approach to one of predict-and-verify. The long-term goal is to enable assessment of environmental impacts of manufactured nanomaterials in a combined computational and experimental framework. This is a radically different approach from the existing strategy of thoroughly test every new nanomaterial and involves an innovative methodology for developing a novel predictive tool.Core/shell semiconductor quantum dots (QDs) are heterogeneous nanomaterials with seemingly infinite applications and unknown potential effects on human health and the environment. As QDs transition from specialized research laboratories to components in consumer and biological devices, there is a need to develop an understanding of how they will interact, persist, and degrade in the environment. The objective of this proposal is to develop an experimental framework to enable a mechanistic understanding of the relationships between QD surface characteristics and the physico-chemical properties of the subsurface environment on the agglomeration, adsorption, and partitioning of core/shell QDs. This objective will be met by synthesizing QDs with four organic coating combinations (hydrophobic interactions or dative bonding, paired with electrostatic repulsions or steric hindrance). The nanoparticles will be fully characterized to assess their size, morphology, monodispersity, concentration, quantum yield and photoluminescence, crystalline structure, ratio of core and shell atoms, and ratio of coating to particle. To develop this mechanistic understanding, the agglomeration kinetics of QDs with common soil colloids, their partitioning behavior between octanol and water, and their adsorption to saturated porous media, all as a function of ionic strength and pH, will be measured. An initial framework using multivariate statistical analysis will enable the modeling and quantification of relationships between pH and ionic strength and the partitioning, agglomeration, and adsorption for each of the four coating possibilities.