Collaborative Research: EAGER: Designing Nanomaterials to Reveal the Mechanism of Single Nanoparticle Photoemission Intermittency

在这个由化学系高分子、超分子和纳米化学计划资助的合作项目中，芝加哥伊利诺伊大学的Preston Snee、威廉与玛丽学院的Kristin Wustholz和普林斯顿大学的Haw Yang试图解开量子点闪烁这个由来已久的谜团。量子点是纳米尺寸的半导体颗粒，具有在各种技术中的应用潜力，包括节能显示器、低成本太阳能电池，以及作为生物医学研究工具。尽管这些点是荧光的，但单个粒子在随机关闭和打开时并不均匀发射。这种“眨眼”现象仍然是一个需要解释的挑战，这种对量子点技术缺乏深入了解限制了量子点技术的实际发展和应用。Snee、Wustholz和Yang的团队结合了化学合成、高级成像和统计分析方面的专业知识，正在评估各种量子点样品的闪烁行为，这些样品的表面结构已经使用合成化学进行了系统的变化。从事这个项目的研究生和本科生研究人员将在实验和计算化学方面获得广泛的经验。合作的研究小组还参与了公共宣传和开发免费(在线)物理化学教科书。这个由美国国家科学基金会资助的项目的结果正被适当地纳入教科书和推广活动中。量子点闪烁现象通常使用幂定律概率统计来描述发射的“关”和“开”的时间尺度；然而，对于这种行为没有直接的物理解释。这个热切的提议的中心假设是，量子点闪烁本质上是光生激子与表面陷阱态相互作用的结果，发射概率分布函数反映了陷阱势垒激活能的分布。这个模型的一般泛函形式归因于Alberg(1985)，他试图解释半导体表面和吸附分子之间的电子转移。与幂函数不同，阿尔贝里模型预测的是对数正态函数。此外，Snee小组最近证明，通过操纵表面化学，量子点可以表现出对数正态闪烁。这个急切的提议的第二个假设是：1)在现有的大量实验工作中报告的明显的幂定律依赖是不受控制的表面化学作用的结果，以及关于如何在时间上将光子计数“入库”的不正确假设的结果，以及2)缺陷位置与分子氧相互作用，并且这种相互作用导致的行为是对数正态分布的离散和，看起来几乎与幂规律分布相同。这些假说正在通过量子点合成、单粒子成像和光子计数实验进行验证。对眨眼统计数据的分析利用了最大似然估计，它解决了先前对眨眼数据进行任意分组可能导致错误结论的问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

In this collaborative EAGER project funded by the Macromolecular, Supramolecular and Nanochemistry Program in the Chemistry Division, Preston Snee of the University of Illinois at Chicago, Kristin Wustholz of the College of William and Mary, and Haw Yang of Princeton University seek to resolve the longstanding mystery of quantum dot blinking. Quantum dots are nanometer size semiconductor particles that have potential for applications in a variety of technologies, including energy-efficient displays, low-cost solar cells, and as biomedical research tools. Although these dots are fluorescent, single particles do not emit uniformly as they turn off and on randomly. This “blinking” phenomenon remains a challenge to explain, and this lack of a deep understanding limits the practical development and application of quantum-dot technology. The team of Snee, Wustholz and Yang combines expertise in chemical synthesis, advanced imaging, and statistical analysis, and is evaluating blinking behavior of various quantum-dot samples whose surface structures have been systematically varied using synthetic chemistry. The graduate and undergraduate researchers working on this project will gain a wide range of experience in experimental and computational chemistry. The collaborating research groups are also engaging in public outreach and the development of a free (online) physical chemistry textbook. The results of this NSF supported project are being incorporated into the textbook and outreach activities where appropriate.The quantum dot blinking phenomenon is generally described using power-law probability statistics to describe the emission "off" and "on" timescales; however, there is no straightforward physical explanation for this behavior. The central hypothesis of this EAGER proposal is that quantum-dot blinking is essentially the result of interactions of photo-generated excitons with the surface trap states, and that the emission probability distribution function reflects a distribution of trap barrier activation energies. The general functional form of this model is attributed to Albery (1985), who sought to explain electron transfer between semiconductor surfaces and adsorbed molecules. In contrast to the power-law function, the Albery model predicts a lognormal function. Furthermore, the Snee group recently demonstrated that quantum dots can exhibit lognormal blinking by manipulating the surface chemistry. Secondary hypotheses of this EAGER proposal are that 1) the apparent power-law dependence reported in the large body of existing experimental works is the result of uncontrolled surface chemistries and improper assumptions regarding how the photon counts should be "binned" in time, and 2) the defect sites interact with molecular oxygen, and that this interaction results in behavior that is a discrete sum of lognormal distributions that appear nearly identical to a power-law distribution. These hypotheses are being examined through combined quantum-dot synthesis, single particle imaging, and photon counting experiments. The analysis of blinking statistics utilizes maximum likelihood estimation, which addresses previous problems with arbitrary binning of blinking data that can lead to erroneous conclusions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.