CAREER: Revealing the Atomistic Fundamentals of Probabilistic Strength Distributions in Nanomaterials via High-Throughput Experimentation

该学院早期职业发展(CALEAR)奖将支持有助于可靠设计纳米结构设备的研究，这些设备在可穿戴医疗设备、下一代电子产品以及坚固和轻质材料中具有广泛应用。纳米材料是这些技术的推动者，因为它们具有承受高强度和变形的能力。然而，由于诸如制造条件和缺陷(例如，空隙和裂缝)引起的早期故障等不希望的行为，该容量可能是高度可变的。对这种变异性有明确的和统计上有意义的测量，建立模型的数学工具，并了解控制它的潜在因素，是本研究项目的目标。所产生的知识将能够通过解释和预测这种可变性，同时利用纳米材料的杰出特性来创建可靠的设计。综合教育计划包括通过对科学现象的概率描述来加强现有课程，通过辅导在高中生中推广机械工程，通过动手实验和实地考察的讲座，以及对代表不足的少数民族学生的全年指导。威布尔分布传统上被用来描述材料强度的统计性质，但它的基本假设在低亚微米到纳米尺度上是不相容的。因此，微纳结构器件的可靠设计是一个关键问题。这项研究的目的是利用高通量测试来研究纳米材料和结构的概率强度分布，以产生用于评估的具有统计学意义的数据，并提供新的假设，为更准确的概率强度理论奠定基础。结合自组装和图案化技术以及纳米机械测试，将从数百个纳米样品(如纳米线和二维材料(如石墨烯))中获得强度数据。与各种技术(例如，电子显微镜和拉曼光谱)的互补表征将被用来理解原子缺陷对强度统计的影响。现有和新的概率强度理论将根据实验数据进行评估，以确保预测的准确性。该奖项反映了NSF的法定使命，并已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。

This Faculty Early Career Development (CAREER) award will support research that contributes to the reliable design of nanostructured devices with broad applications in wearable medical equipment, next-generation electronics, and strong and lightweight materials. Nanomaterials are enablers of these technologies owing to their capacity to withstand high forces and deformations. This capacity, however, can be highly variable due to unwanted behaviors such as early failures arising from manufacturing conditions and defects, e.g., voids and cracks. Having clear and statistically significant measurements of this variability, mathematical tools to model it, and understanding the underlying factors that control it, are the goals of this research project. The generated knowledge will enable the creation of reliable designs, by accounting for and predicting this variability, while leveraging the outstanding properties of nanomaterials. The integrated education plan includes enhancement of existing curriculum with probabilistic descriptions of scientific phenomena, promotion of mechanical engineering among high school students through tutoring, lectures with hands-on experiments and field trips, and year-round mentoring of underrepresented minority students. Weibull’s distribution has traditionally been used to describe the statistical nature of strength in materials, but its foundational assumptions are incompatible at low submicron to nanometer length scale. Thus, it is a critical issue for the reliable design of micro- and nano-structured devices. The objective of this research is to investigate the probabilistic strength distribution of nanoscale materials and structures using high throughput testing to generate statistically significant data for evaluation and to offer new postulates that would form the bases of more accurate probabilistic strength theories. Merging self-assembly and patterning techniques and nanomechanical testing, strength data will be obtained from hundreds of nano-specimens such as nanowires and two-dimensional materials (e.g., graphene). Complementary characterization with various techniques (e.g., electron microscopy and Raman spectroscopy) will be used to understand the effect of atomistic defects on strength statistics. Existing and new probabilistic strength theories will be assessed against the experimental data for predictive accuracy.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.