Automatic assessment of nanostructure quality is essential for scale-up nanomanufacturing. In our previous work, we have developed a method to quantify nanostructure growth quality and detect structural defects through interaction analysis. However, because the method builds on complete feature measurement, its direct application to nanomanufacturing systems is severely constrained by nanostru…
Understanding nanostructure growth faces issues of limited data, lack of physical knowledge, and large process uncertainties. These issues result in modeling difficulty because a large pool of candidate models almost fit the data equally well. Through the Integrated Nanomanufacturing and Nanoinformatics (INN) strategy, we derive the process models from physical and statistical domains, respect…
Abstract The bottom-up fabrication of nanostructures can simultaneously face large uncertainties from experimental runs (R), physical understanding (P), and measurement (M). No systematic strategy has been reported to manage these three types of uncertainties, abbreviated as RPM, concurrently to achieve better understanding of nano fabrication processes. Previously, we developed cross-domain m…