Automated Computer Vision-Enabled Manufacturing of Nanowire Devices.

ABSTRACT: We present a high-throughput method for identifying and characterizing individual nanowires and for automatically designing electrode patterns with high alignment accuracy. Central to our method is an optimized machine-readable, lithographically processable, and multi-scale fiducial marker system─dubbed LithoTag─which provides nanostructure position determination at the nanometer scale. A grid of uniquely defined LithoTag markers patterned across a substrate enables image alignment and mapping in 100% of a set of >9000 scanning electron microscopy (SEM) images (>7 gigapixels). Combining this automated SEM imaging with a computer vision algorithm yields location and property data for individual nanowires. Starting with a random arrangement of individual InAs nanowires with diameters of 30 ±

SUBMITTER: Potocnik T 

PROVIDER: S-EPMC9706672 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature