دورية أكاديمية
Automated Computer Vision-Enabled Manufacturing of Nanowire Devices.
| العنوان: | Automated Computer Vision-Enabled Manufacturing of Nanowire Devices. |
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| المؤلفون: | Potočnik, Teja, Christopher, Peter J, Mouthaan, Ralf, Albrow-Owen, Tom, Burton, Oliver J, Jagadish, Chennupati, Tan, Hark Hoe, Wilkinson, Timothy D, Hofmann, Stephan, Joyce, Hannah J, Alexander-Webber, Jack A |
| بيانات النشر: | American Chemical Society (ACS) Department of Engineering ACS Nano |
| سنة النشر: | 2022 |
| المجموعة: | Apollo - University of Cambridge Repository |
| الوصف: | 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 ± 5 nm on a single chip, we automatically design and fabricate >200 single-nanowire devices. For >75% of devices, the positioning accuracy of the fabricated electrodes is within 2 pixels of the original microscopy image resolution. The presented LithoTag method enables automation of nanodevice processing and is agnostic to microscopy modality and nanostructure type. Such high-throughput experimental methodology coupled with data-extensive science can help overcome the characterization bottleneck and improve the yield of nanodevice fabrication, driving the development and applications of nanostructured materials. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://doi.org/10.17863/CAM.87937Test; https://www.repository.cam.ac.uk/handle/1810/341334Test |
| DOI: | 10.17863/CAM.88760 |
| الإتاحة: | https://doi.org/10.17863/CAM.88760Test https://doi.org/10.17863/CAM.87937Test https://www.repository.cam.ac.uk/handle/1810/341334Test |
| حقوق: | Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: | edsbas.B803514F |
| قاعدة البيانات: | BASE |
| DOI: | 10.17863/CAM.88760 |
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