Electronics

This portfolio includes carbon nanotube growth and processing methods relevant to nanotube manufacturing. 

Patterned Catalyst Techniques for Aligned Single-walled Carbon Nanotube Growth

Single-walled carbon nanotubes (SWNTs) feature exceptional electric properties (conductivity and semi-conductivity) that make them attractive for nano-electronics, optics, material applications and more. This SWNT growth technology yields a dense structure without degraded alignment by eliminating undesired interactions between the SWNT and catalysts on the growth surface. More specifically, a patterned catalyst is used to provide a template to direct SWNT growth, resulting in perfectly aligned high coverage SWNTS.

Benefits

• Higher density
• Large scale
• Higher quality 

Applications

• Patterned catalyst techniques are applicable for standard electronic devices that use thin film semiconductors, such as field effect transistors (FETs), sensors, thin-film transistors (TFTs). These devices can benefit from ability to deposit SWNT onto plastics and other unusual device substrates: steerable antenna arrays, flexible displays, etc.

Medium Scale Carbon Nanotube Thin Film Integrated Circuits on Flexible Plastic Substrates

This technology improves the performance and consistency of integrated circuits featuring semi-conductive carbon nanotube (CNT) transistors. Specifically, metallic conductive pathways in random nanotube networks are reduced using a medium scale carbon nanotube thin film. This process reduces these pathways by cutting fine lines into the carbon nanotube network while preserving its semiconducting properties.

Benefits

• Reduces purely metallic conductive pathways in a carbon nanotube network used to construct electronic circuits.
• Vastly improves carbon nanotube device consistency in production (yield).

Applications

• Primary application is integrated circuits for flexible substrate materials.

Using Nanoscale Thermocapillary Flows to Create Arrays of Purely Semiconducting Single-Walled Carbon Nanotubes

This carbon nanotube (CNT) purification technology facilitates scalable, damage-free separation of arrayed metallic and semi-conductive CNTs. Resulting CNT arrays may be large and feature high Ion/Ioff ratios, allowing for less power loss while powered off, faster switching times, and overall lower operating voltage. The invention improves CNT array quality by creating a temperature gradient to release metallic CNTs from the array matrix.

Benefits

• Less lost power while off
• Faster switching time
• Lower operating voltage

Semiconductor defect detection using Machine Learning

Dr. Goddard and Dr. Schwing have developed a machine learning technique which requires only few training images to detect and classify nano-scale anomalies in semiconductors and in noisy optical images. It is able to automate defect inspection in a 9nm semiconductor wafer with high accuracy and at a high speed in fabrication laboratories using visible light microscopy. This method is faster than atomic force microscopy and scanning electron microscopy, and is more sensitive than current optical microscopy. It can also be used for other applications such as dimension measurements and disease sample measurements.

Sanyogita Purandare, Jinlong Zhu, Renjie Zhou, Gabriel Popescu, Alexander Schwing, and Lynford L. Goddard, "Optical inspection of nanoscale structures using a novel machine learning based synthetic image generation algorithm," Opt. Express  27, 17743-17762 (2019)

Optical inspection of nanoscale structures using a novel machine learning based synthetic image generation algorithm. Sanyogita Purandare, Jinlong Zhu, Renjie Zhou, Gabriel Popescu, Alexander Schwing, Lynford L. GoddardOpt Express. 2019 Jun 24; 27(13): 17743–17762. doi: 10.1364/OE.27.017743