editor's blog
Subscribe Now

Connecting CNTs to Metal

One of the things about CNTs acting as transistors is that the current flowing through them has to get into and out of the CNT from some other substance – typically metal. That junction, as it turns out, can have significant resistance. According to a paper done by a team from Georgia Tech and MIT (Songkil Kim et al), for a single-walled CNT (SWCNT) to connect to metal, there’s a quantum limit of around 65 kΩ.

Multi-walled CNTs (MWCNTs) can provide much lower-resistance connections, but how low depends on how you do it. Sputtering or evaporation only gets you to 3-4 kΩ best case, with no contamination. You can get as low as 700 Ω using TEM-AFM and nano-manipulation + joule heating, but this isn’t a viable commercial process.

The team used E-beam-induced deposition (EBID), which is essentially a localized CVD, where the gas is decomposed with great control using an electron beam. The overall process consists of first graphitizing amorphous carbon and then forming the connections.

Annealing amorphous carbon into graphite proved something of a challenge. They tried using a current to create joule heating, but it was tough to control: as the annealing progressed, the resistance went down, driving up the current and leading to runaway that could cause damage. So they went to an oven instead. They had to keep the temperature at 350 °C, the temperature at which graphitization starts, to keep the CNTs from oxidizing at higher temperatures.

In order to connect the multiple walls that were formed to metal, they directed the e-beam near the connection point. At first they aimed slightly short of the connection, using the backscatter to connect the inner walls – kind of like a basketball layup. Then they focused directly on the connection to finish it up.

This was followed up by an anneal.

The results were as follows:

  • Before making the contact, resistance was in the GΩ range.
  • If only the outer wall was connected, they got a 3.8-kΩ connection.
  • The EBID process alone brought the resistance from GΩ to 300 kΩ.
  • A 10-minute anneal at 350 °C brought the resistance down to 1.4 kΩ.
  • A further 20-25 minutes of annealing brought the resistance all the way down to 116 Ω.

Note that, to the best of my knowledge, this process was not used by the team that created the first CNT sub-systems recently reported at ISSCC.

You can find out more details in the published paper, but note that it’s behind a paywall.

Leave a Reply

featured blogs
Oct 23, 2020
Processing a component onto a PCB used to be fairly straightforward. Through hole products, a single or double row surface mount with a larger center-line rarely offer unique challenges obtaining a proper solder joint. However, as electronics continue to get smaller and conne...
Oct 23, 2020
[From the last episode: We noted that some inventions, like in-memory compute, aren'€™t intuitive, being driven instead by the math.] We have one more addition to add to our in-memory compute system. Remember that, when we use a regular memory, what goes in is an address '...
Oct 23, 2020
Any suggestions for a 4x4 keypad in which the keys aren'€™t wobbly and you don'€™t have to strike a key dead center for it to make contact?...
Oct 23, 2020
At 11:10am Korean time this morning, Cadence's Elias Fallon delivered one of the keynotes at ISOCC (International System On Chip Conference). It was titled EDA and Machine Learning: The Next Leap... [[ Click on the title to access the full blog on the Cadence Community ...

featured video

Demo: Inuitive NU4000 SoC with ARC EV Processor Running SLAM and CNN

Sponsored by Synopsys

Autonomous vehicles, robotics, augmented and virtual reality all require simultaneous localization and mapping (SLAM) to build a map of the surroundings. Combining SLAM with a neural network engine adds intelligence, allowing the system to identify objects and make decisions. In this demo, Synopsys ARC EV processor’s vision engine (VPU) accelerates KudanSLAM algorithms by up to 40% while running object detection on its CNN engine.

Click here for more information about DesignWare ARC EV Processors for Embedded Vision

featured paper

An engineer’s guide to autonomous and collaborative industrial robots

Sponsored by Texas Instruments

As robots are becoming more commonplace in factories, it is important that they become more intelligent, autonomous, safer and efficient. All of this is enabled with precise motor control, advanced sensing technologies and processing at the edge, all with robust real-time communication. In our e-book, an engineer’s guide to industrial robots, we take an in-depth look at the key technologies used in various robotic applications.

Click here to download the e-book

featured chalk talk

Using the Graphical PMSM FOC Component in Harmony3

Sponsored by Microchip and Mouser Electronics

Developing embedded software, and particularly configuring your embedded system can be a major pain for development engineers. Getting all the drivers, middleware, and libraries you need set up and in the right place and working is a constant source of frustration. In this episode of Chak Talk, Amelia Dalton chats with Brett Novak of Microchip about Microchip’s MPLAB Harmony 3, with the MPLAB Harmony Configurator - an embedded development framework with a drag-and-drop GUI that makes configuration a snap.

Click here for more information about Microchip Technology MPLAB® X Integrated Development Environment (IDE)