[LAB Search] Carbon Nanotubes Enable 'Room-Temperature Processing'... Lowering Semiconductor Heat

Professor Kim Jongbaek's Team at Yonsei University Develops New Process
Reduces Chip Heat and Enhances Infrared Sensor Sensitivity

Professor Kim Jongbaek's research team from the Department of Mechanical Engineering at Yonsei University has developed a process to transfer carbon nanotubes, which could previously only be produced at high temperatures, to electronic devices at room temperature without causing any damage. This is significant because it maintains the advantageous properties of the material, such as excellent thermal and electrical conductivity, while laying the groundwork for practical applications in semiconductors and sensors.

Professor Kim Jongbaek's research team from the Department of Mechanical Engineering at Yonsei University developed a process to transfer carbon nanotubes, which could previously only be made at high temperatures, to electronic devices at room temperature without damage. Hyunjoon Han, a combined master's and doctoral student (from left), Professor Kim, and Kyuhyun Hwang, a combined master's and doctoral student, are taking a commemorative photo. Yonsei University

On March 27, Professor Kim's team announced that they had succeeded in transferring carbon nanotubes onto various substrates using a 'sublimation transfer' method that utilizes a thin layer of ice. In this process, a uniform ice layer is formed by condensing water vapor onto a cold substrate, the carbon nanotubes are then temporarily fixed onto the ice layer, and the ice is directly sublimated into gas.

Previously, the structure of the nanotubes would collapse or become entangled during the melting and evaporation phases of water. The research team avoided this problem by converting ice directly into gas without passing through a liquid phase. As a result, this method enabled the transfer of structures while maintaining their integrity, achieving yields of over 95% for patterns as small as 10 micrometers and up to large areas on the centimeter scale.

Carbon nanotubes are nanomaterials with excellent thermal and electrical conductivity and the ability to absorb almost all light. In particular, the vertically aligned 'forest' structure, which stands upright like a forest, can rapidly transfer heat and electricity in a single direction, making it advantageous for improving heat dissipation and sensor performance. However, because carbon nanotubes can only be grown at temperatures above 700 degrees Celsius, it has been difficult to directly integrate them with semiconductor processes or plastic-based electronic devices, which are fabricated at 200 to 450 degrees Celsius or lower.

The research team applied this technique as a thermal management material for semiconductors and confirmed improved performance. When used in smartphone processors, it reduced the temperature at hot spots by up to 4 degrees Celsius compared to conventional thermal pads. Even a slight decrease in chip temperature can prevent performance degradation and expand the stable operating range. This is especially promising for AI computing chips, where heat dissipation is a key factor limiting performance.

In addition, infrared sensors using the carbon nanotube structure as an absorption layer showed signal changes more than three times greater than conventional sensors. The transfer was also successful on thin films less than 1 micrometer thick without causing any damage.

Professor Kim stated, "The key point is that we have enabled direct application of nanomaterials that previously required high-temperature processes at room temperature," adding, "This will enable the implementation of new device structures in a variety of fields, including semiconductor thermal management."

The research team was inspired by the phenomenon of cold ice cream sticking to the tongue, focusing on the adhesive properties of ice to devise a method for transferring structures without adhesives or high-temperature, high-pressure processes. For industrial application, they identified several tasks: scaling up to large-area processes, reducing processing time, and verifying long-term reliability. They plan to further refine the technique so that it can be directly applied to semiconductor packaging and sensor manufacturing processes.

This content was produced with the assistance of AI translation services.