Developing Organic Semiconductor Crystals For Circuits, Displays, And Bioimplantable Sensors

A scanning electron microscopy image of a vertical tetraanaline organic semiconductor crystal. (Credit: Jessica Wang / UCLA)

Flexible electronic devices based on organic semiconductors are believed to be a high potential candidate for the next generation modern electronics. From wearable smart sensors to flexible displays, organic electronics have shown promising development in the last two decades.

Among different processing method, solution shearing is a high potential deposition method to fabricate organic electronics over a large area. In this method, the uniformity and crystallinity of the deposited organic thin film is very sensitive to the shearing speed. It can be expected that if the shearing speed is too fast, unwanted voids will present in the film and which will make the large-scale device integration very difficult. On the other hand, if the shearing speed is too slow, intensive multiple nucleations will present along the meniscus line and thus high grain boundary density will result.

These grain boundaries will unavoidable hurt the carrier transfer mobility while they are hopping from one grain to another. Furthermore, both of these two scenarios will significantly affect the repeatability of fabrication and overall uniformity of the organic devices especially for the in planar devices such as field effect transistors. In this work, we tried to address this issue by using the Marangoni-effect assisted bar coating method to deposit the C8-BTBT organic crystals. Compare with the traditional method with only single solvent, the dual solvent Marangoni-effect assisted bar coating approach can support five times faster shearing speed up to 1000 mm/s without hurting the quality of the organic thin film.

By carefully controlling the solvent composition and the temperature gradient in the solute, we can use the Marangoni-effect induced by the differences in surface tension to provide extra organic molecules to the meniscus line. This extra source of molecules allows us to shear the solution in a quicker way without causing the opening voids due to insufficient supply of the organic molecules. More importantly, the magnitude of such Marangoni-effect can be varied by carefully controlling the temperature gradient and composition of mixed solvents. As this effect is highly localized at the liquid, solid and air interface, the solute outside the meniscus line will not be affected. With the high shearing speed, we found the deposited organic crystals are actually under both compressive and tensile strain depending on their orientations.

We found that the stain up to 0.7% can be observed in the C8-BTBT crystals deposited under 1000 mm/s. These findings demonstrate the great potentials in modifying the crystallinity of these organic semiconductors which is holding together by the van der Waals force. It is believed that this method can be further utilized to adjust the carrier mobility and other electrical properties of the organic thin films.

It is believed that the compressive strain in the right direction can enhance the carrier transfer in between the organic molecules. Another interesting research direction is to perform another solution shearing onto the strained semiconductor and see whether will the intrinsic strain in the crystal be released. These investigations will help us to understand the strain forming and releasing mechanisms in the solution processed organic semiconductors, and how we can utilize it to modify the performance of the devices over a large area.

Our studies on other organic semiconductors are undergoing, we are targeting in coming up with an universal fabrication approach to manipulate the strain effect in the solution processed organic semiconductors.

This study, Marangoni-Effect-Assisted Bar-Coating Method for High-Quality Organic Crystals with Compressive and Tensile Strains was recently published in the journal Advanced Functional Materials.

More from Paddy Kwok Leung Chan

Prediction Of Engine Emissions Through Biologically-Inspired Models

The use of artificial neural networks and other types of prediction models...
Read More
Opinions expressed are solely the authors and do not express the views or opinions of Science Trends nor the author's institution.

Leave a Reply

Your email address will not be published. Required fields are marked *