Multimode Sensing for Roll-to-Roll Flexible
Electronics Print Process Control
Jingyang Yan1,2, Mehdi Riza1,2, Rui Ma2,3, Xian Du*1,2,4
Mechanical & Industrial Engineering Department 1
Center for Personalized Health Monitoring - Institute for Applied Life Sciences 2Electrical and Computer Engineering Department3
College of Information and Computer Sciences4
University of Massachusetts, Amherst
E-mail: xiandu@umass.edu

Microcontact printing holds the promise of large-scale, high rate surface micro-patterning.
We address the real time monitoring, metrology and control issues for the scale-up processusing a roll-to-roll (R2R) continuous printing method. The first key factor is precise web
handling, including high accuracy measurement and control of speed, tension, andregistration of the moving web in real time. The second key factor in scale-up is always theability to image the quality of the printing in real time to provide for feedback regulation of
the printing process to ensure pattern integrity.

Figure 1. (left) Experimental setup for vibration measurement and (right) comparison of the web
tension calculated using the proposed method and the tension measured by tension measuring rollwhen the web tension suddenly changes from 25N to 35N.

Web handling [1]: The tension in a moving web ultimately determines the efficacy of a R2R
printing process. Calculating web tension by measuring the out-of-plane vibration offers a
non-contacting and cost-effective method of tension measurement during the R2R process,which is suitable for situations where contact-based web tension measurement cannot beapplied. We developed a real-time learning-based prediction approach for prediction of webtension based on contactless sensing of out-of-plane web vibration and web moving speed.
We designed and tested a real-time frequency estimation algorithm based on Fourier series.
The real time performance of the proposed algorithm was tested on our lab R2R testbed(Figure 1), performance markers included accuracy, robustness and computation speed. The
experimental results show that the proposed method can predict the web tension with an errorof less than 10% for various setup of tension values and track the tension changes within one
analysis window of 50ms.

Pattern metrology [2]: Printing of Hexadecanethiol (HDT) on thin gold substrates is themost common form of microcontact printing (µCP) using self-assembled monolayers(SAMs). The ability to visualize the HDT-gold on a continuous moving web prior tosubsequent steps – such as etching – is necessary to achieve any acceptable in-process quality
control. We present a real-time imaging technique for inspecting the online print pattern in aroll-to-roll (R2R) process by condensation figures (CFs). The real-time desirable CFs areachieved through controlled consistent condensation of water vapor and a synchronousimaging process (Figures 2). The distribution of droplets of water recorded by high-speed
camera on an HDT-gold surface can be clustered and segmented for determining pre-etch
pattern locations and geometries, as well as print pattern evaluation (Figure 3). Our imaging
system can achieve pattern resolution up to 0.7 µm, web moving speed of 3 in/s, given a lowcost camera with the frame rate up to 1500 fps. We demonstrate that the method can bepromisingly used in combination with a pattern “truth table” for online quality monitoringand in-process control.

Figure 2. Experimental setup for imaging condensation.

Figure 3. Metrology of print pattern with clustering results for various web-moving speeds: (a) 0.3
In/s; (b) 1.5 in/s; (c) 3 in/s. Row 1 – single frame; row 2 – line pattern (yellow contour) recognizedfrom droplet clustering (circle for larger droplet and triangle for small droplet) of stitched images; row
3 – average width and standard deviation of hydrophilic pattern (gold) and pitch of print lines.

Acknowledgements:
This work is supported in part by the National Science Foundation (grant no.
CMMI1916866). Any opinions, findings and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of NationalScience Foundation.
Reference:
1. Jingyang Yan and Xian Du, “Real-time web tension prediction using web moving speed
and natural vibration frequency.” IEEE Transactions on Instrumentation andMeasurement, revision, 2019.
2. Xian Du, David Hardt, Brian Anthony, “Real time imaging of invisible micron-scalemonolayer patterns on a moving web using condensation figure." IEEE Transactions onIndustrial Electronics, DOI: 10.1109/TIE.2019.2914632, 2019.