Improving Stability of Roll-to-Roll (R2R) Gravure-Printed Carbon Nanotube-Based Thin Film Transistors via R2R Plasma-Enhanced Chemical Vapor-Deposited Silicon Nitride

Hybrid Device Fabrication Using Roll-to-Roll Printing for Personal Environmental Monitoring

Roll-to-roll (R2R) printing methods are well known as additive, cost-effective, and ecologically friendly mass-production methods for processing functional materials and fabricating devices. However, implementing R2R printing to fabricate sophisticated devices is challenging because of the efficiency of material processing, the alignment, and the vulnerability of the polymeric substrate during printing. Therefore, this study proposes the fabrication process of a hybrid device to solve the problems. The device was created so that four layers, composed of polymer insulating layers and conductive circuit layers, are entirely screen-printed layer by layer onto a roll of polyethylene terephthalate (PET) film to produce the circuit. Registration control methods were presented to deal with the PET substrate during printing, and then solid-state components and sensors were assembled and soldered to the printed circuits of the completed devices. In this way, the quality of the devices could be ensured, and the devices could be massively used for specific purposes. Specifically, a hybrid device for personal environmental monitoring was fabricated in this study. The importance of environmental challenges to human welfare and sustainable development is growing. As a result, environmental monitoring is essential to protect public health and serve as a basis for policymaking. In addition to the fabrication of the monitoring devices, a whole monitoring system was also developed to collect and process the data. Here, the monitored data from the fabricated device were personally collected via a mobile phone and uploaded to a cloud server for additional processing. The information could then be utilized for local or global monitoring purposes, moving one step toward creating tools for big data analysis and forecasting. The successful deployment of this system could be a foundation for creating and developing systems for other prospective uses.

Advanced Algorithm for Reliable Quantification of the Geometry and Printability of Printed Patterns

In nanoparticle-based printed electronic devices, the printability of the patterns constituting the device are crucial factors. Although many studies have investigated the printability of patterns, only a few have analyzed and established international standards for measuring the dimensions and printability of shape patterns. This study introduces an advanced algorithm for accurate measurement of the geometry and printability of shape patterns to establish an international standard for pattern dimensions and printability. The algorithm involves three core concepts: extraction of edges of printed patterns and identification of pixel positions, identification of reference edges via the best-fitting of the shape pattern, and calculation of different pixel positions of edges related to reference edges. This method enables the measurement of the pattern geometry and printability, including edge waviness and widening, while considering all pixels comprising the edges of the patterns. The study results revealed that the rectangle and circle patterns exhibited an average widening of 3.55% and a maximum deviation of 1.58%, based on an average of 1662 data points. This indicates that the algorithm has potential applications in real-time pattern quality evaluation, process optimization using statistical or AI-based methods, and foundation of International Electrotechnical Commission standards for shape patterns.