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1. Tension Control in Roll-to-Roll Mechanical Peeling for 2D Material Transfer and Transfer Printing

   Zhao, Q. ( December 2021 , 2021 International Conference on Micro- and Nano-devices Enabled by R2R Manufacturing)

   Sreenivasan, S.V. (Ed.)

   A major challenge of the large-scale application of two-dimensional (2D) materials is the scaling up of the process for its growth and transfer. Mechanical peeling has been demonstrated to be a promising method for transferring graphene in a fast and environmentally friendly manner. However, efforts in scaling up the process have been lacking. Performing mechanical peeling using a roll-to-roll (R2R) system could significantly increase the throughput of graphene transfer. Such a R2R process does not exist in industry. In this paper a novel R2R mechanical peeling system that has both speed and tension control capabilities is presented. Controllers that control the peeling tensions on both sides of the peeling front are developed based on a tension dynamics model. Both controllers contain a feedback and a feedforward term to account for large steady-state error. The control performance is validated using both experiments and simulation, demonstrating that the R2R mechanical peeling technique can be a viable method for dry transfer of 2D materials in a high-throughput industrial setting. 

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2. MODEL BASED REPETITIVE CONTROL FOR PEELING FRONT GEOMETRY CONTROL IN A ROLL-TO-ROLL PEELING PROCESS

   Zhao, Qishen ; Martin, Christopher ; Chen, Dongmei ; Li, Wei ( July 2022 , Proceedings of the 2022 International Symposium on Flexible Automation)

   Roll-to-roll(R2R) peeling is an innovative method that transfers flexible electronics and 2D materials from the flexible substrate where they are grown to the end-use substrate. This process enables the full potential of R2R 2D material fabrication methods in a continuous, high-throughput, and environment friendly manner. During the R2R peeling process, the device patterning causes periodic changes in the adhesion energy between the device and substrate. This periodic disturbance can degrade the quality of the final product if not properly controlled. Current control methods used for the R2R peeling process do not explicitly reject the periodic disturbance. It is therefore desirable to develop a controller that is capable of performing periodic disturbance rejection. This paper presents a model-based repetitive controller that integrates a frequency estimation of the disturbance into the R2R peeling control to maintain the optimal peeling process performance. A linear estimator using system identification techniques is employed. The simulation results show that the developed controller achieves better R2R process performance when compared to a conventional model-based controller. 

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3. The Line Speed Effect in Roll-to-Roll Dry Transfer of Chemical Vapor Deposition Graphene,

   Hong, N. ( December 2021 , 2021 International Conference on Micro- and Nano-devices Enabled by R2R Manufacturing)

   Sreenivasan, S.V. (Ed.)

   A roll-to-roll (R2R) technique is especially desirable for transfer of chemical vapor deposition (CVD) graphene towards high-speed, low-cost, renewable, and environmentally friendly manufacturing of graphene-based electronic devices, such as flexible touchscreens, field effect transistors and organic solar cells. A R2R graphene dry transfer system is recently developed. Monolayer graphene is transferred from a copper growth substrate to a polymer backing layer by mechanical peeling. In this work, we present an experimental study to examine the effects of line speed of the mechanical peeling process on the transferred graphene quality. It is shown that the effect of line speed is not monotonic, and an optimal speed exists to yield the highest and most consistent electrical conductivity of transferred graphene among the process conditions studied. This study provides understanding of process parameter effects and demonstrates the potential of the R2R dry transfer process for large-scale CVD graphene toward industrial applications. 

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4. Data-Driven Model Predictive Control for Roll-to-Roll Process Register Error

   https://doi.org/10.1115/IAM2022-96840  

   Shah, Karan ; He, Anqi ; Wang, Zifeng ; Du, Xian ; Jin, Xiaoning ( October 2022 , Proceedings of the 2022 International Additive Manufacturing Conference. 2022 International Additive Manufacturing Conference. Lisbon, Portugal.)

   Roll-to-Roll (R2R) printing techniques are promising for high-volume continuous production of substrate-based products, as opposed to sheet-to-sheet (S2S) approach suited for low-volume work. However, meeting the tight alignment tolerance requirements of additive multi-layer printed electronics specified by device resolution that is usually at micrometer scale has become a major challenge in R2R flexible electronics printing, preventing the fabrication technology from being transferred from conventional S2S to high-speed R2R production. Print registration in a R2R process is to align successive print patterns on the flexible substrate and to ensure quality printed devices through effective control of various process variables. Conventional model-based control methods require an accurate web-handling dynamic model and real-time tension measurements to ensure control laws can be faithfully derived. For complex multistage R2R systems, physics-based state-space models are difficult to derive, and real-time tension measurements are not always acquirable. In this paper, we present a novel data-driven model predictive control (DD-MPC) method to minimize the multistage register errors effectively. We show that the DD-MPC can handle multi-input and multi-output systems and obtain the plant model from sensor data via an Eigensystem Realization Algorithm (ERA) and Observer Kalman filter identification (OKID) system identification method. In addition, the proposed control scheme works for systems with partially measurable system states.

    

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5. Roll‐to‐Roll Dry Transfer of Large‐Scale Graphene

   https://doi.org/10.1002/adma.202106615  

   Hong, Nan ; Kireev, Dmitry ; Zhao, Qishen ; Chen, Dongmei ; Akinwande, Deji ; Li, Wei ( November 2021 , Advanced Materials)

   A major challenge for graphene applications is the lack of mass production technology for large‐scale and high‐quality graphene growth and transfer. Here, a roll‐to‐roll (R2R) dry transfer process for large‐scale graphene grown by chemical vapor deposition is reported. The process is fast, controllable, and environmentally benign. It avoids chemical contamination and allows the reuse of graphene growth substrates. By controlling tension and speed of the R2R dry transfer process, the electrical sheet resistance is achieved as 9.5 kΩ sq⁻¹, the lowest ever reported among R2R dry transferred graphene samples. The R2R dry transferred samples are used to fabricate graphene‐based field‐effect transistors (GFETs) on polymer. It is demonstrated that these flexible GFETs feature a near‐zero doping level and a gate leakage current one to two orders of magnitude lower than those fabricated using wet‐chemical etched graphene samples. The scalability and uniformity of the R2R dry transferred graphene is further demonstrated by successfully transferring a 3 × 3 in²sample and measuring its field‐effect mobility with 36 millimeter‐scaled GFETs evenly spaced on the sample. The field‐effect mobility of the R2R dry transferred graphene is determined to be 205 ± 36 cm² V⁻¹.

    

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