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1. 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)

   Abstract 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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2. PLDI-Based Convexification for Roll-to-Roll Dry Transfer Control

   https://doi.org/10.1016/j.ifacol.2021.11.217  

   Martin, C.; Zhao, Q.; Bakshi, S.; Chen, D.; Li, W. (January 2021, IFAC-PapersOnLine)
3. Roll‐to‐Roll Compatible Topochemical Wetting Control for Metamaterial Printing

   https://doi.org/10.1002/adom.202302785  

   Donie, Yidenekachew J.; Ramamurthy, Maya; Chakraborty, Rohan D.; Francis, Lorraine F.; Frisbie, C. Daniel; Ferry, Vivian E. (January 2024, Advanced Optical Materials)

   Abstract The widespread utilization of metamaterials, despite their immense transformative potential, faces challenges regarding scalability in mass production. To address these limitations, an additive method that leverages liquid inks and selective wetting to produce scalable and cost‐effective metamaterials is presented. UV‐based imprinting lithography is utilized to fabricate surface energy‐modulated patterns, enabling precise solution patterning. This approach, unlike conventional UV‐based imprinting lithography, not only accurately produces the negative replica of the stamp topography during UV‐induced crosslinking but also transfers a hydrophobic layer onto the raised surfaces of the imprinted hydrophilic layer, resulting in 3D shapes with spatially modulated surface energy. In the second process step, a functional ink is dragged over the patterned substrate where it dewets to fill the hydrophilic recesses. This innovative process enables high‐speed metamaterial production, with ink deposition speeds up to 12 m min⁻¹. The method accommodates a wide range of inks, including metals, dielectrics, and semiconductors, providing meticulous control over vertical structures such as pattern thickness and hetero‐multilayer formation. Additionally, it offers flexibility in creating metamaterials on free‐standing ultra‐thin sheets, introducing desirable attributes like foldability and disposability. The effectiveness of this approach is validated through the fabrication and characterization of metallic metamaterials. 

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4. Friction isolated rotary system for high-precision roll-to-roll manufacturing

   https://doi.org/10.1016/j.precisioneng.2020.12.018  

   Kang, Dongwoo; Dong, Xin; Kim, Hyunchang; Park, Pyungwon; Okwudire, Chinedum E. (March 2021, Precision Engineering)

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5. 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.)

   Abstract 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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