3D Printed Functional and Biological Materials on Moving Freeform Surfaces

Zhijie Zhu; Shuang Zhuang Guo; Tessa Hirdler; Cindy Eide; Xiaoxiao Fan; Jakub Tolar; Michael C. McAlpine

doi:10.1002/adma.201707495

3D Printed Functional and Biological Materials on Moving Freeform Surfaces

Zhijie Zhu, Shuang Zhuang Guo, Tessa Hirdler, Cindy Eide, Xiaoxiao Fan, Jakub Tolar, Michael C. McAlpine

Research output: Contribution to journal › Article › peer-review

146 Scopus citations

Abstract

Conventional 3D printing technologies typically rely on open-loop, calibrate-then-print operation procedures. An alternative approach is adaptive 3D printing, which is a closed-loop method that combines real-time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick-and-placing of surface-mounted electronic components yields functional electronic devices on a free-moving human hand. Using this same approach, cell-laden hydrogels are also printed on live mice, creating a model for future studies of wound-healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.

Original language	English (US)
Article number	1707495
Journal	Advanced Materials
Volume	30
Issue number	23
DOIs	https://doi.org/10.1002/adma.201707495
State	Published - Jun 6 2018

Bibliographical note

Funding Information:
M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017–18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation.

Funding Information:
M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017?18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation.

Publisher Copyright:
© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Keywords

3D printing
bioprinting
feedback control
robotics
wireless electronics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Publisher link

10.1002/adma.201707495

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310159

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@article{651d4e8eac4941448eb95dbaf10e59df,

title = "3D Printed Functional and Biological Materials on Moving Freeform Surfaces",

abstract = "Conventional 3D printing technologies typically rely on open-loop, calibrate-then-print operation procedures. An alternative approach is adaptive 3D printing, which is a closed-loop method that combines real-time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick-and-placing of surface-mounted electronic components yields functional electronic devices on a free-moving human hand. Using this same approach, cell-laden hydrogels are also printed on live mice, creating a model for future studies of wound-healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.",

keywords = "3D printing, bioprinting, feedback control, robotics, wireless electronics",

author = "Zhijie Zhu and Guo, {Shuang Zhuang} and Tessa Hirdler and Cindy Eide and Xiaoxiao Fan and Jakub Tolar and McAlpine, {Michael C.}",

note = "Funding Information: M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017–18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation. Funding Information: M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017?18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation. Publisher Copyright: {\textcopyright} 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim",

year = "2018",

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doi = "10.1002/adma.201707495",

language = "English (US)",

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AU - Zhu, Zhijie

AU - Guo, Shuang Zhuang

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AU - Eide, Cindy

AU - Fan, Xiaoxiao

AU - Tolar, Jakub

AU - McAlpine, Michael C.

N1 - Funding Information: M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017–18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation. Funding Information: M.C.M. acknowledges the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health (Award No. 1DP2EB020537) and Regenerative Medicine Minnesota (Award No. RMM 102516 006). J.T. acknowledges the National Institutes of Health (Award No. R01AR063070). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Z.Z. acknowledges the graduate school of the University of Minnesota (2017?18 Interdisciplinary Doctoral Fellowship). The authors thank R. Su for help with profilometry measurements, Prof. S. J. Koester, Y. Zhang, and S. K. Chaganti for help with characterization of the inductive coils, Prof. H. S. Park for valuable suggestions in the development of the visual tracking system, D. Joung for help with characterization of the moisture sensors, and R. T. McElmurry for assistance with the mouse experiments. The authors also thank K. Qiu and N. Carter for their valuable comments and suggestions during the manuscript preparation. Publisher Copyright: © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

PY - 2018/6/6

Y1 - 2018/6/6

N2 - Conventional 3D printing technologies typically rely on open-loop, calibrate-then-print operation procedures. An alternative approach is adaptive 3D printing, which is a closed-loop method that combines real-time feedback control and direct ink writing of functional materials in order to fabricate devices on moving freeform surfaces. Here, it is demonstrated that the changes of states in the 3D printing workspace in terms of the geometries and motions of target surfaces can be perceived by an integrated robotic system aided by computer vision. A hybrid fabrication procedure combining 3D printing of electrical connects with automatic pick-and-placing of surface-mounted electronic components yields functional electronic devices on a free-moving human hand. Using this same approach, cell-laden hydrogels are also printed on live mice, creating a model for future studies of wound-healing diseases. This adaptive 3D printing method may lead to new forms of smart manufacturing technologies for directly printed wearable devices on the body and for advanced medical treatments.

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KW - wireless electronics

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3D Printed Functional and Biological Materials on Moving Freeform Surfaces

Abstract

Bibliographical note

Keywords

UN SDGs

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3D Printed Functional and Biological Materials on Moving Freeform Surfaces

Abstract

Bibliographical note

Keywords

UN SDGs

Publisher link

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Supporting data for "3D Printed Functional and Biological Materials on Moving Freeform Surfaces"

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