In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling

Wang, Jenny

doi:10.2172/1572613

Title: In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling

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Abstract

Additive manufacturing (AM) of multi-material objects enables the design of complex 3D architectures such as printed electronics and devices. The ability to detect the composition of multi-material printed inks in real time is an emerging need for a wide range of manufacturing applications. This study demonstrates the feasibility of using an in situ sensor to locally measure the composition of inks as they are being printed to facilitate greater control over the resulting properties and functionality of printed materials. Dielectric properties of microscale embedded metal particles in a dielectric matrix are measured and characterized as a function of particle size, shape, volume percentage and frequency. Results show that particle shape has a much greater influence on impedance measurements than the particle size. Measurements are found to agree with calculations based on an anisotropic Maxwell-Garnett dielectric function model. The resulting data can be used to generate a calibration curve correlating metal loading with impedance or capacitance and thus applied as an in situ sensor for compositional measurements during extrusion-based AM.

Authors:

Wang, Jenny ^[1]

Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Publication Date:: Tue Oct 29 00:00:00 EDT 2019

Research Org.:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1572613

Report Number(s):: LLNL-TR-795625
996319

DOE Contract Number:: AC52-07NA27344

Resource Type:: Technical Report

Country of Publication:: United States

Language:: English

Subject:: 42 ENGINEERING; 36 MATERIALS SCIENCE

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                    Wang, Jenny. In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling.  United States: N. p., 2019. 
        Web.  doi:10.2172/1572613.

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                    Wang, Jenny. In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling.  United States.  https://doi.org/10.2172/1572613

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                    Wang, Jenny. 2019.  
        "In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling".  United States.  https://doi.org/10.2172/1572613.  https://www.osti.gov/servlets/purl/1572613.

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@article{osti_1572613,

  title        = {In Situ Monitoring of Direct Ink Write Process Using Electromagnetic Resonant Coupling},

  author       = {Wang, Jenny},

  abstractNote = {Additive manufacturing (AM) of multi-material objects enables the design of complex 3D architectures such as printed electronics and devices. The ability to detect the composition of multi-material printed inks in real time is an emerging need for a wide range of manufacturing applications. This study demonstrates the feasibility of using an in situ sensor to locally measure the composition of inks as they are being printed to facilitate greater control over the resulting properties and functionality of printed materials. Dielectric properties of microscale embedded metal particles in a dielectric matrix are measured and characterized as a function of particle size, shape, volume percentage and frequency. Results show that particle shape has a much greater influence on impedance measurements than the particle size. Measurements are found to agree with calculations based on an anisotropic Maxwell-Garnett dielectric function model. The resulting data can be used to generate a calibration curve correlating metal loading with impedance or capacitance and thus applied as an in situ sensor for compositional measurements during extrusion-based AM.},

  doi          = {10.2172/1572613},

  url          = {https://www.osti.gov/biblio/1572613},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Tue Oct 29 00:00:00 EDT 2019},

  month        = {Tue Oct 29 00:00:00 EDT 2019}

}

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https://doi.org/10.2172/1572613

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