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DTSTAMP:20250918T203227Z
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DESCRIPTION:[]Printed electronics has emerged as a versatile technique for 
 on-demand fabrication of passives\, interconnects\, and active devices. Ou
 r group has recently extended this technique to create freeform devices in
  Three-Dimensional space that have opened exciting application areas for t
 his technology. The manufacturing process for printed electronics\, howeve
 r\, can suffer from process drifts and does not have an active feedback lo
 op to fix errors. In this research\, we develop a digital twin for aerosol
  jet 3D printing\, a jetting-based method to create printed electronics to
  address this concern. This work\, done in collaboration with an ECE facul
 ty at CMU\, matches observations with outcomes expected from a physics-bas
 ed process model\, and continuously updates the hidden variables to minimi
 ze this error via probabilistic estimation techniques.\nWe then use the ae
 rosol jet 3D printing to demonstrate devices with extraordinary performanc
 es that cannot be achieved by any other method. Specifically\, we show 3D 
 electrodes by this technique that enable detection of pathogens and breast
  cancer biomarkers in 10-12 seconds at femtomolar levels (fastest detectio
 n yet reported). We also show fully customizable brain-computer interfaces
  (BCIs) that record electrical signals between neurons at densities of tho
 usands of electrodes/cm2\, which is 5-10× the current state-of-the-art te
 chnologies. We also demonstrated the printing of high-capacity Li-ion batt
 eries and thin flexible robotic skins with embedded sensors.\n\nSpeaker(s)
 : Rahul Panat\, \n\nVirtual: https://events.vtools.ieee.org/m/481231
LOCATION:Virtual: https://events.vtools.ieee.org/m/481231
ORGANIZER:p.wesling@ieee.org
SEQUENCE:12
SUMMARY:Digital Twins for Printed Electronics for 3D Packaging\, High-perfo
 rmance Sensors\, and High-capacity Batteries
URL;VALUE=URI:https://events.vtools.ieee.org/m/481231
X-ALT-DESC:Description: <br /><p><img style="float: right\;" src="https://e
 vents.vtools.ieee.org/vtools_ui/media/display/a32c68da-66ce-4d07-8112-ce46
 1a0a8c71" alt="" width="365" height="213">Printed electronics has emerged 
 as a versatile technique for on-demand fabrication of passives\, interconn
 ects\, and active devices. Our group has recently extended this technique 
 to create freeform devices in Three-Dimensional space that have opened exc
 iting application areas for this technology. The manufacturing process for
  printed electronics\, however\, can suffer from process drifts and does n
 ot have an active feedback loop to fix errors. In this research\, we devel
 op a digital twin for aerosol jet 3D printing\, a jetting-based method to 
 create printed electronics to address this concern. This work\, done in co
 llaboration with an ECE faculty at CMU\, matches observations with outcome
 s expected from a physics-based process model\, and continuously updates t
 he hidden variables to minimize this error via probabilistic estimation te
 chniques.<br>We then use the aerosol jet 3D printing to demonstrate device
 s with extraordinary performances that cannot be achieved by any other met
 hod. Specifically\, we show 3D electrodes by this technique that enable de
 tection of pathogens and breast cancer biomarkers in 10-12 seconds at femt
 omolar levels (fastest detection yet reported). We also show fully customi
 zable brain-computer interfaces (BCIs) that record electrical signals betw
 een neurons at densities of thousands of electrodes/cm<sup>2</sup>\, which
  is 5-10&times\; the current state-of-the-art technologies. We also demons
 trated the printing of high-capacity Li-ion batteries and thin flexible ro
 botic skins with embedded sensors.</p>
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