IP Library Granted Patent US 10,336,062
Granted Patent B2
US 10,336,062 · App. 15/457,283 · Granted Jul 2, 2019

Systems and methods for precision inkjet printing

Inventors: S. V. Sreenivasan (Austin, TX); Brent Snyder (Austin, TX); Miaomiao Yang (Austin, TX); Shrawan Singhal (Austin, TX); Ovadia Abed (Austin, TX)
Assignee: Board of Regents, The University of Texas System
B41J2/04508B41J2/0456B41J2/0458B41J2/04561B41J2/04581
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Quick Facts
Patent No.
US 10,336,062
App. No.
15/457,283
Granted
Jul 2, 2019
Kind
B2
Abstract

Systems and methods for precision inkjet printing are disclosed. A method determining an actuation parameter associated with a pressure waveform. Based on the pressure waveform, the method also includes actuating a print head to eject a droplet from a nozzle and acquiring an image of the droplet. The method further includes processing the acquired image to estimate a volume of the droplet and based on the estimated volume of the droplet and a target volume, adjusting the actuation parameter.

Claims (59)

1. A method for precision inkjet printing, comprising:

determining an initial pressure waveform and an associated initial actuation parameter value;

based on the initial pressure waveform, actuating a print head to eject a lead droplet from a nozzle;

acquiring an image of the lead droplet;

processing the acquired image to estimate a volume of the lead droplet;

based on the estimated volume of the lead droplet and a target volume, determining an optimized pressure waveform that actuates the election of a subsequent droplet with the target volume; and

adjusting the initial actuation parameter value to an optimized actuation parameter value associated with the optimized pressure waveform by applying an automated tuning algorithm.

2. The method of claim 1 , wherein the target volume comprises a volume of less than 100 picoliters; and wherein the actuation parameter value is adjusted to optimize the subsequent droplet with a volume variation of less than 15% of 1-sigma from the target volume.

3. The method of claim 1 , wherein determining the optimized pressure waveform comprises calculating an error between the estimated volume of the lead droplet and the target volume.

4. The method of claim 3 , further comprising minimizing the error using an optimization routine.

5. The method of claim 1 , wherein processing the acquired image to estimate the volume of the lead droplet further comprises:

establishing a ruler by calibrating a non-varying artifact on the acquired image based on a diameter of the nozzle;

estimating a perimeter of the lead droplet; and

estimating the volume of the lead droplet based on the estimated perimeter of the droplet.

6. The method of claim 1 , further comprising:

estimating a diameter of the lead droplet based on a measurement after the lead droplet is ejected; and

applying the automated tuning algorithm so that the diameter of the droplet is less than a diameter of the nozzle.

7. The method of claim 1 , wherein actuating the print head is based on selecting a source from among the following: a piezoelectric element, thermal energy, electrical energy, chemical energy, and mechanical energy.

8. The method of claim 1 , further comprising independently controlling a plurality of nozzles to eject a plurality of droplets.

9. The method of claim 1 , wherein the print head is configured to dispense a plurality of fluids, one fluid of the plurality of fluids having a different rheological property than another one fluid of the plurality of fluids.

10. The method of claim 9 , wherein a fluid of the plurality of fluids is selected from among the following: a non-Newtonian materials, a 1D nanomaterial suspended in a solvent, and a 2D nanomaterial suspended in a solvent.

11. The method of claim 1 , wherein the initial actuation parameter value is selected based on a manual tuning process.

12. The method of claim 1 , wherein the initial actuation parameter value is selected based on a lookup table for known materials.

13. The method of claim 1 , wherein the initial actuation parameter value is selected based on a set-point volume.

14. The method of claim 1 , further comprising:

selecting a first number of a plurality actuation parameters; and

selecting a second number of the plurality of actuation parameters based on the first number and an adjustment to the plurality of actuation parameters.

15. The method of claim 1 , wherein the acquired images are captured using a live video feed having a frame rate higher than a frequency of ejection of the droplet.

16. The method of claim 1 , wherein the acquired images are captured using a live video feed having a stroboscopic illumination from a light source.

17. The method of claim 1 , wherein a velocity of ejection of the droplet is greater than 0.1 m/s.

18. The method in claim 17 further comprising calibrating performance of a first inkjet device to a second inkjet device.

19. The method in claim 17 further comprising calibrating an inkjet device to dispense a material with a Z number over 40.

20. The method of claim 1 , further comprising:

estimating a velocity of the droplet;

based on the estimated velocity being less than a minimum target velocity or more than a maximum target velocity, calculating an error between the estimated velocity and the minimum and maximum target velocities;

based on the estimated velocity being more than a minimum target velocity or less than a maximum target velocity, setting an error to zero; and

minimizing the error using an optimization routine.

21. The method of claim 20 , wherein estimating the velocity of the droplet further comprises:

establishing a ruler by calibrating a non-varying artifact on the acquired image based on a diameter of the nozzle;

detecting a position of the droplet at a plurality of distinct locations;

tracking a time stamp for the plurality of distinct locations; and

estimating a velocity for the droplet based on the position and the time stamp for the plurality of distinct locations.

22. The method of claim 1 , wherein the automated tuning algorithm automatically minimizes a fault selected from:

a. large deviation from a target volume;

b. low velocity compared to a target minimum velocity;

c. no dispensed droplet;

d. a single lead droplet with negative velocity and the single lead droplet is pulled back in the nozzle;

e. a single lead drop with undesired lateral velocity;

f. a single lead drop with one or more satellites; and

g. bleeding of the nozzle.

23. The method of claim 22 , wherein minimizing the fault further comprises solving an optimization function that optimizes an objective function comprising an error associated with the fault.

24. The method of claim 23 , wherein the error associated with the fault is a combination of one or more of the following:

a. a function of square of difference between volume of the lead droplet and the target volume;

b. a function of square of difference between volume of the lead droplet and an average volume;

c. a function of square of difference between an estimated velocity and a target velocity;

d. a function of square of difference between a direction of velocity of the lead droplet and a direction of the target velocity; and

e. a function of square of difference between volume of a plurality of lead droplets and a target volume.

25. The method in claim 1 further comprising calibrating performance of a first inkjet device to a second inkjet device.

26. The method in claim 1 further comprising calibrating an inkjet device to dispense a material with a Z number over 40.

Assignments (3)
SECURITY INTEREST Recorded May 24, 2022
From: MOLECULAR IMPRINTS, INC.; MENTOR ACQUISITION ONE, LLC; MAGIC LEAP, INC.
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 060338/0665 →
CONFIRMATORY LICENSE Recorded Apr 27, 2017
From: UNIVERSITY OF TEXAS, AUSTIN
To: NATIONAL SCIENCE FOUNDATION
Reel/Frame 042353/0334 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 13, 2017
From: SREENIVASAN, S.V.; SNYDER, BRENT; YANG, MIAOMIAO; SINGHAL, SHRAWAN; ABED, OVADIA
To: BOARD OF REGENTS, THE UNIVERSITY OF TEXAS SYSTEM
Reel/Frame 041559/0924 →
Continuity (2)
Provisional Application 62308056 · Mar 14, 2016
Related Publication 20170259560A1 · Sep 14, 2017
Cited By (3)
US 12,330,178 US 12,560,531 US 12,668,057