Droplet splash control for extreme ultra violet photolithography

US11940738B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11940738-B2
Application numberUS-202016902085-A
CountryUS
Kind codeB2
Filing dateJun 15, 2020
Priority dateJun 15, 2020
Publication dateMar 26, 2024
Grant dateMar 26, 2024

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

A photolithography system utilizes tin droplets to generate extreme ultraviolet radiation for photolithography. The photolithography system irradiates the droplets with a laser. The droplets become energized and emit extreme ultraviolet radiation. A collector reflects the extreme ultraviolet radiation toward a photolithography target. The photolithography system reduces splashback of the tin droplets onto the receiver by generating a net electric charge within the droplets using a charge electrode and decelerating the droplets by applying an electric field with a counter electrode.

First claim

Opening claim text (preview).

The invention claimed is: 1. A photolithography system, comprising: a droplet generator configured to output a stream of droplets; a droplet receiver positioned to receive and collect the droplets; a laser configured to irradiate the droplets at an irradiation location between the droplet generator and the droplet receiver; a collector configured to receive extreme ultraviolet radiation from the droplets and to reflect the extreme ultraviolet radiation for use in photolithography; a charge electrode positioned between the irradiation location and the droplet receiver; a counter electrode positioned within the droplet receiver downstream from the charge electrode with respect to a direction of travel of the droplets; a droplet sensor positioned within the droplet receiver and configured to generate sensor signals indicative of a speed of the droplets within the droplet sensor; and a control system configured to receive the sensor signals, to apply a first voltage to the charge electrode, and to apply a second voltage to the counter electrode, the first voltage being selected to impart a net electric charge to the droplets as the droplets pass adjacent to the charge electrode, the second voltage being selected to reduce a speed of the droplets within the droplet receiver, wherein the control system is configured to adjust one or both of the first and second voltages responsive to the sensor signals. 2. The photolithography system of claim 1 , wherein the first voltage and the second voltage have a same polarity. 3. The photolithography system of claim 2 , wherein the second voltage has a greater magnitude than the first voltage. 4. The photolithography system of claim 1 , wherein the control system includes a machine learning model that analyzes the sensor signals and outputs voltage adjustment data based on the sensor signals. 5. The photolithography system of claim 4 , wherein the control system adjusts one or both of the first and second voltages based on the voltage adjustment data. 6. The photolithography system of claim 5 , wherein the machine learning model includes a neural network. 7. The photolithography system of claim 5 , wherein the machine learning model includes a decision tree model. 8. A method comprising: outputting a stream of droplets from a droplet generator; irradiating, with a laser, the droplets at an irradiation location between the droplet generator and a droplet receiver; generating a net charge in the droplets downstream from the irradiation location; receiving the droplets in the droplet receiver downstream from the irradiation location; generating, with a droplet sensor positioned within the droplet receiver, sensor signals indicative of a speed of the droplets within the droplet receiver; reducing a speed of the droplets within the droplet receiver by generating an electric field within the droplet receiver; and adjusting the electric field in response to the sensor signals. 9. The method of claim 8 , wherein generating the net charge in the droplets includes applying a first voltage to a charge electrode positioned upstream from the droplet receiver. 10. The method of claim 9 , wherein generating the electric field includes applying a second voltage to a counter electrode. 11. The method of claim 10 , further comprising generating extreme ultraviolet radiation from the droplets by irradiating the droplets with the laser. 12. The method of claim 11 , further comprising performing photolithography with the extreme ultraviolet radiation. 13. The method of claim 10 , further comprising: passing the sensor signals to a control system; and wherein adjusting the electric field includes adjusting, with the control system, the second voltage based on the sensor signals. 14. The method of claim 13 , wherein the machine learning model includes a neural network. 15. The method of claim 13 , wherein the machine learning model includes a decision tree model. 16. The method of claim 13 , further comprising: passing the sensor signals, or data derived from the sensor signals to a machine learning model; analyzing the sensor signals or the data derived from the sensor signals with the machine learning model; generating, with the machine learning model, voltage adjustment data based, at least in part, on the sensor signals; and adjusting one or both of the first and second voltages based on the sensor signals. 17. The method of claim 16 , further comprising generating the voltage adjustment data based, at least in part, on a mass of the droplets. 18. The method of claim 16 , further comprising generating the voltage adjustment data based, at least in part, on a previous speed of the droplets. 19. A method, comprising: outputting a plurality of droplets with a droplet generator; generating extreme ultraviolet radiation by irradiating the droplets with a laser at an irradiation location between the droplet generator and the droplet receiver; inducing a net electric charge in the droplets by applying a first voltage to a charge electrode positioned adjacent to a path of the droplets between the irradiation location and the droplet receiver; generating, with a droplet sensor positioned within the droplet receiver, sensor signals indicative of a speed of the droplets within the droplet receiver; reducing a speed of the droplets by applying a second voltage to a counter electrode positioned within the droplet receiver downstream from the charge electrode; collecting the droplets in the droplet receiver; and adjusting the second voltage in response to the sensor signals. 20. The method of claim 19 , further comprising: passing the sensor signals to a control system; and adjusting, with the control system, one or both of the first and second voltages based on the sensor signals.

Assignees

Inventors

Classifications

  • Arrangements for controlling the supply; Arrangements for measurements · CPC title

  • G03F7/705Primary

    Modelling or simulating from physical phenomena up to complete wafer processes or whole workflow in wafer productions · CPC title

  • by plasma extreme ultraviolet [EUV] sources · CPC title

  • Optical correction elements, filters or phase plates for controlling intensity, wavelength, polarisation, phase or the like · CPC title

  • B23K26/146Primary

    the fluid stream containing a liquid · CPC title

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What does patent US11940738B2 cover?
A photolithography system utilizes tin droplets to generate extreme ultraviolet radiation for photolithography. The photolithography system irradiates the droplets with a laser. The droplets become energized and emit extreme ultraviolet radiation. A collector reflects the extreme ultraviolet radiation toward a photolithography target. The photolithography system reduces splashback of the tin dr…
Who is the assignee on this patent?
Taiwan Semiconductor Mfg Co Ltd
What technology area does this patent fall under?
Primary CPC classification G03F7/705. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 26 2024 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 7 related publications on this page (citations in our corpus or others sharing the same primary CPC).