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Methods and apparatuses for etch profile matching by surface kinetic model optimization

  • US 10,386,828 B2
  • Filed: 12/17/2015
  • Issued: 08/20/2019
  • Est. Priority Date: 12/17/2015
  • Status: Active Grant
First Claim
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1. A method of optimizing a computerized model which relates an etched feature profile on a semiconductor device to a set of independent input parameters via the use of a plurality of model parameters, the method comprising:

  • (a) identifying a set of values for a selected set of the model parameters to be optimized;

    (b) identifying multiple sets of values for a selected set of independent input parameters to optimize over, wherein the independent input parameters comprise an input parameter selected from the group consisting of temperature, plasma density, and etchant flux;

    (c) for each set of values specified in (b), receiving an experimental etch profile resulting from an experimental etch process performed using the set of values specified in (b), wherein the experimental etch process comprised various experiments that etch semiconductor substrates and measure resulting experimentally produced feature profiles with one or more metrology tools;

    (d) for each set of values specified in (b), generating a computed etch profile from the model using the set of values specified in (a) and (b), wherein the computed etch profile is provided for a grid having a grid spacing of between 1 angstrom and 10 micrometers, and wherein the computed etch profile is generated over a plurality of time steps; and

    (e) modifying one or more values specified in (a) for the selected set of model parameters and repeating (d) with the modified one or more values so as to reduce a metric indicative of combined differences between the experimental etch profiles received in (c) and corresponding computed etch profiles generated in (d) over all the sets of values for the selected independent input parameters specified in (b) to thereby produce optimized model parameter values;

    wherein calculating the metrics in (e) comprises;

    projecting the computed and corresponding experimental etch profiles from a first space having multiple dimensions each representing one of a plurality of feature profile coordinates onto a reduced-dimensional subspace having fewer dimensions than the first space and reducing latent statistical correlations in etch profiles, wherein the reduced-dimensional subspace recasts the modifying operation in (e) to a computationally more efficient process; and

    calculating a difference between the profiles as projected onto the subspace.

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