Methods, mediums, and systems for identifying tunable domains for ion beam shape matching

A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to:

• receive one or more desired beam shape parameters for an ion beam and one or more tunable parameters for an ion beam generator configured to generate the ion beam;
• select a set of exploratory points within a search space, each point in the search space representing a combination of values for the tunable parameters;
• for each of the exploratory points, receive measured beam shape parameters based on the combination of values for the tunable parameters defined by the respective exploratory point;
• train a regression model configured to provide predicted beam shape parameters for a predetermined number of interpolated points between the exploratory points;
• define a plurality of clusters within the search space based on the predicted beam shape parameters and the measured beam shape parameters;
• evaluate the plurality of clusters for at least one of a stability or a sensitivity of the tunable parameters within each respective cluster;
• select one of the plurality of clusters based on the evaluating;
• and
• output tuning settings for the combination of values for the tunable parameters corresponding to the selected cluster.

A computing apparatus comprising:

• a processor;
• and
• a memory storing instructions that, when executed by the processor, configure the apparatus to:
• receive one or more desired beam shape parameters for an ion beam and one or more tunable parameters for an ion beam generator configured to generate the ion beam;
• select a set of exploratory points within a search space, each point in the search space representing a combination of values for the tunable parameters;
• for each of the exploratory points, receive measured beam shape parameters based on the combination of values for the tunable parameters defined by the respective exploratory point;
• train a regression model configured to provide predicted beam shape parameters for a predetermined number of interpolated points between the exploratory points;
• define a plurality of clusters within the search space based on the predicted beam shape parameters and the measured beam shape parameters;
• evaluate the plurality of clusters for at least one of a stability or a sensitivity of the tunable parameters within each respective cluster;
• select one of the plurality of clusters based on the evaluating;
• and
• output tuning settings for the combination of values for the tunable parameters corresponding to the selected cluster.

An ion implanter, comprising:

• an ion beam generator to generate an ion beam;
• at least one beamline component to direct the ion beam towards a substrate;
• a processing circuitry;
• and
• a memory communicatively coupled to the processing circuitry, the memory storing instructions that, when executed by the processing circuitry, causes the processing circuitry to:
• receive one or more desired beam shape parameters for the ion beam and one or more tunable parameters for the ion beam generator configured to generate the ion beam;
• select a set of exploratory points within a search space, each point in the search space representing a combination of values for the tunable parameters;
• for each of the exploratory points, receive measured beam shape parameters based on the combination of values for the tunable parameters defined by the respective exploratory point;
• train a regression model configured to provide predicted beam shape parameters for a predetermined number of interpolated points between the exploratory points;
• define a plurality of clusters within the search space based on the predicted beam shape parameters and the measured beam shape parameters;
• evaluate the plurality of clusters for at least one of a stability or a sensitivity of the tunable parameters within each respective cluster;
• select one of the plurality of clusters based on the evaluating;
• and
• output tuning settings for the combination of values for the tunable parameters corresponding to the selected cluster.