Non-destructive sem-based depth-profiling of samples
AssigneeApplied Materials Israel Ltd.
InventorsDror Shemesh, Doron Girmonsky, Uri Hadar, Michal Eilon
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Abstract
Disclosed herein is a computer-based method for non-destructive depth-profiling of samples. The method includes a measurement operation and a data analysis operation. The measurement operation includes, for each of a plurality of landing energies: (i) projecting an electron beam on a sample, which penetrates the sample to a respective depth determined by the landing energy, and (ii) sensing electrons returned from the sample, thereby obtaining a respective sensed electrons data set. The data analysis operation includes generating from the sensed electrons data sets a concentration map, which characterizing at least a vertical dimension of the sample.
Claims20
A system for non-destructive depth-profiling of samples, the system comprising:
- an electron beam (e-beam) source configured to project e-beams on a sample at each of a plurality of landing energies;
- an electron sensing module configured to sense electrons returned from the sample, thereby obtaining a respective sensed electrons data set, wherein the sensed electrons comprise at least backscattered electrons;
- and
- a computational module configured to generate, based on the sensed electrons data sets, a concentration map characterizing at least a vertical dimension of the sample.
A computer-based method for non-destructive depth-profiling of samples, the method comprising:
- a measurement operation comprising for each of a plurality of landing energies, selected so as to allow probing the sample at a plurality of depths:
- projecting an electron beam (e-beam) on a sample, which penetrates the sample to a respective depth determined by the landing energy;
- and
- sensing electrons returned from the sample, thereby obtaining a respective sensed electrons data set, wherein the sensed electrons comprise backscattered electrons;
- and
- a data analysis operation, wherein a concentration map, characterizing at least a vertical dimension of the sample, is generated from the sensed electrons data sets.
A method for training a neural network (NN) for non-destructive depth-profiling of samples, the method comprising operations of:
- generating training data for a NN, which is configured to receive as inputs, sensed electrons data sets of a sample, obtained for each of a plurality of landing energies of inducing electron beams (e-beams), and to output a concentration map of the sample, by sub-operations of:
- generating calibration data by, for each of a plurality of samples:
- projecting thereon a plurality of e-beams at a first plurality of landing energies, respectively, and sensing at least backscattered electrons returned from the sample;
- and
- obtaining a measured concentration map, which characterizes at least a vertical dimension of the sample;
- generating simulated training data for the NN by:
- using the calibration data to calibrate a computer simulation, which is configured to receive as inputs a concentration map of a sample, and a landing energy of an e-beam projected on the sample, and output a corresponding simulated electrons data set;
- and
- using the calibrated computer simulation to generate simulated electrons data sets corresponding to additional landing energies and/or additional samples;
- and
- training the NN using (i) at least the simulated electrons data sets, each labelled by the respective landing energy, as inputs, and (ii) concentration maps, corresponding to the simulated electrons data sets, respectively, as outputs.
Dependencies are inferred from the claim text.