Method of Characterizing Layer Thickness
Assignee3M Innovative Properties Company
InventorsRyan A. Franking, Yutao Gong, David L. Hofeldt
Life of this patent
Estimating the term…
Abstract
A method of characterizing one or more layers of a material includes irradiating the material with a THz pulse such that at least a portion of the THz pulse is reflected from the material as a reflected THz signal; acquiring a first time-domain waveform of the reflected THz signal; and using a neural network to map the first time-domain waveform to a second time-domain waveform defined by a superposition of a plurality of peaked time-domain interface waveforms. Each peaked time-domain interface waveform has a peak corresponding to a reflection from an interface of the material. Proportional thickness of layers may be determined from the time shift between each peaked interface waveform.
Claims18
1-15. (canceled)
A method of characterizing one or more layers of a material, the method comprising:
- irradiating the material with a THz pulse such that at least a portion of the THz pulse is reflected from the material as a reflected THz signal;
- acquiring a first time-domain waveform of the reflected THz signal;
- using a neural network on a computing device to map the first time-domain waveform to a second time-domain waveform defined by a superposition of a plurality of peaked time-domain interface waveforms, each peaked time-domain interface waveform comprising a peak corresponding to a reflection from an interface of the material;
- and
- determining one or more proportional thicknesses of one or more layers of the material from a corresponding one or more spacings between adjacent peaks of the plurality of peaked time-domain interface waveforms.
A method of training a neural network for characterizing one or more layers of a material using a THZ pulse, the method comprising:
- training the neural network on a computing device using training data to determine parameters of the neural network, the training data comprising:
- input data comprising time-domain waveform data corresponding to at least partial reflection of a THz pulse from each test sample of a first plurality of test samples;
- and
- output data comprising a time-domain output waveform for each test sample of the first plurality of test samples, each time-domain output waveform defined by a superposition of a plurality of peaked time-domain interface waveforms, each peaked time-domain interface waveform comprising a peak corresponding to a reflection from an interface of the test sample.
A method of generating training data for a neural network, the training data comprising input data and output data, the method comprising:
- determining the input data as time-domain waveform data corresponding to a first plurality of test samples via computer simulation of at least partial reflection of a THz pulse from each test sample of the first plurality of test samples;
- and
- for each test sample in the first plurality of test samples, determining a time-domain output waveform as a superposition of a plurality of peaked time-domain interface waveforms, each peaked time-domain interface waveform comprising a peak corresponding to a reflection from an interface of the test sample, the output data comprising the time-domain output waveform.
Dependencies are inferred from the claim text.