# US 11,906,424 B2 · Method for identifying chemical and structural variations through terahertz time-domain spectroscopy

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- Number: US 11,906,424 B2
- Document ID: US11906424B2
- Status: Granted
- Kind: B2
- Application number: 17/754,053
- Filed: 2020-10-01
- Published: 2023-01-19
- Granted: 2024-02-20
- Earliest claimed: 2019-10-01
- Assignees: The Regents of the University of California
- Applicants: The Regents of the University of California
- Inventors: Mona Jarrahi; Nezih Tolga Yardimci
- Web page: https://patentgrep.com/patent/US11906424B2

## CPC

- G01N 21/3586: by Terahertz time domain spectroscopy [THz-TDS]
- G01J 3/28: Investigating the spectrum (using colour filters G01J3/51)
- G01J 3/42: Absorption spectrometry; Double beam spectrometry; Flicker spectrometry; Reflection spectrometry (beam switching arrangements G01J3/08)
- G01N 21/8851: {Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges (G01N21/8806 and G01N21/93 - G01N21/95692 take precedence; optical measurement of dimensions G01B11/00; optical scanning G02B26/10; image transformation G06T3/00; computerised image enhancement G06T5/00; image processing per se for flaw detection G06T7/0002)}
- G01N 22/00: Investigating or analysing materials by the use of microwaves or radio waves, i.e. electromagnetic waves with a wavelength of one millimetre or more (G01N3/00 - G01N17/00, G01N24/00 take precedence)
- G01N 33/02: Food
- G01J 2003/423: {Spectral arrangements using lasers, e.g. tunable}
- G01N 21/8914: {characterised by the material examined}
- G01N 21/94: Investigating contamination, e.g. dust (G01N21/85 takes precedence)
- G01N 2021/8883: {involving the calculation of gauges, generating models}
- G01N 2201/1296: using neural networks
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)
- G01J: MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY (light sources F21, H01J, H01K, H05B; investigating properties of materials by optical means G01N)

## Abstract

A terahertz scanner for detecting irregularities, such as chemical or structural variations, in a sample and methods of use thereof are described. The described terahertz scanner and algorithms allow for direct, high-sensitivity, high-throughput, and non-invasive detection of irregularities that range from chemical contaminant to material defects in a variety of substrates and settings.

## Claims

### Claim 1

A method for identifying chemical and structural irregularities in a substrate, comprising:
providing a sample comprising a plurality of points and having chemical or structural variations;
providing a terahertz scanner comprising:
at least one terahertz source generating a terahertz beam along a terahertz beam path, and
at least one terahertz detector, wherein
the terahertz scanner produces a characteristic signal when the terahertz beam is detected by the at least one terahertz detector after interacting with a point of the plurality of points of the sample; and
the terahertz scanner produces a reference signal when the terahertz beam is not intercepted by the sample;
obtaining a characteristic signal and a reference signals for at least one point of the plurality of points of the sample;
extracting one or more characteristic features from a characteristic data set afforded by the characteristic signal, and extracting one or more corresponding reference features from a reference data set afforded by the reference signal; wherein at least one of the characteristic features and the corresponding reference features are selected from a list consisting of: peak intensity, average intensity, delay, pulse width, spectral power, phase of the characteristic signals, and any combination thereof;
analyzing the characteristic features and the corresponding reference features using a machine learning data analysis model to find chemical and or structural information about the sample; and
recognizing irregularities in or differences between the characteristic features and the corresponding reference features to identify the chemical or structural variations in the sample.

### Claim 2 (depends on 1)

The method of claim 1, wherein the machine learning data analysis model is selected from a list consisting of: supervised model, unsupervised model, and any combination thereof.

### Claim 3 (depends on 1)

The method of claim 1, wherein the machine learning data analysis model is trained to recognize the chemical or structural variations in the sample.

### Claim 4 (depends on 1)

The method of claim 1, wherein the terahertz scanner is a terahertz time-domain spectroscopy scanner.

### Claim 5 (depends on 4)

The method of claim 4 wherein the terahertz scanner further comprises:
a femtosecond laser generating an optical beam, and
a plurality of optical lenses for focusing the optical beam along an optical beam path.

### Claim 6 (depends on 5)

The method of claim 5, wherein the femtosecond laser is selected from a list of: a single femtosecond laser combined with a delay stage, and a dual femtosecond laser.

### Claim 7 (depends on 5)

The method of claim 5, wherein the femtosecond laser generates the optical beam at a wavelength selected from: ˜800 nm, 1550 nm.

### Claim 8 (depends on 5)

The method of claim 5, wherein the plurality of optical lenses adjusts a spot size of the optical beam to cover a active area of the terahertz source and the terahertz detector.

### Claim 9 (depends on 4)

The method of claim 4, wherein the terahertz scanner further comprises a plurality of terahertz lenses and or off-axis parabolic mirrors for focusing and or collimating the terahertz beam along the terahertz beam path.

### Claim 10 (depends on 9)

The method of claim 9, wherein the plurality of terahertz lenses is made from a material selected from a list of: polyethylene, TPX, ceramic, Teflon, and any combination thereof.

### Claim 11 (depends on 4)

The method of claim 4, wherein the characteristic signal and the reference signal are in time domain.

### Claim 12 (depends on 11)

The method of claim 11, wherein the characteristic signal and the reference signal in time domain are used to find their corresponding signals in frequency-domain; and extracting the characteristic features and the corresponding reference features in both a time domain and a frequency domain.

### Claim 13 (depends on 1)

The method of claim 1, wherein the chemical or structural variations are selected from a list consisting of: chemical contamination, material defects, other irregularities in a material, and any combination thereof.

### Claim 14 (depends on 13)

The method of claim 13, wherein the chemical contamination comprises a toxin.

### Claim 15 (depends on 14)

The method of claim 14, wherein the toxin is selected from a group consisting of: mycotoxins, aflatoxins, or a combination thereof.

### Claim 16 (depends on 13)

The method of claim 13, wherein the material defects are further selected from a list consisting of: thickness variations, voids, cracks, non-uniformities, and any combination thereof.

### Claim 17 (depends on 1)

The method of claim 1, wherein the sample comprises a battery electrode and the chemical or structural variations are material defects.

### Claim 18 (depends on 1)

The method of claim 1, wherein the sample comprises a composite material and the chemical or structural variations are material defects.

### Claim 19 (depends on 1)

The method of claim 1, wherein the at least one terahertz detector is selected from a list consisting of: a single-pixel terahertz detector, a focal plane 1D or 2D array comprising a plurality of terahertz detectors.

### Claim 20 (depends on 1)

The method of claim 1, wherein the at least one terahertz detector is capable of taking three-dimensional terahertz snapshots of an area as large as ˜10 cm2 within less than a 100 ms.

### Claim 21 (depends on 1)

The method of claim 1, wherein the at least one terahertz source and the at least one terahertz detector comprise plasmonic electrodes.

### Claim 22 (depends on 21)

The method of claim 21, wherein the at least one terahertz source and the at least one terahertz detector are fabricated on a semiconductor substrate and optimized for operation at 800 nm or 1550 nm wavelengths.

### Claim 23 (depends on 21)

The method of claim 21, wherein the at least one terahertz source and the at least one terahertz detector are fabricated on a GaAs, InGaAs and InAs substrate.

### Claim 24 (depends on 1)

The method of claim 1, wherein the sample is placed on a sample holder selected from a list of: a moving conveyor belt, a single or multi-well plate or multiple plates mounted on a motorized translational stage, and any combination thereof.