Methods of analyzing samples using broadband laser light

• US 7,894,057 B2
• Filed: 10/14/2009
• Issued: 02/22/2011
• Est. Priority Date: 03/22/2004
• Status: Active Grant

• Current Assignee: Quantaspec Incorporated
• Original Assignee: Quantaspec Incorporated
• Inventors: Puzey, Kenneth A.
• Primary Examiner(s): Chowdhury; Tarifur
• Assistant Examiner(s): Hansen; Jonathan M
• Application Number:
  US12/578,629
• Publication Number:
  US 20100045977A1
• Time in Patent Office: 496 Days
• Field of Search: 356/326, 356/335, 356/317
• US Class Current: 356/326
• CPC Class Codes: C12Q 1/04 Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor C12Q1/6897 takes precedence
• CPC Class Codes: G01N 2021/1793 Remote sensing
• CPC Class Codes: G01N 2021/3137 with selection of wavelengths after the sample
• CPC Class Codes: G01N 2021/3166 using separate detectors and filters
• CPC Class Codes: G01N 2021/3513 Open path with an instrumental source
• CPC Class Codes: G01N 2021/4707 Forward scatter; Low angle scatter
• CPC Class Codes: G01N 2021/4709 Backscatter
• CPC Class Codes: G01N 2021/4728 Optical definition of scattering volume
• CPC Class Codes: G01N 21/31 Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry G01N21/72 takes precedence
• CPC Class Codes: G01N 21/3504 for analysing gases, e.g. multi-gas analysis
• CPC Class Codes: G01N 21/53 within a flowing fluid, e.g. smoke

Abstract

Broadband light, for example, from a Fabry-Perot quantum cascade laser, is shone onto a sample, and spectral data concerning the broadband light reflected from the sample is collected. The spectral data is analyzed to determine information about one or more substances in the sample. For example, if the sample contains micro-organisms, such as bacteria or fungus, the biological classification(s) (e.g., species) of the micro-organisms can be determined from the spectral data. As another example, if the sample contains virus, the biological classification(s) (e.g., species) of the virus(es) can be determined from the spectral data. As yet another example, if the sample contains particles, size, location and velocity can be determined from the spectral data.

Claims

1. A method of identifying a biological classification of virus present in a sample, the method comprising:

illuminating the sample with a spectral energy band across at least a portion of the characteristic absorption band of the analyte using an illuminator consisting essentially of one or more broadband quantum cascade lasers so as to provide the spectral energy band across a broadband of wavelengths;

collecting spectral data regarding the sample using a detector; and

determining a biological classification of the virus as a function of the spectral data;

wherein the spectral data comprises a plurality of spectral data points and said collecting includes collecting the spectral data points simultaneously with one another; and

wherein said illuminating comprises illuminating the sample using a Fabry-Perot quantum cascade laser.

2. A method according to claim 1, wherein said determining of the biological classification of the virus includes identifying a virus species.

3. A method according to claim 1, wherein the sample includes viruses of differing biological classifications, the method further comprising performing a multivariate analysis of the spectral data so as to distinguish between the differing biological classifications.

4. A method of identifying a biological classification of micro-organisms present in a sample, the method comprising:

illuminating the sample with a spectral energy band across at least a portion of the characteristic absorption band of the analyte using an illuminator consisting essentially of one or more broadband quantum cascade lasers so as to provide the spectral energy band across a broadband of wavelengths;

simultaneously collecting spectral data, from across the broadband of wavelengths, regarding the sample using a detector; and

determining the biological classification of the micro-organisms as a function of the spectral data;

wherein said illuminating comprises illuminating the sample using a Fabry-Perot quantum cascade laser.

5. A method according to claim 4, wherein said determining of the biological classification of the micro-organisms includes identifying the species.

6. A method according to claim 4, wherein the sample includes micro-organisms of differing biological classifications, the method further comprising performing a multivariate analysis of the spectral data so as to distinguish between the differing biological classifications.

7. A method according to claim 4, wherein the micro-organisms include a fungus and said determining the biological classification of the micro-organisms includes determining the biological classification of the fungus.

8. A method according to claim 7, wherein said illuminating comprises illuminating the sample using a Fabry-Perot quantum cascade laser.

9. A method according to claim 7, wherein said determining of the biological classification of the fungus includes identifying a fungal species.

10. A method according to claim 7, wherein the sample include'"'"'s fungi of differing biological classifications, the method further comprising performing a multivariate analysis of the spectral data so as to distinguish between the differing biological classifications.

11. A method according to claim 4, wherein ones of the micro-organisms are bacteria and said determining the biological classification of the micro-organisms includes determining the biological classification of the bacteria.

12. A method according to claim 11, wherein said illuminating comprises illuminating the sample using a Fabry-Perot quantum cascade laser.

13. A method according to claim 11, wherein said determining of the biological classification of the bacteria includes identifying the bacterial species.

14. A method according to claim 11, wherein the sample includes bacteria of differing biological classifications, the method further comprising performing a multivariate analysis of the spectral data so as to distinguish between the differing biological classifications.

15. A method, comprising:

illuminating a plurality of particles, from a stand off distance, with a spectral energy band across at least a portion of the characteristic non-absorption band of the plurality of particles using an illuminator consisting essentially of one or more broadband quantum cascade lasers so as to provide the spectral energy band across a broadband of wavelengths;

collecting spectral data regarding the plurality of particles using a detector; and

determining sizes of the particles based on the spectral data;

wherein said illuminating comprises illuminating the sample using a Fabry-Perot quantum cascade laser.

16. A method according to claim 15, further comprising determining a location of the particles using the spectral data.

17. A method according to claim 15, further comprising determining a velocity of the particles using the spectral data.