The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 09, 2024

Filed:

Jan. 21, 2020
Applicant:

Advanced Optical Technologies, Inc., Albuquerque, NM (US);

Inventors:

Brian G. Hoover, Tijeras, NM (US);

Jonathan H. Turner, Albuquerque, NM (US);

Assignee:

Advanced Optical Technologies, Inc., Albuquerque, NM (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G02B 21/00 (2006.01); G01J 4/04 (2006.01); G01N 21/21 (2006.01); G01N 21/84 (2006.01);
U.S. Cl.
CPC ...
G02B 21/0092 (2013.01); G01J 4/04 (2013.01); G01N 21/21 (2013.01); G01N 2021/8477 (2013.01); G02B 21/0068 (2013.01);
Abstract

A polarimeter and a method of analyzing and imaging microstructural material orientation of a sample are disclosed. The polarimeter, which is a partial Mueller-matrix polarimeter (pMMP), accesses multiple independent polarization channels by employing two independent polarization modulators configured to switch serially among multiple independent settings, wherein the combination of the settings of the first and second polarization modulators defines an independent polarization channel, and wherein an imaging detector produces a set of spatially registered images that are synchronized with the channels formed by the polarization modulators; and wherein a processor connected with a memory executes a classification algorithm stored in the memory that maps the set of images to one or more material orientation images by mapping the set of values for each detector pixel corresponding to the set of spatially registered images to a value of material orientation at each pixel coordinate using a machine-learning model, an electrodynamic model, or a combination thereof. The invention can thereby create material microstructural orientation images of diverse anisotropic materials, for instance polymer domains, fiber bundles or plys, and metallic crystalline grains.


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