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:
May. 28, 2024

Filed:

Jun. 27, 2020
Applicant:

Zeteo Tech, Inc., Sykesville, MD (US);

Inventors:

Michael Mcloughlin, Sykesville, MD (US);

Wayne A. Bryden, Sykesville, MD (US);

Charles J. Call, Sykesville, MD (US);

Dapeng Chen, Sykesville, MD (US);

Assignee:

ZETEO TECH, INC., Sykesville, MD (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H01J 49/16 (2006.01); G01N 15/10 (2006.01); G01N 27/64 (2006.01); H01J 49/00 (2006.01); H01J 49/40 (2006.01);
U.S. Cl.
CPC ...
H01J 49/164 (2013.01); G01N 15/10 (2013.01); G01N 27/64 (2013.01); H01J 49/0036 (2013.01); H01J 49/40 (2013.01); G01N 2015/1029 (2024.01); G01N 2015/103 (2024.01);
Abstract

Disclosed are systems are methods for identifying the composition of single aerosol particles, particularly that of bioaerosol particles, without pre-treatment using complex organic MALDI matrices. A continuous timing laser may be used to index aerosol particles, measure particle properties, and trigger a pulse ionization laser. Ionized fragments and optionally photons associated with each particle producing by the ionization laser may be analyzed using one or more detectors including a TOF-MS detector and an optical detector. The laser pulse may comprise a simultaneous IR and UV laser pulse when fragments comprise predominantly of UV chromophores. Unique spectral data associated with each indexed particle from each detector may be compiled using data fusion to generate compiled spectral data. Machine learning methods may be used to improve the prediction of composition over time.


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