Systems and methods of rapid and autonomous detection of aerosol particles
Inventors
Bryden, Wayne A. • Call, Charles J. • McLoughlin, Michael • Chen, Dapeng • Ecelberger, Scott • JONES, Nathaniel K. • Strohl, Steven • Anderson, Gary
Assignees
Publication Number
US-11658021-B2
Publication Date
2023-05-23
Expiration Date
2040-08-26
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Abstract
Disclosed are systems and methods to provide rapid and autonomous detection of analyte particles in gas and liquid samples. Disclosed are methods and devices for identifying biological aerosol analytes using MALDI-MS and chemical aerosol analytes using LDI and MALDI-MS using time-of-flight mass spectrometry (TOFMS).
Core Innovation
The invention provides autonomous systems and methods for the rapid and accurate detection and identification of aerosolized analyte particles, including both biological and chemical agents, in air and liquid samples. These systems utilize mass spectrometry techniques—such as MALDI-MS and LDI-MS with time-of-flight mass spectrometry (TOFMS)—to analyze captured samples. The systems feature automated handling of sample disks, including loading from a cartridge, deposition of aerosol or liquid particles, application of chemical treatments, drying, analysis, and data transmission, all with minimal operator intervention.
The system addresses the pressing need for real-time or near real-time identification of hazardous aerosol agents, including pathogens and toxins, which is critical for biodefense, environmental bioaerosol monitoring, infrastructure protection, and health care applications. Current technologies for aerosol detection are limited by long preparation times, specificity to target agents, or inability to distinguish between similar but non-hazardous species. The disclosed invention overcomes these challenges by automating sample processing, reducing analysis time to under five minutes, and enabling identification across a broader range of bio- and chemical analytes.
Key features include robotic sample handling, sample disks pre-coated with matrix chemicals for MALDI analysis, integration of fluorescence and optical detection techniques, automated camera examination and drying, and advanced data processing—potentially including machine learning—for accurate analyte identification. The modular, multi-station design allows autonomous operation from collection to analysis and supports data communication with local or remote processing for rapid threat assessment.
Claims Coverage
The independent claims describe four main inventive features covering autonomous sample capture and analysis for aerosols and liquids, as well as the associated methods.
Autonomous sample capture and analysis system for aerosol analyte particles
An autonomous system comprising: - A fresh sample disk loader station configured to receive a cartridge of fresh disks. - A spent disk loader station for return of used disks. - An aerosol sample collection station. - A sample disk holder with a metal stub that can move in at least two orthogonal directions (X-Y-Z) using a stepper motor and actuator, allowing engagement with both the fresh and spent disk cartridges and stations in a predetermined analysis sequence. - One or more analysis stations, where operation is controlled by a microcontroller executing an analysis sequence, and the collection station is configured to produce a sample spot on the disk during analysis.
Method for collecting and analyzing aerosol analyte sample particles in air
A method using the above system, comprising: 1. Loading a fresh sample disk onto the holder. 2. Measuring particle counts in ambient air. 3. When particle counts exceed a threshold, moving the disk to the aerosol collection station to deposit aerosol particles as a ~1 mm spot. 4. Treating the deposited particles with chemicals at the dispensing station. 5. Examining the sample at the camera station (microscope or digital camera). 6. Substantially drying the sample. 7. Moving the disk to one or more analysis stations for analysis.
Autonomous sample capture and analysis system for liquid samples
An autonomous system comprising: - Fresh and spent sample disk or substrate loader stations. - A liquid sample acceptance station. - A liquid chemical dispensing station. - A movable sample disk holder with a metal stub capable of engaging loader stations and moving in at least two directions (X-Y-Z) using stepper motor/actuator in a predetermined analysis sequence. - One or more analysis stations, with operation controlled by a microcontroller.
Autonomous sample capture and analysis system for contaminant particles in a liquid sample with condensation growth tube
A system comprising: - A nebulizer to produce an aerosol from a liquid sample. - At least one condensation growth tube to enlarge contaminant particle size before collection. - Fresh and spent disk loader stations. - An aerosol sample collection station. - A liquid chemical dispensing station. - A camera station (microscope or digital camera). - A drying station (under vacuum). - A movable sample disk holder with a metal stub, capable of engaging with loader stations and moving through stations in a predetermined sequence. - One or more analysis stations, with operation controlled by a microcontroller.
The inventive features outlined provide autonomous, rapid, and systematic approaches for capturing, processing, and analyzing both aerosol and liquid samples for biological and chemical agents, utilizing robotic disk handling, modular station sequencing, and both mass spectrometry and optical analysis capabilities.
Stated Advantages
Enables rapid (near real-time) identification of biological and chemical analytes in less than about five minutes after sample collection.
Operates autonomously with minimal or no intervention by a professional technician or instrument operator.
Simultaneously identifies a wide range of analytes including bacteria, fungi, viruses, biotoxins, and low-volatility chemicals with high specificity and sensitivity.
Reduces or eliminates the delays and limitations of target-specific sample preparation steps found in existing technologies.
Integrates advanced data processing, including machine learning, to automate analysis and improve identification accuracy.
Allows communication with remote or local data processing stations for rapid threat assessment and data management.
Minimizes loss of aerosol particles during collection, enhances sample spot quality, and improves drying efficiency.
Documented Applications
Detection and identification of biohazardous aerosol and chemical threat agents in air for biodefense and infrastructure protection.
Environmental monitoring of bioaerosol threats in public spaces, including airports, office buildings, and mass transit facilities.
Point-of-care healthcare analysis, including rapid differentiation of viral and bacterial infections.
Diagnosis of respiratory diseases using exhaled breath analysis.
Analysis of contaminant particles in ultrapure water and chemical liquids used during semiconductor fabrication.
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