MMoMA will determine how much information it is possible to obtain using a single extraction source from a sample of any material.
Sample Assessment Today
Sample testing is useful for everything from quality assurance in manufacturing, to attribution, to supply chain integrity, to environmental testing for chemical, biological, radioactive, and/or nuclear hazards.
Testing often requires extensive preparation. Obtaining comprehensive information on sample composition, molecular structure, and the presence of trace elements and isotopes may require sending parts of a single sample to an array of different laboratories (or passing around a single sample in series) and then trying to compile and cross-reference results. Both the distributed and series approaches are slow and carry a compounding risk of contamination or other errors throughout the process.
There are countless cases where sample testing would be a critical enabler for new capabilities for both military and commercial use but is currently impractical because of slow speed and limited certainty.
One Beam, Lots of Sensors
The MMoMA goal is to make sample testing as fast, comprehensive, and simple as possible:
- In one device, assess anything – organic, inorganic, and special nuclear materials
- Use ambient conditions – no special environment required
- Require zero sample preparation – what you have is what you use
MMoMA will achieve both extraction of the maximum amount of information and simplicity by exploring innovative methods to combine a single excitation source of continuously variable intensity with multiple detection methods. In simple terms: one beam, lots of different sensors.
Turning Information into Insights
A key element of MMoMA will be the integration of data fusion into its testing, where information from all the different sensors is aggregated and used to assess features such as:
- What a sample is made of
- Where it came from
- How it was made
- Where it was processed
- Where it has travelled
- Other signatures of interest
The MMoMA program will lay the foundation for future field deployable capabilities by determining what it is possible to measure with the beams and sensors we can adapt and refine today; how those devices can be integrated into a whole that is greater than the sum of its parts; and how data fusion can create new insights when all the data from a single sample is gathered at one time in one place.
