Multi Modal Materials Analysis (MMoMA)

The MMoMA program seeks to explore innovative methods to combine a single excitation source of continuously variable intensity with multiple detection methods and in-situ data fusion for assessing features such as a sample's composition, origin, production method, processing location, and/or other signatures of interest. The goal is to swiftly extract the maximum possible amount of information from a single sample of any composition (e.g., organic, inorganic, special nuclear materials) under ambient conditions, requiring zero sample preparation. Phase 1 aims to determine the power of multimodal materials analysis and data fusion compared to state-of-the-art sequential analysis. Phase 2 aims to demonstrate the power of this approach in laboratory-based demonstrations with samples that represent high impact use cases, and for those use cases determine the tradeoffs between the value of each type of information, the accuracy of that information, and the reduced size, weight, and power required. The program seeks to develop the ability to provide information on samples and materials suitable for critical defense needs including supply chain integrity, forensics and attribution, and tamper detection and authentication.