NIR spectroscopy-based analytical tool for immediate determination of chemical signature
Description
Goals: Develop AI/ML based tool that can identify materials composition and size distribution “on the fly”
Detailed example
NIR (Near IR) spectroscopy is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum (from 780 nm to 2500 nm). Every material has their unique spectra.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Importance: NIR is well-suited for soft matter research in space because- 1. It doesn’t require any sample preparation 2. It doesn’t need gravity driven flow 3. Form factor can be of the order of a matchbox Challenges: There is no tool presently available that can perform spectral decomposition to achieve the goals
Controls / human review
ATO: Not reported; PIA: Not published