Project Background and Motivation
"IR and Raman spectroscopy have tremendous potential to solve a wide variety of complex problems. Both techniques are completely complementary providing characteristic fundamental vibrations that are extensively used for the determination and identification of molecular structure." - From Infrared and Raman Spectroscopy
Using In Situ Raman spectroscopy (coupled with a supercritical water gasification reactor) the decomposition and formation of substances can be identified, and in turn rates calculated. An on going direction of research at the University of Washington looks at the decomposition and formation of materials.
Understanding the decomposition and formation of materials have direct clean energy application, for example:
- Information on decomposition parameters of toxic chemicals can lead to identifying manufacturing operating conditions (temperature, pressure, resonance time) that can lead to their full elimination from a process resulting in clean chemistry production.
- Understanding the formation parameters of materials can lead to optimized synthesis parameters to decrease energy consumption
- With the assistance of machine learning it is also the hope that such base formation information can be used as training data, thus enabling the prediction of new materials with desirable properties.
- Note: this is an active research area within the US Department of Energy as apart of the Materials Genome Initiative
The motivation of the project stems from the fact that current method for analyzing spectral data (IR or Raman based) is very manual and tedious. There do currently exist spectral processing softwares, but they have down sides:
- Software is paid + NOT open source
- Additionally to a user needing to have a paid spectral analysis license, commonly the user also needs a paid supplementary software like Microsoft Excel, or Matlab, to use the full functionality of the spectral analysis software.
- At the time of commercialization of the code the software does not update to reflect new findings in this active research
- Process for analyzing is very manual and tedious taking a tremendous amount of time
- Not built for parallel computing i.e. cloud computing
The image below outlines the project motivation and some of the goals for future analysis through using the Raman Noodles software
