FURI | Spring 2020

Raman Spectrometry Conclusions as an Example of Intuitive Software

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There is a lack of accessibility in Raman spectrometry (used to detect the presence of compounds in provided samples). It was determined that by creating a software which aided in reducing human error, along with development of a smaller scale hardware, this accessibility issue could be remedied. In this work the researcher developed an algorithm to automatically compare the obtained spectrum to a database of known spectrums to detect the presence of organic compounds. Future work will involve improving the detection efficiency of the algorithm, offering more intuitive software and making usability simpler.

Student researcher

Natalie Lauren Mason

Computer science

Hometown: Tucson, Arizona, United States

Graduation date: Spring 2022