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Integration Of Raman Spectroscopy And Python-Based Data Analysis For Advancing Neurobiological Research, Natalie E. Dunn
Integration Of Raman Spectroscopy And Python-Based Data Analysis For Advancing Neurobiological Research, Natalie E. Dunn
Doctoral Dissertations
The field of Raman spectroscopy continues to expand into biological applications due to its usefulness as a non-invasive technique that can be utilized qualitatively and quantitatively. However, the inherent weakness of Raman scattering leads to the need for each collected spectra to undergo a preprocessing step to remove noise, background drift, and cosmic rays. Biological research in particular needs large datasets due to the increased variability in samples. As datasets grow, the need to perform preprocessing on each individual spectra becomes daunting. Often, these steps are done by hand with the help of specialized software programs. Preprocessing can be accelerated …
Characterizing Silicate Materials Via Raman Spectroscopy And Machine Learning: Implications For Novel Approaches To Studying Melt Dynamics, Blake O. Ladouceur
Characterizing Silicate Materials Via Raman Spectroscopy And Machine Learning: Implications For Novel Approaches To Studying Melt Dynamics, Blake O. Ladouceur
Doctoral Dissertations
Silicate melt characteristics impose dramatic influence over igneous processes that operate, or have operated on, differentiated bodies: such as the Earth and Mars. Current understanding of these melt properties, such as composition, primarily comes from investigations on their volcanic byproducts. Therefore, it is imperative to innovate on modalities capable of constraining melt information in environments where a reliance on laboratory methods is severed. Recent investigations have turned to Raman Spectroscopy and amorphous volcanics as a suitable pairing for exploring these ideas. Silicate glasses are a proxy for igneous melts; and Raman spectroscopy is a robust analytical technique capable of operating …