Developing a Quantitative Analysis Through IR Spectroscopy
Session Number
1
Advisor(s)
Dr. Kevin Chu, Velexi Corporation
Location
A133
Discipline
Mathematics
Start Date
15-4-2026 10:15 AM
End Date
15-4-2026 11:00 AM
Abstract
Quantitative analysis of chemical compositions is a crucial process within industries such as pharmaceuticals. Improper methods of obtaining mixture concentrations can directly impact the safety and products within these industries. However, when it comes to obtaining the data, the process is labor-intensive or not as efficient. The purpose of this project is to offer an effective framework for analyzing chemical compositions and numerical concentrations through the use of IR spectroscopy. The focus is to interpret the IR Spectra in a quantitative manner, analyzing the intensity of mixtures compounds. Using the relationship between absorbance and transmittance, a proper vector space needs to be established. Additionally, with proper normalization and adjusting Beer Lambert’s Law, the concentration of the mixture can be found. The necessary knowledge of Linear Algebra and physics of IR spectroscopy is required to answer these questions. Subsequently, usage of Python-based data analysis software will be required. Tools like NumPy arrays (numerically interpreting the raw data) and least squared regressions (determining the proper coefficients for the mixture spectra) are used to eventually get our desired output. Through coding and analysis, this project hones in on the enhanced interpretations of spectral features and offers a quantitative analysis on the IR spectra.
Developing a Quantitative Analysis Through IR Spectroscopy
A133
Quantitative analysis of chemical compositions is a crucial process within industries such as pharmaceuticals. Improper methods of obtaining mixture concentrations can directly impact the safety and products within these industries. However, when it comes to obtaining the data, the process is labor-intensive or not as efficient. The purpose of this project is to offer an effective framework for analyzing chemical compositions and numerical concentrations through the use of IR spectroscopy. The focus is to interpret the IR Spectra in a quantitative manner, analyzing the intensity of mixtures compounds. Using the relationship between absorbance and transmittance, a proper vector space needs to be established. Additionally, with proper normalization and adjusting Beer Lambert’s Law, the concentration of the mixture can be found. The necessary knowledge of Linear Algebra and physics of IR spectroscopy is required to answer these questions. Subsequently, usage of Python-based data analysis software will be required. Tools like NumPy arrays (numerically interpreting the raw data) and least squared regressions (determining the proper coefficients for the mixture spectra) are used to eventually get our desired output. Through coding and analysis, this project hones in on the enhanced interpretations of spectral features and offers a quantitative analysis on the IR spectra.