Tailoring Raman Scattering for cancerous cells prediction using oscillating electric fields and machine learning.

Abstract

Raman Effect originates from the inelastic scattering of light, and it can directly probe vibrational states in molecules and materials. The Electromagnetic fields of the incident radiation polarizes the charges of the molecule leading to the creation of an oscillating electric dipole. The scattered light has modified frequencies called Stokes and anti-Stokes frequencies. However, many theories that attempt to describe the existence of modified frequencies cannot account for the effects of the changes of electromagnetic and oscillating electric fields on these frequencies. This study sought to develop a theory that explains the effects of the oscillating electric field created by the oscillating dipole on the Stokes and anti-Stokes lines and their application in predicting cancerous cells. The objectives of this study were to formulate a theory that leads to determination of additional Raman frequency from the effects of electromagnetic fields on oscillating electric dipole; to develop a dataset of the frequencies of modified Stokes and anti-Stokes lines in the Raman scattering for some polar molecules: to examine and explore how Raman dataset and machine learning tool can be used in predicting cancerous cells. A theoretical model was formulated by calculating the energy due to the oscillating electric field created by the oscillating dipole using electrodynamics principles. The parameters needed were investigated by applying some approximations on the theory of retarded potentials, and then Maxwell equations were used to deduce the expression of oscillating electric fields. The frequency corresponding to the energy due to this field will determine the modified frequencies of Stokes and anti-Stokes lines. The dataset was generated, analyzed, and applied in machine learning tool to predict cancer cells. It is indicated from the results that the frequency difference in the peaks of modified Raman lines of molecules with high dipole moments ranges from 4.0x1014s -1 to 9.0x1014s -1 and less than 1.0x1014s -1 for less polar molecules. Based on the theory electromagnetic fields and oscillating electric fields, there are differential modified Raman frequencies data which can be used to distinguish the normal and cancerous cells with 96.75 % accuracy The study concludes that electric fields created by the oscillating electric dipole results to Raman scattering with modified frequencies which are sensitive to chemical structure of a molecule and these can be used to predict the presences of cancerous cells .The theory developed gives a formula that presents new results related to light matter interactions and allows a detailed description of Raman scattering. The law of conservation of energy validates the theory developed although actual experimental studies in future may be able to decide how far it will be a reliable technique