Python module implementing the collocation method for 1D ro-vibrational Schroedinger equation. This repo also includes datasets on ro-vibrational wavefunctions and polarizabilities of 12 diatomic molecules.

Set of python functions to aid in converting Raman cross-section values, including unit conversion

This was created during my research project to evaluate spectroscopic measurement data.

Code for upcoming paper on Optimisation of Raman spectroscopy in an axicon-based backscattering configuration

A script to analyze Raman spectroscopy data in txt files from mapping measurements using pandas dataframes. The data is collected for two-dimensional MoS2 and WS2 sample with calibrational Si to normalize intensity.

Set of data on polarizability with programs for obtaining the derivative of polarizability invariants (for H2, HD and D2) for specific inter-nuclear distance specific to a state defined by rovibrational wavefunction.

Computational condensed matter research code written in C++. Primary applications relate to low-dimensional carbon nanomaterials, phonons, and structural optimization.

Raman Data Analysis Application The Raman Data Analysis application is a user-friendly web tool developed by Nimendra Nawanjana to assist scientists and researchers in the analysis of Raman spectroscopy data.

Raman spectroscopy processing tool

Optimized R-Scripts of Thesis_stat, with more focus on automatisation

This project proposes an ML-based approach to determine the concentration of Pentanediol dissolved in water.

Comparativa de algoritmos de reducción de dimensionalidad para datos de espectroscopía Raman.

My work for an internship to improve my programming skills in Python and R

Please cite this article when using this code: https://doi.org/10.1016/j.physb.2022.414059

A graphical software for interactive rotational factor analysis and visualization of two-way data, mainly intended for vibrational spectra.

Python-based tool for analyzing raw data from Raman mapping measurements

Tool for generating Raman image through PCA and K-Means clustering.

Application of Signal Processing techniques and Continuous Wavelet Transform (CWT) using Machine Learning